Electric Vehicle Routing Optimization Oriented to Intelligent Transportation Systems: A Review and Future Trends

Read full text
Authors: Shiqi Zhang
Cited by: 0
References: 11

Abstract

With increasingly stringent environmental constraints and the rapid growth of urban logistics demand, electric vehicles (EVs) have become an important component of urban delivery systems due to their low-carbon, energy-efficient, and low-noise characteristics. However, limited driving range, charging requirements, and the uneven spatial distribution of charging infrastructure make the electric vehicle routing problem (EVRP) significantly more complex than conventional vehicle routing problems, posing new challenges to logistics operations and traffic management. In recent years, extensive research has been conducted on EV routing optimization, covering route planning, charging strategy coordination, mixed fleet operations, and charging infrastructure deployment. Meanwhile, the rapid development of intelligent transportation systems (ITS) has provided new technical support for EV routing optimization. By leveraging real-time traffic information, data sharing, and intelligent dispatching, ITS enhances the adaptability and responsiveness of routing decisions, thereby improving delivery efficiency and reducing energy consumption and emissions. This paper presents a comprehensive review of EV routing optimization oriented to ITS, systematically summarizing key research issues and application scenarios. Future development trends related to technological integration, infrastructure planning, and system-level coordination are also discussed, providing insights for the development of efficient, low-carbon, and sustainable urban logistics and transportation systems.

Fields of Study & Subjects

Vehicle Routing Optimization Methods Electric Vehicles and Infrastructure Urban and Freight Transport Logistics

Publication details

Journal / source
International Journal of Global Economics and Management
Volume
10
Issue
1
Pages
44–49
Publication date
27 January 2026