INCORPORATING TOLL PRICING POLICY INTO A MICROSIMULATION MODEL FOR LONG-DISTANCE FREIGHT TRANSPORTATION

Transcription

1 INCORPORATING TOLL PRICING POLICY INTO A MICROSIMULATION MODEL FOR LONG-DISTANCE FREIGHT TRANSPORTATION University of Wisconsin Milwaukee Paper No National Center for Freight & Infrastructure Research & Education College of Engineering Department of Civil and Environmental Engineering University of Wisconsin, Madison Authors: Qinfen Mei and Alan J. Horowitz Center for Urban Transportation Studies University of Wisconsin Milwaukee Principal Investigator: Alan J. Horowitz Professor, Civil Engineering and Mechanics Department, University of Wisconsin Milwaukee May 11, 2011

2 Incorporating Toll Pricing Policy into a Microsimulation Model for Long-Distance Freight Transportation Abstract: Many public policies have been enacted by policy makers and these policies have affected or could affect the freight transportation system. Carriers need to minimize costs to maximize the profits and they often need to deliver the goods to the receivers by a specific time, so toll pricing policy has unpredictable effects on trucker routing decisions. Most freight models in the past have considered only travel time as the path building criterion. This working paper proposes to extend the existing MVFC (Mississippi Valley Freight Coalition) microsimulation model to a new model with the capability of incorporating the toll pricing policy into its traffic assignment step. For dynamic traffic assignments in rural areas, long distance truck drivers usually have a required period of resting after the driving limit. Thus, this paper will also consider the truck driver Hour-of-Service rules in the MVFC model. One of the key aspects of this paper is the estimation of values of time especially for different commodities and truck classes. The literature review reveals that there are no studies done for values of time by commodity by truck class in the Mississippi valley region or elsewhere. Thus, a truck cost model developed by Hussein (2010) is modified to calculate truck costs for two scenarios: Scenario One (distance-based costs) and Scenario Two (time-based costs) by changing some input data. Then, a linear regression analysis is performed to estimate values of time and per-mile cost for five commodities and two truck classes for each scenario. By using values of time the collected tolls (in dollars) are converted to extra times (in minutes). Also, distances are converted to the units of time by using a distance weight, also obtained from the linear regressions. Three runs with different assumptions on the MVFC network were performed for the case of three industrial commodities assigned using parameters for motor vehicle parts. The comparisons from one run to the other revealed that in response to tolls, truck drivers change their routes when the impedance of the original route exceeds the alternative route s impedance. The comparisons of the simulation results to actual data from ATR stations in the State of Ohio and from counts provided by the Ohio Turnpike Authority suggest that the values of time for motor vehicle parts in Scenario Two are more reliable than those in Scenario One.

3 INTRODUCTION Background The rapid development of the American economy means that billion more tons of goods are transported on the U.S. freight transportation network each year. The freight system has greatly affected the environment and human activities. State and local governments are charged for constructing, maintaining, operating, funding, and regulating the transportation infrastructures and facilities on which much of the freight moves. Federal, state, and local policy makers have enacted many public policies regarding the freight industry. In terms of revenue generating policies fuel taxes are imposed by federal government and states to build, operate, and maintain the highway system for both freight and passenger vehicles. In addition, other user charges, such as tolls may be adopted by some states and some other authorities to finance highways. These revenue-generating policies have affected the operating costs for shipping a given commodity, so they are of interest to at least two kinds of institutions: carriers and governments. Carriers are the providers of transportation services, meaning they serve both receivers and suppliers; therefore, customer needs come into play when carriers make travel choices. Carriers usually have to follow a schedule and often need to deliver the goods to the receivers by a specific time. In addition, carriers need to minimize the shipping costs to maximize their profits or to remain competitive. Thus, carriers need to make decisions whether to choose alternative routes to avoid tolls when moving the freight. Governments need to evaluate the impacts of truck traffic diversion so as to enact sound transportation policies in the future. Diverted truck traffic will cause congestion, neighborhood, and safety issues on the alternative routes. Also, toll authorities will lose some revenues due to such traffic diversion. Short distance truck drivers shipping the goods in urban areas usually travel between two locations in exactly the driving time. Long distance truck drivers in rural areas need to have a required period of resting after the driving limit according to the Hour-of-Service (HOS) rules, so a long-distance truck driver usually drives longer to finish his trip than the driving time. Thus, the truck driver HOS rules are an important factor that affects truck routings and truck costs for the long distance shipping. In addition, they are very important to the safety of trucking operations -- both for the safety of truck drivers themselves and for the safety of others sharing the roads with them. It is especially important to examine the effects of toll pricing on the freight transportation system. The purpose of this working paper is to develop an efficient model for long-distance freight transportation which is able to simulate truck traffic conditions affected by tolls and other road pricing factors. Definitions of Key Freight Modeling Terms To help better understand the model described in this paper, it is important and useful to define several terms relative to freight models and describe key features of them. 1. Commodity A commodity is commonly defined as physical substance (such as food, grains, and metals) which is interchangeable with another product of the same type, and which investors buy or sell, usually through future contracts. The Quick Response Freight Manual defines it as an item traded

