Anchorage Travel Model Calibration and Validation

Final Draft Anchorage Travel Model Calibration and Validation Prepared for Anchorage Metropolitan Transportation Solutions (AMATS) February 2005 301 West Northern Lights Boulevard Suite 601 Anchorage, Alaska 99503 ANC/TP41158.DOC/050460017

Contents Section Page Introduction...I-1 Background...I-1 Document Organization...I-2 Important Definitions Trips, Trip Origins and Destinations, Trip Productions and Trip Attractions...I-2 1 Travel Model Overview... 1-1 1.1 Basic Process... 1-1 1.2 Traveler Market (Household) Segmentation... 1-2 1.3 Trip Purpose Stratification... 1-2 1.4 Time of Day Periods... 1-3 1.5 Travel Mode Stratification... 1-3 1.6 Transportation Networks... 1-4 2 Travel Model Structure... 2-1 2.1 Land Use and Demographic Inputs... 2-1 2.2 Land Use/Density Inputs... 2-2 2.3 Household Segmentation... 2-2 2.4 Trip Distribution... 2-5 2.5 Time of Day... 2-5 2.6 Mode Choice... 2-6 2.7 Traffic Assignment... 2-6 2.8 Summary... 2-7 3 Traveler Market (Household) Segmentation... 3-1 3.1 Household Size...3-1 3.2 Household Income... 3-3 3.3 Workers per Household... 3-4 3.4 Auto Ownership... 3-6 3.5 Children per Household... 3-7 4 Trip Generation... 4-1 4.1 Home Based Trip Production Models... 4-1 4.2 Non-Home Based Trip Production Models... 4-2 4.3 Commercial Vehicle (Truck) Trips... 4-3 4.4 Trip Attraction Models... 4-3 4.5 Special Generators/Visitors... 4-4 4.6 Other Special Considerations... 4-6 4.7 Validation Results...4-6 ANC/TP41158.DOC/050460017 III

CONTENTS 5 Trip Distribution...5-1 6 Time of Day Factoring...6-1 7 Mode Choice...7-1 7.1 Home Based Work Mode Choice...7-3 7.2 Home Based Shop Mode Choice...7-3 7.3 Home Based School Mode Choice...7-4 7.4 Home Based Other Mode Choice...7-5 7.5 Non-Home Based Trip Mode Choice...7-5 7.6 Validation Results...7-6 8 Traffic Assignment and Volumes...8-1 8.1 Cordon Crossings...8-1 8.2 Facility Type Comparisons...8-3 8.3 Comparisons of Statistical Performance...8-5 8.4 Individual Link Performance...8-6 9 Summary and Conclusions...9-1 Appendix A B C D E F Variable Dictionary Anchorage Travel Model Socioeconomic Database Model Feedback Process Commercial Vehicle Travel Model Special Generators Hotel/Motel Visitor Model Screenlines Figure 2-1 Model Overview Flow Chart... 2-3 3-1 Average Household Size vs. % Total Households by Size Group... 3-2 3-2 Zonal/Regional Income vs. % Total Households by Income Group... 3-3 3-3 Average Workers/Household vs. % Total Households by Group.... 3-5 4-1 Survey vs. Modeled Trips by Community Council Area... 4-7 5-1 Survey vs. Model Trip Length Frequencies (Home based work)... 5-3 5-2 Survey vs. Model Trip Length Frequencies (Home based shop)... 5-3 5-3 Survey vs. Model Trip Length Frequencies (Home based school)... 5-4 5-4 Survey vs. Model Trip Length Frequencies (Home based other)... 5-4 5-5 Survey vs. Model Trip Length Frequencies (Non-home based work)... 5-5 5-6 Survey vs. Model Trip Length Frequencies (Non-home based nonwork)... 5-5 8-1 Maximum Desirable Deviation in Total Screenline Volumes... 8-2 8-2 Anchorage Bowl Screenlines... 8-3 8-3 Statistical Comparison of All Available Measured and Modeled 2002 Weekday Traffic Volumes... 8-5 IV ANC/TP41158.DOC/050460017

CONTENTS Table 3-1 Comparison of Household Size Model Results (2002) and 2000 Census Proportion of Household Size Group (Totals for Anchorage Area)...3-2 3-2 Comparison of Household Income Model Results (2002) and 2000 Census Proportion of Household Income Groups (Totals for Anchorage Area)...3-4 3-3 Comparison of Household Worker Model Results (2002) and 2000 Census Proportion of Household Worker Groups (Totals for Anchorage Area)...3-5 3-4 Auto Ownership Model Variables and Coefficients...3-6 3-5 Comparison of Household Auto Ownership Model Results (2002) and 2000 Census Proportion of Household Auto Ownership Groups (Totals for Anchorage Area)...3-7 4-1 Home Based Work Trip Rates (Workers/HH by Income Group...4-1 4-2 Home Based Shopping Trip Rates (Household Size by Income Group...4-1 4-3 Home Based School Trip Rates (Household Size by Children/HH)...4-2 4-4 Home Based Other Trip Rates (Household Size by Income Group)...4-2 4-5 Special Generators...4-5 4-6 Total Trips by Trip Purpose (Survey-Model Comparison)...4-6 5-1 Average Trip Length (in Minutes) by Trip Purpose...5-2 6-1 AM Peak Period Trip Purpose and Directional Factors...6-1 6-2 PM Peak Period Trip Purpose and Directional Factors...6-1 6-3 Off Peak Period Trip Purpose and Directional Factors...6-2 7-1 Complete List of Mode Choice Variables (All Purposes)...7-2 7-2 Home Based Work Mode Choice Model Variables and Coefficients...7-3 7-3 Home Based Shop Mode Choice Model Variables and Coefficients...7-4 7-4 Home Based School Mode Choice Model Variables and Coefficients...7-4 7-5 Home Based Other Mode Choice Model Variables and Coefficients...7-5 7-6 Non-Home Based Work Mode Choice Model Variables and Coefficients...7-6 7-7 Non-Home Based Non-work Mode Choice Model Variables and Coefficients...7-6 7-8 Survey vs. Model Mode Shares for Home Based Work Trips...7-7 7-9 Survey vs. Model Mode Shares for Home Based Shop Trips...7-7 7-10 Survey vs. Model Mode Shares for Home Based School Trips...7-8 7-11 Survey vs. Model Mode Shares for Home Based Other Trips...7-8 7-12 Survey vs. Model Mode Shares for Non-Home Based Work Trips...7-9 7-13 Survey vs. Model Mode Shares for Non-Home Based Non-work Trips...7-9 7-14 Survey vs. Model Mode Shares for All Purposes...7-10 8-1 Summary of 2002 Weekday Cordon Counts/Volumes and Differences...8-4 8-2 Summary of 2002 Weekday Facility Class Counts/Volumes and Differences...8-5 8-3 Percent Difference Targets for Daily Volumes for Individual Links...8-6 ANC/TP41158.DOC/050460017 V

CONTENTS VI ANC/TP41158.DOC/050460017

Introduction This document summarizes the development, calibration, and validation of a new travel demand model for the Anchorage, Alaska urbanized area. The travel demand model is a primary tool of the Anchorage Metropolitan Area Transportation Solutions (AMATS) planning organization in its analysis and continuing development of the area s Long Range Transportation Plan. The report summarizes the features of the new travel demand model, its internal submodels and linkages structure, data inputs, relevant major assumptions, and, the tests that were performed to validate and measure the performance of the model in reproducing current travel behavior and transportation system usage. Background The design of the travel demand model takes advantage of new data resources describing the household characteristics and travel characteristics of the Anchorage area population, as well as supplemental datasets assembled from government agencies, the Anchorage business community and other sources. Primary resources used in the development of the new model include the following: 2002 Anchorage Household Travel Survey; 2001 PeopleMover Transit Rider Survey; 2000 US Census and Census Transportation Planning Package (CTPP); 2002 Student Enrollment and Public School Attendance Database U.S. Military Base Personnel and Active Armed Forces Data 2002 PeopleMover Transit Rider Counts 2002 Municipality of Anchorage (MOA) and Alaska Department of Transportation (ADOT) Traffic Counts; MOA Planning Department Demographics and Residential Use Inventories; Alaska Department of Labor Wage & Salary Employment Inventories (ES-202 Unemployment Insurance Dataset) MOA and ADOT Road Characteristics Inventories PeopleMover Transit Schedules and Route Maps. These data were used to create a new model of weekday travel in and around the Anchorage area. The new travel demand model can be used to test a range of assumptions regarding changing land use patterns; new and updated transportation projects and ANC/TP41158.DOC/050460017 I-1

INTRODUCTION facilities; and, new or modified public policies regarding land use, and transportation services and facilities. The new travel model design was developed in consultation and with input from local transportation experts and the general community. It is structured to be a responsive as possible to the expected range of questions and issues that Anchorage expects to face regarding its transportation system through 2025. Document Organization The documentation is divided into nine sections. The first section, Travel Model Overview, discusses the basic features, capabilities and dimensions of the model. The second section, Travel Model Structure, provides more information on the actual modeling process and further details some of the topics in Travel Model Overview. The third section, Traveler Market (Household) Segmentation specifically documents the set of models developed to estimate residential market segmentation and provides data on their ability to reproduce 2002 actual conditions. The fourth section, Trip Generation, documents the models used to estimate likelihood of trips either being produced and/or attracted to specific developments and geographic locations. The fifth section, Trip Distribution, discusses the models which were developed to predict general trip patterns and how well they match 2002 known conditions. The sixth section, Time of Day, illustrates the basis used for segmenting daily travel estimates into time period specific estimates. The seventh section, Mode Choice, documents the models and the assumptions used to translate general estimates of travel into those, which are specific to mode of travel. This also details tests and comparisons of model prediction results to 2002 actual travel mode shares. The eighth section, Trip Assignments and Volumes, compares the output of the model in terms of specific traffic volumes for different roads and corridors to independent traffic count data collected in the field. This comparison is evaluated against accepted industry guidelines for travel demand model performance. The ninth section summarizes the results, findings and recommendations arising out of the model calibration and validation work. Important Definitions Trips, Trip Origins and Destinations, Trip Productions and Trip Attractions Common nomenclature is used within the travel modeling community to characterize travel and trip-making. Several definitions are defined below: Trip: A trip is a one-way journey from a point of origin to a destination for a specific purpose, i.e., a home to work journey. Unless otherwise specified, trip means a single person journey. Trips include walking and bicycling (referred to as non-motorized trips) when these are the primary modes of travel. Motorized trips include driving or riding as a passenger in various vehicles autos, trucks, buses, school buses, etc. Sometimes trips will be defined as a mode journey, as in a vehicle trip which is used to represent a vehicle driver journey or a transit trip which applies to a transit passenger journey. Trip Origins and Destinations: Each trip has two end points -- an origin and a destination. I-2 ANC/TP41158.DOC/050460017

INTRODUCTION Trip Productions and Attractions: It is often useful to relate trips to the trip-maker and his/her residence location. Accordingly, all trips which start or end at the trip-maker s home are defined as Home-Based Trip Productions at the home-end and as Home-Based Trip Attractions at the non-home trip end. For trips which neither start or end at the tripmaker s residence, the origin is defined as the Trip Production and the destination is defined as the Trip Attraction. ANC/TP41158.DOC/050460017 I-3

INTRODUCTION I-4 ANC/TP41158.DOC/050460017

SECTION 1 Travel Model Overview The Anchorage area travel model is designed to provide forecasts of prospective usage of the transportation system given a wide variety of assumptions about the available network and service and service cost policies that may be assumed for future conditions. To do this, salient characteristics of the traveling population and the available services must be measured and then translated into statistical models and abstract representation. The goal here is to capture, as well as possible, the significant determinants of traveler response to changes in the system and policies. 1.1 Basic Process The framework for this process is travel activity during a typical weekday. To provide effective models that are sensitive to the range of differences in the characteristics of both the travelers and their travel opportunities, the problem is broken down into specific travel market segments. This section of the report discusses the key market segmentation definitions and assumptions used in the Anchorage model. A brief introduction to the modeling process itself is provided here; the model process is presented in significantly more detail in the remainder of the report. To estimate travel demand, the modeling process is broken into six basic steps. These are: Household Disaggregation Estimation of the socio-economic groups or market segments that prospective travelers belong to Trip Generation Estimation of expected tripmaking rates for each of these segments for a given set of tripmaking purposes Trip Distribution Estimation of expected origin-destination patterns for the defined trip purposes and by a set of time periods Time of Day Segmentation Estimation of the shares of origin-destination trips expected for defined time periods and stratified by trip purpose Modal Choice Estimation of the shares of origin-destination trips expected for separate travel modes for each market segment, trip purpose and time period Trip Assignment Estimation of the expected routes (by mode) for the mode specific interchange sets defined by Modal Choice Understanding how these steps are applied requires a picture of how all of the above segments are defined. ANC/TP41158.DOC/050460017 1-1

TRAVEL MODEL OVERVIEW 1.2 Traveler Market (Household) Segmentation For the Anchorage travel demand model, several separate and distinct submodels were developed to segment households in each subarea (i.e. traffic analysis zone) into five different types of groups. These groups provide breakdowns of the data into different household sizes, range of household incomes, as well as, groups representing different numbers of workers per household and auto ownership groups. The specific defined segments are listed below. Household Size one, two, three, four or more persons Household Income less than $40K, at least $40K, but less than $70K, $70K or more Auto Ownership zero, one, two, three or more vehicles Workers in Household zero, one, two, three or more workers Children in Household zero, one, two, three or more children With the exception of the auto ownership classes, all market segment proportions are derived from the estimated average value for the traffic analysis zone. This segmentation is used to estimate trip generation and mode choice components of the travel demand model. Cross products of segmentation pairs are used to identify more specific market segments. For instance, all two-person households which own two autos. The specific combinations of segments used for the trip generation and mode choice models are identified and described in those sections of this document. 1.3 Trip Purpose Stratification Travel models recognize that trips made for different purposes have different characteristics. To improve accuracy of predictive models, specific models are estimated to represent each defined trip purpose. In the case of the Anchorage, such stratification is used in the trip generation, trip distribution, time-of-day factoring and mode choice submodels. Application of trip purpose stratification recognizes that the basic rates of trips produced at origin locations and attracted to specific destinations; the expected length of trip; the time of day a given trip is made; and, the relative likelihood of using a particular travel mode (e.g. driving an auto versus being a passenger versus riding the bus) are all influenced by the purpose of the trip. The Anchorage travel model has six person trip purposes and two additional commercial vehicle (i.e., truck) trip purposes. These six person trip purposes are: Trips between home and work (Home based Work HBW) Trips between home and shopping (Home based Shop HBS) Trips between home and school (Home based School HBSch) Trips between home and any other type of destination (Home based Other HBO) Trips between work and other places besides work (Non-home based Work NHBW) Trips between two non-home/non-work locations (Non-home based Non-work NHBNW) Two separate trip purposes represent light and heavy commercial truck movements. 1-2 ANC/TP41158.DOC/050460017

TRAVEL MODEL OVERVIEW 1.4 Time of Day Periods Another consideration in travel demand model design is determining what periods of the day will be separately forecast. Modeling traffic by time of day has the advantage of linking traffic volume estimates more closely to determinants such as road capacity, transit service availability, likely times for trips of specific purposes to be made, as well as, such influences as time dependent road use restrictions (e.g. peak period high occupancy vehicle restrictions) and road operation (e.g. reversible lanes). Modeling time periods also provides more directly usable information for road and traffic engineering applications; transit planning; and, for estimating vehicular emissions and pollutants. The Anchorage travel model stratifies travel into three weekday time periods. These are: AM Peak Period (7:00 AM-9:00 AM); PM Peak Period (3:00 PM-6:00 PM); Off Peak Period (12:00 AM-7:00 AM and 9:00 AM-3:00 PM and 6:00 PM-12:00AM) Time period stratification is applied after trip distribution and before mode choice.. The traffic assignment module (which places expected traffic on the most likely routes given road congestion) computes adjusted travel times due to traffic congestion during each time period. These adjusted travel time results are fed back to trip distribution to recalculate origin-destination patterns. Trips for all time periods are distributed to each time period. Then, after each cycle of trip distribution, each time-period-specific trip distribution output is factored by it s time-of-day proportion and directionality percentages to yield trips occurring in each time period. The actual proportion of trips in a given time period is calculated after each cycle of trip distribution. 1.5 Travel Mode Stratification The mode choice models utilize market stratification and trip purpose stratification to predict traveler choice of travel mode for every trip. Travel mode in turn is used to define what routes and services are utilized for the ubiquitous transportation network and it s specific modal network components. The Anchorage mode choice model considers the following modal options: Auto drive alone Auto drive with passenger Auto passenger Public Transit/School Bus Transit Walking Bicycling In the case of transit modes, all trip purposes except home-base school are estimated as public transit trips. Home based school transit trips are estimated as school bus trips. ANC/TP41158.DOC/050460017 1-3

TRAVEL MODEL OVERVIEW 1.6 Transportation Networks The key to understanding how estimated travel demand effects the condition of the transportation system is the definition of the networks that represent linkages between different area locations. In travel models, most often this is represented as a set of interconnected links that approximate the physical layout of various area transportation facilities including highways, streets, exclusive transit facilities, railroads, sidewalks, trails, etc. Expected speeds of travel along these links is used to estimate how long it may take to get between two places via a given mode and route. Bus travel times consider such things as waiting for a bus, transferring between buses, walking to and from the bus stop, and, or course, time spent riding the bus. The objective in defining these networks is to represent how the traveler will see travel options and choose between them. As noted earlier, the Anchorage travel demand model s process is applied separately for three different time periods. The model maintains information about potential paths for in each time period. Potential trip attributes such as auto travel times, frequency of bus services and alternate bus routing patterns are all stratified by time of day. Travel by walking and travel by bicycle are assumed at constant average speeds for all three time periods. The Anchorage travel model transit service, includes a computational submodel that adjusts the speeds and travel times of buses operating in mixed flow traffic with automobiles, based on the level of congestion and operating speeds experienced by autos. This procedure maintains consistency in mode attributes and allows simulation of such effects as traveling through congested areas versus having an independent bus lane to be effectively represented. 1-4 ANC/TP41158.DOC/050460017

