A Full-Factorial Study of Sensor Fusion for Advanced Driver Assistance Systems

In this study, a full-factorial experimental evaluation of a sensor fusion system based on a real vehicle was performed. The experimental results for different driving scenarios and parameters are discussed and the factors that make the most impact are identified. The performance of sensor fusion depends on many factors such as the sensors used, kinematic model used in the Extended Kalman Filter(EKF) motion of the vehicles, type of road, density of vehicles, and gating methods. The interactions between parameters and the extent to which individual parameters contribute to the overall accuracy of a sensor fusion system can be difficult to assess. This study identified that the distance between the vehicles has the largest impact on the estimation error because the vision sensor performs poorly with increased distance. In addition, it was identified that the kinematic models had no significant impact on the estimation. Last but not least, the ellipsoid gates performed better than rectangular gates.