Optimal rebalancing with waiting time constraints for a fleet of connected autonomous taxi

Optimal rebalancing with waiting time constraints for a fleet of connected autonomous taxi
Title:
Optimal rebalancing with waiting time constraints for a fleet of connected autonomous taxi
Other Titles:
2018 IEEE 4th World Forum on Internet of Things (WF-IoT)
Publication Date:
07 May 2018
Citation:
S. P. Chuah, S. Xiang and H. Wu, "Optimal rebalancing with waiting time constraints for a fleet of connected autonomous taxi," 2018 IEEE 4th World Forum on Internet of Things (WF-IoT), Singapore, 2018, pp. 629-634. doi: 10.1109/WF-IoT.2018.8355161
Abstract:
A fleet of cooperative autonomous taxi is an emerging application of IoT in transportation industry. Unlike manned taxis that cruise on roads uncoordinated and often compete for passengers, autonomous vehicle can move cooperatively to transport passengers more efficiently. In this paper, we present a case study on an IoT application of new cooperative management technique for a fleet of autonomous taxi. In transportation network, optimal re-balancing allows sustainable flow of vehicle with a minimum number of vehicle to transport passengers flows in uneven directions. However, long waiting time to board a taxi during peak hours degrades quality of service. To tackle this issue, we extend recent advances in autonomous mobility-on-demand solution to incorporate waiting time policy. Specifically, we introduce stability and control of passenger’s queues in the optimal re-balancing to confine the queues (thus waiting time in queues) to a specified range. We validate our new technique via data-driven simulations of a fleet of autonomous taxi by leveraging on Singapore’s taxi dataset. Data-driven simulations demonstrate promising results of the new technique in ensuring efficient and low waiting time of taxi service for passengers.
License type:
PublisherCopyrights
Funding Info:
National Research Foundation, Prime Ministers Office, Singapore, under NRF-NSFC Joint Research Grant Call on Data Science (NRF2016NRFNSFC001-113)
Description:
© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
ISBN:
978-1-4673-9944-9
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