Frenetic at the SBST 2021 Tool Competition
Ezequiel Castellano, Ahmet Cetinkaya, Cédric Ho Thanh, Stefan Klikovits, Xiao–Yi Zhang, Paolo Arcaini · 2021
Frenetic is a genetic approach that leverages a curvature-based road representation. Given an autonomous driving agent, the goal of Frenetic is to generate roads where the agent fails to stay within its lane. In other words, Frenetic tries to minimize the “out of bound distance”, which is the distance between the car and either edge of the lane if the car is within the lane, and proceeds to negative values once the car drives off. This work resembles classic aspects of genetic algorithms such as mutations and crossover, but introduces some nuances aiming at improving diversity of the generated roads.