Abstract
Shockwave is one of the most complex recurrent traffic flow phenomena on freeway/expressway, whose characteristics are not fully understood. With the field data, we compared the driving behaviors (headways and reaction times) before and during the propagation of shockwaves. The drivers seemed to change their driving strategies when they “recognized” a shockwave, thus a Fuzzy Logic based Shockwave Recognition Algorithm was proposed, and last we proposed a shockwave elimination method applying the ideas of the Shockwave Recognition Algorithm and Internet of Things.
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Bai H, Wu J, Liu C (2006) Motion and haar-like features based vehicle detection. 12th institute of electrical and electronics engineers multimedia modelling conference, Beijing, China, Jan (2006)
Bao Y, Sun X, Wang Z (2009) Performance evaluation of inter-vehicle communication in a unidirectional dynamic traffic flow with shockwave. In: Proceeding of ultra modern telecommunications and workshops, 2009. ICUMT, pp 1–6
Breton P, Hegyi A, De Schutter B, Hellendoorn H (2002) Shockwave elimination/reduction by optimal coordination of variable speed limits. The IEEE 5th international conference on intelligent transportation systems. pp 225–230
Golob TF, Recker WW, Alvarez VM (2004) Freeway safety as a function of traffic flow. Accident Anal Prevention 36:933–946
Hegyi A, Schutter BD, Hellendoorn J (2005) Optimal coordination of variable speed limits to suppress shock waves. IEEE Trans Intell Transp Syst 6(1):102–112
Homburger WS, Kell JH (1984) Fundamentals of traffic engineering, Traffic stream characteristics 12th edn. p 4
Koppa RJ (2000) Monograph of traffic flow theory, Human factors, Chapter 3. FHWA (2000) pp 4–6
Kuhne R, Michalopoulos P (2000) Continuum flow models. Traffic flow theory, chapter 5 FHWA(2000)
Munoz JC, Daganzo CF (2002) The bottleneck mechanism of a freeway diverge. Transp Res Part A 36:483–505
Ranney TA (1999) Psychological factors that influence car-following and car-following model development. Transp Res Part F Traffic Psychol Behav 2(4):213–219
Smith BL, Ling Q, Venkatanarayana R (2003) Characterization of freeway capacity reduction resulting from traffic accidents. J Transp Eng 123:362–368
Tielert T et al (2010) The impact of traffic-light-to-vehicle communication on fuel consumption and emissions. Proceedings of the conference of internet of things (IoT), Nov 29–Dec 1 2010, Tokyo
Xuan J (2000) Usual traffic accident types. Safety and Health at Work 5:17
Yi J, Lin H, Alvarez L, Horowitz R (2003) Stability of macroscopic traffic flow modelling through wave front expansion. Transp Res B 37:661–679
Yuan Y (2006) Study on the expressway shockwave based on video capture technology. MSc Dissertation, Beijing Jiaotong University
Zhang HM (1999) Analyses of the stability and wave properties of a new continuum traffic theory. Transp Res B 33:399–415
Acknowledgments
This work was supported in part by the Fundamental Research Funds for The Central Universities and The National Natural Science Foundation of China (No. 51108192).
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Huang, L., Wu, J. (2013). A Freeway/Expressway Shockwave Elimination Method Based on IoT. In: Chen, F., Liu, Y., Hua, G. (eds) LTLGB 2012. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34651-4_14
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DOI: https://doi.org/10.1007/978-3-642-34651-4_14
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