Title :
Identifying Traffic Jamming by the Spatiotemporal Correlation Function
Author :
Fan, Yaping ; Xue, Yu
Author_Institution :
Inst. of Phys. Sci. & Eng., Guangxi Univ., Nanning, China
Abstract :
In this paper, we identify the traffic jamming in SDNaSch and First-noise traffic model by the spatiotemporal correlation functions, respectively. The correlation in the first model shows the sharp change rather than a crossover type. It indicates the transition from freely moving to jammed traffic. The correlation function of the second model shows rather complicated oscillating behaviors without the sharply changing. It implies the transition from freely moving cross over to jammed traffic.
Keywords :
correlation methods; road traffic; SDNaSch; first-noise traffic model; spatiotemporal correlation function; traffic jamming identification; Automata; Biological system modeling; Correlation; Jamming; Numerical models; Physics; Spatiotemporal phenomena; cellular automaton; correlation function; traffic flow;
Conference_Titel :
Artificial Intelligence and Computational Intelligence (AICI), 2010 International Conference on
Conference_Location :
Sanya
Print_ISBN :
978-1-4244-8432-4
DOI :
10.1109/AICI.2010.202