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Risk Assessment Model and Sensitivity Analysis of Ordinary Arterial Highways Based on RSR–CRITIC–LVSSM–EFAST

Author

Listed:
  • Jianjun Wang

    (College of Transportation Engineering, Chang’an University, Xi’an 710064, China)

  • Chicheng Ma

    (College of Transportation Engineering, Chang’an University, Xi’an 710064, China)

  • Sai Wang

    (College of Transportation Engineering, Chang’an University, Xi’an 710064, China)

  • Xiaojuan Lu

    (College of Transportation Engineering, Chang’an University, Xi’an 710064, China
    Centre for Transportation Research (CTR), Faculty of Engineering, University Malaya, Kuala Lumpur 50603, Malaysia)

  • Dongyi Li

    (College of Transportation Engineering, Chang’an University, Xi’an 710064, China)

Abstract

In this paper, in order to evaluate the traffic safety status of ordinary arterial highways, identify the sources of safety risks, and formulate safety development countermeasures for arterial highways to reduce accident risks, a combination method involving rank-sum ratio (RSR), criteria importance though intercriteria correlation (CRITIC), and least squares support vector machine (LVSSM) is adopted. The traffic safety risk index system and risk assessment model of ordinary arterial highways with two dimensions of risk severity and accident severity are established. Based on the global sensitivity analysis of the extended Fourier amplitude sensitivity test (EFAST), the resulting risk assessment model for ordinary arterial highways is proposed. Combined with the current traffic safety situation of ordinary arterial highways in Weinan City, Shaanxi Province, China, data collection and analyses were carried out from the perspectives of traffic operation status, personnel facilities management, road environment characteristics, and accident occurrence patterns. The results show that the risk level of ordinary arterial highways can be obviously divided into warning areas, control areas, and prompt areas. The proportion of roads through villages and the number of deceleration facilities belong to the highly sensitive indicators of the S107 safety risk, which need to be emphatically investigated. This analysis method based is on the RCLE (RSR-CRITIC-LVSSM-EFAST) risk assessment model and has high operability and adaptability. It can be adaptively divided according to the requirements of risk-level differentiation, and the road risk classification can be displayed more intuitively, which is conducive to formulating targeted improvement measures for arterial highway safety and ensuring the safe and orderly operation of arterial highway traffic.

Suggested Citation

  • Jianjun Wang & Chicheng Ma & Sai Wang & Xiaojuan Lu & Dongyi Li, 2022. "Risk Assessment Model and Sensitivity Analysis of Ordinary Arterial Highways Based on RSR–CRITIC–LVSSM–EFAST," Sustainability, MDPI, vol. 14(23), pages 1-19, December.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:23:p:16096-:d:991022
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    References listed on IDEAS

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    1. Suzana Tajnik & Blaž Luin, 2022. "Impact of Driver, Vehicle, and Environment on Rural Road Crash Rate," Sustainability, MDPI, vol. 14(23), pages 1-18, November.
    2. Xin Yu & Sid Suntrayuth & Jiafu Su, 2020. "A Comprehensive Evaluation Method for Industrial Sewage Treatment Projects Based on the Improved Entropy-TOPSIS," Sustainability, MDPI, vol. 12(17), pages 1-11, August.
    3. Bing Dai & Danli Li & Lei Zhang & Yong Liu & Zhijun Zhang & Shirui Chen, 2022. "Rock Mass Classification Method Based on Entropy Weight–TOPSIS–Grey Correlation Analysis," Sustainability, MDPI, vol. 14(17), pages 1-18, August.
    4. Pires Abdullah & Tibor Sipos, 2022. "Drivers’ Behavior and Traffic Accident Analysis Using Decision Tree Method," Sustainability, MDPI, vol. 14(18), pages 1-11, September.
    5. Yingliu Yang & Lianghai Jin, 2022. "Visualizing Temporal and Spatial Distribution Characteristic of Traffic Accidents in China," Sustainability, MDPI, vol. 14(21), pages 1-16, October.
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