Projects per year
Abstract
Meeting-point-based feeder services using EVs have good potential to achieve an efficient and clean on-demand mobility service. However, customer-to-meeting-point, vehicle routing, and charging scheduling need to be jointly optimized to achieve the best system performance. To this aim, we assess the effect of different system parameters and configure them based on our previously developed hybrid metaheuristic algorithm. A set of test instances based on morning peak hour commuting scenarios between the cities of Arlon and Luxembourg are used to evaluate the impact of the set parameters on the optimal solutions. The experimental results suggest that higher meeting point availability can achieve better system performance. By jointly configuring different system parameters, the overall system performance can be significantly improved (-10.8% total kilometers traveled by vehicles compared to the benchmark) to serve all requests. Our experimental results show that the meeting-point-based system can reduce up to 70.2% the fleet size, 6.4% the in-vehicle travel time and 49.4% the kilometers traveled when compared to a traditional door-to-door dial-a-ride system.
Original language | English |
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Publisher | arXiv.org (Cornell University) |
DOIs | |
Publication status | Published - Jan 2024 |
Keywords
- demand responsive transport
- meeting point
- electric vehicle
- synchronization constraint
- mixed integer linear programming
- metaheuristic
Projects
- 1 Finished
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M-EVRST: Multimodal Electric VEhicle demand RESponsive Transport
Ma, T.-Y. (PI), Klein, S. (CoI), Viti, F. (CoPI), Chow, J. Y. J. (Non Contracting Partner), Connord, R. (CoI) & Venditti, S. (CoI)
Fonds National de la Recherche Luxembourg, Luxembourg Institute of Socio-Economic Research (LISER)
1/04/21 → 31/03/24
Project: Research