Evaluating the safety risk of roadside features for rural two-lane roads using reliability analysis

Jalayer, Mohammad; Zhou, Huaguo

doi:10.1016/j.aap.2016.04.021

Cited by 30 publications

(23 citation statements)

References 33 publications

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“…de Oña et al combined Bayesian statistics with latent class cluster analysis to identify the primary factors impacting road traffic, reveal underlying traffic safety problems and analyze the safety of rural roads [22]. Jalayer and Zhou adopted a reliability analysis method to analyze the influence of roadside clearance width, side slope, and other roadside features on the severity of traffic accidents caused by lane deviation; a reliability index was used to measure road safety grade [23].…”

Section: Statistical Estimation Methodsmentioning

confidence: 99%

A Cask Evaluation Model to Assess Safety in Chinese Rural Roads

et al. 2018

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Suburban roads are an important part of China’s road network and essential infrastructure for rural development. Poorly designed road curves and scarcity of traffic signs have caused an excessively high traffic accident rate in plain topographical areas. In this study, an approach to evaluate and improve rural road traffic safety is introduced. Based on fuzzy and cask theory and weighted analysis, a cask evaluation model is built. It provides a quantitative instant method for analyzing road safety in the absence of traffic accident information or rigorous road space data, by identifying dangerous sections and key impact factors, and ultimately help to put forward traffic safety improvements. Based on the application to a specific section of Xiaodang Central Road in the Fengxian District of Shanghai, the result shows that the pavement conditions of cement-hardened dual-lane rural roads was good, but traffic safety was poor. Missing traffic signs, unreasonable road alignment, and poor roadside conditions were the main problems. Finally, improvements of the short-stave subsystem were proposed: the location of guide signs and roadside conditions should be improved, and the number and efficacy of the rural road traffic signs need to be increased, and markings should be and receive regular maintenance.

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Section: Statistical Estimation Methodsmentioning

confidence: 99%

A Cask Evaluation Model to Assess Safety in Chinese Rural Roads

et al. 2018

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“…Dangerous roadside environment e roadside safety distance is lower than the standard requirement, which can be seen in [2]. ere are dangerous objects within the safe distance of the roadside [2]. ere are unreasonable installations of roadside safety facilities [2].…”

Section: Risk Factor Detailed Informationmentioning

confidence: 99%

“…ere are dangerous objects within the safe distance of the roadside [2]. ere are unreasonable installations of roadside safety facilities [2].…”

Section: Risk Factor Detailed Informationmentioning

confidence: 99%

“…Due to the limitation of terrain conditions in the mountainous areas, "sharp turns", "continuous long downhill", and "multiple tunnels" exist commonly and the de nitions of them can be seen in Table 1. "Dangerous roadside environment" refers to the phenomena including the roadside safe distance being lower than the required distance, or dangerous objects existing within the safe distance, or unreasonable installation of roadside safety facilities [2]. "Dangerous roadside environment" is common on mountainous highways, and it is easy to result in fatal crashes like falling o a cli or falling into a river [3].…”

Section: Introductionmentioning

confidence: 99%

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Crash-Prone Section Identification for Mountainous Highways Considering Multi-Risk Factors Coupling Effect

Xue

Wen

2019

Journal of Advanced Transportation

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In order to identify crash-prone sections of the highways in mountainous areas professionally and exclusively, the common phenomena of “sharp turns”, “continuous long downhill”, “multiple tunnels”, “dangerous roadside environment”, and complex and changeable meteorological environment, which all imply risk factors of the mountainous highways, are comprehensively considered. Utilizing the improved classical coupling model, the coupling mechanism of the risk factors is revealed, and the coupling model of the traffic risk factors is constructed, by which the coupling degrees of multi-risk factors couplings are calculated respectively. Based on the coupling degrees of the above factors, the concept of vehicle operation risk index (VORI) of the mountainous highway is introduced and its numerical value is quantified as the basis for identifying the crash-prone sections. The 21 km of Songming to Huize section of the Songdai Highway in the Yunnan Province of China is selected as an example, and the good applicability of the identification model is verified.

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“…Some researchers have investigated the influence of different geometric and traffic variables [14,18] and roadside variables [13,[19][20] but did not present the speed as an effective variable on safety. They applied several variables, including number of lanes, lane width, shoulder width, median width, median type, radius, sight distance, pavement conditions, roadside hazards, road markings, pedestrian distribution, segment length, traffic flow, posted speed limit, clear zone width, side slope, pedestrian volume, guardrail length, fence length, and land use.…”

Section: Literature Reviewmentioning

confidence: 99%

Evaluating the Relationship between Operating Speed and Collision Frequency of Rural Multilane Highways Based on Geometric and Roadside Features

Mehrabani

Mirbaha

2018

CivileJournal

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Speed is one of the main functional factors that affect road safety in terms of both collision occurrence and collision severity. Previous studies have shown that several roadside and geometric features affect road safety and operating speed. This paper aims to evaluate the effects of roadside and geometric features on operating speed and collision frequency, simultaneously. For this purpose, the operating speed data of 103 segments along with their accident data and roadside and geometric characteristics were collected. Structural equation modelling (SEM) with latent variables was employed to model operating speed and collision frequency, simultaneously. Two latent variables including “geometric effect” and “roadside effect” were defined in SEM. The first latent variable is the combination of the natural logarithm of the segment length, longitudinal slope, the presence of a 2-meter paved shoulder, and curvature of the segment. The indicators of the second latent variable are the number of accesses and the presence of residential land use. The results show that the latent variable “roadside effect” increases collision frequency by a standard regression weight of 3.455; however, it reduces operating speed by a standard regression weight of –0.385. Also, the latent variable “geometric effect” causes an opposite effect on collision frequency and operating speed by the standard regression weight of –5.313 and 0.730, respectively. Besides, lower operating speed causes a reduction in the collision frequency by the standard regression weight of 7.734. The results of this study can be useful for designers and road safety agencies to improve road safety.

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Evaluating the safety risk of roadside features for rural two-lane roads using reliability analysis

Cited by 30 publications

References 33 publications

A Cask Evaluation Model to Assess Safety in Chinese Rural Roads

A Cask Evaluation Model to Assess Safety in Chinese Rural Roads

Crash-Prone Section Identification for Mountainous Highways Considering Multi-Risk Factors Coupling Effect

Evaluating the Relationship between Operating Speed and Collision Frequency of Rural Multilane Highways Based on Geometric and Roadside Features

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