This session presents new research in transit management and performance. Attendees will learn about an innovative real-time performance dashboard for buses and new spatial benchmarking method for analyzing performance through ridership data. They will also learn hear about a study exploring the efficiency of demand responsive transportation (DRT) and another examining chances in travel choices over long-term disruptions.
Full Details about the Lectern Session can be found on the TRB Annual Meeting Event Page.
Full Presentation
Presenter: Kidus Admassu, Microsoft Corporation; Jerome Lynch, Duke University; Robert Goodspeed, University of Michigan, Ann Arbor; Curt Wolf, University of Michigan
Public transit systems provide communities lacking personal modes of transportation with an affordable approach to their mobility. With the advent of wireless technologies, quantitative evidence of system performance can be acquired by embedding GPS sensors in buses. Data collected can be used to: target interventions by identifying probable causes of low performance and ensure good governance by benefiting the communities being served by sharing data. In this paper, a participatory design approach is proposed to develop an online dashboard that can track the transit performance of underserved communities in Benton Harbor, Michigan. Stakeholder surveys and interviews were adopted as qualitative assessment methods that allowed associated stakeholders to share information for making operational decisions that ensure system performance meets community needs. Based on the survey responses obtained, a website dashboard was developed (different from commercial solutions because it is designed with participatory stakeholder inputs) to visualize data collected from GPS sensors in Twin Cities Area Transportation Authority’s (TCATA’s) buses and on-demand trip dispatch logs. To automate the website dashboard, database, and data analysis services are implemented on Amazon Web Services (AWS) storing real-time GPS data, analyzing performance parameters, and posting extracted information from raw data on the website dashboard including the mapping of active buses, information on the on-time performance of fixed route buses, and information associated with on-demand transit service. The resulting dashboard provides the transit agency and community riders alike with a more transparent view of system performance allowing future design interventions to be considered based on quantitative evidence.
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Presenter: Filippos Alogdianakis, Paraskevas Nikolaou, Loukas Dimitriou, University of Cyprus
This paper aim in capturing the essential differences in the case of transit networks changes by incorporating possible spatial spillover effects of ridership. Benchmarking method, namely Data Envelopment Analysis (DEA) was illustrated for incorporating social, infrastructure, and operational characteristics of a previous and new operational public transport system. While neighboring areas are connected through the public network limited researchers have exploited the adaptation of a Spatial benchmarking method for measuring and quantifying spatial autorrelations between areas, or units. This analysis deploys a Spatial DEA (SDEA) model for analyzing the performances of previous and new public transport systems through the ridership as recorded in each bus stop. Significant results reveal the capabilities of SDEA in the network evaluation. Furthermore, the capabilities of SDEA in the target-setting approach revealed significant findings on how the connectivity of a network might be able to capture realistic goals and set strategies for increasing ridership.
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Presenter: Diana Al-Nabulsi, Jun-Seok Oh, Valerian Kwigizile, Western Michigan University; Hyunmyung Kim, Myongji University; Hyung-Min Jun, Studio Galilei
While transit agencies' historic focus on system performance has led to more efficient provisiDemand responsive transit services offer personalized transportation solutions by dynamically adjusting routes and schedules based on passengers' unique origin and destination requirements. This research explores the efficiency of demand responsive transit (DRT) services. First, this study applied the Capacitated Vehicle Routing Problem with Time Windows (CVRPTW) to seeking the optimal DRT operation solution. We formulated the CVRPTW problem and implemented the algorithm for the Kalamazoo Metro’s DRT system that offers door-to-door DRT services in Kalamazoo, Michigan. Second, we applied the Transportation Analysis Transit Analysis and Mobility Optimization System (TAMOS), developed by Studio Galilei in South Korea, to analyze the performance of the real-time DRT operation case. While the DRT services can be optimized when the demand is known or booked prior to the operation, the real-time operation fulfills passengers’ on-demand travel needs. In this study, we investigate the efficiency of DRT services by comparing the current DRT practices with the optimal solution derived from CVRPTW as well as the case with real-time operation. Additionally, we explore the impact of fleet size and maximum pick-up delay on the overall performance of the system. The findings of this study highlight the significant influence of various factors on the performance of DRT system operations. Specifically, the efficiency of the system depends not only on the fleet size but also on the maximum pick-up delay and the detour rate. Therefore, it is crucial to carefully design operational characteristics in order to enhance the overall efficiency of the DRT operation.on of transit, this does not necessarily constitute better service. This is becoming increasing clear as our society evolves to focus more on equity, but measures for progress in this realm lag. Alanna McKeeman will discuss approaches she and her colleagues have used to integrate social equity considerations into transit planning projects, from planning to implementation to evaluation.
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Presenter: Mohamed Noureldin, Ehab Diab, University of Saskatchewan
Substantial funding is allocated towards building new transit infrastructure worldwide. Such large undertakings can disrupt the system and result in the suspension of some of the provided transit services. While there is a considerable number of studies that focused on understanding people’s mode choices during normal operations and short-term disruptions, little has been done to investigate travel choices during long-term disruptive periods. This paper aims at examining changes in travel choices during a long-term disruption that occurred during the COVID-19 pandemic in Montréal. Using two waves of surveys, it explores the impacts of the suspension of the Deux-Montagnes train line due to the construction of a new light rail system, the Réseau express métropolitain (REM), on the travel choices of users that previously used the train line. Associations between respondents’ travel choices and socioeconomics, users’ perceptions, and spatial factors were examined, while exploring the difference between users’ anticipated travel choices reported before the suspension and their actual choices during the suspension. The results show that only 29.0% of the Deux-Montagnes line’s previous users continued to use transit, while many shifted to using cars to reach the same destinations. Nevertheless, a higher percentage of users who live within an 800-metre buffer from a closed station used alternative transit options during the closure than using cars. Respondents who relied on using cars were the least likely to report that they will use the REM service in the future. The study offers transit planners insights into the anticipated impacts of long-term service closures.