Cooperative driving at isolated intersections based on the optimal minimization of the maximum exit time

Wu, Jia; Abbas-Turki, Abdeljalil; Perronnet, Florent · 2013 · Crossref

DOI: 10.2478/amcs-2013-0058

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Summary

This paper addresses the challenge of optimizing traffic flow at isolated intersections through Autonomous Intersection Management (AIM), a cooperative driving framework that replaces traditional traffic lights with vehicle-specific right-of-way assignments. While traditional systems optimize phase durations to reduce average delay, AIM treats each vehicle individually, creating a combinatorial optimization problem for determining the optimal passing sequence. The authors aim to solve this problem efficiently by minimizing the maximum exit time—the time when the last vehicle clears the conflict zone—thereby reducing overall vehicle delay and improving intersection throughput. The study proposes a centralized control protocol called Cooperative Vehicle-Actuation Signalization (CVAS). In this system, vehicles communicate their positions and arrival requests to an intersection manager via wireless technology and discrete point positioning. The intersection manager calculates an optimal passing sequence for vehicles currently approaching the intersection, respecting safety constraints defined by minimum headway times for vehicles on the same lane ($d$) and for vehicles from conflicting movements ($t_L$). To solve the resulting combinatorial problem, which grows exponentially with the number of vehicles, the authors develop a dynamic programming algorithm. This approach decomposes the problem into sub-problems based on the number of vehicles remaining on each lane, constructing a directed graph where nodes represent sub-problems and edges represent the addition of a vehicle to the sequence. The algorithm identifies the shortest path in this graph, corresponding to the sequence that minimizes the maximum exit time, achieving a solution in polynomial time. Experimental results derived from simulations demonstrate the efficacy of the proposed method. Using a two-lane intersection example with four vehicles, the algorithm successfully computed an optimal passing sequence that minimized the maximum exit time to 14 seconds, adhering to all safety headway constraints. The simulation confirms that the dynamic programming approach effectively handles the complexity of individual vehicle scheduling, avoiding the exponential computational cost associated with exhaustive search methods. The results indicate that properly arranging the vehicle passing sequence significantly improves traffic efficiency compared to simpler policies like First Come First Serve. The significance of this work lies in providing a computationally feasible solution for real-time AIM systems. By proving that the optimal minimization of maximum exit time can be solved in polynomial time, the paper establishes a practical foundation for implementing cooperative driving at intersections. This approach allows for precise, individualized right-of-way assignment that adapts to real-time traffic conditions, offering a scalable alternative to traditional traffic light systems and enhancing the safety and efficiency of urban traffic networks through advanced wireless communication and positioning technologies.

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• driver vru interaction