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How to generate a reasonable path for automatic parking assist has been extensively studied. However, it is still a huge challenge to design a path planner that can handle tight space environments for all common parking scenarios. The things need to be considered in the process of path planning algorithm design, including generate a path quickly and low computational costs and collision-free path, make the problem even more difficult to be solved. In this paper, a path planning algorithm based on hybrid A-star and RS algorithm is proposed. The algorithm introduces the concept of guiding points which we can directly generate collision-free path through the RS algorithm, and the guiding point are calculated offline using hybrid A-star algorithm for various working scenarios. And the algorithm was tested and validated by the simulation and vehicle test in two common parking scenarios.

Traffic congestions are increasingly severe in urban areas, especially at the merging areas of the ramps and the arterial roads. Because of the complex conflict relationship of the vehicles in ramps and arterial roads in terms of time-spatial constraints, it is challenging to coordinate the motion of these vehicles, which may easily cause congestions at the merging areas. The connected and automated vehicles (CAVs) provides potential opportunities to solve this problem. A centralized merging control method for CAVs is proposed in this paper, which can organize the traffic movements in merging areas efficiently and safely. In this method, the merging control model is built to formulate the vehicle coordination problem in merging areas, which is then transformed to the discrete nonlinear optimization form. A simulation model is built to verify the proposed method.