How To Model Travel Demand

Similar documents
Overview of the Travel Demand Forecasting Methodology

GTA Cordon Count Program

WICHITA FALLS METROPOLITAN PLANNING ORGANIZATION

Representing Walking in Trip-Based Travel Demand Forecasting Models ~~ A Proposed Framework ~~

Anchorage Travel Model Calibration and Validation

6 REGIONAL COMMUTE PATTERNS

4.5 TRANSPORTATION - YEAR 2025 TRAFFIC CONDITIONS WITH PROPOSED TIMP ESTIMATION OF TRIP REDUCTIONS WITH TIMP TRANSIT AND TDM PROGRAMS

TCRP Report 153: Guidelines for Providing Access to Public Transportation Stations. Part 2: Station Typology and Mode of Access Planning Tool

Appendix E Transportation System and Demand Management Programs, and Emerging Technologies

HOW WILL PROGRESS BE MONITORED? POLICY AREA. 1. Implement the 2040 Growth Concept and local adopted land use and transportation plans

Market Research and Implementation Plan

ARC Bike/Ped Plan Equity Discussion. Presented to ARC Bike/Ped Plan Equity Advisory Group July 29 th, 2015

The Fresno COG Travel Demand Forecasting Model How the Pieces Fit Together

Transportation Breakout Session. Curvie Hawkins Mark Rauscher Mike Sims Paul Moore

Transportation Education Series: Travel Demand Modeling. David Reinke November 2012

11. Monitoring Performance monitoring in LTP2

Appendix J Santa Monica Travel Demand Forecasting Model Trip Generation Rates

GTFS: GENERAL TRANSIT FEED SPECIFICATION

APPENDIX E TASK 5 TECHNICAL MEMORANDUM: TRAVEL DEMAND FORECASTING PROCESS

Evaluation Criteria and Mode Progression for RouteAhead Rapid Transit Projects

CHAPTER 2 Land Use and Transportation

T-BEST: Nothing But the Best for All Your Transit Planning and Ridership Forecasting Needs

INTRODUCTION TO TBEST. An FDOT Model for Short Range Transit Ridership Forecasting

CHAPTER 8: INTELLIGENT TRANSPORTATION STSTEMS (ITS)

Proposed New Starts/Small Starts Policy Guidance

Bus Users in Sydney. Transport Data Centre ISSUES PAPER 2002/02 DECEMBER 2002 ISSN ISBN

Traffic Information in NYC

Pompano Education Corridor Transit Study - Existing Conditions Technical Memorandum #1. Figure 59 Total Number of Employees (2040)

R-06: Innovation and Technology Fund

Model Validation and Reasonableness Checking Manual

Why NEC FUTURE? 457 MILES LONG 2,200 DAILY TRAINS 750,000 DAILY PASSENGERS. Study Partners. Key Needs

Tripp Umbach developed a detailed survey with input from the PDP and distributed the survey to six Downtown Pittsburgh market segments:

School-related traffic congestion is a problem in

Sustainable urban mobility: visions beyond Europe. Brest. Udo Mbeche, UN-Habitat

Examples of Transportation Plan Goals, Objectives and Performance Measures

Urban Transport Issues in Egypt

Planning and Analysis Tools of Transportation Demand and Investment Development of Formal Transportation Planning Process

How To Expand Commuter Rail Between Worcester And Boston

Southwest Light Rail Transit Minneapolis-St. Paul, Minnesota New Starts Project Development (Rating Assigned November 2014)

CITY OF ROANOKE AND TOWN OF VINTON, VIRGINIA. RSTP Funds Joint Application FOR

MODELING TRANSPORTATION DEMAND USING EMME/2 A CASE STUDY OF HIROSHIMA URBAN AREA

Primer on Transportation Funding and Governance in Canada s Large Metropolitan Areas

Data Collection and Sampling issues -Preparing Low Carbon Mobility Plan

Chapter 9: Transportation

Leicestershire County Council Transport Trends in Leicestershire Transport Data and Intelligence (TDI)

Planning and Design for Sustainable Urban Mobility

6. Cost Summary and Analysis This chapter summarizes and analyzes the cost estimates from previous chapters.

Transitways and the RouteAhead for Calgary Transit

Forecasting Stop-Level Ridership for Florida s Transit Systems

Ohio Standard Small/Medium MPO Travel Demand Forecasting Model. Theoretical Training May 10-11, 2006 Abridged to Freight Focus Sept 2010

HOUSEHOLD TRAVEL SURVEY

PUBLIC TRANSPORT NETWORK DESIGN AND APPRAISAL A CASE STUDY OF PORTO

Journey to Work Patterns in the Auckland Region

ORANGE COUNTY TRANSPORTATION AUTHORITY. Final Long-Range Transportation Plan - Destination Attachment A

