Dynamic Path Planning for Autonomous Vehicles: A Neuro-Symbolic Approach

Omar Elrasas, Nourhan Ehab, Yasmin Mansy, Amr El Mougy

2024

Abstract

The rise of autonomous vehicles has transformed transportation, promising safer and more efficient mobility. Dynamic path planning is crucial in autonomous driving, requiring real-time decisions for navigating complex environments. Traditional approaches, like rule-based methods or pure machine learning, have limitations in addressing these challenges. This paper explores integrating Neuro-Symbolic Artificial Intelligence (AI) for dynamic path planning in self-driving cars, creating two regression models with the Logic Tensor Networks (LTN) Neuro-Symbolic framework. Tested on the CARLA simulator, the project effectively followed road lanes, avoided obstacles, and adhered to speed limits. Root mean square deviation (RMSE) gauged the LTN models’ performance, revealing significant improvement, particularly with small datasets, showcasing Neuro-Symbolic AI’s data efficiency. However, LTN models had longer training times compared to linear and XGBoost regression models.

Paper Citation

in Harvard Style

Elrasas O., Ehab N., Mansy Y. and El Mougy A. (2024). Dynamic Path Planning for Autonomous Vehicles: A Neuro-Symbolic Approach. In Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-680-4, SciTePress, pages 584-591. DOI: 10.5220/0012374700003636

in Bibtex Style

@conference{icaart24,
author={Omar Elrasas and Nourhan Ehab and Yasmin Mansy and Amr El Mougy},
title={Dynamic Path Planning for Autonomous Vehicles: A Neuro-Symbolic Approach},
booktitle={Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},
year={2024},
pages={584-591},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012374700003636},
isbn={978-989-758-680-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - Dynamic Path Planning for Autonomous Vehicles: A Neuro-Symbolic Approach
SN - 978-989-758-680-4
AU - Elrasas O.
AU - Ehab N.
AU - Mansy Y.
AU - El Mougy A.
PY - 2024
SP - 584
EP - 591
DO - 10.5220/0012374700003636
PB - SciTePress