A cross-scale traffic-communication control framework for improving safety through proactive congestion mitigation in...

Area of Science:

• Traffic Engineering
• Network Communications
• Autonomous Systems

Background:

• Large-scale traffic accidents stem from shockwaves in congested flow, often caused by unpredictable human driving behaviors.
• Connected and autonomous vehicles (CAVs) offer potential for traffic mitigation but face challenges with communication instability affecting coordination.
• Existing systems struggle to manage mixed traffic environments with both human-driven vehicles (HDVs) and CAVs.

Purpose of the Study:

• To propose a Cross-Network Collaboration-based Congestion Mitigation (CNC-CM) framework to address traffic congestion and accidents.
• To enhance the reliability of communication and coordination between vehicles and the traffic system.
• To develop a proactive approach for dissipating traffic jams before they become hazardous.

Main Methods:

• Developed a Cross-Network Collaboration-based Congestion Mitigation (CNC-CM) framework with a feedback loop between traffic and communication systems.
• Implemented a distance-to-delay interval backtracking algorithm for optimizing long-range hybrid communication routing.
• Designed a multi-scale cooperative strategy: micro-level barrier consensus control for HDVs and macro-level delay-corrected cruising control for CAVs.

Main Results:

• The CNC-CM framework demonstrated a >54.11% enhancement in driving safety by eliminating traffic congestion.
• Significant improvements were observed in traffic efficiency, energy consumption, and communication quality.
• The framework proved robust and effective even with low CAV penetration rates in mixed traffic environments.

Conclusions:

• The proposed CNC-CM framework effectively mitigates traffic congestion and enhances safety by integrating communication and traffic control layers.
• The multi-scale cooperative strategy and optimized communication routing are key to managing complex traffic dynamics.
• This approach offers a viable solution for improving traffic flow and safety in current and future mixed-vehicle environments.