Real-time Routing and Scheduling of On-demand Autonomous Customized Bus Systems

Conference paper (2023)

Authors

Rongge Guo University of Huddersfield
X. Liu Team Bart De Schutter - Mechanical, Maritime and Materials Engineering
Saumya Bhatnagar University of Huddersfield
Mauro Vallati University of Huddersfield
Research Group
Team Bart De Schutter (Mechanical, Maritime and Materials Engineering) (TU Delft)
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Published Date

2023

Language

English

Reuse Rights

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Faculty

Mechanical, Maritime and Materials Engineering

Department

Delft Center for Systems and Control

Research Group

Team Bart De Schutter

Abstract

The integration of autonomous vehicles and on-demand customized bus
systems is expected to be beneficial for responding to real-time
demands. This paper investigates the autonomous customized bus (ACB)
system that leverages passenger demand prediction to enhance service
quality and vehicle utilization. A novel ACB service design optimization
model that determines vehicle movements and passenger-to-vehicle
assignments is developed for the real-time routing and scheduling
problem. Then, a rolling horizon approach, incorporating travel demand
prediction, proactive dispatching and reactive adjustment, is proposed
to address the studied problem. The performance of the introduced ACB
system is evaluated using smartcard data from Beijing and the
state-of-the-art machine learning algorithm. Results show that the
proposed ACB system can effectively improve system performance and
service level in terms of operating cost and passenger waiting time
compared to reactive operations.