SECTION 2 Travel Model Structure The Anchorage travel demand model consists of a series of processes that progressively build up forecasts of travel activity. Major inputs to these processes include the following: Land use and socio-economic data representing area development Multimodal networks representing travel options and connections between different part of the area Figure 2-1 is a flowchart illustrating the detailed sequencing and linking of the various steps used in the travel model. This section focuses on providing a broad overview of the key elements of those steps in the context of the overall process. The subsequent sections will detail assumptions, calibration and validation of each of these steps. 2.1 Land Use and Demographic Inputs Besides the networks representing multimodal transportation facilities available to prospective travelers, another primary input to the travel modeling process is an inventory or forecast of the distribution and make up of land uses, households, population and employment in the study area. In assembling inventories or developing forecasts of these inputs, attention must be paid to providing adequate detail to support the input requirements of the travel demand model. This means both (1) having estimates at the traffic analysis zone level to provide adequate geographic specificity and (2) categorizing data such as types of employment in enough detail to support input requirements. The Anchorage model design requires the following data inputs and associated breakdown for each traffic analysis zone. A detailed description of the data fields is provided in Appendix A Variable Dictionary Anchorage Travel Model Soicioecnomic Database. Traffic Analysis Zone ID Total Population Number of Households Median Household Income (2002 Dollars) Average Number of Workers/Household Enrollment of Schools in Zone Employment Categories Agricultural Employment Mining Employment Construction Employment Manufacturing Employment Transportation/Public Utilities Employment Wholesale Trade Employment Retail Trade Employment Finance, Insurance and Real Estate Employment ANC/TP41158.DOC/050460017 2-1

TRAVEL MODEL STRUCTURE Service Employment Government Employment University Employment School Employment Medical/Health Services Employment Work Trip Parking Costs (2002 Dollars) Other Trip parking Cost (2002 Dollars) Categorization of employment data was based on employer reported North American Industrial Classification System (NAICS) codes to allocate the 2002 employment inventory. Future forecasts use the employment type stratification of the AMATS Land Use Allocation model directly. 2.2 Land Use/Density Inputs The new travel model provides sensitivity to environmental factors that influence tripmaking in general and, specifically, determination of mode choice. To do this, indicators of characteristics such as pedestrian friendliness, mix of land uses and similar measures are calculated based on the spatial structure of the travel model network and land use assumptions. Specifically, the values calculated in this manner are used in the auto ownership model and in all the mode choices models (specific variables used and associated coefficients are documented in Mode Choice (Section 7). These values are calculated for each traffic analysis zone. Street intersection density (per square mile); Ratio of employment to residents (per zone); Employment density (per square half mile and mile); Residential density (per square half mile and mile); 2.3 Household Segmentation Households are segmented into five different primary groupings representing their membership in the household size, number of worker, median income, auto ownership and number of children classes described in Travel Model Overview (Section 1). Depending on the model calculations being performed, each of these groups may or may not be treated separately. The trip generation models use the following household segmentations: Household size and number of workers are used together to estimate home based work productions Household size and median income class are used together to estimate both home based shopping and home based other productions Household size and number of children are used together to estimate home based school trip productions 2-2 ANC/TP41158.DOC/050460017

TRAVEL MODEL STRUCTURE The mode choice model uses the following household segmentations: Separate models for each household size and number of workers category are used together to estimate home based work mode shares Separate models for each household size and median income range category are used together to estimate home based shopping and home based other mode shares In all cases, except the auto ownership and children per household models, the segmentation models use the zonal average value as the input and based on 2002 Census data (both SF1 tables from the general census and CTPP(Census Transportation Planning Package) tabulations), stratify that average into the segments required by the downstream models. For the auto ownership model, a multinomial logit formulation was used. For the children per household model, a cross classification formulation was used. All models are fully documented in Traveler Market (Household) Segmentation (Section 3) of this document. 2.4 Trip Distribution Separate trip distribution models were calibrated for each of the six person travel trip purposes and for the two commercial vehicle trip categories. All trip distribution formulations except home based school are based on the gravity model. Utilizing data from the Anchorage Household Travel Survey, accessibility/deterrence functions were developed for all person based trip purposes except home based school. For medium and heavy duty truck trips, the functions used in the previous Anchorage model (based on FHWA Quick Response Freight Traffic Estimation methods) were utilized. For home based school, a Fratar growth factoring model was used. This model uses a combination of a seed table of known existing origins and destinations and a parallel set of updated trip productions and attractions to grow interchanges in the seed table to match the updated production and attraction values. The process iterates to expand interchange values while using the independently determined productions and attractions for each traffic analysis zone as control totals. The output of the trip distribution model is stratified by both trip purpose and time of day. Time of day stratification is achieved by inputting the time period specific network travel times and creating three person trip tables for each of the eight trip purposes (six for person travel and two for commercial vehicle/truck travel). The process of estimating the number of trips for each trip purpose in each time period, which occurs after trip distribution is completed applies time-of-day factors and directional flow factors to the daily trip distributions to output three time-period partitioned trip tables for each trip purpose. The trip purpose specific trip distribution functions are documented in the Trip Distribution (Section 5) of this document. 2.5 Time of Day Trip estimates from the trip distribution step are used to calculate the number of trips occurring in each of three modeled time periods for all eight purposes. If congested times are used to estimate each of the time periods, origin-destination patterns for parallel (e.g. ANC/TP41158.DOC/050460017 2-5

TRAVEL MODEL STRUCTURE AM peak period home based work vs. PM peak period home based work) can vary significantly. The purpose of this step in travel model processing is to produce a set of triptables which correctly represent the relative directional orientation and the proportion of trips occurring in each modeled period. This is done by multiplying each trip table by household travel survey derived factors indicating the percentage of trips from home vs. trips to home for home based trip purposes (the factor for the non-home based work purpose is based on similar survey information for that activity. Non-home based non-work is always 50/50); then, factoring the resulting table by the total percentage of trips for a given trip purpose occurring in the period. These factors and their application are fully documented in the Time of Day (Section 6) of this document. 2.6 Mode Choice The mode choice models estimate shares of all trips by mode. They comprise the most complex step in travel model processing. For the Anchorage model, mode choice is performed separately for traveler market segments, trip purpose and modeled time period. All non-commercial trip purposes are specified as multinomial logit models which estimate mode shares for all modes identified in Travel Mode Stratification in the Travel Model Overview section (Section 1). Coefficients and performance of these models is fully documented in Mode Choice (Section 7). Operationally, mode share estimates are obtained for each market segment and time period for each home based trip purpose. The segments within each time period are combined to be input to the corresponding trip assignment (either vehicle trips to highway or transit riders to transit routes). For non-home based trip purposes, mode shares are calculated in aggregate for a given time period as input to the traffic assignment process. For commercial trips (medium and heavy duty trucks), these are already estimates of vehicle trips, so no mode choice takes place. 2.7 Traffic Assignment The last step in the travel modeling process is assigning the mode specific and time period specific estimates of origin-destination interchanges to specific routes in the travel model network. The model software provides capabilities to do this for both highway and transit trips. (For transit, only public transit trips are assigned. School bus rider trips are not currently assigned to the network.) Public transit trips are assigned to the transit system network routes which are represented by stops, travel times, and waiting delays to traverse the minimum cost route between a given origin and destination via public bus or other transit mode. This assignment is sensitive to conditions in the public transit network during the assignment s time period (associated road congestion, bus frequencies by route, etc.). The model output is rider volumes by route and specific segment. This data can be examined in aggregate to determine transit riders in specific corridors or areas of the city. Highway vehicle trips are assigned using a mathematical algorithm that is sensitive to the relationship between traffic volume and available road capacity. The algorithm uses this relationship to: 1) estimate expected congestion related delays; 2) considering that delay 2-6 ANC/TP41158.DOC/050460017

TRAVEL MODEL STRUCTURE recalculate the best routes between origins and destinations; 3) reassign traffic to available routes given updates to route times based on delay. This cycle theoretically (equilibrium is actually estimated using a sub-optimal heuristic that approximates an equilibrium state) continues until the condition is reached that no group of travelers can improve their origindestination travel time by choosing an alternate route. At his point, the system is said to be in equilibrium. Either the approximation of an equilibrium condition or a maximum number of iterations to reach this condition ends the assignment process. As referenced above, highway assignments in the Anchorage model are made for three specific time periods. Based on final assignment speeds, the estimated link travel times in the network are updated. These new travel times can then be reinput to the trip distribution process to show impacts of expected congestion on traveler destination and mode choices as part of the travel model feedback process. The cycle of trip distribution, time of day factoring, mode choice and traffic assignment can then be repeated until either the travel times input to the traffic assignment process and those output from the assignment process reach equilibrium of a maximum number of iterations is completed. This process uses a mathematical model termed Method of Successive Averages to achieve equilibrium and ensure closure between input speeds and volumes and those output as the final iteration. This model equilibrium feedback process is described more fully in Appendix B Model Feedback Process. The formulation used to determine overall model equilibrium is discussed in detail in Traffic Assignment and Volumes (Section 8). That section also includes discussion of the process of comparing measured to modeled traffic volumes. 2.8 Summary The purpose of this section has been to provide a roadmap to the remainder of the discussions and an overview of formulations of specific models that make up the Anchorage travel model; and, to broadly explain the process used to apply those models. The remainder of the document discusses the specific models and the measurement of their performance. ANC/TP41158.DOC/050460017 2-7

TRAVEL MODEL STRUCTURE 2-8 ANC/TP41158.DOC/050460017

SECTION 3 Traveler Market (Household) Segmentation This section provides detailed documentation of the models developed to segment households into different groups or market segments. The following three major data sources were utilized: 2000 US Census Transportation Planning Package 2000 US Census SF1 Short Form Statistical Tabulations 2002 Anchorage Household Travel Survey Each of the models which were developed is discussed below. 3.1 Household Size Median household size information must be translated to numbers of households falling into each size group or segment. These segments support disaggregate estimation of auto ownership, cross classification of trip production rates (for home based shop, home based school and home based other) and disaggregate estimation of mode choice (for the same trip purposes). To estimate the proportions of different sized households in each TAZ, median values from the 2000 U.S. Census data are correlated with corresponding percentages of each of the groups. This analysis was performed for both the complete census data sample (100% of the area population) at the block group level and for traffic analysis zones using the Census Transportation Planning Package subset (approximately a 6% sample of the area population). Using these two sources, curves were developed relating the proportion of one person, two person, three person and four or more person households to a range of median values. These curves are illustrated in the graphic below. The number of households in each TAZ is multiplied times these proportions to determine the number of houses in each category. For future conditions, zonal population and households estimates are used to derive mean values and the corresponding size segment for each category in each zone. Figure 3-1 illustrates the family of curves indicating the relationship between average household size and the proportion of households falling into each group for that average. ANC/TP41158.DOC/050460017 3-1

TRAVELER MARKET (HOUSEHOLD) SEGMENTATION Household Size Model Group Proportion 1.00 0.80 0.60 0.40 0.20 0.00 1 Person 2 Person 3 Person 4 Person 1.1 1.4 1.7 Median Houshold Size Figure 3-1. Average Household Size vs. % Total Households by Size Group 2.0 2.3 2.6 2.9 3.2 3.5 3.8 4.1 Aggregating the estimates of household size groups for the Anchorage model s study area, yields the following proportions (Table 3-1) for each group and an overall average for the study area of 2.711. Comparable proportions obtained by aggregating the parallel Census (100% sample) information are also shown in Table 3-1 (average is 2.745). The household size model estimates an average household size of 4.966 for households of four of more persons compared to an actual value of 4.966 based on 2000 U.S. Census information. (Note that while the U.S. Census does include military housing, the estimates from the Anchorage household size model do not.) TABLE 3-1 Comparison of Household Size Model Results (2002) and 2000 Census Proportion of Household Size Group (Totals for Anchorage Area) Household Category Model Total Model Group/ Total Census Total Census Group/ Total One Person 23805.250 22142.234 Two Person 28772.300 30155.318 Three Person 17371.183 16942.179 Four or More 25088.264 25583.270 Totals 95036 1.00 94822 1.00 3-2 ANC/TP41158.DOC/050460017

TRAVELER MARKET (HOUSEHOLD) SEGMENTATION 3.2 Household Income The second model developed was similar to the household size model. This model predicts the proportion of household falling into low, medium and high household income groups based on median income for each traffic analysis zone. Median household income must be translated to numbers of households falling into specified income groups to support disaggregate estimation of auto ownership, cross classification of trip production rates (for home based shop and home based other trip purposes) and disaggregate estimation of mode choice (for home based work, home based shop and home based other trip purposes). To estimate the proportions of income groups in each TAZ, median values from the 2000 U.S. Census are correlated with corresponding percentages of the groups. This analysis was performed for both the complete census data sample (100% of the area population) at the block group level and for traffic analysis zones using the Census Transportation Planning Package subset (approximately 6% sample of the area population). Using these two sources, curves were developed relating the proportion of low income (< $40,000/year), medium income ($40,000/year to $69,999/year), and high income ($70,000/year or more) households to a range of median values. These curves are illustrated in the graphic below. Total households are multiplied times these proportions to determine the number of houses in each category. For future conditions, estimation of zonal median incomes will impact model results by changing the size of the market segment associated with each category in a zone. Figure 3-2 illustrates the family of curves indicating the relationship between the median income for a given traffic analysis zone relative to the median income in the study area (using this ratio allows all estimates to be made relative to the range of household incomes in Anchorage) and the proportion of households falling into each group for that average. Household Income Model Group Proportion 1.000 0.800 0.600 0.400 0.200 0.000 Low Income Medium Income High Income 0.1 0.4 0.7 1.0 1.3 1.6 1.9 2.2 Zonal/Regional Income Figure 3-2. Zonal/Regional Income vs. % Total Households by Income Group ANC/TP41158.DOC/050460017 3-3

TRAVELER MARKET (HOUSEHOLD) SEGMENTATION Aggregating the estimates of household income groups for the Anchorage model s study area, yields the following proportions (Table 3-2) for each group. Comparable proportions obtained by aggregating the parallel 2000 U.S. Census (100% sample) information are also shown in Table 3-2. It should be noted that while the census does include military housing, the estimates from the household income model do not. TABLE 3-2 Comparison of Household Income Model Results (2002) and 2000 Census Proportion of Household Income Groups (Totals for Anchorage Area) Household Category Model Total Model Group/ Total Census Total Census Group/ Total Low Income (>$40000/Yr) 35074.369 32027.337 Medium Income ($40001-$70000/Yr) 29284.308 31587.332 High Income (>$70000/Yr) 30677.323 31466.331 Totals 95036 1.00 95080 1.00 As would be expected, comparisons of the household income model to 2000 U.S. Census data shows greater discrepancies then the household size model. This is likely due to the differences in the years being compared and also in the separate survey reporting categories used to report median zonal income. 3.3 Workers per Household The average number of workers per household is used to generate households falling into worker classes to support disaggregate estimation of auto ownership, estimate of home based work trip productions and estimation of home based work mode. To estimate the proportions of worker classes in each TAZ, average workers per household values from the 2000 U.S. Census are correlated with corresponding percentages of the groups. This analysis was performed for both the complete census data sample (100% of the area population) at the block group level and for traffic analysis zones using the Census Transportation Planning Package subset (approximately 6% sample of the area population). Because the CTPP dataset provides better categorization of the workers per household variable and due to logical inconsistencies in the Census (100%) sample information, curves were developed based exclusively on the CTPP data relating the proportion of zero worker, one worker, two worker, and three or more worker households to a range of average values. These curves are illustrated in Figure 3-3 below. Total households are multiplied times these proportions to determine the number of households in each category. For future conditions, estimation of the zonal average of number of workers per household will impact model results by changing the size of the market segment associated with each category in a zone. 3-4 ANC/TP41158.DOC/050460017

TRAVELER MARKET (HOUSEHOLD) SEGMENTATION Group Proportion 1.200 1.000 0.800 0.600 0.400 0.200 0.000 Household Worker Model 0.8 1.2 1.6 2.0 2.4 2.8 3.2 0 Worker 1 Worker 2 Worker 3+ Worker 0.0 0.4 Average Workers/Household Figure 3-3. Average Workers/Household vs. % Total Households by Group Aggregating the estimates of household worker groups for the Anchorage model s study area, yields the following proportions (Table 3-3) for each group. Comparable proportions obtained by aggregating the parallel 2000 U.S. Census information are also shown in Table 3-3. It should be noted that while the census does include military housing, the estimates from the household worker model does not. TABLE 3-3 Comparison of Household Worker Model Results (2002) and 2000 Census Proportion of Household Worker Groups (Totals for Anchorage Area) Household Category Model Total Model Group/ Total Census Total Census Group/ Total Zero Workers 14204.149 15165.160 One Worker 38282.403 38805.408 Two Workers 36550.385 35283.371 Three or More 6000.063 5655.059 Totals 95036 1.00 95046 1.00 ANC/TP41158.DOC/050460017 3-5

TRAVELER MARKET (HOUSEHOLD) SEGMENTATION 3.4 Auto Ownership The Anchorage travel model includes a model for estimating auto ownership groups. These ownership groups and the resulting estimate of autos per person per TAZ are used as an input to mode choice modeling. Vehicle (auto) ownership group shares were determined using a multinomial logit model formulation. This estimation process was chosen to allow more direct forecasting of auto ownership for future years based on primary forecasting variables. The auto ownership model forecasts group proportions for 0, 1, 2 and 3 or more auto owning households. The variables used for input include household size, number of workers in household, residential density and land use mix of the residence zone. The model is applied separately for each household income group. The logit formulation calculates segment shares based on the proportion of the total of all shares each share represents. These shares are expressed the natural exponent of an empirically derived function. The general formulation is as follows: Share(u i )=e u i/ e u t where: Share(u i ) = calculated share of some group i e u i = the natural exponent of the derived utility u i e u t = sum of all e u for all possible options The auto ownership model uses the following variables in its utility expression: Household size Number of workers per household Income segment (low, medium or high) Density of street intersections within ½ mile Index of zonal mix of residential and employment uses The following table (Table 3-4) lists the associated coefficients used in the auto ownership model: TABLE 3-4 Auto Ownership Model Variables and Coefficients Variable Zero Autos One Auto Two Autos Constant -21.0651 4.1442 2.5154 Household Size -1.23182-1.37421-0.36378 No of Workers -1.39570-0.93408-0.48255 Income Group 22.34620 (high) 18.92600 (med) -11.39630 (low) 2.05728 (high) 0.37583 (med) -1.80951 (low) 0.64969 (high) 0.09619 (med) -0.40170 (low) Intersection Density 0.03418 0.01294 0.00016 Mixed Use Index 0.00199 0.00007 0.00002 For households having 3 or more vehicles, the utility value is 0. This value provides the base reference for scaling the utilities of all other groups. 3-6 ANC/TP41158.DOC/050460017

