@inproceedings{d3da4c5935874a40b6f1ef6bfc9d81d2,
title = "Design of DQN-Based Path Tracking Algorithm for Robust Autonomous Driving",
abstract = "Despite the increasing interest in autonomous driving, significant challenges remain, particularly in achieving high and stable tracking performance. We herein propose a deep Q-network (DQN)-based path tracking algorithm to enhance autonomous vehicle navigation. By interpreting the path tracking task as a sequential decision-making problem, we develop a DQN-based steering control algorithm for precise path tracking. Simulation results confirm that the proposed algorithm significantly enhances tracking accuracy and stability, out performing the conventional methods.",
keywords = "Autonomous driving, deep Q-network, path tracking",
author = "Yang, \{Seung Geon\} and Cho, \{Eun Ho\} and Jeongyun Kim and Lim, \{Seung Chan\}",
note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; 15th International Conference on Information and Communication Technology Convergence, ICTC 2024 ; Conference date: 16-10-2024 Through 18-10-2024",
year = "2024",
doi = "10.1109/ICTC62082.2024.10827039",
language = "English",
series = "International Conference on ICT Convergence",
publisher = "IEEE Computer Society",
pages = "1560--1561",
booktitle = "ICTC 2024 - 15th International Conference on ICT Convergence",
}