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The past decade has witnessed the rapid development of autonomous parking technology, since it has promising capacity to improve traffic efficiency and reduce the burden on drivers. However, it is prone to the trap of self-centeredness when each vehicle is automated parking in isolation. And it is easy to cause traffic congestion and even chaos when multiple autonomous vehicles require of parking into the same lot. In order to address the multiple vehicle parking problem, we propose a parking planning method with genetic algorithm. Firstly, an optimal mathematic model is established to describe the multiple autonomous vehicle parking problem. Secondly, a genetic algorithm is designed to solve the optimization problem. Thirdly, illustrative examples are developed to verify the parking planner. The performance of the present method indicates its competence in addressing parking multiple autonomous vehicles problem.

A rapid path-planning algorithm that generates drivable paths for an autonomous vehicle operating in structural road is proposed in this paper. Cubic B-spline curve is adopted to generating smooth path for continuous curvature and, more, parametric basic points of the spline is adjusted to controlling the curvature extremum for kinematic constraints on vehicle. Other than previous approaches such as inverse kinematics, model-based prediction postprocess approach or closed-loop forward simulation, using the kinematics model in each iteration of path for smoothing and controlling curvature leading to time consumption increasing, our method characterized the vehicle curvature constraint by the minimum length of segment line, which synchronously realized constraint and smooth for generating path. And Differ from the path of robot escaping from a maze, the intelligent vehicle traveling on road in structured environments needs to meet the traffic rules.

Lots of invalid volume of traffic occurs as the vehicle repeatedly seeking the valid berth location, due to the existence of information islands, which reduces traffic efficiency, increases traffic congestion and the emission of pollutants. Aiming at eliminating the existence of information islands, this paper proposed a guidance strategy for parking space of autonomous valet parking, as taking merits of cooperative vehicle infrastructure system. The guidance strategy consists of an optimal guidance model and an adaptive ant-colony algorithm. Firstly, the optimal guidance model takes the minimum total parking cost as the objective function and the capacity of parking space as the constraints. Both the objective costs of parking and the subjective cost of customer are taken into accounts in the objective function.