TRAVELER MARKET (HOUSEHOLD) SEGMENTATION Aggregating the estimates of the sizes of household auto ownership groups for the Anchorage model s study area, yields the following proportions (Table 3-5) for each group. Comparable proportions obtained by aggregating the parallel 2000 U.S. Census information are also shown in Table 3-5. It should be noted that while the census does include military housing, the estimates from the household auto ownership model do not. TABLE 3-5 Comparison of Household Auto Ownership Model Results (2002) and 2000 Census Proportion of Household Auto Ownership Groups (Totals for Anchorage Area) Household Category Model Model Group/ Total Census Census Group/ Total Zero Autos 7317.077 6013.063 One Auto 33643.354 33107.349 Two Autos 39725.418 39689.418 Three or More 14351.151 16035.169 Totals 95036 1.00 95114 1.00 3.5 Children per Household To support estimation of Home Based School trip productions, a cross classification model was developed to correlate the number of school aged children in a household to household size and number of workers in the household. ANC/TP41158.DOC/050460017 3-7

TRAVELER MARKET (HOUSEHOLD) SEGMENTATION 3-8 ANC/TP41158.DOC/050460017

SECTION 4 Trip Generation 4.1 Home Based Trip Production Models Trip generation models and rates are based on information from the 2002 Anchorage Household Travel Survey. Cross-classification methods were used to estimate the number of origins (or productions) associated with each of the four home based trip purposes. These models were developed by cross classifying the trips per household by trip purpose with associated market segments. Review of the associated rates and their ability to replicate totals from the travel survey were used as criteria for both selecting the cross classification dimensions associated with each trip purpose and for determination of the number of cross classification categories. Another criterion in this process was the feasibility of developing reasonable estimation models to predict membership in the cross classification categories. Categorical rates for home base work, home based shop, home based school and home based other trip purposes are presented in the four tables (Table 4-1 through 4-4) below. TABLE 4-1 Home Based Work Trip Rates (Workers/HH by Income Group) No of Workers/HH Low Income Medium Income High Income 0 0.170 0.170 0.170 1 1.170 1.220 1.390 2 2.350 2.440 2.780 3 or more 2.870 2.980 3.430 TABLE 4-2 Home Based Shopping Trip Rates (Household Size by Income Group) Persons/HH Low Income Medium Income High Income 1 0.42 0.47 0.47 2 0.55 0.64 0.64 3 0.57 0.71 0.88 4 or more 0.80 1.08 1.30 ANC/TP41158.DOC/050460017 4-1

TRIP GENERATION TABLE 4-3 Home Based School Trip Rates (Household Size by Children/HH) Persons/HH 1 Child 2 Children 3 or more Children 1 0.00 0.00 0.00 2 0.96 0.00 0.00 3 1.18 2.74 0.00 4 or more 2.40 2.35 4.36 TABLE 4-4 Home Based Other Trip Rates (Household Size by Income Group) Persons/HH Low Income Medium Income High Income 1 1.21 1.27 1.27 2 1.94 2.47 2.47 3 2.04 2.59 3.12 4 or more 4.06 5.44 5.71 These trip generation rates were applied and evaluated by comparing results obtained by their application the expanded totals from the household travel survey. These tests and an analysis of the outcomes is present in the Validation Results section at the end of Trip Generation (Section 4). 4.2 Non-Home Based Trip Production Models In addition to the four home based trip purposes, two additional trip purposes are used to describe the full range of non-commercial trips. The two purposes used for non-commercial trips are non-home based work and non-home based non-work. This distinction was applied to separate out those trips made from a work location to supplemental destinations such as midday trips to visit other businesses for work or personal reasons from other nonwork related non-home based trips. This separation of work-based and non-work based trips has been shown to improve the quality of small area forecasts of number, length and time of day of non-home based trips. The number of these non-home trips is more likely to be influenced by the characteristics of the location of their origin rather than the socio-economic characteristics of the traveler. Because of this, production models correlate these trips to inputs that describe the origin location such as the number of employees at a location. Typically, non-home based trip generation models are specified using such formulations as linear regression. In case of the 4-2 ANC/TP41158.DOC/050460017

TRIP GENERATION Anchorage model, the production models for both non home-based work and non-work are specified as linear regression equations. The equations are presented below. For non-home based work, the final estimated equation was: NHBW Productions=0.809*Total Employment For non-home based non-work, the final estimated equation was: NHBNW Productions= 0.222*Population+ 4.000*Adjusted 1 Retail Employment+ 0.487*Other Employment+ 0.299*Number of Households 4.3 Commercial Vehicle (Truck) Trips The commercial and truck trip generation model previously developed by AMATS was reused. This model is based on a set of standard equations for trip generation developed by the Federal Highway Administration as part of the Quick Response Freight Estimation Method. The FHWA methodology specifies a set of procedures to, first, apply and, then, adjust the generic models based on available local data. These procedural steps were followed and applied as part of AMATS previous calibration process. Full documentation of this model and calibration process is provided as Appendix C Commercial Vehicle Travel Model of this report. (Note that further refinements in truck trip generation rates were formulated for Anchorage special generators). 4.4 Trip Attraction Models To complete the trip generation model set, a set of models were developed to identify where the trip productions were bound that is, the trip attraction end of each trip. As in the case of non-home based trip generation, these trip attraction models are based on the zonal characteristics of potential destination zones and are typically formulated as linear regressions. Information from the 2002 Anchorage Household Travel Survey regarding the destinations of travelers by trip purposes was tallied for each TAZ, together with the information from the land use, employment, and demographic inventories. Regression analysis was applied to this composite TAZ dataset to develop trip attraction equations for each trip purpose. These equations are presented below. Home based work attractions: HBW Attractions=0.994*Total Employment Home based shopping attractions: HBS Attractions=2.314* Adjusted 1 Retail Employment+ 3.080*Construction Employment Home based school attractions: HBSCH Attractions=2.091*Number of Students ANC/TP41158.DOC/050460017 4-3

TRIP GENERATION Home based other attractions: HBO Attractions=0.484*Population+ 3.344* Adjusted 1 Retail Employment+ 0.773*Health Services Employment+ 1.576*Educational Employment+ 0.481*Service (inc FIRE 2 ) Employment+ 3.256*Construction Employment Non-home based work attractions: NHBW Attractions=2.327*Government Employment+ 3.287* Educational Employment+ 0.746* Service (inc FIRE 2 ) Employment+ 1.285* Industrial 3 Employment Non-home based non-work attractions: NHBNW Attractions=0.154*Population+ 3.830* Adjusted 1 Retail Employment+ 3.619*Educational Employment+ 0.592*Service (inc FIRE 2 ) Employment+ 1.704*Construction Employment 4.5 Special Generators/Visitors In addition to the trip generation based directly on zonal households and employment, the AMATS travel model incorporates the following two additional trip generation elements: 1. Estimates of trips to and from a range of special uses (e.g. airports, universities and military bases) that cannot be adequately accounted for using the standard methods described above. 2. Estimates of trips made by non-resident visitors. These two models are described below. The special generators model specifies tripmaking rates and the distribution of trips into the defined trip purposes. In most cases, all special generator trips are attractions (i.e. non-home destinations of home based or other trips being made). However, some uses also generate productions such as residential students at a college or university. The AMATS travel model design also incorporates truck trip generation for some of the special uses. Table 4-5 lists specific uses that were incorporated as special generators in the travel model. A complete listing of the associated trip rates, trip rate basis and purpose/production-attraction breakdowns is provided in Appendix D Special Generators. 4-4 ANC/TP41158.DOC/050460017

TRIP GENERATION TABLE 4-5 Special Generators Elmendorf AFB-Post Rd Gate Ft Richardson Ft Richardson (Trucks only) Ship Creek (Port Area) Ship Creek (Port Trucks only) Columbia Hospital Columbia Hospital (Trucks only) University of Alaska University of Alaska (Trucks only) Alaska Pacific University Alaska Pacific University (Trucks only) Providence Medical Center Providence Medical Center (Trucks only) Loussac Public Library Alaska Native Hospital Alaska Native Hospital (Trucks only) Stevens International Airport Stevens International Airport (Trucks only) Air National Guard Base Eagle River Landfill Out of Area Trips (North) Out of Area Trips (South) Elmendorf AFB-Gov't Hill Gate Elmendorf AFB-Boniface Gate The visitor model predicts the number of trips made by visitors staying at area hotels and motels. There are three inputs to the model, as follows: An inventory of the hotels/motels; their locations in the model area; and the number of guest rooms An estimate of expected hotel occupancy based on type of property and location (currently, the travel model uses three different levels of occupancy) An estimated rate of person trips per occupied room (these trips are treated as home based other productions at the hotel/motel sites) The 2002 hotel/motel inventory and assumed occupancy for each property is provided in Appendix E Hotel/Motel Visitor Model. Based on Institute of Transportation Engineers studies and other trip generation research, the trip rate used is 8.3 trips per occupied room. ANC/TP41158.DOC/050460017 4-5

TRIP GENERATION 4.6 Other Special Considerations Early results from the trip generation process indicated that significant underprediction of total trips was occurring in the vicinity of big box (e.g. Wal-Mart) stores. To correct this, these zones were identified as SPECIAL RETAIL ZONES (SRZ s) and trip rates were adjusted accordingly from national research data. Recent work in evaluating differences between trip generation for big box retail versus other retail, retail employment-related attractions for the home based shopping and home based other trip purposes was examined. This resulted in increasing home based shopping and home based other trip purposes attractions rates for SRZ s by multiplying times 2.644. 4.7 Validation Results After completing specification of all trip generation models, the models were scripted and then applied to the 2002 socio-economic database to test their ability to replicate existing travel. Results of the trip generation process were compared by trip purpose for the Anchorage area. The comparison is not exact because of influences of the special generator, external and visitor trips. Some of these trips are only partially or are not represented in the survey. Table 4-6 shows the comparison of survey vs. model generated total trips by trip purpose. TABLE 4-6 Total Trips by Trip Purpose (Survey-Model Comparison) Trip Purpose Survey Model Survey/Model Home based Work 172600 175500 0.983 Home based Shop 71400 70000 1.020 Home based School 103800 101300 1.024 Home based Other 287500 320000 0.898 Non-home based Work 107100 111300 0.962 Non-home based Nonwork 184600 210300 0.878 All Areas 927000 988400 0.938 The conclusion that can be drawn from this is that approximately 6% of daily person tripmaking is externally or visitor based. A second comparison was made to examine the geographical distribution of trip generation. Total surveyed trips (expanded) by community council area were plotted against total modeled trips for the same areas and the correlation coefficient between the parallel data points was calculated. This plot is shown as Figure 4-1 below. 4-6 ANC/TP41158.DOC/050460017

TRIP GENERATION Survey vs Model Trips Model Trips by Community Council 300000 250000 200000 150000 100000 50000 0 R 2 = 0.9455 0 50000 100000 150000 200000 250000 300000 Survey Trips by Community Council FIGURE 4-1. SURVEY VS. MODELED TRIPS BY COMMUNITY COUNCIL AREA The results show that the trip generation and attractions models developed for Anchorage correlate well on a aggregate basis to observed data from the household survey. For reference, a R 2 (correlation coefficient) of one point zero (1.0) indicates a perfect match. Zero indicates no discernable relationship between two groups of data. ANC/TP41158.DOC/050460017 4-7

TRIP GENERATION 4-8 ANC/TP41158.DOC/050460017

SECTION 5 Trip Distribution Trip distribution models use the estimates of trips produced and trips attracted in an area as inputs to creating patterns of origins and their associated destinations. The Anchorage travel model utilizes two types of trip distribution models. First, a gravity model which utilizes a trip length frequency distribution from local survey data to attempt to replicate current trip patterns based on matching the associated trip length distribution for each trip purpose. Trip lengths are specified in minutes to account for delays encountered, differential speeds of different travel modes, etc. To ensure that survey vs. model trip characteristics are comparable, the starting point for this process is to use the calculated paths in the travel model network to estimate trip lengths for both survey and model trips. The second method is a growth or Fratar model. Unlike a gravity model, the Fratar model does not consider how network operating characteristics may impact travel behavior. The Fratar model starts from an existing condition table of trip interchange data and grows those interchanges based on newly input zonal totals for productions and attractions. Fratar models are typically used where either network conditions over time are expected to remain reasonably stable or where destination choice is not a function of the characteristics of the origin-destination path chosen. In the Anchorage case, Fratar distribution was used for the home based school trip purpose only. The gravity model distribution is used for all other trip purposes. The gravity model is calibrated mathematically by, given the input data, attempting to match each one minute interval (1 to 60 minutes) with the associated proportion of survey trips of that length. In the case of the Anchorage model, this produced discontinuous relationships due to the lumpiness of the survey data. The original curves were smoothed to provide a continuous function. Although the trip distribution models are executed on a time period specific basis, only one daily average curve is used for each trip purpose. For this reason, only daily trip frequency distributions are considered here. It should be noted that inputs to the trip distribution process are stratified by time period. When the model is run using feedback to the distribution process, inputs to distribution include link travel times stratified by time of day period. Distribution for each time period is calculated separately. Because the Anchorage model uses distribution feedback, the trip distribution curves had to be readjusted to consider the feedback effects. Table 5-1 shows the comparison between the survey and travel model average trip lengths by trip purpose and overall. ANC/TP41158.DOC/050460017 5-1

TRIP DISTRIBUTION TABLE 5-1 Average Trip Length (in Minutes) by Trip Purpose Trip Purpose Survey Model Survey/Model Home based Work 12.038 13.354 0.902 Home based Shop 9.566 9.600 0.996 Home based School 9.016 5.578 1.616 Home based Other 9.657 10.638 0.908 Non-home based Work 8.448 7.426 1.138 Non-home based Non-work 9.037 8.554 1.056 All Areas 9.863 10.219 0.965 Longer trip lengths for home based work trips and home based other trips in the model are largely due to the inclusion of through (trips which begin or end outside of the study area) trips in the statistics. Using the corresponding trip lengths but excluding through trips, the home based work and home based other average lengths are about 12.2 and 8.3 minutes respectively. The significantly shorter trip length for home based school trips is based on growing the ASD attendance database; not on a trip length based model. The likely cause of the difference is underreporting in the survey of the shorter, mostly non-motorized, trips. These would be trips made by children walking or riding their bikes to school whose travel was not captured in the survey. Given the incidental nature of many non-home based work trips, it s likely that differences in the survey and model average trip lengths can be attributed to a similar cause. Figures 5-1 through 5-6 detail the relationship between the surveyed trip distribution and modeled trip distribution for each trip purpose. 5-2 ANC/TP41158.DOC/050460017

TRIP DISTRIBUTION HBW Daily Trip Distribution No of Trips 16000.00 14000.00 12000.00 10000.00 8000.00 6000.00 4000.00 2000.00 0.00 Model Daily Survey Daily 1 6 11 16 21 26 31 36 41 46 51 56 Minutes Figure 5-1. Survey vs. Model Trip Length Frequencies (Home based work) HBS Daily Trip Distribution 9000.00 8000.00 7000.00 No of Trips 6000.00 5000.00 4000.00 3000.00 2000.00 1000.00 0.00 Model Daily Survey Daily 1 6 11 16 21 26 31 36 41 46 51 56 Minutes Figure 5-2. Survey vs. Model Trip Length Frequencies (Home based shop) ANC/TP41158.DOC/050460017 5-3

TRIP DISTRIBUTION HBSch Daily Trip Distribution 25000.00 20000.00 No of Trips 15000.00 10000.00 Model Daily Survey Daily 5000.00 0.00 1 6 11 16 21 26 31 36 41 46 51 56 Minutes Figure 5-3. Survey vs. Model Trip Length Frequencies (Home based school) HBO Daily Trip Distribution 35000.00 30000.00 25000.00 No of Trips 20000.00 15000.00 10000.00 Model Daily Survey Daily 5000.00 0.00 1 6 11 16 21 26 31 36 41 46 51 56 Minutes Figure 5-4. Survey vs. Model Trip Length Frequencies (Home based other) 5-4 ANC/TP41158.DOC/050460017

TRIP DISTRIBUTION NHBW Daily Trip Distribution 12000.00 10000.00 No of Trips 8000.00 6000.00 4000.00 Model Daily Survey Daily 2000.00 0.00 1 6 11 16 21 26 31 36 41 46 51 56 Minutes Figure 5-5. Survey vs. Model Trip Length Frequencies (Non-home based work) NHBNW Daily Trip Distribution 25000.00 20000.00 No of Trips 15000.00 10000.00 Model Daily Survey Daily 5000.00 0.00 1 6 11 16 21 26 31 36 41 46 51 56 Minutes Figure 5-6. Survey vs. Model Trip Length Frequencies (Non-home based non-work) Generally, the graphs show a good correspondence between the survey trip distributions and the model trip distributions. The difference in absolute magnitudes of the non-home ANC/TP41158.DOC/050460017 5-5

TRIP DISTRIBUTION based non-work distribution is a reflection of the model trips which start or end outside of the study area; these trips are not included in the household survey trip set. 5-6 ANC/TP41158.DOC/050460017

SECTION 6 Time of Day Factoring Time of day factoring is the straightforward process of converting the trip distribution outputs to a set of triptables that correctly represent the percent of trips in the AM, PM, and off peak periods and their directional orientation. To perform this step, these factors were developed directly from the 2002 household travel survey. The three sets of time period factors are provided in the tables below. TABLE 6-1 AM Peak Period Trip Purpose and Directional Factors Trip Purpose % Trip in Period % Home Origins % Home Destinations Home based work 25.7 95.5 4.5 Home based shop 2.5 79.4 20.6 Home based school 43.2 97.2 2.8 Home based other 14.4 79.8 20.2 Non-home based work a 14.3 81.5 18.5 Non-Home based non-work 7.6 50.0 50.0 Trucks 6.0 50.0 50.0 a For Non-home based work trips, % Home Origins is the percent of trips with a work origin, % Home Destinations is percent of trips with a work destination. TABLE 6-2 PM Peak Period Trip Purpose and Directional Factors Trip Purpose % Trip in Period % Home Origins % Home Destinations Home based work 28.1 13.4 86.6 Home based shop 28.1 35.9 64.1 Home based school 30.9 9.6 90.4 Home based other 25.5 44.9 55.1 Non-home based work a 27.6 17.5 82.5 Non-Home based non-work 26.0 50.0 50.0 Trucks 25.0 50.0 50.0 a For Non-home based work trips, % Home Origins is the percent of trips with a work origin, % Home Destinations is percent of trips with a work destination. ANC/TP41158.DOC/050460017 6-1