4 in commerce, which usually implies an undifferentiated product competing primarily on price and availability. However, a commodity in travel modeling is defined as a single category of anything of economic value that needs to be transported. 2. Value of Time Value of time is the change in amount of a traveler s willingness to pay in money for a unit change in travel time. In transport economics, value of time is the amount of money a user pays to save time or compensate for lost time. 3. Policy A policy is typically described as a principle or rule to guide decisions and achieve rational outcome(s). In NCFRP Report 6, policy is often used to do with general statements of principles or goals, and specific government actions. A general policy statement made by a government agency that conveys the desire to adopt measures for some particular purposes is called a policy-in-principle. A policy-in-fact includes formal actions done by elected officials or government agencies. Government decisions to adopt taxes and fees are policies of interest to this paper, because, one way or another, such decisions either directly affect behavior of various entities relating to freight carriage or change in some way the environment in which actors in the freight system operate and make decisions (NCFRP 06, 2010). 4. Toll Toll is usually the amount of money charged by some authorities for the permission to access a road or a bridge. These roads and bridges are called toll roads and toll bridges. 5. Route A route is a sequence of specific individual facilities (such as, sections of roads, railroad tracks, etc.) that are used to transport freight between the origin and destination on a specific mode (NCHRP 606, 2008). 6. Truck Cost Model Truck cost models are mathematical algorithmsor equations with some parameters used to estimate the truck costs under different equipment configurations, input prices, and gross vehicle weights. 7. Microsimulation Microsimulation is the imitation of traffic conditions based on individuals behavior by using a simulation model. Microsimulation is often used to evaluate the effects of proposed interventions before they are implemented in the real world. 8. Four Step Model A four-step model is usually developed to simulate traffic conditions at present or in the future, which includes trip generation, trip distribution, mode split, and traffic assignment. In the process of this model, trips begin at a trip generation zone, move through a network of links and nodes by mode and end at a trip attraction zone.

5 Trip generation is the first step in the travel forecasting model. This step estimates how many trips begin or end in each zone by trip purpose based on a function of land uses, household demographics, and other socioeconomic factors. In the freight model, trip generation estimates the productions and attractions of freight movements in tonnage that begin or end in a geographically defined analysis zone, based on the zonal economic characteristics reflected by employment in particular economic sectors and by number of households. Trip distribution calculates the number of trips going from each origin to each destination in a trip table or matrix. The gravity model is the most common method for performing this allocation of trips. In the freight model, this step distributes freight flows in tonnage and by commodity group on an O-D basis. The primary impedance variables include average travel distance, average travel time, or composite modal travel time. Mode split determines the percentage of trips between a given origin and destination that use a particular transportation mode. In the freight model, by using the information about relative benefits of the utility of each freight mode, commodity flow tonnages in the O-D tables are factored by modes such as trucks, rail, etc. Trip assignment is the fourth step in the conventional transportation forecasting model, following trip generation, trip distribution, and mode choice. It concerns where trips between a given origin and destination by a particular mode are assigned to the transportation network. In the freight model, this step forecasts freight volumes on individual links of the modal networks. When allocating the freight trips, the optimum path or sequence of links between all geographic zones are found based on some important impedance variables, such as travel time, distance, and costs. 9. Control Delay Control delay is defined by traffic control systems handbook (FHWA) as the component of delay that results when a control signal causes a lane group to reduce speed or to stop; it is measured by comparison with the uncontrolled condition. Control delay includes initial deceleration delay, queue move-up time, stopped delay and final acceleration delay. 10. Level of Service (LOS) Level of service (LOS) defined in traffic engineering is a letter designation that describes a range of operating conditions on a particular type of facility. Letters A through F are used to define six level of service. Level A represents the best level of service which generally describes operating conditions with free flow and very low delay. Level F represents the worst operating conditions. 11. Dynamic Traffic Assignment Dynamic traffic assignment uses a computer program to build paths for the trucks and these paths can vary depending on the network condition, congestion, new facilities, etc. Key factors that go into building the paths include infrastructure or cargo restrictions, although specific routings are usually selected as a function of cost, travel time, and quality of service (NCHRP 384, 2008). Dynamic traffic assignment can calculate new routes as congestion increases. It can be used for simulating the situation that the users are charged different toll rates at different time of day.

