Distributed Model-Predictive Control with Car-to-Car Communication

Modern vehicles offer a number of passive and active driver assistance systems, which shall support the driver in crucial situations. The degree of automation of such systems increases continuously and eventually ends in systems that act fully autonomously within given bounds. Such assistance systems get more and more important in controlling cars in all-day road traffic. In future cars will communicate and negotiate driving strategies. The following videos illustrate a distributed model-predictive control algorithm for autonomous cars in typical traffic scenarios using car-to-car communication. The control algorithm uses a dynamic hierarchy list and avoids collisions through state constraints. The results have been obtained at the Chair of Engineering Mathematics of the University of the Federal Armed Forces (http://www.unibw.de/lrt1/gerdts).

The following video shows the output of the mpc control algorithm for an autonomous crossing scenario:

The following video shows the output of the mpc control algorithm for an autonomous roundabout scenario:

The following video shows the output of the mpc control algorithm for an autonomous takeover scenario: