A guaranteed collision‐free trajectory planning method for autonomous parking

Abstract

Planning a feasible, and safe trajectory is a crucial procedure for autonomous parking which remains to be fully solved. Generally, a trajectory is depicted by a sequence of configurations which include positions, and orientations. However, existing approaches usually design parking trajectories without considering the evolution from one configuration to the next. Hence, these trajectories are practically infeasible in some scenarios, and safety risks may exist. In this paper, a guaranteed collision-free trajectory planning method is proposed for autonomous parking. A dynamic optimisation problem is built, which includes vehicle kinematics, collision avoidance constraints, and physical restraints. Then the dynamic optimisation problem is discretised into a finite-dimensional nonlinear programming problem. To describe collision avoidance constraints, the concepts of the virtual protection frame, and the magnification parameter are introduced. It is highlighted that a novel collision detection criterion is raised from the view of geometry. Tests in three common scenarios, and a complex scenario illustrate the effectiveness of the proposed approach. Moreover, the stability of the algorithm is discussed in this paper. Via the proposed approach, an integrated design of planning, and control is possible.

Online Competition of Trajectory Planning for Automated Parking: Benchmarks, Achievements, Learned Lessons, and Future Perspectives

“…Problems 13-15 contain sharp obstacles, which are deployed to test whether a planned trajectory is free from subtle collisions. Herein, if collision checks or collision-avoidance constraints are not imposed with accuracy, then the resultant trajectories easily involve collisions [27]. Another interesting phenomenon related to problems 13-15 is that the coordinate values of the vehicles and obstacles are dramatically biased from the origin of the coordinate system.…”

Collision Avoidance Path Planning for Vehicles Combining MPC and CACC Controllers

“…They designed a parking collision avoidance model based on vehicle kinematics and collision avoidance constraints. Test results show that this model can effectively reduce the probability of collision during parking [11]. Le investigated a large number of cases of child fatalities caused by motor vehicle collisions in the United States in recent years and summarized several rules that can reduce this type of accidental death [12].…”

“…According to the data relationship in Figure 3, the discrete following model can be obtained as shown in equations ( 10) VOLUME 11, 2023 and (11).…”

Trajectory Planning for Narrow Environments That Require Changes of Driving Directions

“…Special planning situations such as driving in the parking bay may explicitly be integrated into the planning component. Approaches such as [25,26] were suitable in the area of autonomous driving, where tasks such as parking cars often occur. For this, the planning components identify the respective pattern and integrate a pre-defined movement.…”