Prefeasibility Study for the High Speed Line HU-RO Border Bucharest - Constanta Description and Objectives

Congestion Management Systems: A Federal Perspective. 7 Key CMS Components

TRANSPORTATION MODELLING IN CALGARY

5.0 FINANCIAL ANALYSIS AND COMPARISON OF ALTERNATIVES

Why Talk About Transport in Africa? SUSTAINABLE URBAN TRANSPORT IN AFRICA: ISSUES AND CHALLENGES. Urbanization and Motorization in Africa

A Review of Transit Technology Specifications

How To Plan A City Of Korea

Actual Versus Forecast Ridership on MetroLink in St. Clair County, Illinois

An Interactive Preference Analysis Method for Evaluating Possible Intercity Transit Options

Residential Development Travel Plan

GOALS, OBJECTIVES, AND EVALUATION MEASURES

Forecasting Demand for Demand Forecasting. Abstract

Connecticut s Bold Vision for a Transportation Future

Light Rail Transit in Phoenix

Proposed Service Design Guidelines

2012 King County Metro Transit Peer Agency Comparison on Performance Measures

Washington Metropolitan Area Transit Authority Board Action/Information Summary

Request for Proposals. Transportation Model and GIS-Based Analysis Tools in Updating the Long-Range Transportation

A Framework for Monitoring the Performance of Travel Demand Management and Vehicle Miles Traveled (VMT) Reduction Activities

The Northwest Arkansas Travel Demand Model

Network development and design

When is BRT the Best Option? 1:30 2:40 p.m.

Evergreen Line Rapid Transit Project Business Case Executive Summary. February Reviewed by

Ideal Public Transport Fares

CONNECTING NEVADA PHASE II

Article. Commuting to work: Results of the 2010 General Social Survey. by Martin Turcotte

30 Years of Smart Growth

Mercer County Multi-Modal Transportation Plan Year 2025 Travel Demand Model

VIII. TRANSPORTATION

Transportation Alternatives

GIS Analysis of Population and Employment Centers in Metro Denver Served by RTD s FasTracks

APPLICATION FORM MASS TRANSIT PROGRAM GRANT APPLICATION PROJECT NAME LEAD AGENCY PROJECT TYPE GENERAL PROJECT AREA

Chapter 1: Background

Nashville Freight Model. Max Baker, Nashville MPO Rob Bostrom, WSA July 17, 2008 Tennessee MUG

INDOT Long Range Plan

THE IMPLICATIONS OF ALTERNATIVE GROWTH PATTERNS ON INFRASTRUCTURE COSTS

Integrated Public Transport Service Planning Guidelines. Sydney Metropolitan Area

Measuring Transportation

State of Good Repair Roundtable Chicago, Illinois. Asset Management Systems MBTA Approach and Lessons Learned

How To Plan A City Of Mason

Application of a Travel Demand Microsimulation Model for Equity Analysis

4-Step truck model: SCAG case study

Needs Analysis. Long Beach Bicycle Master Plan. Bicycle Commuter Needs. LONG BEACH BICYCLE MASTER PLAN Needs Analysis

Mount Royal College Transit Service Plan

Capital Investment Program

Bus Priority Measures in Calgary: Past, Present and Future. Chris Jordan, M.Sc., P.Eng., Coordinator, Strategic Transit Planning, Calgary Transit

Transcription:

Support to the Casey Overpass Study Central Transportation Planning Staff Support Staff to the Boston Region MPO Overview of the Regional Travel Demand Model Set May 18, 2011 OVERVIEW The model set that the Central Transportation Planning Staff (CTPS), the Boston Region Metropolitan Planning Organization s (MPO) technical staff, uses for forecasting travel demand is based on procedures and data that have evolved over many years. The model set is of the same type as those used in most large urban areas in North America. It uses the best computer models, transportation networks, and input data available to CTPS at this time. The model set is used to simulate existing travel conditions and to forecast future year travel on the entire transportation system spanning most of Eastern Massachusetts, for the transit, auto, and walk/bike modes. The model set simulates the modes and routes of trips from every zone to every other zone. Population, employment, number of households, auto ownership, highway and transit levels of service, downtown parking costs, auto operating costs and transit fares are some of the most important inputs that are used in applying the model to a real world situation. These inputs are constantly updated so that the model set simulates current travel patterns with as much accuracy as possible. The MPO travel model set has been used in a number of recent studies such as the Urban Ring Phase Two Study, the Silver Line Phase III Study, the North Shore Transportation Study, and the South Weymouth Naval Air Station Development Study. MAJOR FEATURES OF THE MODEL Some important features of the model set are listed below. The model area encompasses 164 cities and towns in eastern Massachusetts as shown in Figure 1. The modeled area is divided into 2727 internal Transportation Analysis Zones (TAZ s) as shown in Figure 2. There are 124 external stations around the periphery of the modeled area that allow for travel between the modeled area and adjacent areas of Massachusetts, New Hampshire and Rhode Island. The model set was estimated using data from a Household Travel Survey, External Cordon Survey, several Transit Passenger Surveys, the 2000 U.S. Census data, an employment database for the region, and a vast database of ground counts of transit ridership and traffic volume data collected over the last decade. The transportation system is broken down into three primary modes. The transit mode contains all the MBTA rail and bus lines, commuter boat services, and private express bus carriers. The auto mode includes all of the express highways, principle arterials, many minor arterials and local roadways. Walk/bike trips are also examined and are represented in the non-motorized mode. The non-motorized mode is represented as a network of roadway, bike trails, and major walking paths. 1

