Title :
Study on UGV path selection method based on GIS database
Author :
Wang Meiling;Wang Xinping
Author_Institution :
School of Automation, Beijing Institute of Technology, Beijing, China
Abstract :
As an important research field of ITS, UGV will improve the efficiency of the urban traffic system by its high intelligence. GIS, which has strong capabilities of storage and management for geographic information, will play a key role in path planning for UGV. Firstly, construct a GIS database aiming at the needs for perceiving the urban traffic environment and storing traffic information related to the perception and decision-making of UGV; secondly, establish a prediction model of travel time based on RBF neural network to predict the travel time of each road section, then use the actual travel time achieved by real car experiments to constantly update the predictive travel time; thirdly, a path selection method based on probability is proposed according to people´s demands of daily trips; lastly, the GIS database in the simulation will provide several alternative paths, with which the probabilities of arriving on time and arriving at the optimal time can be calculated for each path, helping UGV select path in accordance with the actual driving tasks. Simulations shown that the proposed path selection method based on GIS database can provide more efficient paths for UGV driving, guiding UGV to complete the driving tasks successfully.
Keywords :
"Roads","Databases","Geographic information systems","Predictive models","Biological neural networks","Path planning"
Conference_Titel :
Connected Vehicles and Expo (ICCVE), 2014 International Conference on
DOI :
10.1109/ICCVE.2014.7297642