@article{ref1,
title="Short-term and long-term impacts of shared autonomous vehicle choice behavior",
journal="Transportation research part D: transport and environment",
year="2024",
author="Huang, Kai and Han, Xu and An, Kun and Liu, Zhiyuan",
volume="132",
number="",
pages="e104221-e104221",
abstract="Shared Autonomous Vehicle (SAV) is an emerging travel mode that can reduce parking spaces and accelerate urban sprawl. The time-space varying demand leads to the imbalance between travel demand and vehicle supply. Using pricing to affect clients' mode choice is a key method for addressing the imbalance problem, which includes long-term pricing and short-term allowance. Hence, in this paper, we propose an innovative method to enhance the SAV utilization rate while considering stochastic demand: fixed price on population mode choice and real-time allowance on personal departure time choice. A mixed integer nonlinear program is formulated to maximize the total profits of SAV operators. To solve this model, a customized gradient search algorithm is proposed. A case study is conducted in Suzhou Industrial Park, China. It reveals the impacts on travel demand and departure time choices and discusses the impacts and policy-making for SAV applications.<p />",
language="en",
issn="1361-9209",
doi="10.1016/j.trd.2024.104221",
url="http://dx.doi.org/10.1016/j.trd.2024.104221"
}