Konsep Inti
This paper presents a real-time and safe motion planning framework for autonomous driving systems using the Model Predictive Path Integral (MPPI) approach. The proposed method can handle obstacles and guarantee bounds for speed, acceleration, and steering rate to generate feasible and collision-free trajectories.
Abstrak
The paper addresses the complex problem of motion planning for autonomous driving systems, which involves satisfying various constraints related to road geometry, semantics, traffic rules, and dynamic obstacles. The authors formulate the motion planning problem as a nonlinear stochastic dynamic optimization problem and solve it using the MPPI strategy.
The key technical contribution of this work is a method to handle obstacles within the MPPI formulation safely. Obstacles are approximated by circles that can be easily integrated into the MPPI cost formulation while considering safety margins. This approach allows the MPPI framework to effectively penalize trajectories at risk of collision.
The proposed MPPI-based motion planner has been implemented and tested on an existing autonomous driving platform. Three driving scenarios were evaluated: lane merge, object avoidance, and vehicle following. The experimental results demonstrate that the generated trajectories are safe, feasible, and achieve the planning objectives. The trajectories respect the constraints on speed, acceleration, and steering rate, ensuring a smooth and accurate ride while avoiding collisions and maintaining a safe distance from obstacles.
The authors note that a slight deviation between the MPPI trajectories and the actual trajectories was observed, which they attribute to the underlying control module. Future work will focus on more complex and realistic scenarios involving a more dynamic environment, as well as improving the vehicle dynamics modeling in the MPPI motion model.
Statistik
The maximum steering rate was ωmax = 0.11rad/s.
The maximum acceleration was amax = 1.1m/s^2.
The minimum acceleration was amin = -2.5m/s^2.
The target speed was set to vG = 30km/h.
Kutipan
"The main technical contribution of this work is a method to handle obstacles within the MPPI formulation safely. In this method, obstacles are approximated by circles that can be easily integrated into the MPPI cost formulation while considering safety margins."
"Experimental results show that generated trajectories are safe, feasible and perfectly achieve the planning objective."