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Journal Article

Citation

El-Agroudy M, Abou-Senna H, Radwan E. Transp. Res. Rec. 2022; 2676(2): 235-246.

Copyright

(Copyright © 2022, Transportation Research Board, National Research Council, National Academy of Sciences USA, Publisher SAGE Publishing)

DOI

10.1177/03611981211039843

PMID

unavailable

Abstract

In the case of the low-density city, empirical evidence continuously demonstrates that transit investment is not a magic bullet. Desirable outcomes are not guaranteed and are often dependent on development density and other urban characteristics. Mobility-as-a-service (MaaS) presents a new approach: a digital platform providing access to multi-modal travel alternatives and totally comprehensive integrated trip-making, planning, and payment services. Review of the literature highlights shortcomings in traditional transportation planning by examining aspects of multi-modal planning such as adoption, parterships, operations, integration, capacity implications, and impact analyses. To enhance the practice of multi-modal planning, the following experiment evaluates various performance measures and inter-modal interactions on International Drive in Orlando, Florida, U.S., via D- and I-optimal experimental designs in a simulated MaaS network. Alternative scenarios are developed comparing varied modal shares across five travel modes: personal vehicles, transit, ridesourcing (or ride-hailing), micro-mobility, and walking. The modal effects are analyzed to highlight the strengths and weakness of each mode under a variety of congestion conditions. While transit enjoys the lowest impact per person, ridesourcing demonstrates adverse effects across all measures. Based on the novel interactions of transit and ridesourcing with directional demand, strategies are outlined for optimizing ridesourcing-transit integration to reduce route travel time, queuing, and overall network delay. The performance impacts of curbside facilities are also discussed for improved multi-modal integration at the street level. These findings are applied to propose a framework for effective planning and implementation of mobility services in low-density cities, focused on operations, city-level connectivity, and curbside management.


Language: en

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