Rasidescu, Victor (Concordia University), Taghavifar, Hamid (Concordia University)

Artificial Potential Fields-Enhanced Socially Intelligent Path-Planning for Autonomous Vehicles Using Type 2 Fuzzy Systems

Scheduled for presentation during the Regular Session "Motion planning" (ThBT9), Thursday, September 26, 2024, 16:10−16:30, Salon 17

2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC), September 24- 27, 2024, Edmonton, Canada

This information is tentative and subject to change. Compiled on December 26, 2024

Abstract

The domain of autonomous vehicle (AV) technology is rapidly evolving, and it presents significant challenges to ensure safety and social harmony in mixed-traffic environments. This study introduces an innovative path-planning model that combines Artificial Potential Fields (APF) with Type-2 Fuzzy Logic Systems to enhance the navigation capabilities of autonomous vehicles in dynamic urban settings. The proposed model uses Social Value Orientation (SVO) to assess and respond to the intentions of other road users, including pedestrians and human-driven vehicles. The system handles uncertainties in sensor data and environmental variations by leveraging the robustness of Type-2 Fuzzy Logic, thus improving decision-making in complex scenarios. Simulation results demonstrate that the model can optimize path planning by predicting and adapting to potential hazards with greater accuracy, significantly reducing the risk of accidents and enhancing traffic flow. This research advances the technical specifications of autonomous navigation systems and addresses the critical aspect of social acceptance by ensuring that AV operations align with human values and safety norms.