Automatic Generation of Road Geometries to Create Challenging Scenarios for Automated Vehicles Based on the Sensor Setup

TL;DR

This paper introduces a method to automatically generate challenging highway scenarios for automated vehicle safety testing by optimizing road geometries to maximize perception difficulty based on sensor setup models.

Contribution

It presents a novel approach to create critical scenarios by calculating optimal road geometries that induce poor perception, enhancing offline safety assessments of automated vehicles.

Findings

Generated scenarios with high perception difficulty for testing

Optimized road geometries for challenging safety scenarios

Applicable to highway operational design domains

Abstract

For the offline safety assessment of automated vehicles, the most challenging and critical scenarios must be identified efficiently. Therefore, we present a new approach to define challenging scenarios based on a sensor setup model of the ego-vehicle. First, a static optimal approaching path of a road user to the ego-vehicle is calculated using an A* algorithm. We consider a poor perception of the road user by the automated vehicle as optimal, because we want to define scenarios that are as critical as possible. The path is then transferred to a dynamic scenario, where the trajectory of the road user and the road layout are determined. The result is an optimal road geometry, so that the ego-vehicle can perceive an approaching object as poorly as possible. The focus of our work is on the highway as the Operational Design Domain (ODD).