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Mitigating Network Congestion by Integrating Transportation Network Companies and Urban Transit
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2022-10-20
[PDF-4.42 MB]
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Alternative Title:Mitigating Network Congestion by Integrating Transportation Network Companies & Urban Transit: STRIDE Project I2 [Project Title from Cover]
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Edition:8/1/2018 to 10/20/2022
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Abstract:Transportation Network Companies (TNCs) like Uber and Lyft, provide a transportation option that offers a higher level of availability, reliability, and convenience than traditional taxi and transit services. However, there are widespread concerns about their impacts on urban congestion and their threat to public transit and taxi services, some of which are affirmed by recent case studies. The research team developed and demonstrated novel methods for calibrating MATSim models using a regionally approved mode split behavioral model and real-world traffic counts; collecting and processing Uber trip-level data using crowdsourcing to address the lack of publicly available TNC data; and modeling ride-hailing, in addition to automobile and transit trips, in the same simulation testbed. Products of this research include: (a) a questionnaire survey for documenting awareness and use of TNC services in the Southeastern US; (b) a rigorously calibrated MATSim model of the Miami Beach area; and (c) a comprehensive digital twin model of the Birmingham region. The latter MATSim model successfully incorporates public transit and ride-hailing services into the Birmingham transportation network, in addition to private automobiles. Overall, this research work provides valuable contributions to the current body of knowledge related to multimodal modeling using an open-source large-scale agent-based transportation simulation platform. The findings of the case studies reported herein provide evidence on the benefits of adopting transit, TNC, and road pricing strategies in small and medium-size urban settings and can assist transportation decision makers, urban planners, transit agencies, and TNC providers in their efforts to optimize their operations and serve the needs of the traveling public.
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