Planning frameworks for autonomous vehicles must be robust and computationally efficient for real time realization. At the same time, they should accommodate the unpredictable behavior of the other participants and produce safe trajectories. In this paper, we present a computationally efficient hierarchical planning framework for autonomous vehicles that can generate safe trajectories in complex driving scenarios, which are commonly encountered in urban traffic settings. The first level of the proposed framework constructs a Model Predictive Control(MPC)routine using an efficient difference of convex programmingapproach, that generates smooth and collision-free trajectories. The constraints on curvature and road boundaries are seamlessly integrated into this optimization routine. The second layer is mainly responsible to handle the unpredictable behaviors that are typically exhibited by the other participants of traffic. It is built along the lines of time scaled collision cone(TSCC)which optimize for the velocities along the trajectory to handle such disturbances. We additionally show that our framework maintains optimal balance between temporal and path deviations while executing safe trajectories. To demonstrate the efficacy of the presented framework we validated it in extensive simulations in different driving scenarios like over taking, lane merging and jaywalking among many dynamic and static obstacles.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Motion Planning Framework for Autonomous Vehicles: A Time Scaled Collision Cone Interleaved Model Predictive Control Approach




    Publication date :

    2019-06-01


    Size :

    933185 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    MOTION PLANNING FRAMEWORK FOR AUTONOMOUS VEHICLES: A TIME SCALED COLLISION CONE INTERLEAVED MODEL PREDICTIVE CONTROL APPROACH

    Theerthala, Raghu Ram / Kumar, A. V. S. Sai Bhargav / Babu, Mithun et al. | British Library Conference Proceedings | 2019


    Development of model predictive motion planning and control for autonomous vehicles

    Tosolin, Guido / Cartró, Jaume / Sharma, Vishwas | Springer Verlag | 2019




    Reactive Path Coordination Based on Time-Scaled Collision Cone

    Singh, Arun Kumar / Pham, Quang Cuong | AIAA | 2018