Abstract
For now, traffic safety and traffic congestion are two difficult problems which freeway traffic management must deal with. And there are so many factors influencing highway traffic, in which some factors are characterized as dynamic, such as traffic stream characteristics, weather conditions, road environmental illumination, and so on. Considering weather conditions, road conditions, and traffic conditions, an evaluation index system is established. And based on the index system, real-time traffic safety level and traffic congestion level are evaluated using fuzzy theory and neural network. Then the highway mainline fuzzy logic control method is proposed based on dynamic traffic evaluation results, which will improve the safety of freeway traffic and alleviate the traffic congestion of freeway through balancing traffic flow on freeway.
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Carlson, R.C., Ioannis, P.: Optimal mainstream traffic flow control of large-scale motorway networks. Transp. Res. Part C: Emerg. Technol. 18(6), 193–212 (2010).
Carlson, R.C., Ioannis, P.: Local feedback-based mainstream traffic flow control on motorways using variable speed limits. IEEE Trans. Intell. Transp. Syst. 12(4), 1261–1276 (2011).
Kuang, Y., Qu, X., Wang, S.: A tree-structured crash surrogate measure for freeways. Accid. Anal. Prev. 77, 137–148 (2015).
Andreas, H., Bart, D.S., Hans, H.: Model predictive control for optimal coordination of ramp metering and variable speed limits. Transp. Res. Part C 13(3), 39–41 (2004)
Rongjie, Y., Mohamed, A.: An optimal variable speed limits system to ameliorate traffic safety risk. Transp. Res. Part C 46, 235–246 (2014)
Tang, H., Chang, Z.L.: Optimization of mainline traffic via an adaptive co-ordinated ramp-metering control model with dynamic OD estimation. Transp. Res. Part C 10(2), 99–120 (2002)
Zhibin, L., Pan, L., Chengcheng, X., Wei, W.: Optimal mainline variable speed limit control to improve safety on large-scale freeway segments. Computer-Aided Civil and Infrastructure Engineering 31, 366–380 (2016)
Lu, K., Xu, J.: Design methods for main line speed control of expressway traffic flow density. Freeway 4, 16–18 (2008)
Liang, X., Liu, Z., Mao, Z.: Fuzzy ramp control in freeway and simulation research. J. Syst. Simul. 17(2), 444–447 (2005).
Kotsialos, A., Papageorgiou, M.: A hierarchical ramp metering control scheme for freeway networks. In: American Control Conference, pp. 2257–2262. Portland, OR, USA (2005)
Shih, C.L., Hsun, J.C.: Chaos and control of discrete dynamic traffic model. J. Frankl. Inst. (S0016–0032) 342(7) 839–851 (2005).
Wang, Y.: Study of traffic congestion’s simulation based on cellular automaton model. J. Syst. Simul. (S1004-731X) 22(9), 2149- 2154 (2010).
Yang, Q., Ma, M., Liang, S., Li, Z.: Stair-like control strategies of variable speed limit for bottleneck regions on freeway. J. Southwest Jiaotong Univ. 50(2), 354–360 (2015)
Bhourin, Haj, S., Kaupplaj.: Isolated versus coordinated ramp metering: field evaluation results of travel time reliability and traffic impact. Transp. Res. Part C: Emerg. Technol. 28, 155–167 (2013).
Zhou, M., Qu, X., Li, X.: A recurrent neural network based microscopic car following model to predict traffic oscillation. Transp. Res. Part C 84, 245–264 (2017)
Acknowledgements
The study is supported by the National Natural Science Foundation of China (NO. 51578247 & 71701070), the Natural Science Foundation of Guangdong Province (NO. 2016A030310427), and the Science and Technology Project of Guangzhou City (NO. 201804010466).
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Zhao, S., Liu, W., Wen, H., Qi, W. (2019). Research on Freeway Mainline Fuzzy Logic Control Based on Dynamic Traffic Evaluation. In: Qu, X., Zhen, L., Howlett, R., Jain, L. (eds) Smart Transportation Systems 2019. Smart Innovation, Systems and Technologies, vol 149. Springer, Singapore. https://doi.org/10.1007/978-981-13-8683-1_9
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DOI: https://doi.org/10.1007/978-981-13-8683-1_9
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