Analysis of factors affecting the frequency of crashes on interstate freeways by vehicle type considering multiple weather variables

Aguilar, Cristopher; Russo, Brendan J.; Mohebbi, Amin; Akbariyeh, Simin

doi:10.1080/19439962.2020.1869875

Cited by 7 publications

(2 citation statements)

References 27 publications

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“…One-degree 6-h NCEP FNL (Final; Operational Global Analysis data are on 1degree by 1 degree grids prepared operationally every six hours) data are used to drive the FLEXPART model [4].…”

Section: Model Description and Experiments Designmentioning

confidence: 99%

Risk Assessment of Possible Hazards of El Dabaa Nuclear Power Plant Using FLEXPART Model

ElShafeey

Eid

Saber

et al. 2023

The 3rd International Electronic Conference on Applied Sciences

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“…One-degree 6-h NCEP FNL (Final; Operational Global Analysis data are on 1degree by 1 degree grids prepared operationally every six hours) data are used to drive the FLEXPART model [4].…”

Section: Model Description and Experiments Designmentioning

confidence: 99%

Risk Assessment of Possible Hazards of El Dabaa Nuclear Power Plant Using FLEXPART Model

ElShafeey

Eid

Saber

et al. 2023

The 3rd International Electronic Conference on Applied Sciences

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show abstract

“…Some scholars have also carried out the safety research of expressway in rainy days from the microperspective of the reduction of friction factors on the pavement of expressway in rainy days and the reduction of reaction ability caused by the obstruction of driver's vision. Aguilar et al [1] used the collision data of interstate highways to explore the factors affecting the collision frequency, with the focus on the impact of weather (precipitation, wind, etc.). The negative binomial model with random parameters is used to check the influence of the above variables on the accident frequency.…”

Section: Introductionmentioning

confidence: 99%

Study on rainy Weather Situation of Highway Based on Historical Rainfall Classification

Zhang¹

2023

AJST

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The traffic system consists of people, vehicles and roads, as well as the environment around the road during driving. Weather has always been an important factor that cannot be ignored along with the highway. Good weather will bring good vision conditions and psychological conditions to drivers, while bad weather conditions will directly or indirectly affect the driver's operation or vehicle power performance. As one of the most common weather, many people neglect the harm of rainy days to highway driving safety. When the rain reaches a certain level, it will lead to water on the road surface and reduce the friction coefficient of the road surface. If the driver drives too fast at this time, it will be more prone to deviation. When it reaches extremely bad conditions, it can even destroy the subgrade and pavement, which directly causes immeasurable safety hazards. Based on the rainfall data corresponding to the rainfall events in the traffic environment in the past few years, this paper proposes a research method for the characteristics of rainy days, which uses the fuzzy recognition method to classify the rainfall types of rainy days, to study the development trend of rainy days. After obtaining the development trend function of the historical type of rainy days, we can determine the type of the rainy day event and the specific time period of the type by comparing the closeness of the function of the current observation value with time and the historical function, so as to achieve the purpose of forecasting the development trend of the current weather event. Taking the change rate of rainfall change as the characteristic function, we can further quantify the change range of rainfall, the key indicator representing the intensity of rainy days. This strategy model is applied to expressway speed management, which can provide a good reference for traffic managers to make speed limit decisions, and can clearly decide when to cancel the speed limit strategy or upgrade to the road closure strategy.

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An image-based crash risk prediction model using visual attention mapping and a deep convolutional neural network

Yang²,

Liu

et al. 2021

Journal of Transportation Safety & Security

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Analysis of factors affecting the frequency of crashes on interstate freeways by vehicle type considering multiple weather variables

Cited by 7 publications

References 27 publications

Risk Assessment of Possible Hazards of El Dabaa Nuclear Power Plant Using FLEXPART Model

Risk Assessment of Possible Hazards of El Dabaa Nuclear Power Plant Using FLEXPART Model

Study on rainy Weather Situation of Highway Based on Historical Rainfall Classification

An image-based crash risk prediction model using visual attention mapping and a deep convolutional neural network

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