The goal of SafeBench is to systematically evaluate the safety and security of autonomous driving (AD) algorithms based on diverse testing scenarios and comprehensive evaluation metrics. Safebench is based on Carla, a high-fidelity and open-sourced AD Simulator. There are three main features that distinguish Safebench from other scenario-based benchmarks:
Safebench provides scenarios for both perception module and control module of AD system. This overview video illustrates the scenarios in Safebench for both modules.