An MPC-Based Approach to Provable System-Wide Safety and Liveness of Autonomous Ground Traffic

Abstract

An important area of cyber-physical systems research is the development of smart ground transportation systems due to their potentially significant impact on safety, the economy, and the environment. We propose an approach based on model predictive control (MPC) for the development of provably collision free autonomous ground transportation systems, and present an autonomous intersection management framework. The MPC approach enables a vehicle to generate its own motion locally in time based on an optimization framework, incorporating constraints based on the states of other vehicles in the neighborhood, the speed limit of a road, the maximum values of acceleration and deceleration, etc. Safety and liveness of the traffic are however system-wide properties, not merely neighborhood properties, and the challenge is to augment this distributed optimization with coordination rules that guarantee overall system-wide safety as well as liveness of the traffic. We design two vehicle-to-vehicle (V2V) coordination rules, along with a vehicle-to-infrastructure rule, and establish the system-wide safety and liveness of the autonomous traffic based on each vehicle's MPC motion planner, operating in conjunction with an algorithm that orders vehicles according to their runtime properties. We also conduct a comparative simulation study of the throughput performance at an intersection of the above approach against another popular algorithm, the All-Way STOP.