The model for this Needs Assessment is set up to examine travel on an average weekday in the spring over four time periods, for the year being examined. The base year is 2009. The forecast year is 2035. FIVE STEP-MODEL The model set is based on the traditional four-step urban transportation planning process of trip generation, trip distribution, mode choice, and trip assignment. This process is used to estimate the daily transit ridership and highway traffic volumes, based on changes to the transportation system. The model set takes into consideration data on service frequency (i.e. how often trains and buses arrive at any given transit stop), routing, travel time and fares for all transit services. The highway network includes all of the express highways and principle arterial roadways as well as many of the minor arterial and local roadways. Results from the computer model provide us with detailed information relating to transit ridership demand. Estimates of passenger boardings on all the existing and proposed transit lines can be obtained from the model output. A schematic representation of the modeling process is shown in Figure 3. The Five-Step Model 1. Vehicle Ownership: Household auto ownership is an input to trip generation and mode choice. It is forecast using a logit model developed with the Household Travel Survey and 2000 U.S. Census data. The model is integrated with the trip production procedures. These models estimate the probability of a household owning a certain number of vehicles as a function of income, household size, workers per household, household density, employment density, household location, and transit walk access factors. 2. Trip Generation: In the first step, the total number of trips produced by the residents in the model area is calculated using demographic and socio-economic data. Similarly, the numbers of trips attracted by different types of land use such as employment centers, schools, hospitals, shopping centers etc., are estimated using land use data and trip generation rates obtained from travel surveys. All of these calculations are performed at the TAZ level. 3 Trip Distribution: In the second step, the model determines how the trips produced and attracted would be matched throughout the region. Trips are distributed based on transit and highway travel times between TAZ and the relative attractiveness of each TAZ. The attractiveness of a TAZ is influenced by the number and type of jobs available, the size of schools, hospitals, shopping centers etc. 4. Mode choice: Once the total number of trips between all combinations of TAZ s is determined, the mode choice step of the model splits the total trips among the available modes of travel. The modes of travel are walk, auto and transit. To determine what proportions of trips each mode receives, the model takes into account the travel times, number of transfers required, and costs associated with these options. Some of the other variables used in the mode choice are auto ownership rates, household size, and income. 2

5. Assignment: After estimating the number of trips by mode for all possible TAZ combinations, the model assigns them to their respective transportation networks. Reports showing the transit and highway usage can be produced as well as the impact of these modes on regional air quality. MODEL APPLICATION Once the calibration is complete, the model for the Casey Overpass Study will be run for the 2035 forecast year no-build scenario, using future year inputs such as projected population and employment by TAZ, in addition to transportation system characteristics. Ridership forecasts are first developed for a no-build forecast year that assumes no improvements in the corridor. Then the transportation network is updated to reflect the project improvements and the model is re-run for the various build options. The outputs of these model runs can then be compared to the nobuild to see what changes in travel patterns occur to the transportation system. MODEL OUTPUTS The travel model can produce several important statistics related to the region s transportation system. Some of these are listed below. Average daily transit ridership by transit sub modes Average weekday station boardings by mode of access Average mode split by geographic region Average trip length for transit and auto trips Origin and destination information of who is using which roadways by time period Total vehicle miles and vehicle hours of travel, made by all vehicles. Average speed of traffic in the region Daily traffic volumes on major freeways, expressways and arterials Amount of air pollution produced by the automobile traffic, locomotives and buses 3

FIGURE 1: Model Area 164 Community Boundary 101 Community Boundary 164 Communities = CTPS Model area 101 Communities = Boston Region MPO 4

FIGURE 2: TAZ Structur e in Casey Overpass Study Area Source: CTPS 2727 TAZ Model for Casey Overpass 5

FIGURE 3: 5-Step Travel Demand Model 6