TIME OF DAY FACTORING TABLE 6-3 Off Peak Period Trip Purpose and Directional Factors Trip Purpose % Trip in Period % Home Origins % Home Destinations Home based work 46.2 50.0 50.0 Home based shop 69.4 50.0 50.0 Home based school 26.0 50.0 50.0 Home based other 60.1 50.0 50.0 Non-home based work a 58.1 50.0 50.0 Non-Home based non-work 66.4 50.0 50.0 Trucks 69.0 50.0 50.0 a For Non-home based work trips, % Home Origins is the percent of trips with a work origin, % Home Destinations is percent of trips with a work destination. After the person trip-tables output by the trip distribution model are factored into tables representing directional trips by time period, this data is input into the mode choice models to determine shares of tripmaking by specific travel modes. 6-2 ANC/TP41158.DOC/050460017

SECTION 7 Mode Choice Mathematically, the mode choice models are the most complex models used in the Anchorage travel model process. Also, in order to measure competition between travel modes, they also have the largest input data requirements. Mode choice modeling in the Anchorage model is stratified in three dimensions: Trip purposes are modeled separately Within each trip purpose, time periods are modeled separately Within each time period and trip purpose, specific traveler markets are modeled separately for the home based trip purposes Mode choice models were separately defined and calibrated for each of the six person based trip purposes (not trucks). The impact of time periods is represented through supplying information regarding network conditions (e.g. road speeds, bus service frequencies) that is specific to the time period in question. Traveler market segments are represented through calibrated parameters used in the trip-purpose-specific mode choice model. Operationally, separate mode choice model runs are made for each segment (within a given trip purpose and time period) and then these results are combined to represent the time period totals. This is shown in the Model Overview flowchart (Figure 2-1). In the Anchorage model, mode choice considers the following modal options: Auto drive alone Auto drive with passenger Auto passenger Public Transit/School Bus Transit Walking Bicycling In the case of transit modes, all trip purposes except home base school estimate public transit trips. Home based school estimates school bus trips. Table 7-1 lists the variables used in the mode choice models and their description. (Note: the variables, which define market segments are defined and listed separately in the following section. ANC/TP41158.DOC/050460017 7-1

MODE CHOICE TABLE 7-1 Complete List of Mode Choice Variables (All Purposes) Variable Models Using Description In-vehicle Travel Time (IVTT) Out-of--vehicle Travel Time (OVTT) Autos Available per Person (AUTOPP) No of Workers per Household (NWHH) All All HBW, HBS, HBO HBW, HBSch Time spent traveling in or on a vehicle. Typically valued lower than time spent waiting for or accessing a mode. Time spent waiting for or accessing a mode. (Walk travel time for the walk mode is not considered to be OVTT). Measured at the TAZ level as zonal auto ownership divided by zonal population Measured at the TAZ level as zonal workers divided by zonal households Total Employment within 1 mile (D_TEMP1) HBW,HBO,NHBW Measured with GIS as the sum of zonal employment within 1 mile of the center of the destination zone adjusted by the percentage of the adjacent zones within the 1 mile radius Total Employment within ½ mile (D_TEMPH) Non-retail Employment within 1/2 mile (D_NREMPH) Average Size per Household (HHSIZE) Average No of Children per Household (AVCHH) Origin Walk Node Density (O_WALKDENS) Destination Walk Node Density (D_WALKDENS) Origin Zone Retail to Total Employment Ratio (O_RERATIOH) Destination Zone Retail to Total Employment Ratio (D_RERATIOH) HBS, NHBNW HBS HBSch HBSch HBSch, NHBW, NHBNW HBSch NHBW NHBW Measured with GIS as the sum of zonal employment within ½ mile of the center of the destination zone adjusted by the percentage of the adjacent zones within the ½ mile radius Measured with GIS as the sum of zonal non-retail employment within ½mile of the center of the destination zone adjusted by the percentage of the adjacent zones within the ½ mile radius Measured at the TAZ level as zonal population divided by zonal households Measured at the TAZ level as zonal number of children divided by zonal households Measured with GIS as the sum of connections (nodes) within ½ mile of the center of the origin zone from detailed network map (not the model network) Measured with GIS as the sum of connections (nodes) within ½ mile of the center of the destination zone from detailed network map (not the model network) Measured with GIS as the sum of zonal retail employment within ½ mile of the center of the origin zone divided by corresponding total employment and adjusted by the percentage of the adjacent zones within the ½ mile radius Measured with GIS as the sum of zonal retail employment within ½ mile of the center of the destination zone divided by corresponding total employment and adjusted by the percentage of the adjacent zones within the ½ mile radius Origin Zone Parking Cost (O_PARKCOST) NHBW, NHBNW Assumed monthly parking charge for origin zone (in 2002 dollars) Destination Zone Parking Cost (D_PARKCOST) Downtown Zone (CBD) NHBW, NHBNW NHBNW Assumed monthly parking charge for destination zone (in 2002 dollars) Identifies trip either starts or ends in downtown zone 7-2 ANC/TP41158.DOC/050460017

MODE CHOICE 7.1 Home Based Work Mode Choice The home based work mode choice model is run separately for four defined market segments. These include the following: Low income-one worker households Low income-two or more worker households Medium and above income- one worker households Medium and above income-two or more worker households Table 7-2 shows the list of variables and the associated coefficients used in the home based work mode choice models. Coefficients provided for the specific market groups listed above are only used in the models applied for those specific market segments (these variables and coefficients appear last and are underlined). TABLE 7-2 Home Based Work Mode Choice Model Variables and Coefficients Variable Drive Alone Drive w/ Passenger Auto Passenger Public Transit Walking Bicycling Model Constant -1.9766-1.6963 0.6550-0.8822-5.8168 IVTT -0.0804-0.0804-0.0804-0.0804-0.0804-0.0804 OVTT -0.1206-0.1206-0.1206 AUTOPP -0.5522-1.1232-2.1585 NWHH 0.2161 Ln(D_TEMP1) 0.3604 1 Worker Household -0.5197 Low Income Household 2.9013 0.9052 7.2 Home Based Shop Mode Choice The home based shop mode choice model is run separately for four defined market segments. These are: Low income-three or more person households Low income-one and two person households Medium and above income- three or more person households Medium and above income- one and two person households Table 7-3 shows the list of variables and the associated coefficients used in the home based shop mode choice models. Coefficients provided for the specific market groups listed above ANC/TP41158.DOC/050460017 7-3

MODE CHOICE are only used in the models applied for those specific market segments (these variables and coefficients appear last and are underlined). TABLE 7-3 Home Based Shop Mode Choice Model Variables and Coefficients Variable Drive Alone Drive w/ Passenger Auto Passenger Public Transit Walking Bicycling Model Constant -0.7321-0.1081-2.1997-2.7804-3.3619 IVTT -0.0693-0.0693-0.0693-0.0693-0.0693-0.0693 OVTT -0.1040-0.1040-0.1040 AUTOPP -0.4342-4.6678-1.9654 D_NREMPH 0.0008 Ln(D_TEMPH) 0.5641 3 or More Person HH 0.7126 1.0733 Low Income Household 1.6626 7.3 Home Based School Mode Choice The home based school mode choice model is produces estimates of mode share for the dive alone, drive with passenger, auto passenger, walking, bicycling and school bus. This model does not estimate public transit mode share and no market segment stratification is used. Table 7-4 shows the list of variables and the associated coefficients used in the home based school mode choice models. TABLE 7-4 Home Based School Mode Choice Model Variables and Coefficients Variable Drive Alone Drive w/ Passenger Auto Passenger School Bus Walking Bicycling Model Constant 6.8889 4.0282 2.1906 2.4959 5.5937 IVTT -0.0001-0.0001-0.0001-0.0001-0.0001-0.0001 Trip Mileage -0.0575 HHSIZE 0.8414 1.6953 1.3040 1.3801 1.6914 NWHH 0.5194-0.5041-1.0928 AVCHH 0.0459-0.1652 0.0409 0.1801-0.3482 O_WALKDENS -0.0058-0.0086 0.0060 0.0066 D_WALKDENS 0.0213 0.0128 0.0259 0.0164 7-4 ANC/TP41158.DOC/050460017

MODE CHOICE 7.4 Home Based Other Mode Choice The home based other mode choice model is run separately for two defined market segments. These are: Three or more person households One and two person households Table 7-5 shows the list of variables and the associated coefficients used in the home based other mode choice models. Coefficients provided for the specific market groups listed above are only used in the models applied for those specific market segments (these variables and coefficients appear last and are underlined). TABLE 7-5 Home Based Other Mode Choice Model Variables and Coefficients Variable Drive Alone Drive w/ Passenger Auto Passenger Public Transit Walking Bicycling Model Constant -0.2192 0.4757-2.7682-2.8514-2.3935 IVTT -0.0716-0.0716-0.0716-0.0716-0.0716-0.0716 OVTT -0.1075-0.1075-0.1075 AUTOPP -0.4686-0.8712-3.2475-1.6513 D_TEMP1 0.0003 0.0004 3 or More Person HH 0.6910 1.0074 7.5 Non-Home Based Trip Mode Choice The non-home based trip mode choice models is produces estimates of mode share for trips with one end at work and the other end at some location other than the traveler s home and where the trip both originate at and is destined to a non home-non work location. The mode choice models for non-home based trips rely on knowledge of the characteristics of the origin and destination locations, not of the characteristics of the traveler. The tables below shows the list of variables and the associated coefficients used in the two non-home based trip mode choice models. ANC/TP41158.DOC/050460017 7-5

MODE CHOICE TABLE 7-6 Non-Home Based Work Mode Choice Model Variables and Coefficients Variable Drive Alone Drive w/ Passenger Auto Passenger Public Transit Walking Bicycling Model Constant -1.9430-1.6368-1.6974-3.4902-7.4196 IVTT -0.0669-0.0669-0.0669-0.0669-0.0669-0.0669 OVTT -0.1003-0.1003-0.1003 O_WALKDENS 0.0004 O_RERATIO 1.8802 D_RERATIO 1.8802 Ln(D_TEMP1) 0.0734 O_PARKCOST -0.0064-0.0064-0.0064 D_PARKCOST -0.0064-0.0064-0.0064 TABLE 7-7 Non-Home Based Non-work Mode Choice Model Variables and Coefficients Variable Drive Alone Drive w/ Passenger Auto Passenger Public Transit Walking Bicycling Model Constant -0.6652-0.1704-3.3072-3.8852-6.1466 IVTT -0.0565-0.0565-0.0565-0.0565-0.0565-0.0565 OVTT -0.0847-0.0847-0.0847 O_WALKDENS 0.0010 CBD 0.7528 0.7528 0.7528 0.7528 0.7528 0.7528 Ln(D_TEMPH) 0.2357 O_PARKCOST 0.0107 0.0107 0.0107 D_PARKCOST 0.0107 0.0107 0.0107 7.6 Validation Results Following the calibration and final adjustment of the mode choice models, the models were applied to forecast 2002 mode choice using the 2002 socio-economic database, travel networks and related assumptions. These forecasts were compared to the mode shares from the household travel survey. The survey data for public transit was also checked and adjusted on the basis of transit rider counts from 2003 to improve the allocation of trips by time of day. Table 7-8 through 7-14 presents the results of this comparison. Information 7-6 ANC/TP41158.DOC/050460017

MODE CHOICE included is number of survey vs. model trips by mode by trip purpose and for the system as a whole. Each table presents the following for each trip purpose: Survey and model trip totals Ratio between the two totals Absolute difference between the two totals Resulting difference of estimated mode share TABLE 7-8 Survey vs. Model Mode Shares for Home Based Work Trips Mode Survey Model Ratio Diff Share Diff DA 143527 142283 0.991 1244 0.006 DP 9768 9637 0.987 131 0.001 AP 11143 10996 0.987 147 0.001 TR 4564 4609 1.010-45 0.000 WALK 5043 6219 1.233-1176 -0.007 BIKE 1683 1837 1.092-154 -0.001 AUTO 153295 151920 0.991 1375 0.007 TOTAL 175728 175581 0.999 147 0.000 TABLE 7-9 Survey vs. Model Mode Shares for Home Based Shop Trips Mode Survey Model Ratio Diff Share Diff DA 36014 34847 0.968 1167 0.002 DP 13920 13481 0.968 439 0.000 AP 18102 17523 0.968 579 0.001 TR 1625 1565 0.963 60 0.000 WALK 2022 2143 1.060-121 -0.003 BIKE 407 432 1.061-25 -0.001 AUTO 49934 48328 0.968 1606 0.002 TOTAL 72090 69991 0.971 2099 0.000 ANC/TP41158.DOC/050460017 7-7

MODE CHOICE TABLE 7-10 Survey vs. Model Mode Shares for Home Based School Trips Mode Survey Model Ratio Diff Share Diff DA 0 7 0.000-7 0.000 DP 31863 32008 1.005-145 0.006 AP 31064 31660 1.019-596 0.001 SB 20773 22004 1.059-1231 -0.007 WALK 14763 15072 1.021-309 0.000 BIKE 3996 4069 1.018-73 0.000 AUTO 31863 32015 1.005-152 0.006 TOTAL 102459 104820 1.023-2361 0.000 TABLE 7-11 Survey vs. Model Mode Shares for Home Based Other Trips Mode Survey Model Ratio Diff Share Diff DA 118049 132311 1.121-14262 -0.002 DP 59580 65806 1.105-6226 0.002 AP 84248 92436 1.097-8188 0.005 TR 3251 3002 0.923 249 0.002 WALK 18643 21915 1.176-3272 -0.004 BIKE 3423 4565 1.334-1142 -0.002 AUTO 177629 198117 1.115-20488 -0.001 TOTAL 287194 320035 1.114-32841 0.000 Note: Model Totals include Hotel Visitor Model Trips 7-8 ANC/TP41158.DOC/050460017

MODE CHOICE TABLE 7-12 Survey vs. Model Mode Shares for Non-Home Based Work Trips Mode Survey Model Ratio Diff Share Diff DA 77965 82575 1.059-4610 0.001 DP 8267 8756 1.059-489 0.000 AP 9188 9730 1.059-542 0.000 TR 500 583 1.166-83 0.000 WALK 10453 11323 1.083-870 -0.002 BIKE 327 255 0.780 72 0.001 AUTO 86232 91331 1.059-5099 0.002 TOTAL 106700 113222 1.061-6522 0.000 TABLE 7-13 Survey vs. Model Mode Shares for Non-Home Based Non-work Trips Mode Survey Model Ratio Diff Share Diff DA 85847 102078 1.189-16231 0.006 DP 33488 40704 1.215-7216 -0.002 AP 46365 56354 1.215-9989 -0.003 TR 750 955 1.273-205 0.000 WALK 7571 9295 1.228-1724 -0.001 BIKE 726 888 1.223-162 0.000 AUTO 119335 142782 1.196-23447 0.004 TOTAL 174747 210274 1.203-35527 0.000 ANC/TP41158.DOC/050460017 7-9

MODE CHOICE TABLE 7-14 Survey vs. Model Mode Shares for All Purposes Mode Survey Model Ratio Diff Share Diff DA 461402 494101 1.071-32699 0.005 DP 156886 170392 1.086-13506 -0.001 PA 200110 218699 1.093-18589 -0.002 TR 10691 10714 1.002-23 0.001 SB 20773 22004 1.059-1231 0.000 WALK 58495 65967 1.128-7472 -0.003 BIKE 10562 12046 1.141-1484 -0.001 AUTO 618288 664493 1.075-46205 0.004 TOTAL 918919 993923 1.082-75004 0 Examining the predicted vs. observed mode shares indicates that given similar assumptions regarding socio-economic conditions and networks, the model has the ability to reproduce the observed mode choice behavior. 7-10 ANC/TP41158.DOC/050460017

SECTION 8 Traffic Assignment and Volumes One of the most important indicators of model performance is the direct measurement of how well the travel model, in an attempt to replicate base (in this case, 2002) conditions can mimic existing traffic conditions as indicated by field counts of traffic volumes throughout the network. Such model validation is industry standard practice and a necessary prerequisite to using the model to forecast expected futures. To guide travel modelers in establishing minimum standards for the travel model development process, the Federal Highway Administration has published a set of guidelines for acceptable performance. To validate the Anchorage model, four different types of model performance were measured. These included the following: Measured versus modeled aggregate traffic counts for selected cordons or cutline crossings Percent difference in volume between measured and modeled stratified by facility type Correlation measures between measured and modeled volumes for all available count locations Comparison of measured and modeled volumes at individual locations. The count data used for comparison was all day weekday traffic counts for 2002. Sources were both ADOT and MOA counts supplied for this purpose and the ADOT Volumes map for the Anchorage and the Eagle River areas. These observed volumes were compared to the sum of the AM, PM and off peak period outputs for the 2002 Base travel model alternative utilizing trip distribution feedback. The results of each of these comparisons along with the corresponding Federal guidelines are presented below. 8.1 Cordon Crossings Measurement of traffic across cordons or screenlines provides an indication of how well the model performs in replicating major trip patterns and movements throughout the network. Cordons typically encompass all facilities that serve the same definable travel corridor. This allows for the fact that the model may not perfectly represent competition between parallel facilities. Federal guidelines for acceptable performance are based on a sliding scale which ranges from acceptable deviations of 65% for 5000 vehicles to 15% for 200,000 of more vehicles (Figure 8-1). ANC/TP41158.DOC/050460017 8-1

TRAFFIC ASSIGNMENT AND VOLUMES 0.7 0.6 0.5 Deviation 0.4 0.3 0.2 0.1 0 5 15 25 45 65 85 105 125 145 165 185 200 250 Volume(1000's) Figure 8-1. Maximum Desirable Deviation in Total Screenline Volumes For evaluating the Anchorage model s performance, 23 separate cordons were defined. These ranged from specific east-west and north-south crossings in the downtown area to longer cordons which, in some cases, bisect the entire Anchorage Bowl. The cordons used and their associated identifiers are shown in Figure 8-2. Once the cordons were defined, special procedures were written to automatically generate inputs to a set of spreadsheets to report their performance both in tabular and graphic form. The resulting spreadsheet reports which list and display counted and modeled traffic volumes for all links intersected by each cordon are provide as Appendix F Screenlines. Table 8-1 itemizes performance of each cordon along with the measured deviation and the corresponding maximum deviation based on the Federal guideline. (Diff equals actual difference Max Diff equals maximum desirable difference based on Federal guideline). Based on Table 8-1, all cordons meet or exceed Federal guidelines. Of the 23, only six cordon have deviations greater than 0.10 and no screenlines have deviations greater than 0.20. Also, there does not seem to be any discernable pattern linking the cordons with a greater than 0.10 deviation. They are distributed throughout the study area. This is an indicator that there is no systematic bias in the model process. Examination of graphs showing the relative facility counts and volumes for each cordon (Appendix F Screenlines), shows that, in almost all cases, the relative magnitude of traffic volumes on specific facilities in a given corridor (i.e. for a given cordon) correlates well with observed count data. 8-2 ANC/TP41158.DOC/050460017

