Workshop Synthesis: Conducting Travel Surveys using Portable Devices - Role of Technology in Travel Surveys

AbstractThe aim of this paper is to synthesize discussions of a workshop that was developed as part of the ISCTSC10 conference. Workshop attendees discussed the role of technologies such as GPS, smartphones and life-logging cameras in travel surveys, post-processing of location and time data collected by those technologies, their usability, and future opportunities and challenges

Effectiveness of Transit Strategies Targeting Elderly People

The problem of the aging population has brought new challenges for transportation researchers. The Department of Health and Human Services predicts by the year 2030, the elderly population (65+) in the US will approximately be doubled. As the percentage of seniors rapidly increases within the population, it becomes more important to provide them with innovative transportation alternatives that help them maintain their independence while also assuring safety and comfort of other transit users. Exploring the strategies that can improve seniors’ perception of the public transit system was the main goal of this study. A comprehensive survey was designed and seniors’ travel attributes in the Chicago Metropolitan Area were collected. The survey covered four common trip purposes (shopping, doctor visit, social, and work) and different travel modes available in the Chicago region including various combinations of non-motorized, auto drive, and three commonly used public transit modes of Metra Commuter Rail, Chicago Transit Authority (CTA) and PACE Suburban Bus. Survey respondents were also asked to provide their opinions about the existing and alternative transit services within the region. A descriptive analysis of the stated preference data was then conducted. The results of the analysis represent seniors’ preferred alternatives and effective strategies for system improvement. Furthermore, policy analysis using the modeled results examines the effective factors that could be considered and applied to improve transit services to encourage senior citizens to use public transportation facilities more often

Behavioral acceptance of automated vehicles: The roles of perceived safety concern and current travel behavior

With the prospect of next-generation automated mobility ecosystem, the realization of the contended traffic efficiency and safety benefits are contingent upon the demand landscape for automated vehicles (AVs). Focusing on the public acceptance behavior of AVs, this empirical study addresses two gaps in the plethora of travel behavior research on identifying the potential determinants thereof. First, a clear behavioral understanding is lacking as to the perceived concern about AV safety and the consequent effect on AV acceptance behavior. Second, how people appraise the benefits of enhanced automated mobility to meet their current (pre-AV era) travel behavior and needs, along with the resulting impacts on AV acceptance and perceived safety concern, remain equivocal. To fill these gaps, a recursive trivariate econometric model with ordinal-continuous outcomes is employed, which jointly estimates AV acceptance (ordinal), perceived AV safety concern (ordinal), and current annual vehicle-miles traveled (VMT) approximating the current travel behavior (continuous). Importantly, the co-estimation of the three endogenous outcomes allows to capture the true interdependencies among them, net of any correlated unobserved factors that can have common impacts on these outcomes. Besides the classical socio-economic characteristics, the outcome variables are further explained by the latent preferences for vehicle attributes (including vehicle cost, reliability, performance, and refueling) and for existing shared mobility systems. The model estimation results on a stated preference survey in the State of California provide insights into proactive policies that can popularize AVs through gearing towards the most affected population groups, particularly vehicle cost-conscious, safety-concerned, and lower-VMT (e.g., travel-restrictive) individuals

Electric Vehicle Adoption Behavior and Vehicle Transaction Decision: Estimating an Integrated Choice Model with Latent Variables on a Retrospective Vehicle Survey

Electric vehicles (EVs) promise a sustainable solution to mitigating negative emission externalities of transportation systems caused by fossil-fueled conventional vehicles (CVs). While recent developments in battery technology and charging infrastructure can help evolve the niche market of EVs into the mass market, EVs are yet to be widely adopted by the public. This calls for an in-depth understanding of public adoption behavior of EVs as one dimension of vehicle decision making, which itself may be intertwined with other vehicle decision-making dimensions, especially vehicle transaction. This study presents an integrated choice model with latent variables (ICLV) to investigate households’—as a decision-making unit—decisions on vehicle transaction type (i.e., no transaction, sell, add, and trade) and vehicle fuel type (i.e., CVs and all EV types, including hybrid EV, plug-in hybrid EV, and battery EV) choice. To analyze the ICLV model empirically, one of the first revealed preferences national vehicle survey involving CVs and all EV types was conducted, which retrospectively inquired about 1,691 American households’ dynamics of vehicle decision making and demographic attributes over a 10-year period as well as their attitudes/preferences. The model estimation results highlight that EV adoption and vehicle transaction choice is influenced mainly by (1) the dynamics of household demographic attributes and (2) four latent constructs explaining attentiveness to vehicle attributes, social influence, environmental consciousness, and technology savviness. Notably, EV adoption promotion policies are found to be likely most effective on socially influenced individuals, who tend to consider advertisement and social trend more when making vehicle decisions

Exploring the Role of Perceived Range Anxiety in Adoption Behavior of Plugin Electric Vehicles

