Transferability of safety performance functions and hotspot identification for freeways of the United States and China

Feng, Mingjie; Wang, Xuesong; Lee, Jae Young; Abdel-Aty, Mohamed; Mao, Suyi

doi:10.1016/j.aap.2020.105493

Cited by 17 publications

(6 citation statements)

References 34 publications

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“…A "hotspot" (also known as a black spot) is the category assigned to a road location that has recorded high numbers of accidents compared to other locations [17][18][19][20][21][22]. Generally, accident-prone location(s) will be identified during the initial phase of the road safety management process.…”

Section: Introductionmentioning

confidence: 99%

“…Generally, accident-prone location(s) will be identified during the initial phase of the road safety management process. The identification of road accident hotspots is a systematic method for identifying road segments with a high accident risk that exceeds the standard limit of road safety [21,22]. The GIS software is a large geographic database and is a useful tool to determine hotspots.…”

Section: Introductionmentioning

confidence: 99%

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Road Accident Hotspots on Jordan’s Highway Based on Geometric Designs Using Structural Equation Modeling

et al. 2023

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One of the primary objectives of transportation engineering is to increase the safety of road infrastructure. This study seeks to determine the relationship between geometric design parameters in relation to road accident criteria based on accident hotspots on Jordan’s Desert Highway. The road accident data (from 2016 to 2019) were collected from the Jordan Traffic Department. The spatial pattern of hotspots was identified using a GIS tool named Getis-Ord Gi* based on the severity index of road accidents. A topographic survey was conducted to investigate the road alignment and intersections at hotspot locations. The study utilized the Structural Equation Modeling (SEM) technique via SmartPLS to highlight the correlation between geometric designs in relation to road accidents. The hotspot analysis (Gits-Ord Gi) discovered 80 road accident hotspots along the highway. The study found that horizontal alignment and road intersections significantly impact road accidents in hotspot locations. Furthermore, vertical alignment has no effect on road accidents in hotspot areas. The study enhanced the comprehension of the factors associated with road geometrics and intersections that affect the occurrence of road accidents.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Road Accident Hotspots on Jordan’s Highway Based on Geometric Designs Using Structural Equation Modeling

et al. 2023

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“…Various studies have been conducted to develop SPFs at intersections (1,(19)(20)(21)(22)(23). Crash data have an overdispersion problem where the variance is greater than the average.…”

Section: Network Screeningmentioning

confidence: 99%

Development of New Performance Measures Based on Data Mining Weights for Hotspot Identification

Son

Park

Lee

et al. 2022

Transportation Research Record

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In this study, new performance measures are proposed for hotspot identification in urban intersections. These measures reflect severity factor weights, which are determined based on data mining. To estimate the severity factor weights of crashes at urban intersections, the study utilizes tree-based random forest (RF) and extreme gradient boosting (XGB) methods. The importance of variables in the severity classification model is standardized and utilized for calculating the score of each crash, which is aggregated into intersections. The aggregated score is used as a dependent variable for the safety performance functions (SPFs) in the network screening process. To illustrate the under-dispersed severity score aggregation data, SPFs that follow the COM-Poisson distribution as well as the negative binomial (NB) are developed. Independent variables in SPFs set up intersection geometry elements that can be collected from online GIS services. Four additional performance measures are proposed, each reflecting a severity weight. Data about a total of 42,513 intersection crashes from 2017 to 2018 in South Korea were collected for crash injury severity analysis. Hotspot identification was performed on 81 intersections, and three consistency tests were conducted to validate the four measures. Tests show that the RF-based weighted [Formula: see text] and [Formula: see text] have the best consistency. Since the severity factor weights of each crash are reflected, intersections vulnerable to dangerous crashes can be analyzed in more detail. Using this method, it is expected that effective safety improvement project plans can be established with the input of safety managers in the future.

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“…Considering the different characteristics of traffic flow in different regions, the research conclusion according to US collision data cannot be directly transferred to other countries. For example, Feng et al [9] uses the crash data of Shanghai, China, and Florida, USA, to establish safety performance functions (SPFs), respectively, and investigate the transferability between the two SPFs. It was found that the transferability of SPFs between Florida and the Chinese cities turned out to be unsatisfactory and this phenomenon was contributed by the difference in traffic flow.…”

Section: Introductionmentioning

confidence: 99%

Exploring Driver Injury Severity in Single-Vehicle Crashes under Foggy Weather and Clear Weather

Fan

Cai

Liu

et al. 2021

Journal of Advanced Transportation

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The purpose of this study is to investigate and compare the significant influencing factors of driver injury severity in single-vehicle (SV) crashes under foggy and clear weather conditions. Based on data for SV crashes in Shandong Province, China, the mixed logit model (MLM) was employed to interpret driver injury severity for SV crashes in clear and foggy weather. The results showed that there are significant differences in the influencing factors of the severity of SV crashes in foggy and clear weather. Specifically, 15 factors are significantly associated with the severity of SV crashes in clear weather, and 18 factors are significantly associated with the severity of SV crashes in foggy weather. In addition, young drivers (age < 30), non-dry road surfaces, and signal control significantly influence the severity of foggy weather crashes but not clear weather crashes. Self-employment and weekends have significant effects on the severity of crashes only in clear weather. Interestingly, drivers whose occupation is farming showed opposite trends in the effect of crash severity in foggy and clear weather. Based on the findings of this research, some potential countermeasures can be adopted to reduce crash severity in foggy and clear weather.

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Transferability of safety performance functions and hotspot identification for freeways of the United States and China

Cited by 17 publications

References 34 publications

Road Accident Hotspots on Jordan’s Highway Based on Geometric Designs Using Structural Equation Modeling

Road Accident Hotspots on Jordan’s Highway Based on Geometric Designs Using Structural Equation Modeling

Development of New Performance Measures Based on Data Mining Weights for Hotspot Identification

Exploring Driver Injury Severity in Single-Vehicle Crashes under Foggy Weather and Clear Weather

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