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Reliability Modelling on Drivers’ Decision during the Yellow Phase of a Signal Intersection


Affiliations
1 Department of Civil Engineering, National Institute of Technology, Jamshedpur 832 014, India
2 Department of Civil Engineering, Indian Institute of Technology Roorkee, Roorkee 247 667, India
 

During the yellow phase starts of a traffic signal, the drivers are unable to take quick decisions whether to stop or cross the signal-controlled intersection. This dilemma zone (DZ) can cause a mix-up among drivers during the yellow phase and may lead to accidents. In the present study we use a DZ prediction model for analysis. In this study, approach speed, acceleration/ deceleration of different vehicle categories, distance to stop line, offset of yellow time, and presence or absence of countdown timer are considered as the main factors influencing the model. In order to address several drawbacks associated with traditional regressionbased models, a kriging-based surrogate model has been developed to explore the drivers’ behaviour during the yellow phase.

Keywords

Dilemma Zone, Kriging Model, Traffic Intersection, Yellow Phase Drivers.
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  • MoRTH, Road Accidents in India. Transport Research Wing, Ministry of Road Transport and Highway, Government of India, New Delhi, 2017.
  • Biswas, S. and Ghosh, I., Modeling of the drivers’ decisionmaking behavior during yellow phase. KSCE J. Civ. Eng., 2018, 22, 1–13.
  • Pathivada, B. K. and Perumal, V., Analyzing dilemma driver behavior at signalized intersection under mixed traffic conditions. Transp. Res. Part F, 2019, 60, 111–120.
  • Gazis, D., Herman, R. and Maradudin, A., The problem of the amber signal light in traffic flow. Oper. Res., 1960, 8, 112– 132.
  • Zegeer, C. V., Effectiveness of Green Extension Systems at High Speed Intersections, Lexington, KY, USA, 1977.
  • Parsonson, P. S., Roseveare, R. W. and Thomas, J. M., Small area detection at intersection approaches. J. Transp. Eng., 1974, 44, 8–17.
  • Papaioannou, P., Driver behaviour, dilemma zone and safety effects at urban signalized intersections in Greece. Accid. Anal. Prev., 2007, 39, 147–158.
  • Gates, T. J. and Noyce, D. A., Dilemma zone driver behavior as a function of vehicle type, time of day, and platooning. Transp. Res. Rec. J. Transp. Res. Board, 2010, 2149, Trans, 84–93.
  • Elmitiny, N., Yan, X., Radwan, E., Russo, C. and Nashar, D., Classification analysis of driver’s stop/go decision and red-light running violation. Accid. Anal. Prev., 2010, 42, 101–111.
  • Wei, H., Li, Z., Yi, P. and Duemmel, K. R., Quantifying dynamic factors contributing to dilemma zone at high-speed signalized intersections. Transp. Res. Rec. J. Transp. Res. Board, 2011, 2259, 202–212.
  • Rakha, H., El-Shawarby, I. and Setti, J. R., Characterizing driver behavior on signalized intersection approaches at the onset of a yellow-phase trigger. IEEE Trans. Intell. Transp. Syst., 2007, 2259, 630–640.
  • Chiou, Y. C. and Chang, C. H., Driver responses to green and red vehicular signal countdown displays: safety and efficiency aspects. Accid. Anal. Prev., 2010, 42, 1057–1065.
  • Long, K., Han, L. D., and Yang, Q., Effects of countdown timers on driver behavior after the yellow onset at Chinese intersections. Traffic Inj. Prev., 2011, 12, 538–544.
  • Shen, J. and Wang, W., Effects of flashing green on driver’s stop/go decision at signalized intersection. J. Cent. South Univ., 2015, 22, 771–778.
  • Ma, W., Liu, Y. and Yang, X., Investigating the impacts of green signal countdown devices: empirical approach and case study in China. J. Transp. Eng., 2010, 136, 1049–1055.
