Model Predictive Trajectory Planning of Autonomous Vehicles Considering Dynamic Driving Constraints

A key problem to be solved for automated driving is to generate a feasible trajectory regarding the constraints imposed by vehicle physical limits and road surface. This paper presents a model predictive trajectory planning framework for automated driving, which takes the dynamic driving constraints into consideration. The constraints are calculated by a separate dynamic driving constraints computation module and represented in the form of inequalities. This module decouples the planner from the vehicle physics such that the planner only needs to consider the kinematics of the vehicle. Therefore, the planner can generate feasible trajectories without directly knowing the properties of vehicle or actuators. The proposed model predictive trajectory planning framework is evaluated in simulation with three different scenarios and the results demonstrate the effectiveness of the proposed framework even in critical use cases of automated driving vehicles.