6 12. Multiclass Traffic Assignment Multiclass traffic assignment usually tracks truck trips separately from passenger vehicles, so it can treat truck trips separately by truck size. 13. Clock Time Clock time is the current simulation time, which the simulation model keeps track, in whatever measurement units are suitable for the system being modeled. 14. Extra Time Extra time presents the value of impedance which can be added to links in the simulation model but it does not affect clock time. For example, tolls and intersection delay can be coded as extra times. 15. Impedance Impedance is a model variable of each road network link, which represents travel time, distance, cost or a combination of them. Sometimes it is also called disutility or generalized cost. It usually has units of minutes. 16. Automatic Traffic Recorders (ATRs) Automatic Traffic Recorders (ATRs) are loops in the pavement surface that continuously and automatically collect long-term traffic volume data. 17. Electronic Toll Collection (ETC) Electronic toll collection allows the automatic in-lane toll collection process to replace the manual collection process. By using electronic toll collection, drivers do not have to stop and pay cash at a toll booth and toll booth facility operators can improve customer service and satisfaction by speeding the vehicles through the toll plaza. 18. Average Annual Daily Truck Traffic (AADTT) Average annual daily truck traffic (AADTT) is the total volume of truck traffic on a highway segment for one year, divided by the number of days in the year (QRFM II, 2007). 19. Calibrate Calibration consists of changing values of model input parameters in an attempt to match field conditions within some acceptable criteria (Melendez, 2010). 20. Validate Validation is checking a model for how well its assumptions, constants, variables and values fit specific local system and predicts current conditions (Melendez, 2010).

7 Introduction of Freight Model As mentioned, this paper is attempting to enhance a freight model with the capability of modeling the effects of tolls and other pricing factors. Before delving into the description of the model, it is important to introduce some information and theories about freight models. Transportation planners and policy-makers have a great interest in understanding freight activity and have attempted to better incorporate freight into the travel models. However, efforts to develop microsimulation models of freight demand have lagged noticeably behind models for passenger travel, because freight transportation is determined by numerous of factors and modeling freight movements is a very complicated process. Horowitz (2010) mentioned that there are only a few fledging attempts at using the microsimulation for short-distance urban shipping (Hunt, Stefan and Frownlee, 2006; de Jong and Ben-Akiva, 2007; Hunt and Stefan, 2007; Wisetjindawat, et al., 2007; Wang and Holguin-Veras, 2008) and none for long-distance shipping. One of the most common modeling techniques for travel demand is the traditional four-step model, which is usually used for personal travel. Four-step models have offered a familiar platform and opportunities to share existing network and algorithms for developing a macroscopic approach to simulating freight movements. Truck-based model and commodity-based model are two major types of freight models. The truck-based models (shown in Figure 1) measure the freight transportation in the form of truck movements without consideration of the amount of commodity production and consumption. These models obviously eliminate the mode choice steps since by definition they include only the truck freight mode. The commodity-based models (shown in Figure 2) closely resemble the four-step travel demand model for passengers including generation of shipments, distribution of shipments, mode split allocation of shipments, and the network assignment of the resulting vehicles. Traffic assignment is the last step of four-step model, which assigns the modal freight trips to the paths identified from the modal network and forecasts freight volumes on individual links of this modal network. The model looks for optimum paths between all geographic zones, and this path is based on impedance factors such as travel time, travel distance, and cost.

