vehicle-collision-avoidance

This project was created for the 24 hour Bosch hackathon challenge focused on vehicle collision avoidance systems. It implements object detection and tracking from a provided dataset, identifies driving scenarios, and simulates collision avoidance strategies.

Main Features:

. Loads and processes object data from a .csv dataset . Visualizes vehicle environment and object motions over time . Identifies driving scenarios like CPNCO, CPTA, CPLA . Calculates braking distances and deceleration parameters . Simulates collision avoidance outcomes for identified scenarios

Programing language Used:

. Python . Opencv2 , numpy . Carla (virtual enviroment) . Tensorflow (optional for ML models)

Gitting Started:

. clone the repo . Install dependencies . copy The file's Into carla exmple folder .

Next Steps:

. Improve object trajectory forecasting . Expand to more scenarios and sensors . Implement on a real vehicle

Contributors:

@Atocodes, @zakurity, @gabrial