Investigation of drivers’ behavior towards speeds using crash data and self-reported questionnaire

Hassan, Hany M.; Shawky, Mohamed; Kishta, Mohammad; Garib, Atef M.; Al-Harthei, Hussain

doi:10.1016/j.aap.2016.10.027

Cited by 38 publications

(18 citation statements)

References 14 publications

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“…7a, an increase in the number of people with technical and further education in the drivers' residency neighborhoods would increase the risk of a serious injury crash instead of a minor injury crash. This result was consistent with previous studies that found that drivers with higher levels of education accepted more risk in driving and were more involved in traffic crashes [58,59]. Therefore, driver safety education, pedestrian awareness campaigns and other behavioral change programs should be targeted at neighborhoods with higher proportions of people with technical education.…”

Section: Drivers' Residency Neighborhood Characteristicssupporting

confidence: 92%

Neighborhood Influences on Vehicle-Pedestrian Crash Severity

et al. 2017

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Socioeconomic factors are known to be contributing factors for vehicle-pedestrian crashes. Although several studies have examined the socioeconomic factors related to the location of the crashes, limited studies have considered the socioeconomic factors of the neighborhood where the road users live in vehicle-pedestrian crash modelling. This research aims to identify the socioeconomic factors related to both the neighborhoods where the road users live and where crashes occur that have an influence on vehicle-pedestrian crash severity. Data on vehicle-pedestrian crashes that occurred at mid-blocks in Melbourne, Australia, was analyzed. Neighborhood factors associated with road users' residents and location of crash were investigated using boosted regression tree (BRT). Furthermore, partial dependence plots were applied to illustrate the interactions between these factors. We found that socioeconomic factors accounted for 60% of the 20 top contributing factors to vehicle-pedestrian crashes. This research reveals that socioeconomic factors of the neighborhoods where the road users live and where the crashes occur are important in determining the severity of the crashes, with the former having a greater influence. Hence, road safety countermeasures, especially those focussing on the road users, should be targeted at these high-risk neighborhoods.

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Section: Drivers' Residency Neighborhood Characteristicssupporting

confidence: 92%

Neighborhood Influences on Vehicle-Pedestrian Crash Severity

et al. 2017

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“…In a study done using the data obtained from Iran's traffic police, overspeed, fatigue, and drowsiness were the factors leading to the seriousness of drivers' errors in accidents (7). Overspeed is one of the negative behaviours that affect the health of drivers and other people (20). Overspeed, due to the possibility of a front-end accident with other vehicles and also deviation from the main lane have the highest possibility of fatal accidents (20).…”

Section: Discussionmentioning

confidence: 99%

“…Overspeed is one of the negative behaviours that affect the health of drivers and other people (20). Overspeed, due to the possibility of a front-end accident with other vehicles and also deviation from the main lane have the highest possibility of fatal accidents (20). Overspeed exerts different effects on the occurrence of road accidents, based on road features, such as the width of the road (14).…”

Section: Discussionmentioning

confidence: 99%

Factors contributing to fatal road traffic accidents in the South of Kerman during the period from 2013 to 2017, Iran

Nasiri

Nazari

Kamali

et al. 2019

JOHE

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Article InfoBackground: Several factors influence the growth in the number of road traffic accidents and the resulting death rate. Road accident scenarios can be considered in different seasons and time intervals. In the present study, the role of factors effective in the growth of the number of accidents was explored in the south of Kerman during the period from 2013 to 2017. Materials and Methods: In this cross-sectional study, the data were collected from the Traffic Police Unit's database in the south of Kerman during the period from 2013 to 2017. The data obtained included the time of the day, roads of accidents, numbers of fatal accidents, and years of occurrence. The data were analysed using the logistic regression. Results: After examining the role of various factors in fatal road traffic accidents, it became clear that the chances of death were higher in road accidents on main roads (OR = 1.30; 95%CI=1.02-1.70; p=0.037) than on rural roads. In terms of the seasons of occurrence, death rates were higher in autumn (OR= 1.30; 95%CI=1.02-1.80; p=0.027) than in winter. From among the effective factors, overspeed (OR= 1.90; 95%CI=1.40-2.50; p<0.001) and deviation to the left lane (OR = 2.20; 95% CI = 1.70-2.90; p-value<0.001) were more likely to lead to death than drowsiness and inattention to the front. Conclusion: The results showed that overspeed, deviation to the left lane, as well as accidents on main roads, and in autumn resulted in an increase in the mortality rate. The severity of road accidents would probably decrease in the region by paying more attention to main roads especially in autumn and training drivers.

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“…The results of this model showed that desired speed distribution had the most significant effect on lane change frequency due to high coefficient values (positive). A previous study [69] found that speed distribution had a vital role in road safety. Subsequently, the average desired speed also had a high effect on lane change frequency with a high coefficient value.…”

Section: D Surface Plots and Regression Modelmentioning

confidence: 98%

Simulation-Based Analysis of the Effect of Significant Traffic Parameters on Lane Changing for Driving Logic “Cautious” on a Freeway

Farooq

Juhász

2019

Sustainability

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Lane changing of traffic flow is a complicated and significsant behavior for traffic safety on the road. Frequent lane changing can cause serious traffic safety issues, particularly on a two-lane road section of a freeway. This study aimed to analyze the effect of significant traffic parameters for traffic safety on lane change frequency using the studied calibrated values for driving logic “conscious” in VISSIM. Video-recorded traffic data were utilized to calibrate the model under specified traffic conditions, and the relationship between observed variables were estimated using simulation plots. The results revealed that changes in average desired speed and traffic volume had a positive relationship with lane change frequency. In addition, lane change frequency was observed to be higher when the speed distribution was set large. 3D surface plots were also developed to show the integrated effect of specified traffic parameters on lane change frequency. Results showed that high average desired speed and large desired speed distribution coupled with high traffic volume increased the lane change frequency tremendously. The study also attempted to develop a regression model to quantify the effect of the observed parameters on lane change frequency. The regression model results showed that desired speed distribution had the highest effect on lane change frequency compared to other traffic parameters. The findings of the current study highlight the most significant traffic parameters that influence the lane change frequency.

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Investigation of drivers’ behavior towards speeds using crash data and self-reported questionnaire

Cited by 38 publications

References 14 publications

Neighborhood Influences on Vehicle-Pedestrian Crash Severity

Neighborhood Influences on Vehicle-Pedestrian Crash Severity

Factors contributing to fatal road traffic accidents in the South of Kerman during the period from 2013 to 2017, Iran

Simulation-Based Analysis of the Effect of Significant Traffic Parameters on Lane Changing for Driving Logic “Cautious” on a Freeway

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