8 FIGURE 1 Truck-based Model (NCHRP606) FIGURE 2 Commodity-based Model (NCHRP606) Description of MVFC Model (Horowitz, 2010) The traffic assignment model for this paper is a part of the MVFC microsimulation model, so there is a need to briefly describe the MVFC model. The Mississippi Valley Freight Coalition (MVFC), a consortium of ten state DOTs, and the Center for Freight Infrastructure Research and Education (CFIRE, a national university transportation center) teamed to develop a microsimulation of freight demand for a 10-state region in the central U.S., even though it is challenging to work on such a large scale. The current MVFC model covers five indicator commodities (corn, soybeans, dairy products, plastics and motor vehicle parts) which are particularly important for the Mississippi Valley region, and trucking is the only mode of interest. MVFC microsimulation involves several complicated processes, during which many random shipments for a given commodity are generated and then randomly assigned to random vehicles which are finally loaded on a road network. For the road network, the model has adopted the ORNL network containing all major highways in the U.S. and these highways are represented as 112,000 links. The model retains all the details for the ten MVFC states and 100 miles extension of these states, while it reduces the network outside the defined area to interstate highway, only. Eventually, the reduced network has approximately 44,000 links with many attributes retained from the original ORNL network, but only speed and distance on links have been used in the current microsimulation. And also, the information on link capacity within the region is not used because only a fraction of traffic is being simulated.

9 For the traffic analysis zones which were defined to be consistent with FAF, they were used within the region only for the purpose of tabulating statistics and rough-checking establishment locations. The MVFC model loaded trips from external super-establishments at intersections nearest the mathematical centroid of FAF zones; such intersections were usually interchanges on interstate highways. To obtain truck volumes on each road, the traffic assignment algorithm inputted a very large set of trip records, each trip being identified by its origin location (longitude and latitude), destination location, start time, and truck type. Traffic assignments are potentially both multiclass (many vehicle classes) and dynamic. The MVFC microsimulation model for long-distance freight transportation has the capability of addressing many of the public policies related to freight movements (shown on Table 1).

10 TABLE 1 Public Policies Addressed in the MVFC Microsimulation Model Can be Addressed by Policy a Model (Y/N) Model Feature Assessment 1 HOS Rules for Truck Drivers Y In a dynamic model, average resting time for truck drivers can be added as time interval after a maximum of 11 hours is driven. Average driving time before resting can be added into the model as well. In the current model, 10 hours are assumed as truckers resting time and 11 hours are assumed as driving time. It is notable that driver s resting time affects the model clock time, not the impedance. Resting time can be also used as a factor in the truck cost model but current cost model does not consider it. Average resting time and driving time can be obtained by survey but it is time- and moneyconsuming, so a literature review was conducted but there was little data available. Thus, it's not practical to simulate the real average resting time and driving time, so the current model uses the HOS rule limit (10 hours resting after 11 hours driving) for average resting time and driving time. In the truck cost model, most factors are based on distance so the resting time as time interval only has little effect on costs. 2 Truck Speed Limits and Speed Governor Rules Y Actual speed should be used on each link, but in current model, speed for each link is inputted by using the speed limit. To deal with intersection delay, extra time is added to each direction of each surface street to account (roughly) for control delay at the ends of those links. Speed is also used within the truck cost model to obtain the value of time. Actual speed is based on all the traffic including trucks and autos. Trucks consist of empty trucks and trucks loaded with all commodities and wastes. However, it is quite complicated to run the model considering all vehicles so the current model just considers two classes of trucks and up to five commodities (dairy, plastics, motor vehicle parts, corn, and soybeans). Speed limit is used instead of actual speed. In the truck cost model, an accurate speed would give better estimates for value of time.

11 TABLE 1 Public Policies Addressed in the MVFC Microsimulation Model (Continuation) Can be Addressed by Policy a Model (Y/N) Model Feature Assessment 3 Federal Emission Standards for Diesel Engines Y To meet the requirements of Federal Emission Standards for Diesel Engines, the total truck costs will be raised by adding the costs for purchasing new trucks, maintenance and operating, and purchasing new equipment. Finally, the raised total truck costs will result in the higher value of time. Most of the emission reduction technologies cause a slight reduction in fuel economy (NCFRP 06), so it can offset a little of the raised truck costs. 4 Idling Restrictions for Trucks and Locomotives N The model is not able to simulate idling time periods, and idling time does not affect driver behavior. Resting time periods are related to idling. Value of time obtained from truck cost model might be affected by equipment for reducing idling. 5 State Truck Route Restrictions Y Restricted links can be given a very large travel time. However, the current model does not have truck restriction routes. Our current model is based on the network provided by Oak Ridge National Laboratory, which contains only major road and does not have truck route restrictions.

