Integrating End-to-End and Modular Driving Approaches for Online Corner Case Detection in Autonomous Driving

Autor:	Kaljavesi, Gemb, Su, Xiyan, Diermeyer, Frank
Rok vydání:	2024
Předmět:	Computer Science - Artificial Intelligence Computer Science - Robotics
Druh dokumentu:	Working Paper
Popis:	Online corner case detection is crucial for ensuring safety in autonomous driving vehicles. Current autonomous driving approaches can be categorized into modular approaches and end-to-end approaches. To leverage the advantages of both, we propose a method for online corner case detection that integrates an end-to-end approach into a modular system. The modular system takes over the primary driving task and the end-to-end network runs in parallel as a secondary one, the disagreement between the systems is then used for corner case detection. We implement this method on a real vehicle and evaluate it qualitatively. Our results demonstrate that end-to-end networks, known for their superior situational awareness, as secondary driving systems, can effectively contribute to corner case detection. These findings suggest that such an approach holds potential for enhancing the safety of autonomous vehicles. Comment: IEEE SMC 2024
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2409.01178 Zobrazit plný text záznamu View this record from Arxiv