Algorithmization of constrained monotonic maneuvers for an advanced driver assistant system in the intelligent urban buses

The paper presents a motion algorithmization subsystem used as a part of an advanced driver assistance system (ADAS) which is intended to help a human operator perform difficult maneuvers with intelligent urban buses in a more effective way. The algorithmization task, being a tight combination of motion planning and feedback control, is addressed in the presence of various constraints imposed on the nonholonomic vehicle motion, like limited motion curvature and curvature rate, obstacle collision avoidance, and maneuvering without a change of a longitudinal velocity sign (monotonic maneuvers). Description of the system is followed by exemplary results obtained on a laboratory testbed emulating a driver workplace with ADAS.