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In this article, we propose an optimization-based integrated behaviorplanning and motion control scheme, which is an interpretable and adaptableurban autonomous driving solution that complies with complex traffic ruleswhile ensuring driving safety. Inherently, to ensure compliance with trafficrules, an innovative design of potential functions (PFs) is presented tocharacterize various traffic rules related to traffic lights, traversable andnon-traversable traffic line markings, etc. These PFs are further incorporatedas part of the model predictive control (MPC) formulation. In this sense,high-level behavior planning is attained implicitly along with motion controlas an integrated architecture, facilitating flexible maneuvers with safetyguarantees. Due to the well-designed objective function of the MPC scheme, ourintegrated behavior planning and motion control scheme is competent for variousurban driving scenarios and able to generate versatile behaviors, such asovertaking with adaptive cruise control, turning in the intersection, andmerging in and out of the roundabout. As demonstrated from a series ofsimulations with challenging scenarios in CARLA, it is noteworthy that theproposed framework admits real-time performance and high generalizability.

Integrated Behavior Planning and Motion Control for Autonomous Vehicles with Traffic Rules Compliance