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Travel demand modeling has traditionally focused on person travel by auto. This is not surprising, as autos generate more than 90% of all vehicle-miles traveled (FHWA 2016b). However, trucks generate the core demand for transportation infrastructure maintenance. Trucks also consume 25% of all fuel in the United States (BTS 2016), contributing disproportionately to greenhouse gas (GHG) emissions. Furthermore, growth in freight transportation is expected to significantly outpace growth in passenger transportation (Chow et al. 2010, p. 1012). Given their disproportional impact upon the transportation system, it is not surprising that most statewide models account for freight modeling, particularly in areas with high levels of congestion.
To learn more about Statewide freights models and their applications, click here.
High Speed Rail Models
California High-Speed Rail Model
This section summarizes Section 7.3.2 of NCHRP Synthesis 514. More detailed information can be found in the report.
There are a few high-speed rail models developed and implemented in the United States. One such model is the California High-Speed Rail Ridership and Revenue Model. The California HighSpeed Rail Authority maintains a separate ridership forecasting model used to support business and system planning, as well as corridor studies and analysis of alternative alignments and phasing of implementation. It is a complete statewide model, and uses some of the same data used to develop the Caltrans California Statewide Travel Demand Model. It incorporates a more sophisticated mode choice model better suited for evaluating HSR alternatives, but otherwise covers the same travel markets as the Caltrans model, and at comparable levels of spatial, temporal, and behavioral resolution. It also includes an explicit risk and uncertainty assessment process. This is a necessity for HSR forecasting, but unfortunately unique among the statewide models.
Bi-level Modeling Framework
The modeling system employs the bi-level structure. The long-distance model includes trips within the state longer than 50 miles, stratified by four trip purposes. They include business, commuting, recreational, and all other trips, a common scheme used in long-distance travel models. The trip frequency and destination choice models were estimated using the a statewide household long-distance survey data and a RP/SP survey. The mode choice model is a combined model of main, access, and egress mode choice.
The short-distance model includes person trip tables by mode and trip purpose from the regional travel models used by the Southern California Association of Governments (SCAG) and the Metropolitan Transportation Commission (MTC). They are the MPOs for the Los Angeles Basin and San Francisco Bay Areas, respectively. Trip tables for their base and forecast years are used to represent short-distance travel . The mode choice model is an adaptation of the 1996 Baycast model developed for MTC, which has been calibrated to reproduce base year transit ridership within each metropolitan area. The resulting system provides consistent forecasts of short-distance mode choice within both regions. The station spacing outside of those regions is too far apart to enable short-distance HSR trips, obviating the need for short-distance models within the rest of the state.
The current model and its predecessors have been used to generate ridership and revenue estimates for initial and detailed system planning and in support of corridor studies and evaluation of candidate initial operating segments. This has included the environmental studies required at all levels of analyses for the program, and use for station-level impact analyses. The latter has required post-processing of the model outputs, for the model was not designed to support detailed analyses at a fine level of geography.
This section summarizes Section 5.5 of NCHRP Synthesis 514. More detailed information can be found in the report.
Some statewide models incorporate parts of adjacent states, some of which had almost as much detail as the statewide model in that state. Urban areas beyond the state border, especially when they are agglomerations, heavily influence both person and freight traffic patterns. The ability to bring the effect of important nearby markets into the model was one of the driving motivations for building the Chesapeake megaregional model. The benefits obtained from doing so were clear. There has been surprisingly little interest in consolidating resources by building multi-state or megaregional models, despite the apparent benefits. Several reasons were cited for this:
- Lack of control over model design, development priorities, or delivery deadlines;
- Increased effort required to run the model, owing to increased coordination with and data supplied by other states involved;
- Unique analytical requirements that other states do not have; and
- A desire to retain capability to quickly adapt or change the model if required to meet new analytical requirements.
These requirements appear to outweigh the potential for cost- and data-sharing, and ability to satisfy common goals for model functionality and elimination of boundary effects at state borders. Moreover, computational and institutional issues will need to be overcome before multi-state models emerge in practice.
National models strongly relate to statewide models since they use similar data sources and the movement to develop national models came from a statewide modeling committee research suggestion. The conventional thinking is that an accurate national model could be used as a source of information – networks, trip table, standard attributes – for developing more detailed statewide models. The National Travel Demand Forecasting Model Phase I Final Scope report developed a framework for developing a national model. The scope had the following components:
- Identify alternative model structures;
- Obtain and prepare input data;
- Model development and validation;
- Develop tools and documentation; and
- Future directions.
There has been significant movement in starting the development of the national model by FHWA, Office of Policy. This agency has started research on new sources of data for long distance travel as a first step in developing the national model.
- Donnelly, R. & Moeckel, NCHRP Synthesis 514 Statewide and Megaregional Travel Forecasting Models, Transportation Research Board, Washington, DC, 2017. http://www.trb.org/NCHRP/Blurbs/176702.aspx