Comparison of Path Algorithms in Driverless Vehicles and Application to Complex Paths

DOI

10.2991/978-94-6463-821-9_20How to use a DOI?

Keywords

Driverless Vehicles; Dijkstra’s Algorithm; A* Algorithm; Learning Algorithm

Abstract

This thesis focuses on path planning for driverless vehicles and discusses various path algorithms in depth. Driverless vehicles need path algorithms that can plan the optimal route from the starting point to the endpoint for the vehicle based on the map and the destination, taking into account the traffic conditions, real-time road conditions, etc., avoiding congestion and dangerous areas, such as planning routes around congested roads in the morning and evening peaks, and improving the travel efficiency. This paper concludes that traditional algorithms are more efficient in simple structured environments, but have poor adaptability in the face of complex paths; deep learning algorithms, although computationally complex and requiring a large amount of data, show strong adaptability and learning ability in complex dynamic environments, such as mountainous harsh environments. Comprehensive analysis of the advantages and disadvantages of different algorithms in specific complex path scenarios provides a basis for the selection and optimization of path algorithms for unmanned vehicles, which helps to improve the safety, efficiency and reliability of unmanned systems driving on complex paths, and promotes the further development and improvement of unmanned technology.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Yilin Zhang
AU  - Yuhan Zhang
PY  - 2025
DA  - 2025/08/31
TI  - Comparison of Path Algorithms in Driverless Vehicles and Application to Complex Paths
BT  - Proceedings of the 2025 2nd International Conference on Mechanics, Electronics Engineering and Automation (ICMEEA 2025)
PB  - Atlantis Press
SP  - 171
EP  - 180
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-821-9_20
DO  - 10.2991/978-94-6463-821-9_20
ID  - Zhang2025
ER  -