In a world where inclusion is a priority, many urban infrastructures are still unsuitable for people with reduced mobility (PRM). An autonomous car equipped with sensors and a camera could simulate the journey of a person with reduced mobility. This would make it possible to identify accessible infrastructures and encourage their improvement.
Identify accessible pathways for individuals with reduced mobility (PRM). Using computer vision and advanced object detection models like YOLOv8, it analyzes images or video feeds to detect if a path is wide enough for PRM.
Ensures immediate halting of the system when a critical situation or obstacle is detected, prioritizing safety. It uses real-time sensor data to instantly trigger a stop command, preventing potential accidents or damage.
Enables precise navigation by following a pre-recorded GPS route. By continuously adjusting its trajectory based on real-time position data, the vehicle ensures smooth navigation, effectively staying on track and responding to any deviations.
Our Team
Duc-Anh LE dale@insa-toulouse.fr
Antoine AVY avy@insa-toulouse.fr
Lucie VORMS vorms@insa-toulouse.fr
Manon SANCHEZ sanchez@insa-toulouse.fr
Jean-Yves SAINT-LOUBERT saint-lo@insa-toulouse.fr
Diskouna John GNANGUESSIM gnanguessim@insa-toulouse.fr