Maren L Outwater

Innovative Framework for Modeling Freight Transportation in Los Angeles County, California

Freight transportation is a critical element of the transportation system and the economy of Los Angeles County, California. Freight transportation links the large consumer market, major manufacturing industry sector, and international trade network of Los Angeles to the rest of the United States and the world. As the agency responsible for transportation planning and programming in Los Angeles County, the Los Angeles County Metropolitan Transportation Authority needs comprehensive tools for understanding the demands of the freight transportation sector and the effects of transportation investment on this sector. A project was undertaken to design a comprehensive, innovative, multimodal modeling framework to support freight transportation decision making in Los Angeles County. The proposed modeling approach combines elements of two state-of-the-art freight modeling techniques: logistics chain modeling and tour-based truck modeling. The reasons for selecting this approach are described; background on the m...

California Statewide Model for High-Speed Rail

The California High Speed Rail Authority and the Metropolitan Transportation Commission are developing an innovative statewide model to support evaluation of high-speed rail alternatives in the State of California. This statewide model will also support future planning activities of the California Department of Transportation. The approach to this statewide model explicitly recognizes the unique characteristics of intraregional travel demand and interregional travel demand. As a result, interregional travel models capture behavior important to longer distance travel, such as induced trips, business and commute decisions, recreational travel, attributes of destinations, reliability of travel, party size, and access and egress modal options. Intraregional travel models rely on local highway and transit characteristics and behavior associated with shorter distance trips (such as commuting and shopping).

DESIGN OF AN INTEGRATED LAND USE AND ACTIVITY-BASED TRAVEL MODEL SYSTEM FOR THE PUGET SOUND REGION

Results of a design process for new integrated land use and transportation models recently completed for the Puget Sound Regional Council (PSRC) are presented. The design process, which began with an analysis of policy requirements and assessment of the current models in use at PSRC and nationally, employed an iterative and participatory approach to ensure that model requirements were clearly identified and that the proposed model design would address those requirements. Development of the model requirements drew on a broad survey of the literature and of operational models; the proposed model design offers a unique approach to the development of a new land use and travel model system that corresponds to a behavioral integration of the choice processes across relevant time frames.

DEMAND FORECASTING MODEL FOR PARK-AND-RIDE LOTS IN KING COUNTY, WASHINGTON

As the demand for using park-and-ride lots grows, the need to accurately forecast these trips also grows. Initially, demand for park-and-ride lots was forecast using a technique that identified the draw area for each lot and estimated demand without regard to capacity. These were simplifying assumptions that are no longer appropriate with respect to current demand for park-and-ride lots. In King County, Washington, the 12 largest park-and-ride lots are currently operating at 95 percent utilization. According to a recent park-and-ride lot survey in King County, there is significant latent demand for using lots that are full. The analysis of demand for parking in park-and-ride lots in King County was developed as part of the Washington State Department of Transportation Public/Private Partnership Program for the Park-and-Ride Capacity Enhancement Project. There were 17 park-and-ride lots considered for capacity enhancement. The approach to evaluate park-and-ride lot demand uses a technique to identify intermediate stop choices, such as park-and-ride lots, as part of the overall modal choice. User and nonuser surveys were evaluated to identify the importance of specific variables, such as security or amenities. A combination of the survey results and an application of the demand forecasting model were used to estimate shifts in demand for parking from increased capacity and user fees. Several different user fees were tested and compared with stated preference results from the user and nonuser surveys. The project resulted in significantly different demand for park and ride than previous modeling efforts because of the impact of lot capacity and effects of user fees.

Market Segmentation Approach to Mode Choice and Ferry Ridership Forecasting

The San Francisco Bay Area Water Transit Authority is evaluating expanded ferry service, as required by the California legislature. Predicting ferry ridership has historically been difficult because water-transit riders often choose their travel mode based on factors other than travel time and cost. Most forecast models place a premium on time and cost and ignore other traveler attitudes. Structural equation modeling was used to identify simultaneously travel behavior and the causal relationships between a travelers socioeconomic profile and travel attitudes. These market segments were used to estimate stated-preference (SP) mode choice models for 14 alternative modes, which separated the travelers reaction to time savings by market segment and recognized that modal choices were different for market segments that were sensitive to travel stress or a desire to help the environment. The focus was on the application of the model to evaluate three future-year alternatives and to test the sensitivity of pricing policies, service changes, and alternative transit modes. These sensitivity runs included increased tolls on bridges, parking charges for Bay Area Rapid Transit stations, reduced ferry headways, alternative transit investments (express buses) in ferry corridors, and combinations of these assumptions. The results from these model runs were used to support the environmental impact statement and implementation and operations plan and were used to prioritize routes for further consideration based on the ridership potential in the corridor. Preliminary work to competitively position a ferry system that maximizes ferry mode share based on the market segments in the corridor was undertaken for a few routes.

