A Sensor Fusion and Localization System for Improving Vehicle Safety In Challenging Weather Conditions
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The safety of autonomousconnected vehicles primarily relies on their ability to accurately sense the environment. The sensing problem is significantly challenging in weather conditions which include sudden change in lighting, smoke, fog, snow, and rain. Therefore, accurate sensing in adverse weather conditions is a critical and important safety problem that needs to be solved for any successful deployment of autonomous vehicles. There is currently no single sensor currently available in the market that can handle all the possible performance aspects and adverse weather conditions. The objective of this project is to use a combination of Radars and FIR cameras in addition to a LIDAR based system to map the environment and localize the vehicle with respect to the lanes on the road. This project will develop a prototype of an all weather sensing and localization system which will be useful for any autonomous or connected vehicle. The performance of the developed system will be corroborated with several data sets collected at Rellis. Demonstrations of the developed technology will also be done at the yearly Automated Vehicle Symposium, and SAE conferences.