Design And Implementation Of Path Planning Algorithm For Airport Special Vehicles

Airport special vehicles are important tools for airport ground transportation.The safety and efficiency of airport special vehicles take important part in aviation security,because of the development of civil aviation industry.Decisions of the optimal path is necessary,especially in the severe environments.It is also one of many key points for the construction of smart or intelligent airport in the future.Because of the special application and relevant specification of airport special vehicles,it is meaningful to apply path planning algorithm to optimize the vehicle routes,which might reduce the influence of human factors.The research focuses on path planning for airport special vehicles in the aircraft stand areas.The algorithm is used to optimize the path length and improving the efficiency.The random grid map and the actual airport grid map are established.With these maps,the applicability and performance of the algorithms would be verified.According to traditional path planning algorithm,Dijkstra algorithm is worse in time consuming,and RRT algorithm has randomness.A* algorithm has a good performance both in the path length and searching velocity.The traditional A* has 8 searching neighbourhoods,which affects the degree of freedom.Therefore,the Improved A* algorithm is proposed.Firstly,the searching neighborhood is enlarged for 16 direction.For its added freedom the problems of long planning path and large corner degree could be solved.Secondly,guide vector is given to optimize the number of neighborhood and improve efficiency.The redundant nodes in primary planning path are removed,which is effective for a smooth path.Finally,smart device based on ROS is built to verify the Improved A* algorithm.As is shown in simulation experiments,the Improved A* could be proved its high performance in path planning.Compared with the traditional algorithms,such as A*,Dijkstra and RRT,the Improved A* has advantage in successful searching ratio of 100%.Its planning path is smooth.And also,the average time consume is reduced by 50%.In the experiment of smart device,the Improved A* algorithm can stably optimize the path.Compared with the traditional A*,the minimum time cost is shortened from 82.25 s to 48.83 s.The path length and time cost are greatly shortened.It shows that the Improved A* algorithm can optimize the path and improve the efficiency.