Multisensor vehicle tracking method for intelligent highway system

Abstract

Presents a vehicle tracking method which fuses data from an image sensor and radar installed on the roadside. The image sensor is widely used for road monitoring systems, but it is difficult to detect a vehicle in poor visibility. On the other hand, millimeter waves are less attenuated by fog, rain and snow. Consequently, it is possible to detect vehicles in all weather by using radar together with the image sensor. As for observation accuracy, the image sensor is superior in the accuracy of angle measuring. On the other hand, radar is superior in accuracy for range measurement. By utilizing these various features, therefore, the tracking performance is improved. This method adopts a correlation technique that uses a likelihood of range rate observed by radar, in addition to a likelihood of position, so that this method is generally able to track the vehicles from observation vectors even if false detection occurs. The performance of this method is evaluated by simulations.