Study on risk assessment of expressway nighttime maintenance construction: A Dynamic Bayesian Network model

Zhen Tian,Yanyang Shen,Jinhua Fan,Qianqian Chen,Huaichen Hu,M.S Nazir,H.A Aziz

doi:10.1051/e3sconf/202125702047

Zhen Tian, Yanyang Shen + Show 5 more

Open Access

https://doi.org/10.1051/e3sconf/202125702047

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Abstract

There are many risk factors and large uncertainties in expressway nighttime maintenance construction(ENMC), and the state of risk factors will change dynamically with time. In this study, a Dynamic Bayesian Network (DBN) model was proposed to investigate the dynamic characteristics of the time-varying probability of traffic accidents during expressway maintenance at night. Combined with Leaky Noisy-or gate extended model, the calculation method of conditional probability is determined . By setting evidences for DBN reasoning, the time series change curve of the probability of traffic accidents and other risk factors are obtained. The results show that DBN can be applied to risk assessment of ENMC.

Highlights

Accident statistical analysis and research showed that the accident rate and fatality rate of nighttime maintenance construction operations are much higher than that of day maintenance construction[1]
3.1 Defining the risk factors used in the ENMC model According to literature review, our study is to investigate the ENMC workplace, including conduct lots of surveys with relevant personnel
We found that the time of ENMC is a total of 9 hours usually from 9:00 PM to 6:00 AM the day, so the DBN constructed in this study can establish an hourly time point to the event node, A total of 10 time steps to represent the changing events evolution mechanism (The temporal plate division can be adjusted according to the actual situation of each place)

Summary

Introduction

Accident statistical analysis and research showed that the accident rate and fatality rate of nighttime maintenance construction operations are much higher than that of day maintenance construction[1]. In order to analyze the risk of expressway construction work area, Kairan Zhang et al [2], Yingfeng Li et al.[3], Xianghai Meng et al.[4], Sze and Soong[5], and Higa et al.[6] identified operationrelated risk factors. Biao Wu et al.[8] conducted risk assessment on risk factors in the work area; Jikun Liu et al.[9]proposed a LECT evaluation method that can identify key risk factors in the operation process; Rahman et al.[10] studied the effect of dynamic information signs on controlling the speed of the driver. The current researchers mainly focus on the identification and evaluation of risk factors in the daytime maintenance of expressways or the construction operations of new construction, renovation and expansion. It is a very important way to quantitatively analyze the risks of ENMC through the DBN method

Dynamic Bayesian Network

Methodology

Scenario analysis and evaluate of DBN model

D2 D3 D4 D5 D6 D7

Findings

Conclusions