Title :
Optimal path solution of urban traffic road
Author :
Xu Yongsheng ; Wang Jianling
Author_Institution :
Coll. of Electr. Eng., Northwest Univ. for Nat., Lanzhou, China
Abstract :
Based on the deteriorating traffic conditions, three traffic parameters, path saturation, vehicle speed, road length were selected and computed for data fusion by D-S evidence theory to get the weight of each road, and then with pulse coupled neural network the optimal path was selected according to the calculated weights. Experimental results show that the method can not only shorten the travel time, but also effectively solve the problem of urban road congestion.
Keywords :
inference mechanisms; neural nets; road traffic; traffic engineering computing; uncertainty handling; D-S evidence theory; Dempster-Shafer theory; data fusion; path saturation parameter; pulse coupled neural network; road length parameter; urban road congestion; urban traffic road; vehicle speed parameter; Biological neural networks; Educational institutions; Neurons; Path planning; Real time systems; Roads; Vehicles; evidence theory; optimal path; pulse coupled neural network; traffic parameters;
Conference_Titel :
Natural Computation (ICNC), 2011 Seventh International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-9950-2
DOI :
10.1109/ICNC.2011.6022193
