The emergence of digital twin technology has provided new ideas for vehicle path planning.To address autonomous vehicles’path conflicts in park logistics and enhance the efficiency of logistics and distribution,an im...The emergence of digital twin technology has provided new ideas for vehicle path planning.To address autonomous vehicles’path conflicts in park logistics and enhance the efficiency of logistics and distribution,an improved A^(*)algorithm path planning method for autonomous vehicles based on digital twin technology in parks has been proposed.This method involves creating an environment map model of the park environment and designing a conflict-free path planning algorithm based on this model.An ambient dynamic time window,combined with an improved A^(*)algorithm,is used to plan conflict-free paths for autonomous vehicles.Simulation results demonstrate that this method reduces the average completion time for single-vehicle path planning tasks within the park by 33 seconds.Additionally,there is an average decrease of 16.40%in total task completion time and a 15.45%reduction in conflict adjustment time.The application of this method can improve the efficiency of logistics and distribution within the park,ultimately reducing the economic cost of transportation.展开更多
基金supported by National Key Research and Development Program of China(2022YFD2100201)Key R&D Specialization of Henan Province(231111241100)+1 种基金Projects of higher Education institutions in Henan Province(22A460010)High level Talent Fund Projects of Henan University of Technology(2021BS081).
文摘The emergence of digital twin technology has provided new ideas for vehicle path planning.To address autonomous vehicles’path conflicts in park logistics and enhance the efficiency of logistics and distribution,an improved A^(*)algorithm path planning method for autonomous vehicles based on digital twin technology in parks has been proposed.This method involves creating an environment map model of the park environment and designing a conflict-free path planning algorithm based on this model.An ambient dynamic time window,combined with an improved A^(*)algorithm,is used to plan conflict-free paths for autonomous vehicles.Simulation results demonstrate that this method reduces the average completion time for single-vehicle path planning tasks within the park by 33 seconds.Additionally,there is an average decrease of 16.40%in total task completion time and a 15.45%reduction in conflict adjustment time.The application of this method can improve the efficiency of logistics and distribution within the park,ultimately reducing the economic cost of transportation.