Incremental Integration of Land Use and Activity-Based Travel Modeling: Workplace Choices and Travel Demand

Recent advances in activity-based travel modeling and integrated land use and transportation modeling have significantly advanced the understanding of and the capacity to model location choices and travel behavior more realistically. These advances, however, come with greater data requirements, and the risk and the substantial cost involved with adoption of these models have slowed their move to operational use. The purpose of this research was twofold. First, the study addressed one aspect of an incremental approach that more carefully balanced the risks and benefits of moving operational models in new directions: replacement of the choice model of home-based work destination in the four-step travel model system with a pair of choice models at the level of the individual worker. The new choice models were implemented as long-term choices in the linked land use model system. Second, the models were used to provide a way to derive matches between workers and their workplace with commonly available data. These matches complemented synthetic populations and provided a key input for activity-based travel models. The models predicted whether a worker would choose to work at home on a long-term basis; if he or she did not, an out-of-home job was chosen. These models linked an individual worker to a specific job at a workplace and therefore directly predicted commuting patterns. The paper presents the model specifications, estimation results, and results of validation of the models against observed commuting data from the Census Transportation Planning Package. The model reproduced observed commuting flows well, and computational performance was fast, even though the model operated at the level of the individual worker and job.

Characteristics of Premium Transit Services that Affect Choice of Mode

Traditionally, travel models use travel time and cost to assess the usefulness of each mode of transportation to make a particular trip. Other factors that affect the selection of mode are accounted for using a single constant term that represents other attributes. In many cases, these attributes represent conditions that may not be the same for all trips. Travel forecasting models would benefit by incorporating an expanded list of non-traditional attributes so that the probability of using transit to make a trip is more specifically related to the characteristics of a potential transit journey. Potential non-traditional transit characteristics include on-board and station amenities, reliability, span of service, and service visibility/ branding. These characteristics are not typically directly considered in travel forecasting models. This research sought to improve the understanding of the full range of determinants for transit travel behavior and to offer practical solutions to practitioners seeking to represent and distinguish transit characteristics in travel forecasting models. The key findings of this research include the value of non-traditional transit service attributes on travelers’ choice of mode, in particular the influence of awareness and consideration of transit service on modal alternatives, and the importance of traveler attitudes toward both awareness and consideration of transit and on the choice of transit or auto in mode choice. The appendices present detailed research results including a state-of-the-practice literature review, survey instruments, models estimated by the research team, model testing, and model implementation and calibration results. The models demonstrate an approach for including non-traditional transit service attributes in the representation of both transit supply (networks) and demand (mode choice models), reducing the magnitude of the modal specific constant term while maintaining the ability of the model to forecast ridership on specific transit services. The testing conducted in this project included replacing transit access and service modes, such as drive to light rail or walk to local bus, as alternatives in the mode choice model with transit alternatives defined by the elements of the path, such as a short walk to transit path, a no-transfer path, or a premium service path.

Quantitative Approaches for Project Prioritization

Transportation projects in major metropolitan regions can vary widely in the types of benefits that they provide and in the scales of those benefits. Travel forecasting models and related procedures can provide reasonable estimates of those benefits, and many benefits can be distilled into equivalent monetary benefits by the use of consumer surplus or other valuation approaches. In theory, those methods could also be used to prioritize projects for funding consideration. However, an approach that simply chooses projects that provide the greatest net economic benefits may not result in a mix of projects that most effectively accomplishes broad regional goals. This paper describes an approach to project prioritization that was developed to support stakeholder-based weighting of multiple goals and, for each goal, multiple measures. The approach uses the analytic hierarchy approach to develop weights for each goal and a conjoint-based method to estimate stakeholder weights for each measure. The approach was applied as part of Washington States Puget Sound Regional Councils Transportation 2040 process and achieved the goals in VISION 2040, the long-range land use plan. Weighting exercises were conducted with two stakeholder groups, and the results were applied to a set of proposed ferry, rail, highway, and local road projects. This paper describes the details of this case study and provides observations and conclusions from the work. The principal findings of the experiments were that statistically robust modeling conducted in real time during planning committee meetings can improve the transparency, equity, and collaboration of the project prioritization process.

Research to Examine Behavioral Responses to Automated Vehicles

This chapter provides a discussion of the important research topics for understanding behavioral responses to highly automated vehicles (AVs) as discussed at a breakout session at the Automated Vehicle Symposium (AVS) 2018. The session, and thus this chapter, highlights the need for valid behavioral data on which to base assumptions, models, forecasts, and impacts to inform AV adoption behaviors, the pathways of AV ownership and use, and the potential impact of AVs on human activity-travel behaviors and longer-term location choices.

Implementation of a Practical Model System to Predict Long-Distance Travel for the Entire U.S. Population

This paper describes a model system designed and implemented to simulate long-distance travel for all U.S. households. The model system was created in the final phase of FHWA research project Foundational Knowledge to Support a Long-Distance Passenger Travel Demand Modeling Framework. It is a tour-based system simulating individual tours for individual households from a synthetic population. The models are disaggregate models of auto ownership, tour generation, tour duration, travel party size, tour destination choice, and tour mode choice. The model system runs in 1 to 2 h on a standard PC, simulating a full year’s long-distance tours for the entire U.S. population. The paper describes the model structure, input data, and software implementation and provides some results from the initial model calibration, validation, highway assignment, and sensitivity tests.