Enforcing safety while preventing overly conservative behaviors is essential for autonomous vehicles to achieve high task performance. In this paper, we propose a barrier-enhanced parallel homotopic trajectory optimization (BPHTO) approach with the over-relaxed alternating direction method of multipliers (ADMM) for real-time integrated decision-making and planning. To facilitate safety interactions between the ego vehicle (EV) and surrounding vehicles, a spatiotemporal safety module exhibiting bi-convexity is developed on the basis of barrier function. Varying barrier coefficients are adopted for different time steps in a planning horizon to account for the motion uncertainties of surrounding HVs and mitigate conservative behaviors. Additionally, we exploit the discrete characteristics of driving maneuvers to initialize nominal behavior-oriented free-end homotopic trajectories based on reachability analysis, and each trajectory is locally constrained to a specific driving maneuver while sharing the same task objectives. By leveraging the bi-convexity of the safety module and the kinematics of the EV, we formulate the BPHTO as a bi-convex optimization problem. Then constraint transcription and the over-relaxed ADMM are employed to streamline the optimization process, such that multiple trajectories are generated in real time with feasibility guarantees. Through a series of experiments, the proposed development demonstrates improved task accuracy, stability, and consistency in various traffic scenarios using synthetic and real-world traffic datasets.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Barrier-Enhanced Parallel Homotopic Trajectory Optimization for Safety-Critical Autonomous Driving


    Beteiligte:
    Zheng, Lei (Autor:in) / Yang, Rui (Autor:in) / Yu Wang, Michael (Autor:in) / Ma, Jun (Autor:in)


    Erscheinungsdatum :

    01.02.2025


    Format / Umfang :

    1346386 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Homotopic Optimization for Autonomous Vehicle Maneuvering

    Zhou, Jian / Balachandran, Arvind / Olofsson, Bjorn et al. | IEEE | 2024


    Practical Techniques for Low-Thrust Trajectory Optimization with Homotopic Approach

    Jiang, Fanghua / Baoyin, Hexi / Li, Junfeng | AIAA | 2012



    HOMOTOPIC-BASED PLANNER FOR AUTONOMOUS VEHICLES

    Europäisches Patentamt | 2025

    Freier Zugriff

    HOMOTOPIC-BASED PLANNER FOR AUTONOMOUS VEHICLES

    KABZAN JURAJ / FRAZZOLI EMILIO | Europäisches Patentamt | 2022

    Freier Zugriff