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Research on Freeway Mainline Fuzzy Logic Control Based on Dynamic Traffic Evaluation

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Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 149))

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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References

  1. 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).

    Article  Google Scholar 

  2. 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).

    Article  Google Scholar 

  3. Kuang, Y., Qu, X., Wang, S.: A tree-structured crash surrogate measure for freeways. Accid. Anal. Prev. 77, 137–148 (2015).

    Article  Google Scholar 

  4. 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)

    Google Scholar 

  5. Rongjie, Y., Mohamed, A.: An optimal variable speed limits system to ameliorate traffic safety risk. Transp. Res. Part C 46, 235–246 (2014)

    Article  Google Scholar 

  6. 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)

    Article  Google Scholar 

  7. 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)

    Article  Google Scholar 

  8. Lu, K., Xu, J.: Design methods for main line speed control of expressway traffic flow density. Freeway 4, 16–18 (2008)

    Google Scholar 

  9. Liang, X., Liu, Z., Mao, Z.: Fuzzy ramp control in freeway and simulation research. J. Syst. Simul. 17(2), 444–447 (2005).

    Google Scholar 

  10. Kotsialos, A., Papageorgiou, M.: A hierarchical ramp metering control scheme for freeway networks. In: American Control Conference, pp. 2257–2262. Portland, OR, USA (2005)

    Google Scholar 

  11. Shih, C.L., Hsun, J.C.: Chaos and control of discrete dynamic traffic model. J. Frankl. Inst. (S0016–0032) 342(7) 839–851 (2005).

    Google Scholar 

  12. Wang, Y.: Study of traffic congestion’s simulation based on cellular automaton model. J. Syst. Simul. (S1004-731X) 22(9), 2149- 2154 (2010).

    Google Scholar 

  13. 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)

    Google Scholar 

  14. 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).

    Article  Google Scholar 

  15. 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)

    Article  Google Scholar 

Download references

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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Correspondence to Weiwei Qi .

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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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