12 TABLE 1 Public Policies Addressed in the MVFC Microsimulation Model (Continuation) Can be Addressed by Policy a Model (Y/N) Model Feature Assessment 6 Truck Size and Weight Rules Y Number of trucks varies by various shipment sizes, so larger size trucks would imply a smaller number of trucks for shipping the same amount cargos. Some states allow bigger trucks to travel on the roads and some companies would consider split shipments for smaller trucks at the border of states which have different truck size and weight rules, so multiclass assignment is needed. The model could consider these kinds of situations in future applications. 7 Highway Tolls and Other User Charges Y Toll lanes are assigned with extra time based on value of time and the toll. Extra time increases directly with the amount of toll but inversely decreases with the value of time. Diverted trucks are expected on free alternative routes and they would affect other traffic on these alternative routes. Congestion on original routes would be alleviated. However, the model does not consider some situations. For example, some truck companies still prefer toll roads since they want cargos to be delivered on time. The costs might rise on alternative routes due to longer distances, and this situation would have impacts on level of service of the alternative routes. In the model, a good value of time and toll will give more reasonable truck traffic assignments, and reasonable revenue estimates.

13 TABLE 1 Public Policies Addressed in the MVFC Microsimulation Model (Continuation) Can be Addressed by Policy a Model (Y/N) Model Feature Assessment 8 Truck Parking Restrictions N 9 Level of Investment in Highway Infrastructure Y Level of investment in highway infrastructure will change the capacity of highways, and it will affect the destination choice and mode choice. Current model does not consider it. Higher level of investment in highway infrastructure has bigger capacity. 10 Hazmat rules Y Similar to truck route restriction rule, a very large travel time is added to the links on which trucks loaded with hazardous products are restricted to travel. Current model does not consider hazmat. The road network does not have any routes restricting trucks loaded with hazardous products. 11 Peak Pricing for Port Trucks Y By using value of time, pricing at peak time for port trucks can be converted to extra time and then the extra time is added on each toll link. Current model does not consider it. Current model simulates ten states in the Midwest area and port trucks have little effects on traffic congestion, so peak pricing for port trucks is not considered.

14 TABLE 1 Public Policies Addressed in the MVFC Microsimulation Model (Continuation) Can be Addressed by Policy a Model (Y/N) Model Feature Assessment Restrictions on Port Drayage Trucks Truck driver background checks Restrictions on Locomotive Horns Truck electronic onboard recorder rules N N N N 16 Land use planning requirements Y The model can be modified for forecasting future traffic conditions that vary according to land use planning assumptions. Current model does not consider it. The model can be built for future traffic forecasting when land use for industry is changed by planning, e.g. some factories will move in or move out, new industry area will be built, etc. Current model does not have the capability of addressing it. 17 Property taxes Y Same as 16

15 TABLE 1 Public Policies Addressed in the MVFC Microsimulation Model (Continuation) Can be Addressed by Policy a Model (Y/N) Model Feature Assessment 18 Fuel standards Y 19 Fuel taxes Y Same as 18 According to fuel standards, fuel cost in the truck cost model will be affected, which will result in changes to the value of time. 20 Customs regulations Y High travel time is added on delay links, which affects both clock time and impedance. Current model does not consider it. In the future, we can modify the model by considering customs regulations since there are many trucks traveling across the border between Michigan and Canada Programs and incentives to improve fuel efficiency CAFE standards for trucks Requirements or subsidies for renewable fuels (ethanol, biodiesel) Y Same as 18 Y Same as 18 Y Same as 18

16 TABLE 1 Public Policies Addressed in the MVFC Microsimulation Model (Continuation) Can be Addressed by Policy a Model (Y/N) Model Feature Assessment 24 Investment and incentives for alternative fuel infrastructure and vehicles Y Same as Low-carbon-fuel standard Y Same as Level of highway funding Y Same as 9 27 Modal split of funding N The model is built only for trucks now. 28 Highway operations and maintenance decisions Y Model can simulate some situations caused by work zones like congestion. Current model does not consider it. 29 Seasonal load limits on highways Y Multiclass traffic assignment could be used for different sizes of loads by seasons. Current model does not consider it. There are no routes limiting seasonal loads for trucks, so current model does not need to simulate it.