A sustainable solution to negative externalities imposed by road transportation is replacing internal combustion vehicles with electric vehicles (EVs), especially plug-in EV (PEV) encompassing plugin hybrid EV (PHEV) and battery EV (BEV). However, EV market share is still low and is forecast to remain low and uncertain. This shows a research need for an in-depth understanding of EV adoption behavior with a focus on one of the main barriers to the mass EV adoption, which is the limited electric driving range. The present study extends the existing literature in two directions; First, the influence of the psychological aspect of driving range, which is referred to as “range anxiety”, is explored on EV adoption behavior by presenting a nested logit (NL) model with a latent construct. Second, the two-level NL model captures individuals’ decision on EV adoption behavior distinguished by vehicle transaction type and EV type, where the upper level yields the vehicle transaction type selected from the set of alternatives including no-transaction, sell, trade, and add. The fuel type of the vehicles decided to be acquired, either as tradedfor or added vehicles, is simultaneously determined at the lower level from a set including conventional vehicle, hybrid EV, PHEV, and BEV. The model is empirically estimated using a stated preferences dataset collected in the State of California. A notable finding is that anxiety about driving range influences the preference for BEV, especially as an added than traded-for vehicle, but not the decision on PHEV adoption

Coordinated Transit Response Planning and Operations Support Tools for Mitigating Impacts of All-Hazard Emergency Events

This report summarizes current computer simulation capabilities and the availability of near-real-time data sources allowing for a novel approach of analyzing and determining optimized responses during disruptions of complex multi-agency transit system. The authors integrated a number of technologies and data sources to detect disruptive transit system performance issues, analyze the impact on overall system-wide performance, and statistically apply the likely traveler choices and responses. The analysis of unaffected transit resources and the provision of temporary resources are then analyzed and optimized to minimize overall impact of the initiating event

Evolution of Mode Use During the COVID-19 Pandemic in the United States: Implications for the Future of Transit

The COVID-19 pandemic has brought about transformative changes in human activity-travel patterns. These lifestyle changes were naturally accompanied by and associated with changes in transportation mode use and work modalities. In the United States, most transit agencies are still grappling with lower ridership levels, thus signifying the onset of a new normal for the future of transit. This paper addresses this challenge using a novel panel survey data set collected from a representative sample of individuals across the United States. The study involved the estimation of a panel multinomial probit model of mode choice to capture both socio-economic effects and period (pre-, during-, and post-COVID) effects that contribute to changes in mode choice. This paper provides rich insights into the evolution of commute mode use as a result of the pandemic, with a particular focus on public transit. Through a rigorous modeling approach, this paper provides a deep understanding of how transit use has evolved, how it is likely to evolve into the future, and the socio-economic and demographic characteristics that affect the evolution (and expected future use) of public transit. Results suggest that transit patronage is likely to remain depressed by about 30% for the foreseeable future, in the absence of substantial changes in service configurations. This study also shows that minority groups and those living in higher density regions are more likely to exhibit a return to transit use in the post-pandemic period

Introducing CRISTAL: A Model of Collaborative, Informed, Strategic Trade Agents With Logistics [Presentation]

Accessibility: This item is not machine readable, please contact NTL Ask A Librarian service for remediation or help with access.PowerPoint presentation covering Transportation Research Board paper: Introducing CRISTAL: A Model of Collaborative, Informed, Strategic Trade Agents With Logistics [Transportation Research Board Annual Meeting 2023 (Paper 23-02960); Committee Meeting, Freight Transportation Planning and Logistics (AT015)]. Paper describes the CRISTAL Freight Transportation model, its initial implementation, and applications to date. CRISTAL stands for Collaborative, Informed, Strategic Trade Agents With Logistics and is an agent-based model

Effectiveness of Transit Strategies Targeting Elderly People: Survey Results and Preliminary Data Analysis

The U.S. Department of Health and Human Services has shown that America???s senior population has been growing and will almost double by 2030. This trend continues to challenge researchers who are looking to increase seniors??? awareness or favorable views toward public transportation and researchers who are developing innovative public transportation alternatives for seniors. These alternatives will try to wean seniors from their reliance on cars, while not compromising other transit riders??? safety and comfort. The research team at the University of Illinois at Chicago undertook this study as a first step toward meeting this challenge. To collect information on seniors??? travel attributes and their opinions about Northeastern Illinois??? public transportation system and potential service alternatives, the research team developed a comprehensive survey, covering four common trip purposes (doctor visits, shopping trips, social or recreational travel, and work trips) and various travel modes. These modes included combinations of nonmotorized travel, auto use, and three commonly used public transportation modes (Metra, Pace, and the Chicago Transit Authority). The research team tested this survey on a small sample of respondents; modified it to maximize the number of accurate, unbiased responses; and sent it to 2,000 seniors who have resided in one of metropolitan Chicago???s six counties. Two hundred eighty seniors sent back complete and useful surveys that provided data for this study. Most of these seniors were unfamiliar with Northeastern Illinois??? public transportation system and did not view it as a driving alternative, partly because they view it as more hazardous than driving their own cars and less convenient than getting a ride from friends or family members. To help change these perceptions, the research team suggests that Northeastern Illinois??? public transit operators provide printed timetables and maps on their trains, buses, or stations; increase vehicle frequencies; provide real-time arrival information at stations and on cell phones; order more low floor and kneeling buses, clean their stations and vehicles better, and provide shuttle services specifically designed for seniors. 17.ICT-R27-17published or submitted for publicationis peer reviewe