Finding uncertainty of sensor fusion in automotive driving

Sammanfattning

Human error has been the most common cause of car accidents. Advances in sensing and data fusion have made recent progress in autonomous vehicles that will increase the potential of drastically improving safety, efficiency, and cost of transportation. In this thesis, we present an overview of finding the error probability of sensor fusion in automotive driving, and we will investigate the collision probabilities in automated vehicles. In our study, we simulate automated driving systems in a virtual environment using real-world maps using MATLAB Automated Driving Toolbox, Simulink, and Roadrunner. During the study, we will investigate different scenarios such as weather conditions, noise, lighting, and road conditions with an ‘ego- vehicle’ equipped with multiple sensors such as; lidar and vision sensors.