The use of lane assistance systems can reduce the stress levels experienced by drivers and allow for better lane keeping in narrow, bus-dedicated lanes. A Vehicle Positioning System (VPS) was originally developed by the University of Minnesota?s Intelligent Vehicles (IV) Lab for this purpose. The system provides the lane level ("which lane on the road") position of a vehicle with respect to a known reference (i.e., a mile marker or start of roadway) by the use of encoded position information in RFID (Radio Frequency IDentification) tags on the roadway, read by the vehicle. However, the lateral position resolution of VPS is constrained to one lane width, which is insufficient for lane-assistant systems. In addition, urban areas offer significant obstacles to implementation of such systems, including restricted views of satellites, multi-path reflection of satellite signals, and cellular network holes that interfere with DGPS correction.
This research project developed a method for replacing differential Global Positioning System (DGPS) sensing with a high accuracy vehicle positioning system which fuses data from RFID and LiDAR (Light Detection and Ranging) curb detection.
In-lane level ("where in the lane") lateral position estimation was supplemented by a LiDAR unit that generates an accurate position of the vehicle with respect to the curb, which is cross referenced with a map database that provides the distance from the lane center to the curb, thus providing the vehicle's lateral offset from the lane center. On-board odometry is used to maintain accurate longitudinal position in between tag reads. By fusing the information from the VPS, LiDAR, and on-board odometry, high accuracy, "where in lane" level vehicle positioning can be maintained from this enhanced VPS during DGPS outages.