Vehicle tracking with lane assignment by camera and lidar sensor fusion

A multi-sensor system for vehicle tracking and lane detection is presented in this contribution. The system utilizes a lidar and a monocular camera sensor. The main focus for the lidar lies in the field of vehicle detection and the camera is initially used for lane detection. Therewith realized and introduced applications onto the market are driver assistance systems for adaptive cruise control (ACC) and lane departure warning (LDW). More sophisticated ACC functionalities like collision mitigation and collision avoidance systems require a higher reliability and accuracy of the environment recognition. The joint use of both sensors facilitates this without additional expenses for hardware. It exploits the advantages of the different sensor concepts to extend the capabilities for interpretation of the vehicle environment. In our case this ensures a more accurate estimation of the dimensions and positions of the vehicles within the lane respectively the entire road. Finally, we present an innovative human machine interface (HMI) solution to display the desired assistance functionality with high transparency and clarity to the driver.

[1]  J. Wenger Short range radar - being on the market , 2007, 2007 European Radar Conference.

[2]  Edward Hoare,et al.  Trials of automotive radar and lidar performance in road spray , 1998 .

[3]  Klaus Dietmayer,et al.  Pedestrian recognition in urban traffic using a vehicle based multilayer laserscanner , 2002, Intelligent Vehicle Symposium, 2002. IEEE.

[4]  Bin Dai,et al.  A Vehicle Detection Method via Symmetry in Multi-Scale Windows , 2007, 2007 2nd IEEE Conference on Industrial Electronics and Applications.

[5]  T. Ogawa,et al.  Lane Recognition Using On-vehicle LIDAR , 2006, 2006 IEEE Intelligent Vehicles Symposium.

[6]  G. Toussaint Solving geometric problems with the rotating calipers , 1983 .

[7]  J. Goldbeck,et al.  Lane detection and tracking by video sensors , 1999, Proceedings 199 IEEE/IEEJ/JSAI International Conference on Intelligent Transportation Systems (Cat. No.99TH8383).

[8]  Alberto Elfes,et al.  Using occupancy grids for mobile robot perception and navigation , 1989, Computer.

[9]  Ming-Hui Wen,et al.  Comparison of head-up display (HUD) vs. head-down display (HDD): driving performance of commercial vehicle operators in Taiwan , 2004, Int. J. Hum. Comput. Stud..

[10]  Andrew Zisserman,et al.  Multiple View Geometry , 1999 .

[11]  Alberto Elfes,et al.  Occupancy grids: a probabilistic framework for robot perception and navigation , 1989 .

[12]  T. Ogawa,et al.  Road Environment Recognition Using On-vehicle LIDAR , 2006, 2006 IEEE Intelligent Vehicles Symposium.

[13]  J. Wenger Short range radar - Being on the market , 2007, 2007 European Microwave Conference.