An Algorithm for Supervised Driving of Cooperative Semi-Autonomous Vehicles (Extended)

TL;DR

This paper introduces a cooperative, supervised control algorithm for semi-autonomous vehicles that prevents collisions and deadlocks at intersections and merging points, ensuring safety while maintaining human control.

Contribution

It presents a novel supervised coordination scheme that overrides human inputs only when safety is at risk, ensuring safe, scalable, real-time vehicle cooperation.

Findings

The approach prevents collisions and deadlocks in simulated scenarios.

Computations are feasible in real-time for up to a dozen vehicles.

The method is scalable to real-world traffic situations.

Abstract

Before reaching full autonomy, vehicles will gradually be equipped with more and more advanced driver assistance systems (ADAS), effectively rendering them semi-autonomous. However, current ADAS technologies seem unable to handle complex traffic situations, notably when dealing with vehicles arriving from the sides, either at intersections or when merging on highways. The high rate of accidents in these settings prove that they constitute difficult driving situations. Moreover, intersections and merging lanes are often the source of important traffic congestion and, sometimes, deadlocks. In this article, we propose a cooperative framework to safely coordinate semi-autonomous vehicles in such settings, removing the risk of collision or deadlocks while remaining compatible with human driving. More specifically, we present a supervised coordination scheme that overrides control inputs from human drivers when they would result in an unsafe or blocked situation. To avoid unnecessary intervention and remain compatible with human driving, overriding only occurs when collisions or deadlocks are imminent. In this case, safe overriding controls are chosen while ensuring they deviate minimally from those originally requested by the drivers. Simulation results based on a realistic physics simulator show that our approach is scalable to real-world scenarios, and computations can be performed in real-time on a standard computer for up to a dozen simultaneous vehicles.