TRAFFIC ASSIGNMENT AND VOLUMES Figure 8-1 ANC/TP41158.DOC/050460017 8-3

TRAFFIC ASSIGNMENT AND VOLUMES TABLE 8-1 Summary of 2002 Weekday Cordon Counts/Volumes and Differences ID Cordon Count Volume Diff Max Diff 101 N of Tudor Rd Minnesota to Muldoon 251582 213846 0.150 0.150 201 N of Dimond Av Minnesota to Birch 152853 148502 0.028 0.201 301 S of O'Malley C St to Hillside 73446 69282 0.057 0.288 401 S of Glenn Hwy Ingra to Muldoon 133621 117008 0.124 0.217 501 W of Muldoon Tudor Rd to Glenn Hwy 104740 100093 0.044 0.245 601 W of Boniface Tudor Rd to Davis 144484 146529 0.014 0.213 602 W of Birch Rabbit Creek to Abbott 25010 26068 0.042 0.416 701 E of Lake Otis Tudor Rd to Commercial Rd 193863 189001 0.025 0.172 702 E of Lake Otis De Armoun to Dowling 57459 61801 0.076 0.317 801 E of New Seward Rabbit Creek to 3rd 295053 279182 0.054 0.123 901 S of Int'l Airport Minnesota to Lake Otis 212495 197652 0.070 0.162 1001 S of Dimond Minnesota to Birch 117861 97897 0.169 0.232 2001 N of Eagle River Glenn Hwy 24599 24443 0.006 0.418 2002 N of Eagle River Rd Access Glenn to Birchwood 37470 35613 0.050 0.368 2003 S of Hiland Glenn Hwy 48224 56701 0.176 0.338 2005 N of 3rd St C St to Port Access 19071 19809 0.039 0.448 2006 W of Gambell -3rd St to 16th 72766 62875 0.136 0.305 2007 S of 9th L St to Medfra 112614 109349 0.029 0.311 2008 E of Ingra 3rd to 15th 76077 81407 0.070 0.284 2010 N of Fireweed/Northern Lights Minnesota to 229702 217208 0.054 0.153 2013 M ldoon E of Northwood Northern Lights to Int'l Airport 83372 80889 0.030 0.273 2014 N of Int'l Airport Spenard to Lake Otis 226517 217426 0.040 0.154 2016 W of Minnesota Raspberry to Klatt 68604 56806 0.172 0.362 2020 S End of Study Area Seward Hwy 8960 8754 0.023 0.538 Combined Cordon Totals 2770443 2618141 0.055 Note: Differences >0.10 are highlighted 8.2 Facility Type Comparisons The second validation test performed on the Anchorage model was to compare the percentage of measured versus modeled traffic for different facility types. This measures how well assumed and calculated speeds in the model are distributing traffic between the different types of facilities present in the model. As with cordons, FHWA has developed guidelines to measure what is considered to be acceptable performance for a travel model. 8-4 ANC/TP41158.DOC/050460017

TRAFFIC ASSIGNMENT AND VOLUMES The facility types specified for comparison in the Federal guidelines are Freeways, Major Arterials, Minor Arterials and Collectors. To create a basis for comparison with the defined facility classes, the Anchorage model designations were grouped into these four categories using the following rules. Freeways were designed as Freeways (CLASS=1); Expressways and major arterials were designated as Major Arterials (CLASS=2,3); Minor arterials and frontage roads were designated as Minor Arterials (CLASS=4); Collectors and local roads were designated as Collectors (CLASS=5,6). Counts and volumes for each category were summarized and then the aggregate difference was compared to the corresponding Federal guideline. This summary is presented below in Table 8-2. TABLE 8-2 Summary of 2002 Weekday Facility Class Counts/Volumes and Differences Facility Class Count Volume Diff Max Diff Freeway 1049059 1066200 1.016 0.070 Major Arterial 4696423 4390255 0.935 0.100 Minor Arterial 1511410 1236461 0.818 0.150 Collector 442589 318774 0.720 0.250 All Classes 7699481 7011690 0.911 As the table indicates, measured and modeled volumes for freeways and major arterials are well within the identified targets. For minor arterials and collectors the model is slightly underpredicting but is within 5% of the targets in both cases. Particularly for the most significant facilities, this indicates good correspondence with traffic count information. This conclusion is reinforced by the results of statistical analysis presented below. 8.3 Comparisons of Statistical Performance While both the cordon and facility class comparisons use a subset of the count information, the third performance evaluation approach used measures the overall statistical performance of the model by comparing all available counts to corresponding model volumes. Figure 8-3 is a scattergram, which shows all measured and modeled volumes pairs. Fitting a linear function to this dataset yields an R 2 or correlation coefficient of.9043, which exceeds the Federal guideline of.880. The second statistical measure used is rootmean-square-error (RMSE). The RMSE for the same dataset is 29.15. This RMSE value is comparable with findings for other regional travel models (no Federal guidelines are proscribed). ANC/TP41158.DOC/050460017 8-5

TRAFFIC ASSIGNMENT AND VOLUMES Counts/Volumes Travel Model Volumes 70000 60000 50000 40000 30000 20000 10000 0 R 2 = 0.9043 0 10000 20000 30000 40000 50000 60000 Daily Traffic Counts Figure 8-3. STATISTICAL COMPARISON OF ALL AVAILABLE MEASURED AND MODELED 2002 WEEKDAY TRAFFIC VOLUMES 8.4 Individual Link Performance Federal guidelines are also provided for percent difference targets between measured and modeled traffic volumes for individual links based on total link volume. These targets are listed in Table 8-3. TABLE 8-3 Percent Difference Targets for Daily Volumes for Individual Links Average Annual Daily Traffic Maximum Desirable Deviation <1,000.60 1,000-2,500.47 2,500-5,000.36 5,000-10,000.29 10,000-25,000.25 25,000-50,000.22 >50,000.21 8-6 ANC/TP41158.DOC/050460017

TRAFFIC ASSIGNMENT AND VOLUMES Using these guidelines, all count locations specific performance was evaluated. Of the 655 individual counts, 233 exceed the Federal targets. However, when corrections are made for directional imbalances in the model due to count information being non-directional, this number is reduced to 80. When only those locations with a daily count of greater than 2500 are considered, the number of locations exceeding Federal targets is 53 or about 8.1% of all count locations. In general, this indicates that the Anchorage model is replicating existing traffic behavior not only at the systemwide, facility group, and cordon levels, but also at the level of the individual road segment. ANC/TP41158.DOC/050460017 8-7

TRAFFIC ASSIGNMENT AND VOLUMES 8-8 ANC/TP41158.DOC/050460017

SECTION 9 Summary and Conclusions A new and more robust travel demand model has been calibrated and validated for the Anchorage metropolitan area. This memorandum documents the new model structure, inputs, calibration and validation. This new Anchorage travel demand model incorporates up-to-date travel behavior relationships for Anchorage residents (2002 Household Travel Survey) and the latest available demographic and employment attributes (2000 U. S. Census and 2002 Alaska Department of Labor employment database) for the metropolitan area. The new model structure is significantly more robust and sophisticated than the travel model previously used in Anchorage. It incorporates dynamic relationships and sensitivity to land use development densities and patterns, household composition and demographic characteristics, transportation system connectivity, cost and level of service performance, and traveler decision-making regarding mode choice selection from available options. In addition to traditional travel model functionality and features, the new Anchorage travel model interfaces seamlessly with the Anchorage Land Use Allocation Model. It also now incorporates a rich and powerful set of over two dozen performance evaluation capabilities, display outputs and metrics. These evaluation tools are entirely new -- and critically important to assist in assessing alternative transportation scenarios and related transportation system planning, operations, and design analysis. Additionally, the entire model tool set is integrated in a user-friendly, menu-driven software environment which is far easier to use and maintain. Technical documentation is internally embedded for each model software application step. The details of the model calibration are documented in this report. The new travel model validation is complete and demonstrated to be in compliance with Federal Highway Administration federal guidelines. Socio-economic and demographic attributes of households are consistent with 2000 U.S. Census and State/local data Model-estimated person trip generation matches the 2002 Anchorage Household Travel Survey results Model-estimated transit passenger trips are within 1 percent of People Mover s reported bus riders for 2002 Model-estimated vehicle volumes compared to observed traffic counts for each of 23 different cordons across road links are each within FHWA guideline criteria. For all cordons combined, actual vs. model-estimated traffic volumes are within 5.5% ANC/TP41158.DOC/050460017 9-1

SUMMARY AND CONCLUSIONS A statistical linear regression fit of model-estimated vehicle volumes compared to all available observed traffic counts throughout the Anchorage road network shows a R 2 correlation coefficient of 0.9043, again bettering the FHWA guideline criteria of 0.880. In sum, the Anchorage Metropolitan Area Transportation Solutions (AMATS) organization now has an up-to-date, context-sensitive, powerful, proven and fully integrated travel demand modeling and analysis toolkit to address transportation planning and analysis needs. 9-2 ANC/TP41158.DOC/050460017

Appendix A Variable Dictionary Anchorage Travel Model Socioeconomic Database ANC/TP41158.DOC/050460017

APPENDIX A Variable Dictionary Anchorage Travel Model Socioeconomic Database (Note: Does not include computed values) Traffic Analysis Zone ID ZONE [integer] Total Population - POP [integer] Number of Households TOTALHH [integer] Median Household Income (2002 Dollars) AVINC [integer] Average Number of Workers/Household AVWHH [real (X.XXX)] Enrollment of Schools in Zone SENROLL [integer] EMPLOYMENT CATEGORIES o o o o o o o o o o o o o Agricultural Employment AEMP [integer] Mining Employment BEMP [integer] Construction Employment CEMP [integer] Manufacturing Employment DEMP [integer] Transportation/Public Utilities Employment EEMP [integer] Wholesale Trade Employment FEMP [integer] Retail Trade Employment GEMP [integer] Finance, Insurance and Real Estate Employment HEMP [integer] Service Employment IEMP [integer] Government Employment JEMP [integer] University Employment UEMP [integer] School Employment SEMP [integer] Medical/Health Services Employment XEMP [integer] Work Trip Parking Costs (2002 Dollars-Daily) - WPKCOST [real (X.XX)] Other Trip parking Cost (2002 Dollars-Monthly) - WPKCOST [real (X.XX)] ANC/TP41158.DOC/050460017 A-1

VARIABLE DICTIONARY ANCHORAGE TRAVEL MODEL SOCIOECONOMIC DATABASE ANC/TP41158.DOC/050460017 A-2

Appendix B Model Feedback Process ANC/TP41158.DOC/050460017

APPENDIX B Model Feedback Process Feedback Using the Method of Successive Averages (Source: TransCAD V4.7 Travel Demand Forecasting) In [direct feedback], congested travel times taken from the trip assignment results are directly fed back into the highway skim procedure. This method is commonly called the Direct Feedback Method. While Direct Feedback is relatively easy to understand and implement, many modelers who have implemented this method have reported a requirement of many feedback iterations before convergence occurs, or worse, the failure to reach convergence. Theoretically, there is no guarantee of convergence with this method (TMIP: Incorporating Feedback in Travel Forecasting, March, 1996). Because of this problem, alternatives to the Direct Feedback Method have been developed. One method that has had success is the Method of Successive Averages (MSA). In the MSA method, output volumes from trip assignment from previous iterations are weighted together to produce the current iteration s link volumes. Adjusted congested times are then calculated based on the normal volume-delay relationship. This adjusted congested time is then fed back to the skimming procedures. The adjusted volume is calculated based on the following equation: ANC/TP41158.DOC/050460017 B-1

MODEL FEEDBACK PROCESS ANC/TP41158.DOC/050460017 B-2

Appendix C Commercial Vehicle Travel Model ANC/TP41158.DOC/050460017

APPENDIX C Commercial Vehicle Travel Model This section documents the estimation of base year commercial vehicle (or truck) models to support the update of the Anchorage Transportation demand Model. Truck models were developed using local socioeconomic (employment and population) data; local truck classification data recently collected by both the Municipality of Anchorage (MOA) and Alaska Department of Transportation (ADOT); and techniques outlined in the Quick Response Freight Manual (QFRM). The QFRM was developed by Cambridge Systematics for the Federal Highway Administration (FHWA) as a sketch planning tool for Metropolitan Planning Organizations (MPOs) and state departments of Transportation (State DOTs) to implement cost-effective truck activity models. The Anchorage truck models represent base year daily (24-hour) conditions of single unit and combination commercial vehicle traffic. The truck vehicle categories correspond to those specified in the QFRM and also correspond to the standard vehicle classifications as specified by FHWA. These include: Single unit trucks FHWA Classes 5 to 7; and Combination trucks FHWA Classes 8 to 13. The following sections present the data used to support truck model development, the model development and application procedures used to both estimate and apply truck models for Anchorage, and the outputs generated from the truck modeling process. The model development and application section presents the methods used to develop truck trip generation, distribution, and assignment models, as well as the procedures used to validate the models. 1.1 Data Inputs The data inputs used to develop truck activity models for the Anchorage metropolitan area included employment data, transportation networks, and truck classification data. Socioeconomic Dataset Socioeconomic data, primarily employment data, were obtained from the MOA to represent base year conditions by transportation analysis zone (TAZ) contained in the transportation network. Data were aggregated to be consistent with QRFM techniques. Employment data were aggregated into four categories: 1) Agriculture, Mining, and Construction; 2) Manufacturing, Transportation, Communications, Utilities, and Wholesale Trade; 3) Retail Trade; and 4) Office and Services. Household data were also used to represent household activity by TAZ. ANC/TP41158.DOC/050460017

COMMERCIAL VEHICLE TRAVEL MODEL Transportation Network The updated highway network from the Anchorage Transportation Demand Model was refined to incorporate roadway restrictions of heavy-duty truck movements on specific segments of Northern Lights Boulevard and E Street. This revised network was used to obtain zone-to-zone travel times and impedances to apply truck trip distribution (gravity) models. Vehicle Classifications Truck classification data obtained from the MOA and ADOT were incorporated into the highway networks and were used for truck model validation. Classification data were obtained from the Highway Performance Monitoring System (HPMS) dataset. HPMS data was supplemented by classification data from the MOA and ADOT. Vehicle counts and classification data were also obtained from the Port of Anchorage and the Anchorage Landfill to specifically model special truck generators. 1.2 Model Development and Application Results This section presents the model development, application, and validation procedures used to estimate truck models for the Anchorage metropolitan area. Truck Trip Generation Models The QFRM procedures were used to perform truck trip generation. The data processing and modeling steps for truck trip generation are presented below. Internal TAZs Truck trip generation rates from the QFRM, as shown in Table 1.1, were applied to employment and households in each internal TAZ. Employment by category and household were taken from two Excel files developed by the MOA: EMPLOY.XLS and POPTAZ.XLS. According to a note in the employment file, military employment was not included. However, there did seem to be some employment allocated to the military base zone, which is, perhaps, civilian employment on the base. Also note that there were a number of zones with neither employment nor households. Accordingly, these internal zones did not generate any truck trips. ANC/TP41158.DOC/050460017 C-2

Table 1.1 Trip Generation Rates Applied to Internal Zones Generator Employment: Agriculture, Mining and Construction Manufacturing, Transportation, Communications, Utilities and Wholesale Trade Commercial Vehicle Trip Destinations (or Origins) per Day QFRM Rates Adjusted Rates Single Unit (6+ Tires) Combination Single Unit (6+ Tires) Combination 0.289 0.174 0.358 0.230 0.242 0.104 0.300 0.137 Retail Trade 0.253 0.065 0.314 0.086 Office and Services 0.068 0.009 0.084 0.012 Households 0.099 0.038 0.123 0.050 Source: Table 4.1, page 4-4, Quick Response Freight Manual (Cambridge Systematics, 1996). Trip generation rates were increased by 24 and 32 percent for single unit and combination vehicles, respectively, to bring the total screenline volumes closer to the validation data. External TAZs As recommended by the QFRM, vehicle classification count data was used to estimate truck productions and attractions at the two external stations. Truck counts on the links closest to the external stations in the validation database were used for this purpose, ensuring a good fit of trips generated by the model to the observed data. Special Generators Based on information provided by the MOA, the Port of Anchorage and the Anchorage Landfill were treated as special generators based on high levels of truck activity compared to the average transportation analysis zone within the Anchorage metropolitan area. Port of Anchorage (TAZ 13) For the Port TAZ, the number of total truck trips generated using the QFRM technique, including light duty, single unit, and combination vehicles, was comparable to the number of combination vehicle trips cited in the Traffic Flow Study conducted for the Port of Anchorage in 1996 (see Table 1.2 below). Since the Port s Traffic Flow Study figures are corroborated by information gathered during the recently-conducted carrier interviews, the combination vehicle trip productions and attractions were increased, resulting in the following trips generated by vehicle category: ANC/TP41158.DOC/050460017

COMMERCIAL VEHICLE TRAVEL MODEL Table 1.2 Comparison of Combination Vehicle Traffic at the Port Port Tenant From Port Study From Interviews MAPCO 55 30 to 40 QFRM Trip Generation Tesoro 48 Texaco 55 SeaLand 202 100 to 200 TOTE 213 164 TOTAL 573 Combination: 39 Total Commercial Vehicle: 571 Note: Port study and interviews represent Tuesday, a high volume day for Port traffic. Landfill (TAZ 648) For the landfill, information provided by the MOA, including the total number of trips by vehicle category for 1997 and monthly volumes, was used to generate the following productions and attractions: Single unit 75 trips (these represent mostly garbage trucks); and Combination 41 trips (these represent tractor-trailer combinations). Trips were scaled by the total volume for the month of September to represent an average annual condition. Total Trips The total trips generated by vehicle category for the Anchorage metropolitan area are shown in Table 1.3. TransCAD Files The truck trip generation data is stored in the geographic layer TRIPGEN.DBD. Productions and attractions are stored in the fields P_SINGLE, A_SINGLE, P_COMBI, and A_COMBI. The scaled up versions of the productions and attractions are stored in fields with the prefixes P2 and A2. Productions and attractions were balanced and written to the binary data tables BALANCED.BIN and BALANCD_2.BIN. 1.2.2 Trip Distribution Models The QFRM procedures were also used to perform truck trip distribution as presented below. ANC/TP41158.DOC/050460017 C-4

