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Routing and charging optimization for electric bus operations.
- Source :
-
Transportation Research Part E: Logistics & Transportation Review . Jan2024, Vol. 181, pN.PAG-N.PAG. 1p. - Publication Year :
- 2024
-
Abstract
- The transition to alternative energy sources and the adoption of on-demand operating modes in urban bus systems are crucial steps towards reducing carbon footprints and improving public transit services. This paper presents a two-phase approach for the collaborative optimization of charging schedules and passenger services, aimed at enhancing the operation of on-demand electric bus systems. First, we propose a label-setting dynamic programming algorithm that enables the efficient generation of bus-trips for each bus line in response to passenger requests. Second, we introduce a time–space network optimization model that facilitates integrated multiple bus-trip planning for the transit network, involving multiple bus lines and charging spots. The model selects bus-trips from various time–space arcs, which represent passenger carrying, bus deployment, and bus charging activities. To validate the effectiveness of our approach, we conduct a case study using real-world data from bus lines in Beijing, China. Computational results demonstrate that our approach can handle on-demand electric bus operations within minutes of solution time, efficiently serving over 2,000 passengers. Practically, our approach achieves a notable reduction in average transit time and effectively reduces the waste of public transit resources. The proposed approach can serve as a beneficial tool for decision-makers and operators seeking to enhance the performance and environmental impact of their electric bus systems. • This paper aims at enhancing on-demand bus operational efficiency. • This paper proposes an optimization approach for electric bus operations. • This paper provides practical solutions for responsive transit systems. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 13665545
- Volume :
- 181
- Database :
- Academic Search Index
- Journal :
- Transportation Research Part E: Logistics & Transportation Review
- Publication Type :
- Academic Journal
- Accession number :
- 174530638
- Full Text :
- https://doi.org/10.1016/j.tre.2023.103372