scholarly journals Predictors of Self-reported Crashes among Iranian Drivers: Exploratory Analysis of an Extended Driver Behavior Questionnaire

2018 ◽  
Vol 30 (1) ◽  
pp. 35-43 ◽  
Author(s):  
Amin Mohamadi Hezaveh ◽  
Trond Nordfjærn ◽  
Amir Reza Mamdoohi ◽  
Özlem Şimşekoğlu
Keyword(s):  
Traffic Safety ◽  
Road Traffic ◽  
Driver Behaviour ◽  
Factor Solution ◽  
Traffic Crashes ◽  
Traffic Fatality ◽  
Road Traffic Safety ◽  
Traffic Violations ◽  
Safety Countermeasures ◽  
Iranian Context

More than 16,500 people lose their lives each year due to traffic crashes in Iran, which reflects one of the highest road traffic fatality rates in the world. The aim of the present study is to investigate the factors structure of an extended Driver Behaviour Questionnaire (DBQ) and to examine the gender differences in the extracted factors among Iranian drivers. Further, the study tested the association between DBQ factors, demographic characteristics, and self-reported crashes. Based on Iranian driving culture, an extended (36 items) Internet-based version of the DBQ was distributed among Iranian drivers. The results of Exploratory Factor Analysis based on a sample of 632 Iranians identified a five-factor solution named “Speeding and Pushing Violations”, “Lapses and Errors”, “Violations Causing Inattention”, “Aggressive Violations” and “Traffic Violations” which account for 44.7 percent of the total variance. The results also revealed that females were more prone to Lapses and Errors, whereas males reported more violations than females. Logistic regression analysis identified Violations Causing Inattention, Speeding and Pushing Violations as predictors of self-reported crashes in a three-year period. The results were discussed in line with road traffic safety countermeasures suitable for the Iranian context.

scholarly journals Revealing the Spatial Pattern of Weather-Related Road Traffic Crashes in Slovenia

2021 ◽  
Vol 11 (14) ◽  
pp. 6506
Author(s):  
Danijel Ivajnšič ◽  
Nina Horvat ◽  
Igor Žiberna ◽  
Eva Konečnik Kotnik ◽  
Danijel Davidović
Keyword(s):  
Traffic Safety ◽  
Spatial Information ◽  
Road Traffic ◽  
Road Traffic Crash ◽  
Navigation Systems ◽  
Traffic Crashes ◽  
Road Traffic Crashes ◽  
Traffic Crash ◽  
Road Traffic Safety ◽  
Adverse Weather

Despite an improvement in worldwide numbers, road traffic crashes still cause social, psychological, and financial damage and cost most countries 3% of their gross domestic product. However, none of the current commercial or open-source navigation systems contain spatial information about road traffic crash hot spots. By developing an algorithm that can adequately predict such spatial patterns, we can bridge these still existing gaps in road traffic safety. To that end, geographically weighted regression and regression tree models were fitted with five uncorrelated (environmental and socioeconomic) road traffic crash predictor variables. Significant regional differences in adverse weather conditions were identified; Slovenia lies at the conjunction of different climatic zones characterized by differences in weather phenomena, which further modify traffic safety. Thus, more attention to speed limits, safety distance, and other vehicles entering and leaving the system could be expected. In order to further improve road safety and better implement globally sustainable development goals, studies with applicative solutions are urgently needed. Modern vehicle-to-vehicle communication technologies could soon support drivers with real-time traffic data and thus potentially prevent road network crashes.

Safety Enhancement by Automated Driving: What are the Relevant Scenarios?

2020 ◽  
Vol 64 (1) ◽  
pp. 1686-1690
Author(s):  
Niklas Grabbe ◽  
Michael Höcher ◽  
Alexander Thanos ◽  
Klaus Bengler
Keyword(s):  
Traffic Safety ◽  
Road Traffic ◽  
Test Cases ◽  
Automated Driving ◽  
Road Traffic Safety ◽  
Human Driver ◽  
Driving Task ◽  
Promising Solution ◽  
Vehicle Automation ◽  
Safety Enhancement

