The automotive industry continues to incorporate advanced technology and control systems design into new vehicles. Features such as adaptive cruise control, lane keep assist, autonomous park assist, and adaptive lights are becoming more common in the automotive market. These exciting technologies greatly increase vehicle safety!
Adaptive cruise controls measure the distance and speed of nearby vehicles and adjust the speed of the vehicle with the cruise control to maintain safe following distances. Typically a system will use a radar that measures range, range rate and azimuth to vehicles in its field of view.
A typical situation is shown below. The car with adaptive cruise control is traveling near three additional vehicles. Two cars have been tracked for awhile but a third is passing and plans to insert itself into the space between the tracking car and one of the tracked cars. How does the cruise control keep the three cars straight?
Every measurement has uncertainty. The following drawing shows the uncertainty ellipsoids for the three vehicles. As you can see they overlap so a measurement could be associated with more than one car.
The Princeton Satellite Systems Target Tracking Module for MATLAB implements track oriented Multiple Hypothesis Testing (MHT). MHT is a Bayesian method for reliably associating measurements with tracks. The system is shown below:
The system includes a powerful track pruning algorithm that eliminates the need for ad-hoc track pruning. Without track pruning the number of tracks maintained would grow exponentially. The system generates hypotheses that are collections of tracks that are consistent, that is the tracks do not share any measurements. Measurements are incorporated into tracks and tracks are propagated using Kalman Filters. The MHT system also can handle multiple sensors for automobiles with cameras and radar.