Semi-autonomous Intersection Collision Avoidance through Job-shop Scheduling

Abstract

In this paper, we design a supervisor to prevent vehicle collisions at intersections. An intersection is modeled as an area containing multiple conflict points where vehicle paths cross in the future. At every time step, the supervisor determines whether there will be more than one vehicle in the vicinity of a conflict point at the same time. If there is, then an impending collision is detected, and the supervisor overrides the drivers to avoid collision. A major challenge in the design of a supervisor as opposed to an autonomous vehicle controller is to verify whether future collisions will occur based on the current drivers choices. This verification problem is particularly hard due to the large number of vehicles often involved in intersection collision, to the multitude of conflict points, and to the vehicles dynamics. In order to solve the verification problem, we translate the problem to a job-shop scheduling problem that yields equivalent answers. The job-shop scheduling problem can, in turn, be transformed into a mixed-integer linear program when the vehicle dynamics are first-order dynamics, and can thus be solved by using a commercial solver.

Submitted to Hybrid Systems: Computation and Control (HSCC) 2016

Cited by in corpus (4)

• Optimal Control of Connected and Automated Vehicles at Multiple Adjacent Intersections
• Safety Verification and Control for Collision Avoidance at Road Intersections
• Time-Optimal Coordination for Connected and Automated Vehicles at Adjacent Intersections
• An Optimal Coordination Framework for Connected and Automated Vehicles in two Interconnected Intersections