Cooperative Decision-Making and Motion Optimization in Mixed-Traffic Environments
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Electrical and Autonomous Vehicles".
Deadline for manuscript submissions: 20 May 2025 | Viewed by 92
Special Issue Editors
Interests: mixed traffic; autonomous vehicle control; signal control
Interests: V2X and safety control; traffic big data; road network risk assessment; traffic policy decision analysis
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
As autonomous driving technology continues to advance, mixed-traffic environments—where autonomous vehicles (AVs) and human-driven vehicles (HVs) share the road—pose unique challenges and opportunities for vehicle coordination and motion optimization. In such environments, effective decision-making and coordination among vehicles are crucial to ensuring safety, efficiency, and fluid traffic flow. The integration of advanced communication technologies, such as V2X (Vehicle-to-Everything) and 5G, with innovative algorithms for decision-making and motion planning, is essential for the development of intelligent transportation systems (ITSs) that can handle these complexities.
This Special Issue focuses on the latest research and innovations in vehicle coordination and motion optimization in mixed-traffic environments. We aim to address the various challenges and explore potential solutions that can enhance the interaction between AVs and HVs, improve traffic safety, and optimize traffic management.
Topics of interest include, but are not limited to, the following:
- Coordinated decision-making algorithms for mixed-traffic environments;
- Motion planning and control for autonomous vehicles in mixed traffic;
- V2X communication technologies for vehicle coordination;
- Human-machine interaction and behavioral modeling in mixed traffic;
- Traffic flow optimization in mixed-traffic scenarios;
- Safety and reliability analysis in mixed-traffic environments;
- Multi-agent systems and cooperative control for vehicle networks;
- Integration of 5G/6G technologies in vehicle decision-making and motion optimization;
- AI and machine learning approaches for predictive modeling in mixed traffic.
Dr. Shaohua Cui
Dr. Miaomiao Liu
Guest Editors
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Keywords
- mixed-traffic environments
- cooperative decision-making
- motion optimization
- autonomous vehicles (AVs)
- human-driven vehicles (HVs)
- V2X communication
- traffic flow optimization
- multi-agent systems
- 5G/6G technologies in transportation
- predictive modeling in mixed traffic
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