17 Problem Statement To reduce the shipping costs, some truck drivers move to the alternative routes to avoid tolls. This situation is called truck traffic diversion. However, truck traffic diversion is not easily ascertained by simply looking at how much truck drivers have to pay to access the toll roads and bridges. Travel time and distance of the road segments are usually considered as the two important impedance factors for assigning the traffic on the road network. Most models considered only travel time as the path building criterion. All sources of impedance should be taken into account when simulating truck traffic. For dynamic traffic assignment in rural areas, long distance truck drivers have to stop their vehicles to have a rest after driving 11 hours according to the HOS rules. There is a need to add the rest periods into the model in order to know the drivers total traveling time. Thus, HOS rules can affect the routing of a truck as well as the cost of a haul. In order to better address the conditions of the truck traffic diversion by using a traffic assignment model in this paper, several research questions need to be considered: 1. How does the MVFC microsimulation model incorporate the public policy (e.g. toll pricing) into the traffic assignment step? 2. What is the relationship among these three impedance factors (travel time, distance, and cost) or is there a function for converting one factor to another? 3. How can we convert the impedance factors in different units into the same units? 4. Where and how can we obtain the value of time by commodity by truck class? 5. Are there some other factors affecting the truck traffic diversion except travel time, distance, and cost? 6. Will the impedance factors affect the truck traffic diversion in a realistic way? 7. What is the average driving time before resting, if a rest is required? 8. What is the average resting time? The questions above address the purpose of the model. Answering question 2 through question 4 and question 6 is the focus of this paper.

18 LITERATURE REVIEW Introduction Many public policies have affected or could affect the whole freight transportation system. This paper focuses on incorporating the toll pricing policy into the MVFC freight simulation model. Because under this type of policy vehicles are charged for accessing the existing toll roads and bridges; some truck drivers will divert to free alternative roads to seek maximized profits for their trucking firms. Before developing a model to simulate the truck traffic conditions affected by the toll pricing, this chapter will present a literature review of existing studies about some key factors and components of this policy and model. Toll Pricing The cost for construction and maintenance of highways and bridges is largely covered by the revenues from fuel taxes and other user charges, especially tolls. Highway and bridge tolls are set by state, local governments and private authorities. The form and the level of tolls would have vital effects on freight system. In particular, tolls are one type of operating costs for trucking firms that can not easily be passed on to customers so they would affect freight (NCFRP 06, 2010). NCFRP 06 (2010) further pointed out that tolls also affect which road the truck drivers choose, and peak period pricing will have some effect on when they use them. Montana highway reconfiguration study (Montana DOT, 2005) stated that highway toll studies generally focus on the tradeoffs that people make in terms of paying extra cost to reduce travel time (or conversely, their willingness to sit in slower traffic to save tolls). Highway toll studies also reflect driver decisions when they faced these choices (i.e., how drivers value their own time during daily delivery runs). The study also mentioned that the actual form of driver compensation is also different by type of trip. For short-distance drivers who are often paid by the hour, they would gain nothing by paying tolls out of their pockets to save time. For long-distance drivers who are usually paid by a fixed amount per delivery, they have motivation to save time to finish shipments. Value of Time As pointed out in the Montana highway reconfiguration study, value of time is very important because it can be used for different purposes. First, it is usually used as one component of the measurement of total economic benefits from alternative highway improvement projects. Second, some studies adopt a value of time to estimate the effects of proposed tolls, new highway connections, highway widening, or lane use policies affecting peak period capacity. Third, there are also some different uses of values of time, such as predicting how travelers would react to tradeoffs between travel time and travel cost in making highway routing decisions, or travel mode choices, or time-of-day travel decisions. Hence, the right way to view the value of time can be different depending on the specific type of user decision being considered and the specific type of application for it. In this paper, in order to incorporate the highway toll policy into a microsimulation model for freight movements, value of time would be considered as an input to the trip assignment step to convert tolls into equivalent minutes of extra travel time. Besides the toll, distance is another impedance factor for truck drivers to determine which routes to travel on. Value of time, also as one of the parameters affecting the weight in the impedance function for distance relative to

