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Accelerating Discoveries in Traffic Science

Accelerating Discoveries in Traffic Science

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PUBLISHED
25.04.2023
DOI
https://doi.org/10.7307/ptt.v35i2.54
ISSUE
2023 (Vol 35), Issue 2
LICENSE
Copyright (c) 2024 Yang Wang, Bin Li, Zhenghui Zhao, Kuanwu Tang
Creative Commons 4.0 logo
This work is licensed under a
Creative Commons Attribution-NonCommercial-
NoDerivatives 4.0 International License.

Optimal Routing and Charging of Electric Logistics VehiclesBased on Long-Distance Transportation and Dynamic Transportation System

Authors:Yang Wang, Bin Li, Zhenghui Zhao, Kuanwu Tang

Abstract

The application of electric vehicles (EVs) in the logistics industry has become more extensive. However, the mileage limitation of electric logistics vehicles (ELVs) and the long-distance distribution of ELVs have become urgent problems. Therefore, this paper proposes a long-distance distribution model for ELVs based on dynamic traffic information considering fleet mileage, distribution time and total distribution cost as the optimisation objectives, thus reasonably planning road selection and charging, and alleviating “mileage anxiety” in the long-distance distribution of ELVs. The model proposed in this paper comprehensively considers the characteristics of the high-speed and low-speed roads, the changes in road traffic flow on weekdays and non-weekdays, the time-of-use electricity price of electric vehicle charging stations (EVCSs) and uses the M/M/s queuing theory model to determine the charging waiting time. Finally, a real traffic network is taken as an example to verify the practicability and effectiveness of this model.

Keywords:electric logistics vehicle, long-distance distribution, path planning, charging scheduling

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