Interaction-Aware Motion Planning for Autonomous Vehicles with Multi-Modal Obstacle Uncertainty Predictions

Abstract

This paper proposes an interaction and safety-aware motion-planning method for an autonomous vehicle in uncertain multi-vehicle traffic environments. The method integrates the ability of the interaction-aware interacting multiple model Kalman filter (IAIMM-KF) to predict interactive multi-modal maneuvers of surrounding vehicles, and the advantage of model predictive control (MPC) in planning an optimal trajectory in uncertain dynamic environments. The multi-modal prediction uncertainties, containing both the maneuver and trajectory uncertainties of surrounding vehicles, are considered in computing the reference targets and designing the collision-avoidance constraints of MPC for resilient motion planning of the ego vehicle. The MPC achieves safety awareness by incorporating a tunable parameter to adjust the predicted obstacle occupancy in the design of the safety constraints, allowing the approach to achieve a trade-off between performance and robustness. Based on the prediction of the surrounding vehicles, an optimal reference trajectory of the ego vehicle is computed by MPC to follow the time-varying reference targets and avoid collisions with obstacles. The efficiency of the method is illustrated in challenging highway-driving simulation scenarios and a driving scenario from a recorded traffic dataset.

15 pages

References in corpus (4)

• Resilient Branching MPC for Multi-Vehicle Traffic Scenarios Using Adversarial Disturbance Sequences
• Trajectory Planning Under Environmental Uncertainty With Finite-Sample Safety Guarantees
• Safe Motion Planning against Multimodal Distributions based on a Scenario Approach
• Decision-Time Postponing Motion Planning for Combinatorial Uncertain Maneuvering

Cited by in corpus (5)

• Uncertainty-Aware DRL for Autonomous Vehicle Crowd Navigation in Shared Space
• Spatiotemporal Receding Horizon Control with Proactive Interaction Towards Autonomous Driving in Dense Traffic
• Barrier-Enhanced Parallel Homotopic Trajectory Optimization for Safety-Critical Autonomous Driving
• Data-Driven Robust Optimization for Energy-Aware Safe Motion Planning of Electric Vehicles
• Cooperative Safety Intelligence over V2X Networks: A Survey