Table 1.3 Summary of Households, Employment, and Commercial Vehicle Trips Variable Count (TAZs with value) Sum RETAIL 554 24,188 FIRESVCS 554 73,317 MANUFWTCU 554 22,214 RESOURCES 554 11,819 TOTALEMP 554 131,538 SFHH 580 40,366 MFHH 580 47,782 POP 580 232,853 TOTHH 580 88,148 Single Unit Productions 557 36,388 Single Unit Attractions 557 36,359 Combination Productions 557 14,073 Combination Attractions 557 14,080 Note: Trips represent productions and attractions scaled up from QFRM. Gravity Models The trip distribution models were estimated using gravity models with an exponential specification and with coefficients by vehicle category as recommended by the QFRM. The models take the following form: ( c* tij ) F ij = e where: F is the friction factor; t is the travel time between Zones i and j; and c is a coefficient. The coefficients recommended by the QFRM are 0.1 for single unit vehicles and 0.03 for combination vehicles. These coefficients were used when distributing internal trips. However, a modified coefficient was applied when distributing trips from the external stations, as explained under the validation and calibration section. Transportation Networks and Travel Times The highway network used to generate zone-to-zone travel times was basically the same as for passenger travel modeling with one exception: several links along Northern Lights Boulevard ANC/TP41158.DOC/050460017

COMMERCIAL VEHICLE TRAVEL MODEL and on E Street north of 3 rd were disabled for combination vehicles. This adjustment was taken to simulate the more circuitous path that heavy-duty vehicles are likely to take when traveling to and from the airport or port. Separate travel time matrices for single unit and combination vehicles were applied in conjunction with the coefficients described above to produce the truck friction factor matrices for each vehicle class. TransCAD Files The network file used in producing travel times was SS_STRTS.NET. A selection set (NO_TRKS) in the map (TRUCKS.MAP) was used to disable links, when necessary, using the network update feature. The friction factors are contained in a matrix file called TRKFFACT.MTX with matrices SINGLE and COMBI. The final truck trip table is stored in TRUCKS_3.MTX. 1.2.3 Truck Trip Assignment Models The truck trip tables were assigned using an all-or-nothing assignment method contained in TransCAD and the SS_STRTS.NET network file. Again, specific links on Northern Lights Boulevard and E Street were disabled when assigning combination vehicle traffic. Link-level outputs from the final model run were stored in two binary data files: SINGLE_3.BIN and COMBI_3.BIN. Total VMT without centroids was 225,334 and 113,513 for single unit and combination traffic, respectively. 1.2.4 Truck Model Validation and Calibration This section presents the process used to validate truck models for the Anchorage metropolitan area. As stated previously under truck trip generation, trip generation rates were increased by 24 and 32 percent for single unit and combination trucks to better match observed data. Validation Database The database of vehicle classification counts was developed from several different sources, the primary source being the HPMS database. This source was expanded and modified in the following manner: The percent single unit and combination traffic in the HPMS data were combined with the 1994 AADT and split into two-way traffic to come up with truck counts by direction on each link that had HPMS classification data; Where new classification count data were available (those locations counted in September 1998), the new truck percents were scaled by the 1994 AADT on the link to come up with validation counts; and In some cases, where 1994 data were not available, AADT from adjacent links or AADT from the next most recent year were applied to come up with the validation counts. These steps produced the most consistent and complete validation database possible with the available data. ANC/TP41158.DOC/050460017 C-6

Validation Procedures Because validation data were not available for many links, it was not possible to successfully use the built-in TransCAD screenline analysis procedures. Rather, the screenlines were drawn on a map as graphic representations and then a selection set of links with validation data that crossed the screenlines was developed for comparison of counts to assigned flows. The screenline locations are shown in Figure 1.1 and include: 1. Glenn Highway near northernmost external station; 2. Glenn Highway approaching Anchorage proper; 3. Port of Anchorage (Ocean Dock Road); 4. North-south between International Airport and Raspberry; 5. North-south between O Malley and Huffman; 6. Seward Highway near the southernmost external station; 7. East-west airport approaches; 8. East-west, west of Seward Highway; 9. East-west, east of Boniface; and 10. East-west, west of Birch, Abbott, and Rabbit Creek. Summary of Calibration Three separate model runs were completed before the model was judged to perform satisfactorily. The results and adjustments made are described below. Baseline 1 The initial run revealed a problem with trip distribution in that almost all the trips generated at the external stations were remaining intra-taz trips. This occurred because the external zones are connected to the network with extraordinarily long connectors (almost 40 miles for Zone 901) and trips were simply not being distributed out of the zone with the QFRM gravity models. Some experimentation with the exponential function was made to select a coefficient that would result in a flatter curve, resulting in lower friction factors over the 30- to 40-mile distance range. This coefficient, 0.015, was applied only when distributing trips to or from the external stations in subsequent model runs. The other adjustment made at this stage was that the trip generation from the Port of Anchorage TAZ was revised to match the link counts on Ocean Dock Road. These were the only problems diagnosed at this stage and other aspects of the model performance, such as overall screenline performance, were not examined at this time. Baseline 2 An analysis of links crossing the screenlines revealed that the total assigned volumes were approximately 60 percent of the link counts by approximately 24 and 32 percent for single unit and combination vehicles, respectively (see attached Table 1.4). In addition, the link volumes crossing Screenline 1 were quite low. Two adjustments were made to the trip generation models for the next model run: ANC/TP41158.DOC/050460017

COMMERCIAL VEHICLE TRAVEL MODEL The HPMS-based counts, rather than the previously-used ADOT classification count were used for trip generation at TAZ 900; and The QFRM trip generation rates were increased by 24 and 32 percent to bring up the total link volumes. Baseline 3 After making the above-described adjustments, another model run and screenline analysis were made. As shown in the attached Table 1.5, the total assigned volume fit was much closer to the observed volumes. The combination vehicle volume was 4 percent higher compared to observed data, while the single-unit traffic was low by 12 percent. The combination vehicle traffic was higher than expected because of the change in traffic generated at the Port TAZ between Baseline 2 and Baseline 3. In Baseline 2, the Port trip generation had been matched to the counts on Ocean Dock Road. In Baseline 3, the trip generation from the Port was inadvertently left at the higher levels developed through the special generator analyses. Since the level of traffic generated at the Port is subject to judgement, these results were left in place for the time being. TransCAD Files A selection set of the links used in the screenline analysis has been saved in TRUCKS.MAP. 1.3 Outputs Daily truck trips, trip tables by single and combination units, and a combined truck network assignment were validated for the truck model. These data will be used as inputs into the timeof-day and trip assignment elements of the base year Anchorage Transportation Demand Model. The procedures presented above will also form the foundation for developing future forecasts of truck travel in the Anchorage metropolitan region. ANC/TP41158.DOC/050460017 C-8

Table 1.4 Screenline Validation Results Baseline 2 Count Data Link Flows Link Flow/Link Count Ratio Single Unit Combination Single Unit Combination Single Unit Combination Link ID FEANME AB_H_S BA_H_S AB_H_C BA_H_C AB_FLOW BA_FLOW AB_FLOW BA_FLOW AB BA Total AB BA Total 1 15402 GLENN 813 813 542 542 432 353 221 127 0.53 0.43 0.48 0.41 0.24 0.32 2 15809 NEWGLENN 621 621 99 99 1,203 1,277 615 704 1.94 2.05 2.00 6.21 7.11 6.66 3 3894 OCEANDOCK 28 86 20 217 102 101 383 380 3.63 1.18 1.78 19.14 1.75 3.22 4 15725 BRAYTON 151 151 60 60-65 - 31-0.43 0.22-0.51 0.25 4 2163 C 991 991 142 142 570 700 233 299 0.58 0.71 0.64 1.65 2.11 1.88 4 16181 MINNESOTA 1,120 1,120 92 92 834 592 325 236 0.74 0.53 0.64 3.54 2.57 3.05 4 15726 NEWSEWARD 2,012 2,012 1,006 1,006 1,788 1,662 838 765 0.89 0.83 0.86 0.83 0.76 0.80 4,273 4,273 1,300 1,300 3,192 3,019 1,397 1,330 0.75 0.71 0.73 1.07 1.02 1.05 5 5857 BIRCH 210 210 9 9 32 36 13 15 0.15 0.17 0.16 1.40 1.65 1.52 5 5067 LAKEOTIS 108 108 15 15 76 59 30 22 0.71 0.54 0.62 1.91 1.43 1.67 5 4397 C 84 84 28 28 89 88 34 33 1.06 1.04 1.05 1.21 1.19 1.20 5 239 SOUTHPORT 22 22 - - 9 10 4 4 0.43 0.47 0.45 - - - 424 424 53 53 207 193 80 74 0.49 0.46 0.47 1.52 1.41 1.47 6 3904 NEWSEWARD 126 155 65 58 126 155 65 58 1.00 1.00 1.00 1.00 1.00 1.00 7 15894 DIMOND 119 119 22 22 - - - - - - - - - - 7 760 RASPBERRY 20 20 7 7 11 11 5 5 0.54 0.54 0.54 0.70 0.69 0.69 7 16205 INTERNATIONAL 462 462 115 115 204 211 94 95 0.44 0.46 0.45 0.81 0.83 0.82 AIRPORT 7 1578 OLDINTERNATIONAL 192 192 38 38 154 143 65 63 0.80 0.75 0.77 1.70 1.63 1.67 AIRPORT 793 793 183 183 369 365 164 163 0.46 0.46 0.46 0.90 0.89 0.89 8 11233 WHITNEY 374 374 110 110 152 105 74 69 0.41 0.28 0.34 0.67 0.63 0.65 8 8572 16TH 80 80 34 34 87 47 22 9 1.08 0.58 0.83 0.63 0.27 0.45 8 8266 NORTHERNLIGHTS 232 232 116 116-533 - 164-2.30 1.15-1.41 0.71 8 8140 TUDOR 3,208 3,208 2,085 2,085 786 1,015 335 440 0.25 0.32 0.28 0.16 0.21 0.19 8 6861 76TH 94 94 16 16 22 88 8 43 0.23 0.94 0.59 0.51 2.72 1.61 8 4581 100TH 27 27 5 5 4 4 1 1 0.15 0.15 0.15 0.31 0.29 0.30 4,015 4,015 2,366 2,366 1,052 1,792 440 726 0.26 0.45 0.35 0.19 0.31 0.25 9 11592 COMMERCIAL 462 462 132 132 35 33 12 12 0.08 0.07 0.07 0.09 0.09 0.09 9 9572 PENLAND 295 295 147 147 169 168 49 49 0.57 0.57 0.57 0.33 0.33 0.33 9 9494 DEBARR 593 720 22-739 651 282 248 1.25 0.90 1.06 12.82-12.82 9 15987 TUDOR 1,662 1,662 1,662 1,662 1,383 1,431 649 698 0.83 0.86 0.85 0.39 0.42 0.41 3,012 3,139 1,964 1,942 2,325 2,283 992 1,006 0.77 0.73 0.75 0.51 0.52 0.51 10 5946 O MALLEY 933 933 41 41 163 169 64 67 0.17 0.18 0.18 1.59 1.66 1.62 10 5692 HUFFMAN 66 66 8 8 23 18 10 7 0.35 0.28 0.32 1.17 0.88 1.03 998 998 49 49 186 187 74 74 0.19 0.19 0.19 1.52 1.53 1.52 15,105 15,319 6,639 6,807 9,193 9,726 4,431 4,642 0.61 0.63 0.62 0.67 0.68 0.67 ANC/TP41158.DOC/050460017 C-9

COMMERCIAL VEHICLE TRAVEL MODEL Table 1.5 Screenline Validation Results Baseline 3 Count Data Link Flows Link Flow/Link Count Ratio Single Unit Combination Single Unit Combination Single Unit Combination SC Link ID FEANME AB_H_S BA_H_S AB_H_C BA_H_C AB_FLOW BA_FLOW AB_FLOW BA_FLOW AB BA Total AB BA Total 1 15402 GLENN 813 813 542 542 803 803 520 520 0.99 0.99 0.99 0.96 0.96 0.96 2 15809 NEWGLENN 621 621 99 99 1,775 1,773 1,100 1,101 2.86 2.85 2.86 11.11 11.12 11.12 3 3894 OCEANDOCK 28 86 20 217 102 101 384 385 3.63 1.18 1.78 19.22 1.77 3.25 4 2163 C 991 991 142 142 567 569 257 252 0.57 0.57 0.57 1.81 1.78 1.80 4 15725 BRAYTON 151 151 60 60 4 15726 NEWSEWARD 2,012 2,012 1,006 1,006 2,231 2,214 1,084 1,074 1.11 1.10 1.10 1.08 1.07 1.07 4 16181 MINNESOTA 1,120 1,120 92 92 1,143 1,192 482 503 1.02 1.06 1.04 5.24 5.46 5.35 5 239 SOUTHPORT 22 22 10 13 4 5 0.47 0.58 0.52 5 4397 C 84 84 28 28 131 128 55 52 1.56 1.52 1.54 1.95 1.85 1.90 5 5067 LAKEOTIS 108 108 15 15 44 37 15 12 0.41 0.34 0.38 1.00 0.78 0.89 5 5857 BIRCH 210 210 9 9 41 32 17 13 0.19 0.15 0.17 1.89 1.37 1.63 6 3904 NEWSEWARD 126 155 65 58 126 155 65 58 1.00 1.00 1.00 1.00 1.00 1.00 7 760 RASPBERRY 20 20 7 7 14 14 6 6 0.67 0.67 0.67 0.91 0.91 0.91 7 1578 OLDINTERNATIONAL 192 192 38 38 190 177 86 83 0.99 0.92 0.96 2.23 2.15 2.19 AIRPORT 7 15894 DIMOND 119 119 22 22 0 0 0 0 0.00 0.00 0.00 0.00 0.00 0.00 7 16205 INTERNATIONALAIR 462 462 115 115 241 264 123 126 0.52 0.57 0.55 1.07 1.09 1.08 PORT 8 4581 100TH 27 27 5 5 15 21 6 8 0.55 0.78 0.66 1.26 1.72 1.49 8 6861 76TH 94 94 16 16 70 123 36 63 0.75 1.31 1.03 2.33 3.99 3.16 8 8140 TUDOR 3,208 3,208 2,085 2,085 1,357 1,580 660 759 0.42 0.49 0.46 0.32 0.36 0.34 8 8266 NORTHERNLIGHTS 232 232 116 116 1,454 621 6.26 3.13 5.35 2.68 8 8572 16TH 80 80 34 34 58 35 15 7 0.72 0.43 0.57 0.43 0.20 0.32 8 11233 WHITNEY 374 374 110 110 369 320 255 172 0.99 0.86 0.92 2.32 1.56 1.94 9 9494 DEBARR 593 720 22 691 607 280 219 1.17 0.84 0.99 12.74 22.71 9 9572 PENLAND 295 295 147 147 229 200 72 60 0.78 0.68 0.73 0.49 0.41 0.45 9 11592 COMMERCIAL 462 462 132 132 168 57 72 22 0.36 0.12 0.24 0.55 0.16 0.36 9 15987 TUDOR 1,662 1,662 1,662 1,662 1,954 2,080 1,064 1,123 1.18 1.25 1.21 0.64 0.68 0.66 10 5692 HUFFMAN 66 66 8 8 33 41 14 18 0.50 0.62 0.56 1.64 2.21 1.93 10 5946 O MALLEY 933 933 41 41 148 137 61 55 0.16 0.15 0.15 1.50 1.36 1.43 15,105 15,319 6,639 6,807 12,509 14,128 6,733 7,317 0.83 0.92 0.88 1.01 1.07 1.04 ANC/TP41158.DOC/050460017 C-10

