Optimal Electric Bus Scheduling with Multiple Vehicle Types Considering Bus Crowding Degree
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 149, Issue 2
Abstract
Electric buses are environmentally friendly with the features of zero emissions and low noise levels. Therefore, it is an inevitable trend to replace traditional fuel buses with electric buses. In the urban transportation system, the most common electric bus scheduling mode is single-vehicle-type scheduling, where crowdedness in peak hours could impair the bus service level. In contrast, a high vacancy rate in off-peak hours might lead to a waste of resources. To balance efficiency and the bus service level, this paper built an electric bus scheduling model with multiple vehicle types distinguished by vehicle configurations, such as bus capacity, battery capacity, purchase cost, charging power, and electricity consumption rate. The optimization objective was to minimize the bus system costs, including bus depreciation costs, charging costs, and congestion time costs. Then, a genetic algorithm was designed to solve the model, and the model is verified by a case study of one bus line in Nanjing, China. Compared with the single-vehicle-type scheduling schemes, including large and small vehicle types, the experimental results showed that the proposed model can reduce total bus system costs by 3.52% and 6.85%, respectively. The research results can provide references for bus companies to formulate driving plans and configure vehicles.
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Data Availability Statement
Some or all data, models, or codes that support the findings of this study are available from corresponding author upon reasonable request.
Acknowledgments
This research was supported by the National Natural Science Foundation of China (52072066), Jiangsu Province Science Fund for Distinguished Young Scholars (BK20200014), and Jiangsu Transportation Science and Technology Program (2020Y12).
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Information & Authors
Information
Published In
Journal of Transportation Engineering, Part A: Systems
Volume 149 • Issue 2 • February 2023
Copyright
© 2022 American Society of Civil Engineers.
History
Received: May 6, 2022
Accepted: Sep 28, 2022
Published online: Nov 24, 2022
Published in print: Feb 1, 2023
Discussion open until: Apr 24, 2023
ASCE Technical Topics:
- Air pollution
- Algorithms
- Benefit cost ratios
- Buses
- Business management
- Case studies
- Electric power
- Emissions
- Energy engineering
- Engineering fundamentals
- Environmental engineering
- Financial management
- Highway transportation
- Infrastructure
- Mathematics
- Methodology (by type)
- Pollution
- Practice and Profession
- Public transportation
- Research methods (by type)
- Transportation engineering
- Vehicles
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