Abstract
The introduction of electric vehicles (EVs) into public transit systems poses challenges in harmonizing charging requirements with vehicle operations, especially during rush hours. In this study, we propose a Charging-on-the-move Public Transit System (CPTS) based on existing feasible technologies. This system adopts electric-driven modular vehicle units, including Modular Trolleybuses (MT) and Modular Buses (MB). These modular vehicle units can seamlessly join and detach during operation. The MT acquires power from the overhead catenary via a pantograph, enabling the charging of MBs on the move when they join into the same platoon. The optimization problem of CPTS is formulated as a sub-station-to-main station assignment (S2Ma) problem and a passenger-to-MB assignment (P2Ma) problem, aiming to jointly minimize system energy consumption and passenger travel costs. We introduce a nested genetic algorithm that incorporates the Lin–Kernighan-Helsgaun (LKH) traveling salesman problem (TSP) solver to address the proposed optimization model for CPTS. The case study, based on real road networks and actual demands not only demonstrates the superiority of the solution algorithm proposed in this paper but also proves that CPTS has advantages in transportation services compared to traditional public transit and taxi services. Sensitivity analyses go a step further in clarifying how changes in both demand and supply of CPTS affect its performance, offering valuable managerial insights.
Original language | English (US) |
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Pages (from-to) | 1 |
Number of pages | 1 |
Journal | IEEE Transactions on Transportation Electrification |
Volume | 11 |
Issue number | 1 |
DOIs | |
State | Published - 2025 |
Keywords
- Charging-on-the-move public transit system (CPTS)
- Costs
- electric bus
- Electrification
- energy consumption
- Genetic algorithms
- Landline
- modular vehicle
- passenger travel cost
- Roads
- Transportation
- traveling salesman problem
- Traveling salesman problems
ASJC Scopus subject areas
- Automotive Engineering
- Transportation
- Energy Engineering and Power Technology
- Electrical and Electronic Engineering