Safety Verification and Control for Collision Avoidance at Road Intersections
Heejin Ahn, Domitilla Del Vecchio

TL;DR
This paper introduces a supervisory control algorithm for intersection safety that verifies collision risks using jobshop scheduling and MILP approximations, ensuring real-time safe vehicle crossing.
Contribution
It presents a novel safety verification method translating intersection crossing into a jobshop scheduling problem with MILP bounds, enabling real-time collision avoidance control.
Findings
The supervisor guarantees safety and non-blocking behavior.
MILP bounds effectively approximate the nonlinear vehicle dynamics.
Simulations confirm real-time applicability for realistic scenarios.
Abstract
This paper presents the design of a supervisory algorithm that monitors safety at road intersections and overrides drivers with a safe input when necessary. The design of the supervisor consists of two parts: safety verification and control design. Safety verification is the problem to determine if vehicles will be able to cross the intersection without colliding with current drivers' inputs. We translate this safety verification problem into a jobshop scheduling problem, which minimizes the maximum lateness and evaluates if the optimal cost is zero. The zero optimal cost corresponds to the case in which all vehicles can cross each conflict area without collisions. Computing the optimal cost requires solving a Mixed Integer Nonlinear Programming (MINLP) problem due to the nonlinear second-order dynamics of the vehicles. We therefore estimate this optimal cost by formulating two related…
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