VISUAL TRACKING FOR INTELLIGENT VEHICLE-HIGHWAY SYSTEMS

The complexity and congestion of current transportation systems often produce traffic situations that jeopardize the safety of the people in volved, These situations vary from maintaining a safe distance behind a leading vehicle to safely allowing a pedestrian to cross a busy stre et. Environmental sensing plays a critical role in virtually all of th ese situations, Of the sensors available, vision sensors protide infor mation that Is richer and more complete than other sensors, making the m a logical choice for a multisensor transportation system, In this pa per we propose robust detection and tracking techniques for intelligen t vehicle-highway applications where computer vision plays a crucial r ole, In particular, se demonstrate that the Controlled Active Vision f ramework [15] can be utilized to provide a visual tracking modality to a traffic advisory system in order to increase the overall safety mar gin in a variety bf common traffic situations, We have selected two ap plication examples. vehicle tracking and pedestrian tracking, to demon strate that the framework fan provide precisely the type of informatio n required to effectively manage the given traffic situation.