Multiagent System–Based Near-Real-Time Trajectory and Microscopic Timetable Optimization for Rail Transit Network
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 147, Issue 2
Abstract
In the rail transit field, the practical operation process suffers from potential energy waste caused by disturbances. The present paper proposes a multiagent system (MAS) to reduce rail transit energy consumption when disturbances occur. The system is able to optimize speed trajectory and microscopic timetable for each train in near real time when disturbances occur. Two case studies have been carried out to investigate the feasibility and efficiency of the proposed methodology. In the first case study, three trains are simulated with 1,212 different scenarios with a disturbance that comes from the leading train. The results of those scenarios show that the proposed system is able to guarantee safety and has good potential in reducing energy consumption in such conditions. In the second case study, a train running among seven stations with potential delays is simulated. The result shows that each train agent can support a microscopic timetable optimization in near real time and results in a 13.40% energy savings. An additional 2,340 scenarios are simulated, and an average of 4.12% energy savings is achieved.
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Data Availability Statement
All data presented in this paper are available upon request.
Acknowledgments
The authors would like to acknowledge the support from the Key Program Special Fund of Xi’an Jiaotong-Liverpool University, project code KSF-E-04.
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Published In
Journal of Transportation Engineering, Part A: Systems
Volume 147 • Issue 2 • February 2021
Copyright
© 2020 American Society of Civil Engineers.
History
Received: Feb 29, 2020
Accepted: Aug 17, 2020
Published online: Nov 19, 2020
Published in print: Feb 1, 2021
Discussion open until: Apr 19, 2021
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