Evaluation of Level Crossing Accident Factors by Logistic Regression Method: A Case Study

Yıldız, Kürşat; Ateş, Ahmet Derya

doi:10.1007/s40996-020-00367-z

Cited by 3 publications

(3 citation statements)

References 7 publications

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“…The objective was to define and delete outlier's accident cases in addition to refining the accident causes registered in the formal accident reports. The verified LR model was used to rank the accident causes based on the Wald statistic [19]. The AHP approach was used to verify the results of the LR model in a more comprehensive systematic approach.…”

Section: Methodsmentioning

confidence: 99%

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Assessing the Risk of University-Student Driving to enhance Safe and Sustainable Traffic Management: A Logistic Regression and Analytic Hierarchy Approach

et al. 2022

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Road accidents have become more common these days and it is pathetic when the accidents happen due to ignorance. The research objective is focused on university students, creating awareness about road safety and improving a sustainable traffic management scenario in the Kingdom of Saudi Arabia. An analytical hierarchy process and a logistic regression model were used to determine the risk priorities ranking of severity factors based on the comparisons of different driver behaviour factors. A cross-sectional survey was conducted among 3200 university students in Saudi Arabia to evaluate the risk associated with accident factors. The main factors taken for risk analysis were Stability during driving, not adhering to rules, committing human errors, Insufficient Visibility, Facing Vehicles Issues. The model estimation analysis revealed the severity, which was based on the student's behavioural factors as a driver which contributed to the high fatality. It is further proposed to teach an interdisciplinary course on Traffic Management to various university students. The awareness towards traffic sense and safety rules would bring down the accidents rates and help the government to maintain smooth traffic density.

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Section: Methodsmentioning

confidence: 99%

“…It is a very easy and convenient method, as it links with output and input variables. Moreover, it identifies a positive or negative direction and whether the collision was a severe fatal one or non-fatal with selected variables in confidence level [19]. The mathematical expressions are demonstrated below.…”

Section: Methodsmentioning

confidence: 99%

Assessing the Risk of University-Student Driving to enhance Safe and Sustainable Traffic Management: A Logistic Regression and Analytic Hierarchy Approach

et al. 2022

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“…Many authors (SZE, WONG, 2007;TAO et al, 2015;AGARWAL, KACHROO, REGENTOVA, 2016;YILDIZ, ATEŞ, 2020) applied the model to investigate the factors associated with traffic accidents in the built environment. While these studies significantly contributed to identifying critical elements in road safety, they rarely focused on the spatial component through the integration of the regression model with geospatial tools.…”

Section: Estimación De La Susceptibilidad De Los Peatones a Accidentes De Tráfico En Curitiba Brasilmentioning

confidence: 99%

Estimating Pedestrian Susceptibility to Traffic Accidents in Curitiba, Brazil

Moroz

Gadda

Bastos

2021

BARU

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Even though pedestrians represented 40% of all urban displacements in Brazil in 2017, they are still highly vulnerable to traffic accidents, with a mortality rate of 2.89 per 100 thousand inhabitants in 2018. The literature suggests a relationship between the occurrence of traffic accidents and demographic, socioeconomic, and urban structure variables. In this study, this relationship was investigated through a data-driven statistical model (logistic regression) combined with GIS spatial analysis, applied to estimate the pedestrian susceptibility to traffic accidents in the City of Curitiba, in Southern Brazil. By adopting broadly available spatial information, the proposed methods were robust in estimating the events, presenting an area under the ROC curve of 0.82 in the cross-validation. Additionally, the results highlighted a strong and statistically significant correlation between the pedestrian crashes and the analyzed variables of road system hierarchy, presence of BRT routes, land-use, population density and per capita income.

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Modeling Highway-Rail Grade Crossing (HRGC) Crash Frequency

Soltaninejad,

Salum,

Kodi

et al. 2024

Preprint

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Substantial research in highway safety has focused on roadway crash frequency analysis; however, only a few studies have focused on the safety at highway-rail grade crossings (HRGCs). This study aimed to determine factors affecting the frequency of crashes at HRGCs. The statistical modeling and analysis were based on five years of HRGC crashes (2017–2021) that occurred on state-maintained HRGCs in Florida. Police reports of 2,092 crashes flagged as "railroad crossing" were downloaded and reviewed. The manual review of the police reports indicated that only 1,690 reports were classified as HRGC crashes. The Bayesian negative binomial model was applied to identify various contributing factors associated with the frequency of HRGC crashes. The following variables significantly increase the number of HRGC crashes: high-speed facilities, number of tracks, facilities with 4 to 5 lanes, presence of railroad crossing gates, proximity to a traffic control signal, and high traffic volume. To mitigate these risks, engineering treatments such as improved signing and pavement markings and implementation of Intelligent Transportation Systems (ITS) technologies are recommended.

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Evaluation of Level Crossing Accident Factors by Logistic Regression Method: A Case Study

Cited by 3 publications

References 7 publications

Assessing the Risk of University-Student Driving to enhance Safe and Sustainable Traffic Management: A Logistic Regression and Analytic Hierarchy Approach

Assessing the Risk of University-Student Driving to enhance Safe and Sustainable Traffic Management: A Logistic Regression and Analytic Hierarchy Approach

Estimating Pedestrian Susceptibility to Traffic Accidents in Curitiba, Brazil

Modeling Highway-Rail Grade Crossing (HRGC) Crash Frequency

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