Appendix D Special Generators ANC/TP41158.DOC/050460017

APPENDIX D Special Generators TAZ PRATE PID ARATE AID HBWP HBSP HBSCHP HBOP NHBWP NHBNWP SINGLEP COMBIP HBWA HBSA HBSCHA HBOA NHBWA NHBNWA SINGLEA COMBIA LOCID 1 0.0492 Base Emp 0.0492 Base Emp 0.000 0.000 0.000 0.000 0.000 0.000 0.700 0.300 0.000 0.000 0.000 0.000 0.000 0.000 0.700 0.300 Elmendorf-Post Rd 2 1.4250 Base Pop 2.1700 Base Emp 0.300 0.330 0.183 0.183 0.565 0.264 0.086 0.084 Ft Richardson 2 0.0240 Base Emp 0.0240 Base Emp 0.000 0.000 0.000 0.000 0.000 0.000 0.700 0.300 0.000 0.000 0.000 0.000 0.000 0.000 0.700 0.300 Ft Richardson - Truc 13 1.5420 Emp 1.5420 Emp 0.203 0.797 0.203 0.797 Ship Creek (Trucks) 13 114.94 Freight Tons (M) 114.94 Frieght Tons (M) 0.000 0.000 0.000 0.000 0.000 0.000 0.150 0.850 0.000 0.000 0.000 0.000 0.000 0.000 0.150 0.850 Ship Creek - Port 142 4.3950 Beds 16.535 Beds 0.500 0.500 0.499 0.218 0.142 0.141 Columbia Hospital 142 0.0960 Emp 0.0960 Emp 0.000 0.000 0.000 0.000 0.000 0.000 0.875 0.125 0.000 0.000 0.000 0.000 0.000 0.000 0.875 0.125 Columbia Hos - Truck 217 0.0770 Students 0.9570 Students 0.608 0.392 0.240 0.000 0.565 0.053 0.068 UAA 217 0.1060 Emp 0.1060 Emp 0.000 0.000 0.000 0.000 0.000 0.000 0.875 0.125 0.000 0.000 0.000 0.000 0.000 0.000 0.875 0.125 UAA-Trucks 249 0.1150 Students 1.4360 Students 0.608 0.392 0.240 0.000 0.565 0.053 0.068 APU 249 0.1060 Emp 0.1060 Emp 0.000 0.000 0.000 0.000 0.000 0.000 0.875 0.125 0.000 0.000 0.000 0.000 0.000 0.000 0.875 0.125 APU-Trucks 253 0.0770 Students 0.9570 Students 0.608 0.392 0.240 0.000 0.565 0.053 0.068 UAA 253 0.1060 Emp 0.1060 Emp 0.000 0.000 0.000 0.000 0.000 0.000 0.875 0.125 0.000 0.000 0.000 0.000 0.000 0.000 0.875 0.125 UAA-Trucks 267 0.2270 Out Patients 0.9120 OutPatients 0.603 0.397 0.507 0.185 0.084 0.108 Providence Medical 267 0.0960 Emp 0.0960 Emp 0.000 0.000 0.000 0.000 0.000 0.000 0.875 0.125 0.000 0.000 0.000 0.000 0.000 0.000 0.875 0.125 Provid Hosp-Trucks 272 22.73 Emp 55.54 Emp 1.000 0.036 0.553 0.411 Library 288 None 2.8600 Emp 0.414 0.408 0.049 0.049 Alaska Native Hospit 288 0.0960 Emp 0.0960 Emp 0.000 0.000 0.000 0.000 0.000 0.000 0.875 0.125 0.000 0.000 0.000 0.000 0.000 0.000 0.875 0.125 Al Native Hosp - Trk 328 0.0020 Enplanements 0.0180 Enplanements 0.500 0.500 0.231 0.454 0.086 0.086 Airport 328 0.0065 Landings 0.0065 Landings 0.000 0.000 0.000 0.000 0.000 0.000 0.808 0.192 0.000 0.000 0.000 0.000 0.000 0.000 0.808 0.192 Airport-Trucks 343 None 1.3600 Unit 0.375 0.313 0.156 0.156 Air National Guard 648 0.0590 Region Pop(100s) 0.0590 Region Pop(100s) 0.650 0.350 0.650 0.350 Eagle River Site 900 38.65 Ext Pop(100s) 18.825 Ext Pop(100s) 0.253 0.100 0.000 0.447 0.060 0.100 0.026 0.014 0.060 0.180 0.684 0.052 0.028 North External 901 2.4050 Region Emp(100s) 4.0350 Region Pop(100s) 0.175 0.080 0.312 0.117 0.200 0.069 0.046 0.120 0.721 0.120 0.023 0.016 South External 910 2.4300 Base Pop 3.2890 Base Emp 0.300 0.330 0.183 0.183 0.565 0.264 0.086 0.084 Elmendorf-Gov't Hill 911 2.4300 Base Pop 3.2890 Base Emp 0.300 0.330 0.183 0.183 0.565 0.264 0.086 0.084 Elemendorf-Boniface ANC/TP41158.DOC/050460017 F-25

Appendix E Hotel/Motel Visitor Model ANC/TP41158.DOC/050460017

APPENDIX E Hotel/Motel Visitor Model ZONE ROOMS OCC NAME ADDRESS 27 59 0.60 Ramada Limited Hotel of A 207 MULDOON RD 30 100 0.60 Comfort Inn 111 W SHIP CREEK AVE 43 20 0.60 Anchorage Uptown Suites 234 E SECOND AVE 45 31 0.60 Anchorage Grand Hotel 505 W SECOND AVE 53 600 0.80 Hilton Anchorage Hotel 500 WEST THIRD AVE 53 26 0.60 Historic Anchorage Hotel 330 E ST 69 90 0.60 Ramada Inn Anchorage Dowt 115 E THIRD AVE 70 39 0.60 Merrill Field Inn 420 SITKA ST 71 41 0.60 Econo Lodge 642 E FIFTH AVE 79 547 0.80 The Hotel Captain Cook FOURTH AVENUE AT K STREET 79 14 0.60 Copper Whale Inn 440 L ST 81 251 0.75 Holiday Inn Downtown 239 W FOUTH AVE 81 43 0.60 Anchor Arms Hotel 433 EAGLE ST 85 60 0.60 Rodeway Inn 1124 E 5TH AVE 86 130 0.60 Days Inn Downtown 321 E FIFTH AVE 89 198 0.75 Westmark Anchorage Hotel 720 WEST FIFTH AVE 89 84 0.60 Inlet Inn 539 H ST 91 38 0.60 The Voyager Hotel 501 K ST 102 392 0.80 Anchorage Marriott Downtown 820 WEST 7TH AVE 106 148 0.75 Marriott Residence Inn 1025 E 35TH AVE. 107 375 0.80 Sheraton Anchorage Hotel 401 E SIXTH AVE 113 111 0.75 Hawthorn Suites 1110 W EIGHTH AVE 116 111 0.75 Clarion Suites 325 W EIGHTH AVE 116 95 0.60 Aspen Hotel 108 E 8TH AVE. 153 180 0.60 Inlet Tower Hotel & Suite 1200 L ST 155 20 0.60 Anchorage Suit Lodge 441 E 15TH AVE 257 102 0.75 Springhill Suites 3401 A ST 268 83 0.60 Best Western Golden Lion 1000 E 36TH AVE 279 40 0.60 Best Inns & Suites 4110 SPENARD RD 279 38 0.60 Spenard Hotel Motel Inn 3960 SPENARD RD 279 34 0.60 Chelsea Inn Hotel 3836 SPENARD RD 298 101 0.75 Hampton Inn 4301 CREDIT UNION DR 300 86 0.60 Puffin Inn 4400 SPENARD RD 303 217 0.75 Best Western Barratt Inn 4616 SPENARD RD 303 128 0.60 Holiday Inn Express 4411 SPENARD RD 303 102 0.60 Best Value Inn Executive S 4360 SPENARD RD 310 248 0.80 Millennium Alaskan Anchor 4800 SPENARD ROAD 316 125 0.75 Hilton Garden Inn 100 W TUDOR RD 316 122 0.75 Homewood Suites by Hilton 140 W TUDOR RD 316 106 0.75 Fairfield Inn & Suites 5060 A STREET 319 141 0.75 Coast International Inn 3333 W INT'L AIRPORT RD 326 154 0.75 Courtyard by Marriott 4901 SPENARD RD 326 79 0.60 Microtel Inn & Suites 5205 NORTHWOOD DR 335 24 0.60 Arctic Inn Motel 842 W INT'L AIRPORT RD 394 109 0.60 Dimond Center Hotel 700 E DIMOND BLVD ANC/TP41158.DOC/050460017 E-1

HOTEL/MOTEL VISITOR MODEL ANC/TP41158.DOC/050460017 E-2

Appendix F Screenlines ANC/TP41158.DOC/050460017

APPENDIX F Screenlines (101) North of Tudor Minnesota to O Malley ABLKNME ABCOUNT BACOUNT TOTCOUNT ABCAP BACAP TOTCAP ABVOL BAVOL TOTVOL MinnesotaDr_SB 22236 20636 42872 24900 24900 49800 21808 17536 39345 ArcticBlvd_SB 11080 11907 22987 15000 15000 30000 4278 3544 7823 CSt_NB 14749 15643 30392 24900 24900 49800 9434 13157 22591 DenaliSt_NB 4100 4100 8200 15000 15000 30000 5324 2748 8071 OldSewardHwy_SB 6135 6135 12270 16600 16600 33200 2748 4423 7171 NewSewardHwy_NB 26812 0 26812 58500 0 58500 27744 0 27744 NewSewardHwy_SB 26812 0 26812 58500 0 58500 29334 0 29334 MacInnesSt_SB 748 748 1496 5000 5000 10000 31 24 54 LakeOtisPkwy_SB 12795 12795 25590 23000 23000 46000 14426 11983 26409 BragawSt_SB 3820 3504 7324 15000 15000 30000 3476 3866 7341 BonifacePkwy_SB 7566 7173 14739 16600 16600 33200 8993 8716 17709 BaxterRd_SB 2522 2522 5044 5000 5000 10000 624 556 1180 MuldoonRd_SB 12000 12000 24000 23000 23000 46000 8818 8712 17530 PattersonSt_SB 1522 1522 3044 5000 5000 10000 800 744 1544 Screenline Totals 152897 98685 251582 306000 189000 495000 137836 76010 213846 50000 45000 40000 35000 30000 25000 20000 15000 10000 5000 0 Counts Model MinnesotaDr_SB ArcticBlvd_SB CSt_NB DenaliSt_NB OldSewardHwy_SB NewSewardHwy_NB NewSewardHwy_SB MacInnesSt_SB LakeOtisPkwy_SB BragawSt_SB BonifacePkwy_SB BaxterRd_SB MuldoonRd_SB PattersonSt_SB ANC/TP41158.DOC/050460017 F-1

SCREENLINES (201) North of Dimond Avenue Minnesota to Birch ABLKNME ABCOUNT BACOUNT TOTCOUNT ABCAP BACAP TOTCAP ABVOL BAVOL TOTVOL MinnesotaDr_SB 17849 0 17849 39000 0 39000 16896 0 16896 MinnesotaDr_NB 17800 0 17800 39000 0 39000 19434 0 19434 CSt_NB 5800 5800 11600 20750 20750 41500 3636 3677 7313 88thAve_EB 2500 2685 5185 6500 6500 13000 1645 1771 3416 LakeOtisPkwy_SB 5905 5905 11810 23000 23000 46000 8941 7190 16132 KingSt_SB 750 750 1500 6500 6500 13000 1109 1095 2204 NewSewardHwy_SB 27816 0 27816 39000 0 39000 27150 0 27150 NewSewardHwy_NB 28089 0 28089 39000 0 39000 25503 0 25503 OldSewardHwy_SB 8801 8801 17602 23000 23000 46000 7544 10593 18137 HomerDr_SB 1780 0 1780 18000 0 18000 3022 0 3022 BraytonDr_SB 0 3660 3660 0 18000 18000 0 1718 1718 DimondBlvd_EB 2500 2500 5000 5500 5500 11000 3123 2345 5467 AbbottLoopRd_SB 1581 1581 3162 5000 5000 10000 1178 933 2110 Screenline Totals 121171 31682 152853 264250 108250 372500 119182 29320 148502 30000 25000 20000 15000 10000 Counts Model 5000 0 MinnesotaDr_SB MinnesotaDr_NB CSt_NB 88thAve_EB LakeOtisPkwy_SB KingSt_SB NewSewardHwy_SB NewSewardHwy_NB OldSewardHwy_SB HomerDr_SB BraytonDr_SB DimondBlvd_EB AbbottLoopRd_SB ANC/TP41158.DOC/050460017 F-2

(301) South of O Malley C Street to Hillside ABLKNME ABCOUNT BACOUNT TOTCOUNT ABCAP BACAP TOTCAP ABVOL BAVOL TOTVOL CSt_SB 4367 4404 8771 15000 15000 30000 4317 4522 8839 OldSewardHwy_SB 11302 11302 22604 7500 7500 15000 8868 9323 18191 BraytonDr_SB 0 5400 5400 0 18000 18000 0 1220 1220 NewSewardHwy_SB 15155 0 15155 39000 0 39000 16564 0 16564 NewSewardHwy_NB 13500 0 13500 39000 0 39000 16560 0 16560 ElmoreRd_SB 626 626 1252 7400 7400 14800 621 662 1284 BirchRd_SB 1146 1146 2292 5000 5000 10000 719 827 1546 HillsideDr_SB 2236 2236 4472 7400 7400 14800 2509 2568 5078 Screenline Totals 48332 25114 73446 120300 60300 180600 50158 19123 69282 25000 20000 15000 10000 Counts Model 5000 0 CSt_SB OldSewardHwy_SB BraytonDr_SB NewSewardHwy_SB NewSewardHwy_NB ElmoreRd_SB BirchRd_SB HillsideDr_SB ANC/TP41158.DOC/050460017 F-3

SCREENLINES (401) South of Glenn Hwy Ingra to Muldoon ABLKNME ABCOUNT BACOUNT TOTCOUNT ABCAP BACAP TOTCAP ABVOL BAVOL TOTVOL GambellSt_SB 18800 0 18800 33200 0 33200 22687 0 22687 IngraSt_SB 0 19478 19478 0 33200 33200 0 18155 18155 KarlukSt_SB 1200 1200 2400 5000 5000 10000 1552 1023 2576 AirportHeightsDr_SB 6451 5737 12188 15000 15000 30000 10773 8929 19702 TurpinSt_SB 3530 3530 7060 5000 5000 10000 1131 1330 2460 BonifacePkwy_SB 9776 9554 19330 16600 16600 33200 8130 8426 16556 BragawSt_SB 9965 9965 19930 12400 12400 24800 8517 8106 16624 McCarreySt_NB 2382 1200 3582 6500 6500 13000 997 1036 2033 OklahomaDr_SB 800 800 1600 5000 5000 10000 615 287 902 MuldoonRd_SB 13943 15310 29253 18400 18400 36800 7288 8025 15314 Screenline Totals 66847 66774 133621 117100 117100 234200 61691 55317 117008 35000 30000 25000 20000 15000 10000 5000 0 Counts Model GambellSt_SB IngraSt_SB KarlukSt_SB AirportHeightsDr_SB TurpinSt_SB BonifacePkwy_SB BragawSt_SB McCarreySt_NB OklahomaDr_SB MuldoonRd_SB ANC/TP41158.DOC/050460017 F-4

(501) West of Muldoon Tudor to Glenn Hwy ABLKNME ABCOUNT BACOUNT TOTCOUNT ABCAP BACAP TOTCAP ABVOL BAVOL TOTVOL 36thAve_EB 676 676 1352 5000 5000 10000 1072 1042 2113 NorthernLightsBlvd_EB 7478 7234 14712 16600 16600 33200 5367 5176 10544 DebarrRd_EB 7175 7175 14350 23000 23000 46000 5459 6293 11753 MuldoonRd_SB 12000 12000 24000 23000 23000 46000 8818 8712 17530 NewGlennHwy_EB 24085 0 24085 58500 0 58500 28093 0 28093 NewGlennHwy_WB 24085 0 24085 58500 0 58500 27881 0 27881 6thAve_EB 778 778 1556 5000 5000 10000 782 745 1528 BoundaryDr_EB 300 300 600 5000 5000 10000 217 435 652 Screenline Totals 76577 28163 104740 194600 77600 272200 77689 22404 100093 30000 25000 20000 15000 10000 Counts Model 5000 0 36thAve_EB NorthernLightsBlvd_EB DebarrRd_EB MuldoonRd_SB NewGlennHwy_EB NewGlennHwy_WB 6thAve_EB BoundaryDr_EB ANC/TP41158.DOC/050460017 F-5

SCREENLINES (601) West of Boniface Tudor to Davis ABLKNME ABCOUNT BACOUNT TOTCOUNT ABCAP BACAP TOTCAP ABVOL BAVOL TOTVOL DebarrRd_EB 12700 12700 25400 23000 23000 46000 11161 12269 23430 TudorRd_EB 21201 20825 42026 23000 23000 46000 21061 21895 42955 NorthernLightsBlvd_EB 12410 12410 24820 16600 16600 33200 10844 11232 22076 NewGlennHwy_WB 21615 0 21615 39000 0 39000 26579 0 26579 DavisSt_EB 4504 4504 9008 11250 11250 22500 2756 2945 5701 NewGlennHwy_EB 21615 0 21615 39000 0 39000 25787 0 25787 Screenline Totals 94045 50439 144484 151850 73850 225700 98188 48341 146529 50000 45000 40000 35000 30000 25000 20000 15000 10000 5000 0 Counts Model DebarrRd_EB TudorRd_EB NorthernLightsBlvd_EB NewGlennHwy_WB DavisSt_EB NewGlennHwy_EB ANC/TP41158.DOC/050460017 F-6

(602) West of Birch Rabbit Creek to Abbott ABLKNME ABCOUNT BACOUNT TOTCOUNT ABCAP BACAP TOTCAP ABVOL BAVOL TOTVOL RabbitCreekRd_EB 3626 3626 7252 7400 7400 14800 4410 4471 8881 DeArmounRd_EB 1010 1010 2020 7400 7400 14800 535 552 1088 HuffmanRd_EB 1030 1030 2060 7400 7400 14800 976 932 1908 OMalleyRd_EB 3600 3600 7200 7400 7400 14800 3580 3670 7250 AbbottRd_EB 3239 3239 6478 7400 7400 14800 3341 3600 6941 Screenline Totals 12505 12505 25010 37000 37000 74000 12843 13225 26068 10000 9000 8000 7000 6000 5000 4000 3000 2000 1000 0 RabbitCreekRd_EB DeArmounRd_EB HuffmanRd_EB OMalleyRd_EB AbbottRd_EB Counts Model ANC/TP41158.DOC/050460017 F-7

SCREENLINES (701) East of Lake Otis Tudor to Commercial ABLKNME ABCOUNT BACOUNT TOTCOUNT ABCAP BACAP TOTCAP ABVOL BAVOL TOTVOL TudorRd_EB 24810 24810 49620 23000 23000 46000 22419 23144 45563 ProvidenceDr_EB 5981 5269 11250 15000 15000 30000 4821 4316 9137 NorthernLightsBlvd_EB 18000 18000 36000 16600 16600 33200 19270 20617 39887 20thAve_EB 1300 1300 2600 5000 5000 10000 1042 1174 2216 16thAve_EB 200 200 400 5000 5000 10000 5 16 21 DebarrRd_EB 17500 17500 35000 16600 16600 33200 16786 19038 35823 MerrillFieldDr_EB 200 200 400 5500 5500 11000 181 193 374 CommercialDr_EB 6679 6679 13358 15000 15000 30000 5390 5229 10618 5thAve_EB 21954 23281 45235 16600 16600 33200 23190 22170 45361 Screenline Totals 96624 97239 193863 118300 118300 236600 93104 95896 189001 60000 50000 40000 30000 20000 Counts Model 10000 0 TudorRd_EB ProvidenceDr_EB NorthernLightsBlvd_EB 20thAve_EB 16thAve_EB DebarrRd_EB MerrillFieldDr_EB CommercialDr_EB 5thAve_EB ANC/TP41158.DOC/050460017 F-8