19 time, will be used to convert the units of distance to the units of time. Thus, the importance for good values for travel time is obvious and a review of earlier work will be very useful. Studies about Value of Time in US VOT Obtained from Literature Review To get a reasonable estimate for values of time for trucks, Outwater and Kitchen (PSRC, 2008) conducted a national literature search of observed or estimated truck values of time and this literature search identified a range of $40 per hour to $50 per hour for light, medium and heavy trucks. Another literature review was also conducted by Outwater and Kitchen, along with Ardussi, Bassok and Rossi (PSRC, 2009) because they needed truck values of time as an input to a trip assignment model whenever tolls are imposed to convert tolls into equivalent minutes of travel time. The sources from literature review are identified as follows: Smalkowski et al conducted interviews in Minnesota in 2003 using an adaptive stated preference survey to derive a truck value of time of $49 per hour. Surveys were conduced for for-hire, fleet and private trucks.(psrc, 2009) Kawamura estimated a value of time for trucks at $28 per hour from stated preference data collected in California in His research found that for-hire trucks tend to have a higher value of time than private ones and companies that pay drivers hourly wages have higher values of time than those who pay commissions or fixed salary. (PSRC, 2009) In 2006, FHWA reported that shippers and carriers assign a value to increases in travel time of $25 to $200 per hour, depending on the commodity carried. The value of reliability for trucks is another 50 to 250% higher. (PSRC, 2009) In 2005, FHWA reported that the delay cost for trucks in bottlenecks was $32 per hour. This value of time was noted as a conservative estimate of value of time from the FHWA Highway Economic Requirements System (HERS). (PSRC, 2009) Wigan et al estimated $1.30 pallet/hour for urban full truck loads (FTL) and $1.40 pallet/hour for metropolitan multi-drop deliveries based on contextual stated preference (CSP) surveys of Australian shippers. Using an average size of 19 pallets per medium truck and 34 pallets per heavy truck, Wigan et al estimate a range of value of travel time of $25-27 per hour for medium trucks and $44-48 per hour for heavy trucks. This study also estimated a value of reliability at $1.25 for urban FTL and $1.97 for metropolitan multi-drop per 1% reduction. (PSRC, 2009) Holguin-Veras estimated the necessary conditions for off-hour deliveries to determine the effectiveness of urban freight road pricing in competitive markets. In this research, he found that receivers are likely to experience incremental costs in the range of $14 to $49 per hour of off-hour operation. (PSRC, 2009) Having found the difficulty of identifying trip decision-makers, the PSRC working group agreed that a reasonable value of time for trucks in the Puget Sound region was $40 per hour for light trucks, $45 per hour for medium trucks, and $50 per hour for heavy trucks, which are

20 consistent with the results from Outwater and Kitchen (2008) described earlier. From the results of literature review, some studies (Smalkowski et al 2003, Kawamura 2000, FHWA 2005, 2006, Holguin-Veras) presented some meaningful truck values of time but did not specify detailed value of time based on different type of trucks, which have been done by Wiganet and Outwater. However, Wiganet and Outwater did not analyze these values of time according to different type of commodities loaded on trucks. Killough (2008) has focused on value analysis of truck toll lanes in congested conditions. To make an assessment of the truck toll lane contribution to improve travel time reliability and see how consideration of reliability enhanced the ROI analysis, he assumed a value of $73 per hour for heavy truck and a per-mile truck toll lane cost of $0.86, according to the finding that shippers and carriers value travel time are at $25 to $200 per hour depending on the cargo by the Federal Highway Administration (FHWA). Even though a value of time is observed, the author did not identify truck value of time for different types of commodities. And also, he just gave the value of time for heavy-duty trucks. Concas and Kolpakov (2009) also conducted a study with the objective to compile and synthesize current and past research on the value of time (VOT) and the value of reliability of time (VOR). A summary table of review work about value of time was provided on Table 2 but there is no study about value of time specific for different commodities and truck classes.