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Effects of different factors on drivers’ guidance compliance behaviors under road condition information shown on VMS

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  • Zhong, Shiquan
  • Zhou, Lizhen
  • Ma, Shoufeng
  • Jia, Ning

Abstract

It is generally accepted that compliance behavior is affected by many factors. The purpose of this study is to investigate the effects of diverse factors on drivers’ guidance compliance behaviors under road condition information shown on graphic variable message sign (VMS), and based on this to find out a better information release mode. The involved data were obtained from questionnaire survey, and ordinal regression was used to analyze the casual relation between guidance compliance behavior and its influencing factors. Based on an overall analysis of conditions in driver’s route choice, an accurate method was proposed to calculate the compliance rate. The model testing information indicated that ordinal regression model with complementary log–log being the link function was appropriate to quantify the relation between the compliance rate and the factors. The estimation results showed that age, driving years, average annual mileage, monthly income, driving style, occupation, the degree of trust in VMS, the familiarity with road network and the route choice style were significant determinants of guidance compliance behavior. This paper also compared two different guidance modes which were ordinary guidance mode (M1) and predicted guidance mode (M2) through simulation. The average speed fluctuations and average travel time supported that M2 had better effect in improving traffic flow and balancing traffic load and resource. Some detailed suggestions of releasing guidance information were proposed with the explanation by flow-density curve and variation of traffic flows. These findings are the foundation to design and improve guidance systems by assessing guidance effect and modifying guidance algorithm.

Suggested Citation

  • Zhong, Shiquan & Zhou, Lizhen & Ma, Shoufeng & Jia, Ning, 2012. "Effects of different factors on drivers’ guidance compliance behaviors under road condition information shown on VMS," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(9), pages 1490-1505.
    • Handle: RePEc:eee:transa:v:46:y:2012:i:9:p:1490-1505
    DOI: 10.1016/j.tra.2012.05.022
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    Cited by:

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    2. Zhao, Wenjing & Ma, Zhuanglin & Yang, Kui & Huang, Helai & Monsuur, Fredrik & Lee, Jaeyoung, 2020. "Impacts of variable message signs on en-route route choice behavior," Transportation Research Part A: Policy and Practice, Elsevier, vol. 139(C), pages 335-349.
    3. Quy Nguyen-Phuoc, Duy & An Ngoc Nguyen, Nguyen & Nguyen, Minh Hieu & Ngoc Thi Nguyen, Ly & Oviedo-Trespalacios, Oscar, 2022. "Factors influencing road safety compliance among food delivery riders: An extension of the job demands-resources (JD-R) model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 166(C), pages 541-556.
    4. Fernando Romero & Juan Gomez & Thais Rangel & Rafael Jurado-Piña & José Manuel Vassallo, 2020. "The influence of variable message signs on en-route diversion between a toll highway and a free competing alternative," Transportation, Springer, vol. 47(4), pages 1665-1687, August.
    5. Lianzhen Wang & Han Zhang & Lingyun Shi & Qingling He & Huizhi Xu, 2021. "Optimization Model of Regional Traffic Signs for Inducement at Road Works," Sustainability, MDPI, vol. 13(13), pages 1-14, June.
    6. Mariano Gallo & Mario Marinelli, 2020. "Sustainable Mobility: A Review of Possible Actions and Policies," Sustainability, MDPI, vol. 12(18), pages 1-39, September.
    7. Timothy C. Matisziw, 2019. "Maximizing Expected Coverage of Flow and Opportunity for Diversion in Networked Systems," Networks and Spatial Economics, Springer, vol. 19(1), pages 199-218, March.
    8. Wang, Jiawen & You, Lan & Hang, Jiayu & Zhao, Jing, 2023. "Pre-trip reservation enabled route guidance and signal control cooperative method for improving network throughput," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).

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