Capturing Travel Mode Adoption in Designing On-Demand Multimodal Transit Systems

This paper studies how to integrate rider mode preferences into the design of on-demand multimodal transit systems (ODMTSs). It is motivated by a common worry in agencies that an ODMTS may be poorly designed if latent demand, is, new riders adopting system, not captured. proposes bilevel optimization model address this challenge, which leader problem determines design, and follower problems identify most cost efficient convenient route for under chosen design. The contains choice every potential whether adopts given her proposed route. To solve model, exact decomposition method includes Benders optimal cuts no-good ensure consistency choices problems. Moreover, improve computational efficiency, upper lower bounds on trip durations problems, valid inequalities strengthen cuts, approaches reduce size with problem-specific preprocessing techniques. validated using extensive study real data set from Ann Arbor Area Transportation Authority, agency broader Ypsilanti region Michigan. considers impact number factors, including price shuttles, hubs, access criteria. ODMTSs feature high adoption rates significantly shorter compared existing system highlight benefits ensuring low-income riders. Finally, demonstrates efficiency case enhancements baseline several orders magnitude. Funding: research was partly supported National Science Foundation [Leap HI Proposal NSF-1854684] Department Energy [Research Award 7F-30154].