GAMEOPT: Optimal Real-time Multi-Agent Planning and Control at Dynamic Intersections

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, $100\times$ 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.