Reforming mixed operation schedule for electric buses and traditional fuel buses by an optimal framework

Autor: Mengyuan Duan, Geqi Qi, Wei Guan, Chaoru Lu, Congcong Gong
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: IET Intelligent Transport Systems, Vol 15, Iss 10, Pp 1287-1303 (2021)
Druh dokumentu: article
ISSN: 1751-9578
1751-956X
DOI: 10.1049/itr2.12098
Popis: Abstract Bus scheduling plays a significant role in public transportation and supports the sustainable development of transportation systems. Challenges are beginning to appear with the newly emerging electric buses (EBs), as scheduling changes due to fleet composition make traditional fixed timetables no longer able to satisfy operational needs. Moreover, the fixed‐trip time hypothesis has been inappropriate for large cities due to the variety of urban traffic statuses. This paper proposes an optimal framework for reforming the mixed operation schedule for electric buses and traditional fuel buses under stochastic trip times. Based on the primary grouping genetic algorithm (GGA), a straightforward framework with a Monte Carlo simulation is presented to optimize the scheduling scheme. Case studies based on the operating environment and service trips of real bus lines in Beijing are conducted to verify the effectiveness of the proposed model by considering both the composition of fleet types and time stochasticity. Additionally, the impacts of stochasticity, fleet composition, government subsidies and cost factors on operational costs are investigated. Considering stochastic trip times, the achieved scheduling strategies can provide the optimal proportion of electric and traditional fuel buses and make a crucial impact on operational costs.
Databáze: Directory of Open Access Journals
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