Comprehensive Reactive Safety: No Need For A Trajectory If You Have A Strategy

TL;DR

This paper introduces Comprehensive Reactive Safety, a new framework for autonomous vehicle motion planning that considers future environment updates to improve safety and reduce conservativeness, validated through simulations.

Contribution

It proposes a novel reactive safety framework that relaxes the need for strict trajectory certification by incorporating future environment reactions into planning.

Findings

Reactive ILQR achieves better safety and negotiation in urban scenarios.

The framework reduces conservativeness compared to traditional reachability-based methods.

Simulation results show improved performance in lane merging and unprotected turns.

Abstract

Safety guarantees in motion planning for autonomous driving typically involve certifying the trajectory to be collision-free under any motion of the uncontrollable participants in the environment, such as the human-driven vehicles on the road. As a result they usually employ a conservative bound on the behavior of such participants, such as reachability analysis. We point out that planning trajectories to rigorously avoid the entirety of the reachable regions is unnecessary and too restrictive, because observing the environment in the future will allow us to prune away most of them; disregarding this ability to react to future updates could prohibit solutions to scenarios that are easily navigated by human drivers. We propose to account for the autonomous vehicle's reactions to future environment changes by a novel safety framework, Comprehensive Reactive Safety. Validated in simulations in several urban driving scenarios such as unprotected left turns and lane merging, the resulting planning algorithm called Reactive ILQR demonstrates strong negotiation capabilities and better safety at the same time.