Investigating the Role of Traffic Volumes on the Occurrence of the Accidents on the National Roads: a Case Study in Romania

Cadar, Rodica Dorina; Boitor, Melania Rozalia; Dumitrescu, Mara

doi:10.21163/gt_2017.122.03

Cited by 8 publications

(4 citation statements)

References 9 publications

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“…The outcome was identified further in the research to highlight the correlation between traffic volumes and accidents through power regression. The results have proved the significant impact of traffic volumes in crash occurrence up to a definite congestion level [16].…”

Section: Variation Of Crashes With Traffic Volumementioning

confidence: 74%

Factors Affecting Traffic Accidents Density on Selected Multilane Rural Highways

Albayati

Shakoree²,

Ramadan

2021

Civ Eng J

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Estimations of average crash density as a function of traffic elements and characteristics can be used for making good decisions relating to planning, designing, operating, and maintaining roadway networks. This study describes the relationships between total, collision, turnover, and runover accident densities with factors such as hourly traffic flow and average spot speed on multilane rural highways in Iraq. The study is based on data collected from two sources: police stations and traffic surveys. Three highways are selected in Wassit governorate as a case study to cover the studied locations of the accidents. Three highways are selected in Wassit governorate as a case study to cover the studied locations of the accidents. The selection includes Kut–Suwera, Kut–ShekhSaad, and Kut–Hay multilane divided highways located in the south of Iraq. The preliminary presentation of the studied highways was performed using Geographic Information System (GIS) software. Data collection was done to obtain crash numbers and types over five years with their locations, hourly traffic flow, and average spot speed and define roadway segments lengths of crash locations. The cumulative speed distribution curves introduce that the spot speed spectrum for each highway's whole traffic extends over a relatively wide range, indicating a maximum speed of 180 kph and a minimum speed of 30 kph. Multiple linear regression analysis is applied to the data using SPSS software to attain the relationships between the dependent variables and the independent variables to identify elements strongly correlated with crash densities. Four regression models are developed which verify good and strong statistical relationships between crash densities with the studied factors. The results show that traffic volume and driving speed have a significant impact on the crash densities. It means that there is a positive correlation between the single factors and crash occurrence. The higher volumes and the faster the driving speed, the more likely it is to crash. As the hourly traffic flow of automobile grows, the need for safe traffic facilities also extended. Doi: 10.28991/cej-2021-03091719 Full Text: PDF

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Section: Variation Of Crashes With Traffic Volumementioning

confidence: 74%

Factors Affecting Traffic Accidents Density on Selected Multilane Rural Highways

Albayati

Shakoree²,

Ramadan

2021

Civ Eng J

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“…The correlation between accidents and AADT was highlighted by many researchers. Cadar et al [39] proved that accident risk is significantly proportional with traffic volume up to a certain level of congestion. The proportional relationship has also been proved by the HSM [35].…”

Section: Resultsmentioning

confidence: 99%

Multilevel Analysis of Road Accident Frequency: The Impact of the Road Category

Ghadi¹

2023

IJTDI

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This work attempts to develop a universal model for predicting micro-and macro-level accident frequency. The study implies that the number of accidents may vary depending on the type of roadway and the characteristics of its small segments, both at the group and individual levels. A multilevel model has been designed to address the nested link between individual road segments and multiple road classifications. The multilevel analysis allows one to investigate the hierarchical nature of road accident parameters at the micro and macro levels to comprehend the risk of specific road segments within distinct roadway categories. To accomplish this, a case study of fifty-seven roads has been selected, covering five main categories: motorway, expressway, primary arterial, secondary main roads, and minor roads. In addition, each roadway has been subdivided into several flexible-length segments, each of which is identified by its traffic and geometrical characteristics. The outcome confirms that the accident frequency per road segment is more likely to vary between roads with distinct categories. Moreover, road types with low design requirements are more hazardous than well-designed roads, even with lower speed restrictions and traffic numbers.

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“…On the one hand, it could be explained by the increasing number of sudden lane-changing related crashes, accounting for approximately 17% of severe accidents [84]. On the other hand, various pieces of literature have identified a positive correlation between traffic volume and accident frequency [85,86]. In addition, excessive speed driving could be more frequent on roads with a higher speed limit, which also contributes to higher crash frequency.…”

Section: Hierarchy Factormentioning

confidence: 99%

Comparing and Contrasting the Impacts of Macro-Level Factors on Crash Duration and Frequency

Chand

Alsultan

et al. 2022

IJERPH

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Road traffic crashes cause social, economic, physical and emotional losses. They also reduce operating speed and road capacity and increase delays, unreliability, and productivity losses. Previous crash duration research has concentrated on individual crashes, with the contributing elements extracted directly from the incident description and records. As a result, the explanatory variables were more regional, and the effects of broader macro-level factors were not investigated. This is in contrast to crash frequency studies, which normally collect explanatory factors at a macro-level. This study explores the impact of various factors and the consistency of their effects on vehicle crash duration and frequency at a macro-level. Along with the demographic, vehicle utilisation, environmental, and responder variables, street network features such as connectedness, density, and hierarchy were added as covariates. The dataset contains over 95,000 vehicle crash records over 4.5 years in Greater Sydney, Australia. Following a dimension reduction of independent variables, a hazard-based model was estimated for crash duration, and a Negative Binomial model was estimated for frequency. Unobserved heterogeneity was accounted for by latent class models for both duration and frequency. Income, driver experience and exposure are considered to have both positive and negative impacts on duration. Crash duration is shorter in regions with a dense road network, but crash frequency is higher. Highly connected networks, on the other hand, are associated with longer length but lower frequency.

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Investigating the Role of Traffic Volumes on the Occurrence of the Accidents on the National Roads: a Case Study in Romania

Cited by 8 publications

References 9 publications

Factors Affecting Traffic Accidents Density on Selected Multilane Rural Highways

Factors Affecting Traffic Accidents Density on Selected Multilane Rural Highways

Multilevel Analysis of Road Accident Frequency: The Impact of the Road Category

Comparing and Contrasting the Impacts of Macro-Level Factors on Crash Duration and Frequency

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