The Research of the Car Following Behavior Model in VANET

Jian Yao; Deng Pan Yang; Hao You Peng

doi:10.4028/www.scientific.net/AMR.915-916.1428

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 915-916The Research of the Car Following Behavior Model...

The Research of the Car Following Behavior Model in VANET

Abstract:

Based on the characteristics of the car-following model and analyzing from the angle of traffic engineering, this paper classifies car following models into four categories, that is, the stimulus-response model, the safe-distance model, the psychology-physiology model and the artificial intelligence model. In addition, it expounds the modeling ideas, the model structures as well as the advantages and disadvantages of these models. Finally it points out the development tendency and the direction of study method of modeling of car-following model to show direction and provide important reference for establishing car-following models suitable for Chinese traffic characteristics.

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Periodical:

Advanced Materials Research (Volumes 915-916)

Pages:

1428-1432

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.915-916.1428

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Online since:

April 2014

Authors:

Jian Yao, Deng Pan Yang*, Hao You Peng

Keywords:

Car Following Model, Psychology-Physiology Model, Safe-Distance Model, Stimulus-Response Model

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* - Corresponding Author

References

[1] Wang Jun, Microscopic Traffic Simulation　Considering Driving Characteristics[D], QingHua University.

Google Scholar

[2] Chandler R., Herman R. and Montroll. Traffic dynamics: Studies in car following. Operations Research, 1958, 6: 165-184.

DOI: 10.1287/opre.6.2.165

Google Scholar

[3] Gazis D C, Herman R, Rothery R W. Nonlinear follow-the-leader models of traffic flow[J]. Operations Research , 1961, 9(4): 545-567.

DOI: 10.1287/opre.9.4.545

Google Scholar

[4] Kometani E, Sasaki T. Dynamic behavior of traffic with a nonlinear spacing-speed Relationship[C]. Elsevier, Proceedings of the symposium on theory of traffic flow. New york: Elsevier, 1959: 105-119.

Google Scholar

[5] Van Winsum W. the hunman Element in car following models[J]. transportation research part F, 1999, 2(4): 207-211.

DOI: 10.1016/s1369-8478(00)00008-5

Google Scholar

[6] Andersen G J, Sauer C W. optical information for car following: the driving by visual angle(DVA) model[J]. human factors, 2007, 49(5): 878-896.

DOI: 10.1518/001872007x230235

Google Scholar

[7] Kikuchi C, Chakroborty P. car following model based on a fuzzy inference system[J]. transportation research record, 1992(1194): 82-91.

Google Scholar

[8] Dougherty M. A review of neural networks applied to transport[J]. Transportation research part C, 1995, 3(4): 247-260.

Google Scholar

[9] Jia Hongfei, Juan Zhicai, Wang Xiaoyuan. Development of a car-following model based on artificial neural networks[J]. Journal of highway and transportation research and development, 2001, 18(4), 92-94.

Google Scholar

[10] Zhou Lijun, Wang Dianhai, Li Weiqing. Application of artificial neural network and particle Swarm optimization in car-following model[J]. Journal of jili university: Engineering and Technology Edition, 2009, 39(4): 896-899.

Google Scholar