Simulative Performance Analysis of an AD Function with Road Network Variation

TL;DR

This paper introduces a simulation-based method to evaluate automated driving functions by varying road network parameters, demonstrating how topology influences ADF performance through an automated scenario testing pipeline.

Contribution

It presents a novel approach to test ADFs by varying road network configurations, expanding beyond traffic participant variations to assess topology effects.

Findings

Road network variations significantly impact ADF performance.

Automated scenario generation streamlines testing process.

Key performance indicators effectively evaluate ADF safety and reliability.

Abstract

Automated driving functions (ADFs) have become increasingly popular in recent years. However, their safety must be assured. Thus, the verification and validation of these functions is still an important open issue in research and development. To achieve this efficiently, scenario-based testing has been established as a valuable methodology among researchers, industry, as well as authorities. Simulations are a powerful way to test those scenarios reproducibly. In this paper, we propose a method to automatically test a set of scenarios in many variations. In contrast to related approaches, those variations are not applied to traffic participants around the ADF, but to the road network to show that parameters regarding the road topology also influence the performance of such an ADF. We present a continuous tool chain to set up scenarios, variate them, run simulations and finally, evaluate the performance with a set of key performance indicators (KPIs).