GameOpt: Optimal Real-time Multi-Agent Planning and Control for Dynamic Intersections
Authors : Nilesh Suriyarachchi, Rohan Chandra, and Dinesh Manocha
Conference : The 25th IEEE International Conference on Intelligent Transportation Systems (ITSC 2022) pp. 2599-2606 , Macau, China
Date: October 08 - October 12, 2022
We propose GAMEOPT: a novel hybrid approach to cooperative intersection control for dynamic, multi-lane, unsignalized intersections. Safely navigating these complex and accident prone intersections requires simultaneous trajectory planning and negotiation among drivers. GAMEOPT is a hybrid formulation that first uses an auction mechanism to generate a priority entrance sequence for every agent, followed by an optimization-based trajectory planner that computes velocity controls that satisfy the priority sequence. This coupling operates at real-time speeds of less than 10 milliseconds in high density traffic of more than 10, 000 vehicles/hr, 100× faster than other fully optimization-based methods, while providing guarantees in terms of fairness, safety, and efficiency. Tested on the SUMO simulator, our algorithm improves throughput by at least 25%, time taken to reach the goal by 75%, and fuel consumption by 33% compared to auction-based approaches and signaled approaches using traffic-lights and stop signs.
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