Automated driving offers great possibilities in traffic safety advancement. However, evidence of safety cannot be provided by current validation methods. One promising solution to overcome the approval trap (Winner, 2015) could be the scenario-based approach. Unfortunately, this approach still results in a huge number of test cases. One possible way out is to show the current, incorrect path in the argumentation and strategy of vehicle automation, and focus on the systemic mechanisms of road traffic safety. This paper therefore argues the case for defining relevant scenarios and analysing them systemically in order to ultimately reduce the test cases. The relevant scenarios are based on the strengths and weaknesses, in terms of the driving task, for both the human driver and automation. Finally, scenarios as criteria for exclusion are being proposed in order to systemically assess the contribution of the human driver and automation to road safety.

scholarly journals Assessing inequality, irregularity, and severity regarding road traffic safety during COVID-19

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Lei Lin ◽  
Feng Shi ◽  
Weizi Li
Keyword(s):  
New York ◽  
Los Angeles ◽  
Traffic Safety ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Human Mobility ◽  
Critical Conditions ◽  
Road Traffic Safety ◽  
Accident Data ◽  
The Impact

AbstractCOVID-19 has affected every sector of our society, among which human mobility is taking a dramatic change due to quarantine and social distancing. We investigate the impact of the pandemic and subsequent mobility changes on road traffic safety. Using traffic accident data from the city of Los Angeles and New York City, we find that the impact is not merely a blunt reduction in traffic and accidents; rather, (1) the proportion of accidents unexpectedly increases for “Hispanic” and “Male” groups; (2) the “hot spots” of accidents have shifted in both time and space and are likely moved from higher-income areas (e.g., Hollywood and Lower Manhattan) to lower-income areas (e.g., southern LA and southern Brooklyn); (3) the severity level of accidents decreases with the number of accidents regardless of transportation modes. Understanding those variations of traffic accidents not only sheds a light on the heterogeneous impact of COVID-19 across demographic and geographic factors, but also helps policymakers and planners design more effective safety policies and interventions during critical conditions such as the pandemic.

scholarly journals Classification of Russian cities by levels of road traffic safety: specifics of required management decisions

2018 ◽  
Vol 170 ◽  
pp. 05009
Author(s):  
Artur Petrov ◽  
Daria Petrova
Keyword(s):  
Regression Analysis ◽  
Russian Federation ◽  
Traffic Safety ◽  
Road Traffic ◽  
Spatial Differentiation ◽  
Rate Heterogeneity ◽  
Accident Rate ◽  
Road Traffic Safety ◽  
Relative Disadvantage

The article considers the results of research of accident rate heterogeneity in cities-administrative centers of subjects of Russian Federation (2015, 2016). Using methods of ranging, regression analysis and spatial differentiation these cities were classified into 5 classes on the basis of relative disadvantage in road traffic safety sphere. For each group of cities differentiated recommendations on financing regional road traffic safety programs were suggested.

scholarly journals Road Transport Accidents in Nigeria and the Role of Automotive Active Safety System

2016 ◽  
Vol 11 (1) ◽  
pp. 49-54
Author(s):  
Olasunkanmi Oriola Akinyemi ◽  
Hezekiah O Adeyemi ◽  
Olusegun Jinadu
Keyword(s):  
Traffic Safety ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Transportation Network ◽  
Road Transport ◽  
Road Accident ◽  
Active Safety ◽  
Road Accidents ◽  
Road Transportation ◽  
Road Traffic Safety

Abstract Analysis of road traffic accidents revealed that most accidents are as a result of drivers’ errors. Over the years, active safety systems (ASS) were devised in vehicle to reduce the high level of road accidents, caused by human errors, leading to death and injuries. This study however evaluated the impacts of ASS inclusions into vehicles in Nigeria road transportation network. The objectives was to measure how ASS contributed to making driving safer and enhanced transport safety. Road accident data were collected, for a period of eleven years, from Lagos State Ministry of Economic Planning and Budget, Central Office of Statistics. Quantitative analysis of the retrospective accident was conducted by computing the proportion of yearly number of vehicles involved in road accident to the total number of vehicles for each year. Results of the analysis showed that the proportion of vehicles involved in road accidents decreased from 16 in 1996 to 0.89 in 2006, the injured persons reduced from 15.58 in 1998 to 0.3 in 2006 and the death rate diminished from 4.45 in 1998 to 0.1 in 2006. These represented 94.4 %, 95 % and 95 % improvement respectively on road traffic safety. It can therefore be concluded that the inclusions of ASS into design of modern vehicles had improved road safety in Nigeria automotive industry.

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