(702) East of Lake Otis DeArmoun to Dowling ABLKNME ABCOUNT BACOUNT TOTCOUNT ABCAP BACAP TOTCAP ABVOL BAVOL TOTVOL DeArmounRd_EB 2130 2106 4236 7400 7400 14800 2723 2872 5594 AbbottRd_EB 6390 6390 12780 7400 7400 14800 6604 6144 12749 HuffmanRd_EB 3605 3605 7210 7400 7400 14800 4048 4056 8104 OMalleyRd_EB 6825 6825 13650 7400 7400 14800 5740 5985 11725 80thAve_EB 2805 2805 5610 7400 7400 14800 3432 3796 7228 72ndAve_EB 1466 1467 2933 7400 7400 14800 2031 2173 4204 68thAve_EB 3317 3317 6634 7400 7400 14800 2797 2937 5734 DowlingRd_EB 1453 1453 2906 7500 7500 15000 1582 1784 3367 84thAve_WB 750 750 1500 7400 7400 14800 1486 1610 3096 Screenline Totals 28741 28718 57459 66700 66700 133400 30443 31358 61801 16000 14000 12000 10000 8000 6000 4000 2000 0 Counts Model DeArmounRd_EB AbbottRd_EB HuffmanRd_EB OMalleyRd_EB 80thAve_EB 72ndAve_EB 68thAve_EB DowlingRd_EB 84thAve_WB ANC/TP41158.DOC/050460017 F-9

SCREENLINES (801) East of New Seward Hwy Rabbit Creek to 3 rd ABLKNME ABCOUNT BACOUNT TOTCOUNT ABCAP BACAP TOTCAP ABVOL BAVOL TOTVOL 15thAve_EB 11677 11677 23354 20750 20750 41500 15023 13381 28404 BensonBlvd_EB 20500 0 20500 33200 0 33200 19981 0 19981 NorthernLightsBlvd_EB 0 20500 20500 0 33200 33200 0 22377 22377 5thAve_EB 0 24000 24000 0 24900 24900 0 22688 22688 4thAve_EB 9600 0 9600 22500 0 22500 7781 0 7781 3rdAve_WB 0 8162 8162 0 22500 22500 0 6282 6282 9thAve_EB 1380 1380 2760 5000 5000 10000 962 1307 2269 6thAve_WB 20000 0 20000 24900 0 24900 22887 0 22887 LoreRd_EB 500 500 1000 5000 5000 10000 86 1142 1228 DimondBlvd_EB 8800 8800 17600 16600 16600 33200 12173 10859 23032 68thAve_EB 400 400 800 5000 5000 10000 105 337 442 OMalleyRd_EB 7974 8182 16156 8300 8300 16600 8294 8580 16873 AcademyDr_EB 1500 1500 3000 7500 7500 15000 104 127 230 OldSewardHwy_SB 4000 4000 8000 12450 12450 24900 5078 5117 10195 DeArmounRd_EB 3926 3926 7852 7400 7400 14800 2505 2846 5352 HuffmanRd_EB 7715 7715 15430 7500 7500 15000 6043 5815 11857 DowlingRd_EB 17500 17500 35000 20750 20750 41500 12760 12607 25367 TudorRd_EB 22021 22318 44339 23000 23000 46000 21244 22137 43381 36thAve_EB 8500 8500 17000 15000 15000 30000 4021 4535 8556 Screenline Totals 145993 149060 295053 234850 234850 469700 139045 140137 279182 50000 45000 40000 35000 30000 25000 20000 15000 10000 5000 0 Counts Model 15thAve_EB BensonBlvd_EB NorthernLightsBlvd_EB 5thAve_EB 4thAve_EB 3rdAve_WB 9thAve_EB 6thAve_WB LoreRd_EB DimondBlvd_EB 68thAve_EB OMalleyRd_EB AcademyDr_EB OldSewardHwy_SB DeArmounRd_EB HuffmanRd_EB DowlingRd_EB TudorRd_EB 36thAve_EB ANC/TP41158.DOC/050460017 F-10

(901) South of International Airport Road Minnesota to Lake Otis ABLKNME ABCOUNT BACOUNT TOTCOUNT ABCAP BACAP TOTCAP ABVOL BAVOL TOTVOL MinnesotaDr_NB 24579 0 24579 39000 0 39000 22821 0 22821 MinnesotaDr_SB 25317 0 25317 39000 0 39000 23222 0 23222 ArcticBlvd_SB 7643 7791 15434 15000 15000 30000 7110 7675 14785 CSt_NB 9385 9855 19240 20750 20750 41500 7402 7974 15376 NewSewardHwy_NB 30446 0 30446 39000 0 39000 28293 0 28293 NewSewardHwy_SB 30495 0 30495 39000 0 39000 31683 0 31683 OldSewardHwy_SB 12987 12987 25974 16600 16600 33200 7354 14689 22043 HomerDr_SB 2010 0 2010 18000 0 18000 4569 0 4569 BraytonDr_SB 0 5000 5000 0 18000 18000 0 3113 3113 LakeOtisPkwy_SB 17000 17000 34000 23000 23000 46000 17015 14734 31749 Screenline Totals 159862 52633 212495 249350 93350 342700 149468 48185 197652 40000 35000 30000 25000 20000 15000 10000 5000 0 Counts Model MinnesotaDr_NB MinnesotaDr_SB ArcticBlvd_SB CSt_NB NewSewardHwy_NB NewSewardHwy_SB OldSewardHwy_SB HomerDr_SB BraytonDr_SB LakeOtisPkwy_SB ANC/TP41158.DOC/050460017 F-11

SCREENLINES (1001) South of Dimond Minnesota to Birch ABLKNME ABCOUNT BACOUNT TOTCOUNT ABCAP BACAP TOTCAP ABVOL BAVOL TOTVOL FrontageRd_SB 530 0 530 18000 0 18000 0 0 0 MinnesotaDr_SB 13480 0 13480 39000 0 39000 13016 0 13016 FrontageRd_NB 3100 0 3100 18000 0 18000 841 0 841 MinnesotaDr_NB 13480 0 13480 39000 0 39000 7682 0 7682 CSt_NB 100 100 200 18400 18400 36800 248 237 485 NewSewardHwy_SB 19057 0 19057 39000 0 39000 17685 0 17685 NewSewardHwy_NB 18918 0 18918 39000 0 39000 19891 0 19891 HomerDr_SB 3380 0 3380 18000 0 18000 178 0 178 BraytonDr_SB 0 5000 5000 0 18000 18000 0 2876 2876 OldSewardHwy_SB 9221 9221 18442 16600 16600 33200 7581 7267 14848 IndependenceDr_SB 2211 2211 4422 5000 5000 10000 2912 1726 4638 LakeOtisPkwy_SB 7337 7857 15194 16600 16600 33200 7371 6372 13742 BirchRd_SB 1329 1329 2658 7400 7400 14800 916 1100 2015 Screenline Totals 92143 25718 117861 274000 82000 356000 78320 19577 97897 25000 20000 15000 10000 Counts Model 5000 0 FrontageRd_SB MinnesotaDr_SB FrontageRd_NB MinnesotaDr_NB CSt_NB NewSewardHwy_SB NewSewardHwy_NB HomerDr_SB BraytonDr_SB OldSewardHwy_SB IndependenceDr_SB LakeOtisPkwy_SB BirchRd_SB ANC/TP41158.DOC/050460017 F-12

(2001) North of Eagle River Glenn Highway ABLKNME ABCOUNT BACOUNT TOTCOUNT ABCAP BACAP TOTCAP ABVOL BAVOL TOTVOL GlennHwy_SB 12278 12321 24599 39000 39000 78000 12501 11943 24443 Screenline Totals 12278 12321 24599 39000 39000 78000 12501 11943 24443 24650 24600 24550 24500 Counts Model 24450 24400 24350 GlennHwy_SB ANC/TP41158.DOC/050460017 F-13

SCREENLINES (2002) North of Eagle River Road Access Glenn to Birchwood ABLKNME ABCOUNT BACOUNT TOTCOUNT ABCAP BACAP TOTCAP ABVOL BAVOL TOTVOL NewGlennHwy_NB 17490 0 17490 39000 0 39000 16841 0 16841 NewGlennHwy_SB 17490 0 17490 39000 0 39000 17181 0 17181 OldGlennHwy_NB 1245 1245 2490 6200 6200 12400 789 802 1591 Screenline Totals 36225 1245 37470 84200 6200 90400 34811 802 35613 20000 18000 16000 14000 12000 10000 8000 6000 4000 2000 0 NewGlennHwy_NB NewGlennHwy_SB OldGlennHwy_NB Counts Model ANC/TP41158.DOC/050460017 F-14

(2003) South of Hiland Glenn Highway ABLKNME ABCOUNT BACOUNT TOTCOUNT ABCAP BACAP TOTCAP ABVOL BAVOL TOTVOL NewGlennHwy_NB 24892 0 24892 58500 0 58500 27237 0 27237 NewGlennHwy_SB 23332 0 23332 58500 0 58500 29464 0 29464 Screenline Totals 48224 0 48224 117000 0 117000 56701 0 56701 35000 30000 25000 20000 15000 Counts Model 10000 5000 0 NewGlennHwy_NB NewGlennHwy_SB ANC/TP41158.DOC/050460017 F-15

SCREENLINES (2005) North of 3 rd C Street to Port Access ABLKNME ABCOUNT BACOUNT TOTCOUNT ABCAP BACAP TOTCAP ABVOL BAVOL TOTVOL OceanDockRd_NB 1299 1299 2598 6500 6500 13000 818 764 1582 PortAccessRd_NB 0 8910 8910 0 16600 16600 0 8834 8834 PortAccessRd_NB 7563 0 7563 16600 0 16600 9393 0 9393 Screenline Totals 8862 10209 19071 23100 23100 46200 10210 9599 19809 10000 9000 8000 7000 6000 5000 4000 3000 2000 1000 0 OceanDockRd_NB PortAccessRd_NB PortAccessRd_NB Counts Model ANC/TP41158.DOC/050460017 F-16

(2006) West of Gambell 3 rd to 16 th ABLKNME ABCOUNT BACOUNT TOTCOUNT ABCAP BACAP TOTCAP ABVOL BAVOL TOTVOL 16thAve_EB 1630 1630 3260 6500 6500 13000 1197 2124 3321 15thAve_EB 6204 7861 14065 15000 15000 30000 5013 8487 13500 4thAve_EB 9432 0 9432 22500 0 22500 10492 0 10492 3rdAve_EB 0 5693 5693 0 15000 15000 0 6712 6712 6thAve_EB 13242 0 13242 24900 0 24900 13646 0 13646 9thAve_EB 4048 3448 7496 15000 15000 30000 2183 1821 4004 5thAve_EB 0 19578 19578 0 24900 24900 0 11200 11200 Screenline Totals 34556 38210 72766 83900 76400 160300 32532 30343 62875 25000 20000 15000 10000 Counts Model 5000 0 16thAve_EB 15thAve_EB 4thAve_EB 3rdAve_EB 6thAve_EB 9thAve_EB 5thAve_EB ANC/TP41158.DOC/050460017 F-17

SCREENLINES (2007) South of 9 th L to Medfra ABLKNME ABCOUNT BACOUNT TOTCOUNT ABCAP BACAP TOTCAP ABVOL BAVOL TOTVOL ASt_SB 0 12873 12873 0 24900 24900 0 14792 14792 GambellSt_SB 23233 0 23233 33200 0 33200 25017 0 25017 LSt_SB 16339 0 16339 24900 0 24900 13703 0 13703 ISt_SB 0 16270 16270 0 24900 24900 0 21326 21326 ESt_SB 1793 1793 3586 5000 5000 10000 383 597 980 CSt_SB 19339 0 19339 24900 0 24900 13172 0 13172 IngraSt_SB 0 19478 19478 0 33200 33200 0 19840 19840 MedfraSt_SB 748 748 1496 5000 5000 10000 249 271 520 Screenline Totals 61452 51162 112614 93000 93000 186000 52523 56826 109349 30000 25000 20000 15000 Counts Model 10000 5000 0 ASt_SB GambellSt_SB LSt_SB ISt_SB ESt_SB CSt_SB IngraSt_SB MedfraSt_SB ANC/TP41158.DOC/050460017 F-18

(2008) East of Ingra 3 rd to 15 th ABLKNME ABCOUNT BACOUNT TOTCOUNT ABCAP BACAP TOTCAP ABVOL BAVOL TOTVOL 15thAve_EB 11320 11320 22640 20750 20750 41500 14437 12360 26798 5thAve_EB 21109 21966 43075 16600 16600 33200 22189 22392 44581 3rdAve_EB 5181 5181 10362 15000 15000 30000 5629 4400 10029 Screenline Totals 37610 38467 76077 52350 52350 104700 42255 39153 81407 50000 45000 40000 35000 30000 25000 20000 15000 10000 5000 0 15thAve_EB 5thAve_EB 3rdAve_EB Counts Model ANC/TP41158.DOC/050460017 F-19

SCREENLINES (2010) North of Fireweed/ Northern Lights Minnesota to Muldoon ABLKNME ABCOUNT BACOUNT TOTCOUNT ABCAP BACAP TOTCAP ABVOL BAVOL TOTVOL ASt_SB 0 16296 16296 0 24900 24900 0 19589 19589 MinnesotaDr_SB 0 15600 15600 0 16600 16600 0 16673 16673 MinnesotaDr_SB 17436 0 17436 24900 0 24900 15150 0 15150 SpenardRd_SB 0 4142 4142 0 12000 12000 0 2456 2456 CSt_SB 16810 0 16810 24900 0 24900 17688 0 17688 ArcticBlvd_SB 3600 3600 7200 5000 5000 10000 1399 1617 3016 NewSewardHwy_SB 26200 27500 53700 33200 33200 66400 28029 29026 57055 LakeOtisPkwy_SB 10000 10000 20000 12450 12450 24900 9199 4498 13697 BragawSt_SB 9297 9154 18451 18750 18750 37500 10298 8599 18897 BonifacePkwy_SB 10303 9912 20215 16600 16600 33200 12808 12771 25579 BaxterRd_SB 3300 3300 6600 5000 5000 10000 2262 2156 4417 MuldoonRd_SB 16294 16958 33252 23000 23000 46000 11265 11725 22990 Screenline Totals 113240 116462 229702 163800 167500 331300 108099 109109 217208 60000 50000 40000 30000 20000 Counts Model 10000 0 ASt_SB MinnesotaDr_SB MinnesotaDr_SB SpenardRd_SB CSt_SB ArcticBlvd_SB NewSewardHwy_SB LakeOtisPkwy_SB BragawSt_SB BonifacePkwy_SB BaxterRd_SB MuldoonRd_SB ANC/TP41158.DOC/050460017 F-20

(2013) East of Northwood Northern Lights to International Airport ABLKNME ABCOUNT BACOUNT TOTCOUNT ABCAP BACAP TOTCAP ABVOL BAVOL TOTVOL IntlAirportRd_WB 18074 18074 36148 30000 30000 60000 19560 18938 38498 SpenardRd_SB 9710 9710 19420 15000 15000 30000 6988 11255 18244 McRaeRd_WB 1382 1382 2764 5000 5000 10000 1747 1819 3566 NorthernLightsBlvd_WB 12491 12549 25040 16600 16600 33200 9786 10796 20582 Screenline Totals 41657 41715 83372 66600 66600 133200 38081 42808 80889 45000 40000 35000 30000 25000 20000 Counts Model 15000 10000 5000 0 IntlAirportRd_WB SpenardRd_SB McRaeRd_WB NorthernLightsBlvd_WB ANC/TP41158.DOC/050460017 F-21

SCREENLINES (2014) North of International Airport Spenard to Lake Otis ABLKNME ABCOUNT BACOUNT TOTCOUNT ABCAP BACAP TOTCAP ABVOL BAVOL TOTVOL MinnesotaDr_SB 23716 0 23716 24900 0 24900 24632 0 24632 CSt_NB 12977 12977 25954 24900 24900 49800 9303 12393 21696 MinnesotaDr_NB 21567 0 21567 58500 0 58500 18188 0 18188 SpenardRd_SB 9405 9405 18810 7500 7500 15000 8534 11553 20087 NorthwoodSt_SB 1065 1066 2131 5000 5000 10000 756 536 1292 ArcticBlvd_SB 7355 6772 14127 15000 15000 30000 5207 8691 13898 NewSewardHwy_NB 30446 0 30446 39000 0 39000 28293 0 28293 HomerDr_SB 1011 0 1011 18000 0 18000 1388 0 1388 0 0 1260 1260 0 18000 18000 0 3113 3113 NewSewardHwy_SB 30495 0 30495 39000 0 39000 31683 0 31683 OldSewardHwy_SB 11500 11500 23000 16600 16600 33200 8772 12636 21408 LakeOtisPkwy_SB 17000 17000 34000 23000 23000 46000 17015 14734 31749 Screenline Totals 166537 59980 226517 271400 110000 381400 153771 63655 217426 40000 35000 30000 25000 20000 15000 10000 5000 0 Counts Model MinnesotaDr_SB CSt_NB MinnesotaDr_NB SpenardRd_SB NorthwoodSt_SB ArcticBlvd_SB NewSewardHwy_NB HomerDr_SB 0 NewSewardHwy_SB OldSewardHwy_SB LakeOtisPkwy_SB ANC/TP41158.DOC/050460017 F-22

(2016) West of Minnesota Raspberry to Klatt ABLKNME ABCOUNT BACOUNT TOTCOUNT ABCAP BACAP TOTCAP ABVOL BAVOL TOTVOL DimondBlvd_WB 14076 15004 29080 24900 24900 49800 12655 17010 29665 100thAve_WB 3915 3915 7830 15000 15000 30000 5606 2161 7767 KlattRd_WB 3015 3015 6030 13000 13000 26000 2699 2917 5616 StrawberryRd_EB 900 900 1800 0 24000 24000 0 0 0 RaspberryRd_WB 11850 12014 23864 12400 12400 24800 8343 5415 13757 Screenline Totals 33756 34848 68604 65300 89300 154600 29303 27503 56806 35000 30000 25000 20000 15000 Counts Model 10000 5000 0 DimondBlvd_WB 100thAve_WB KlattRd_WB StrawberryRd_EB RaspberryRd_WB ANC/TP41158.DOC/050460017 F-23

SCREENLINES (2020) South End of Study Area New Seward Highway ABLKNME ABCOUNT BACOUNT TOTCOUNT ABCAP BACAP TOTCAP ABVOL BAVOL TOTVOL NewSewardHwy_SB 4480 4480 8960 7400 7400 14800 4687 4067 8754 Screenline Totals 4480 4480 8960 7400 7400 14800 4687 4067 8754 9000 8950 8900 8850 8800 Counts Model 8750 8700 8650 NewSewardHwy_SB ANC/TP41158.DOC/050460017 F-24