DocumentCode :
2347772
Title :
Empirical Slow-to-Start Behavior from NGSIM Trajectory Data
Author :
Li, Xingang ; Jia, Bin ; Gao, Ziyou
Author_Institution :
MOE Key Lab. for Urban Transp. Complex Syst. Theor. & Technol., Beijing Jiaotong Univ., Beijing, China
fYear :
2011
fDate :
15-19 April 2011
Firstpage :
1069
Lastpage :
1073
Abstract :
The slow-to-start rule is usually adopted in cellular automaton traffic flow model. And it is deemed as the mechanism for metastable states and hysteresis effect. In this paper, we explore the slow-to-start behavior by analyzing the vehicle trajectory data provided by the Next Generation Simulation program. Then the slow-to-start rule is verified in several cellular automaton traffic flow models. The results show that the acceleration rate will increases as the speed increasing. The starting up gap does not change while the acceleration rate increases as the stop time becomes larger. The slow-to start behavior really exist, and the slow-to-start rule in VDR model is realistic. But the slow-to-start rule in MCD model is not consistent with empirical results.
Keywords :
cellular automata; road traffic; MCD model; NGSIM trajectory data; VDR model; cellular automaton traffic flow model; empirical slow-to-start behavior; hysteresis effect; metastable states; next generation simulation program; vehicle trajectory data; Acceleration; Data models; Mathematical model; Smoothing methods; Trajectory; Vehicles; Slow-to-start rule; cellular automaton; traffic flow;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Sciences and Optimization (CSO), 2011 Fourth International Joint Conference on
Conference_Location :
Yunnan
Print_ISBN :
978-1-4244-9712-6
Electronic_ISBN :
978-0-7695-4335-2
Type :
conf
DOI :
10.1109/CSO.2011.127
Filename :
5957840
Link To Document :
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