  • Sharma, A., Vanajakshi, L., Girish, V., and Harshitha, M. S., Impact of signal timing information on safety and efficiency of signalized intersections. J. Transp. Eng., 2012, 138, 467–478.
  • Köll, H., Bader, M. and Axhausen, K. W., Driver behaviour during flashing green before amber a comparative study. Accid. Anal. Prev., 2004, 36, 273–280.
  • Easa, S. M., Reliability-based design of intergreen interval at traffic signals. J. Transp. Eng., 1993, 119(2), 255–271.
  • Li, K., Dong, S., Sun, J. and Yu, X., Study on the influence of signal countdown device on traffic safety of intersections. In IEEE International Conference on Measuring Technology and Mechatronics Automation, Zhangjiajie, Hunan, China, 2009, pp. 602– 606.
  • Yang, Z., Tian, X., Wang, W., Zhou, X. and Liang, H., Research on driver behavior in yellow interval at signalized intersections. Math. Probl. Eng., 2014, 2014, 1–8.
  • Sharma, A., Bullock, D. and Peeta, S., Estimating dilemma zone hazard function at high speed isolated intersection. Transp. Res. Part C, 2010, 19, 400–412.
  • Biswas, S., Ghosh, I. and Chandra, S., Influence of signal countdown timer on efficiency and safety at signalized intersections. Can. J. Civ. Eng., 2017, 44, 308–318.
  • Hurwitz, D. S., Wang, H., Knodler, M. A., Ni, D. and Moore, D., Fuzzy sets to describe driver behavior in the dilemma zone of high-speed signalized intersections. Transp. Res. Part F, 2012, 15, 132–143.
  • Bonneson, J., Nevers, B., Zegeer, J., Nguyen, T. and Fong, T., Guidelines for quantifying the influence of area type and other factors on saturation flow rate. Texas Department of Transportation, The Texas A&M University System College Station, Texas, USA, 2005.
  • Biswas, S., Chakraborty, S., Ghosh, I. and Chandra, S., Saturation flow model for signalized intersection under mixed traffic condition. Transp. Res. Rec., 2018, 0361198118777407.
  • Mukhopadhyay, T., Chakraborty, S., Dey, S., Adhikari, S. and Chowdhury, R., A critical assessment of kriging model variants for high-fidelity uncertainty quantification in dynamics of composite shells. Arch. Comput. Methods Eng., 2016, 24(3), 1–24.
  • Kaymaz, I., Application of kriging method to structural reliability problems. Struct. Saf., 2005, 27, 133–151.
  • Wang, X. and Kockelman, K. M., Application of the dynamic spatial ordered probit model: patterns of land development change in Austin, Texas. Pap. Reg. Sci., 2009, 88, 345–365.

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  • Reliability Modelling on Drivers’ Decision during the Yellow Phase of a Signal Intersection

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Authors

Sabyasachi Biswas
Department of Civil Engineering, National Institute of Technology, Jamshedpur 832 014, India
Indrajit Ghosh
Department of Civil Engineering, Indian Institute of Technology Roorkee, Roorkee 247 667, India

Abstract


During the yellow phase starts of a traffic signal, the drivers are unable to take quick decisions whether to stop or cross the signal-controlled intersection. This dilemma zone (DZ) can cause a mix-up among drivers during the yellow phase and may lead to accidents. In the present study we use a DZ prediction model for analysis. In this study, approach speed, acceleration/ deceleration of different vehicle categories, distance to stop line, offset of yellow time, and presence or absence of countdown timer are considered as the main factors influencing the model. In order to address several drawbacks associated with traditional regressionbased models, a kriging-based surrogate model has been developed to explore the drivers’ behaviour during the yellow phase.

Keywords


Dilemma Zone, Kriging Model, Traffic Intersection, Yellow Phase Drivers.

References





DOI: https://doi.org/10.18520/cs%2Fv118%2Fi4%2F654-661