A framework to integrate mode choice in the design of mobility-on-demand systems

File Description SizeFormat 
MoD_supply_demand_full_text.pdfFile embargoed until 03 October 20201.75 MBAdobe PDF    Request a copy
Title: A framework to integrate mode choice in the design of mobility-on-demand systems
Authors: Liu, Y
Bansal, P
Daziano, R
Samaranayake, S
Item Type: Journal Article
Abstract: Mobility-on-Demand (MoD) systems are generally designed and analyzed for a fixed and exogenous demand, but such frameworks fail to answer questions about the impact of these services on the urban transportation system, such as the effect of induced demand and the implications for transit ridership. In this study, we propose a unified framework to design, optimize and analyze MoD operations within a multimodal transportation system where the demand for a travel mode is a function of its level of service. An application of Bayesian optimization (BO) to derive the optimal supply-side MoD parameters (e.g., fleet size and fare) is also illustrated. The proposed framework is calibrated using the taxi demand data in Manhattan, New York. Travel demand is served by public transit and MoD services of varying passenger capacities (1, 4 and 10), and passengers are predicted to choose travel modes according to a mode choice model. This choice model is estimated using stated preference data collected in New York City. The convergence of the multimodal supply-demand system and the superiority of the BO-based optimization method over earlier approaches are established through numerical experiments. We finally consider a policy intervention where the government imposes a tax on the ride-hailing service and illustrate how the proposed framework can quantify the pros and cons of such policies for different stakeholders.
Issue Date: 31-Aug-2019
Date of Acceptance: 23-Sep-2018
DOI: 10.1016/j.trc.2018.09.022
ISSN: 0968-090X
Publisher: Elsevier BV
Start Page: 648
End Page: 665
Journal / Book Title: Transportation Research Part C: Emerging Technologies
Volume: 105
Copyright Statement: © 2019 Elsevier Ltd. All rights reserved. This manuscript is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence
Keywords: 09 Engineering
08 Information and Computing Sciences
15 Commerce, Management, Tourism and Services
Logistics & Transportation
Publication Status: Published
Embargo Date: 2020-10-03
Online Publication Date: 2018-10-03
Appears in Collections:Civil and Environmental Engineering