Future advanced driver assistance systems require an accurate and up-to-date picture of the surrounding environment for applications such as forward collision assistants or adaptive cruise control. Today, the relative position of other vehicles with respect to the ego-vehicle is obtained with on-board ranging sensors.
Radar sensors, laser scanners and cameras make it possible to detect and track surrounding vehicles, cyclists or pedestrians. These sensors, however, have some important limitations. On-board ranging sensors have a limited perception range and field of view and are easily obstructed by other vehicles.
By adding communication capabilities to future vehicles, cooperative approaches can offer a complementary source of relative position information.
Many Advanced Driver Assistance Systems rely on an accurate self-localization. This is usually provided by Global Navigation Satellite Systems (GNSS) along with on-board sensors, such as inertial sensors, speed sensors, wheel-tick sensors and steering wheel angle sensors. However, this approach suffers from incremental error growth when long GNSS outages occur. Additionally, it is widely accepted that GNSS has a poor performance in urban-like environments due to satellite line-of-sight blockage, signal attenuation and multipath propagation. We propose a solution in which the error associated to GNSS-based positioning is contained by using surrounding road infrastructure objects (RIO) that are detected with a radar sensor. Since the position of these objects is a-priori not known, we suggest sharing their estimated location among the vehicles using vehicle-to-vehicle communication and, in this way, improve their over-all position accuracy over time.
For the purpose of performing measurements and demonstrating our algorithms, our group has a test vehicle. The Mercedes G400 is equipped with processing units, OBD-II interface for the speed, inertial sensors and GNSS receivers. Additionally, it features a laser scanner and a radar system mounted on the front bumper.