scholarly journals Road traffic accidents on Senai-Desaru expressway

2018 ◽  
Vol 250 ◽  
pp. 02002 ◽  
Author(s):  
Nordiana Mashros ◽  
SittiAsmah Hassan ◽  
Yaacob Haryati ◽  
Mohd Shahrir Amin Ahmad ◽  
Ismail Samat ◽  
...  
Keyword(s):  
Traffic Safety ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Contributing Factors ◽  
Property Damage ◽  
Crash Frequency ◽  
Crash Data ◽  
Run Off ◽  
Accident Data ◽  
Road Segments

Understanding and prioritising crash contributing factors is important for improving traffic safety on the expressway. This paper aims to identify the possible contributory factors that were based on findings obtained from crash data at Senai-Desaru Expressway (SDE), which is the main connector between the western and eastern parts of Johor, Malaysia. Using reported accident data, the mishaps that had occurred along the 77.2 km road were used to identify crash patterns and their possible related segment conditions. The Average Crash Frequency and Equivalent Property Damage Only Average Crash Frequency Methods had been used to identify and rank accident-prone road segments as well as to propose for appropriate simple and inexpensive countermeasures. The results show that the dominant crash type along the road stretches of SDE had consisted of run-off-road collision and property damage only crashes. All types of accidents were more likely to occur during daytime. Out of the 154 segments, the 4 most accident-prone road segments had been determined and analysed. The results obtained from the analyses suggest that accident types are necessary for identifying the possible causes of accidents and the appropriate strategies for countermeasures. Therefore, this accident analysis could be helpful to relevant authorities in reducing the number of road accidents and the level of accident severity along the SDE.

ASSESSMENT OF THE PRECISION OF DATA COLLECTED ABOUT THE TRAFFIC ACCIDENTS WITH PROPERTY DAMAGE ONLY IN CLAIM HANDLING PROCESS BY INSURANCE COMPANIES

Transport ◽  
2014 ◽  
Vol 32 (2) ◽  
pp. 160-166
Author(s):  
Erik Ernits ◽  
Dago Antov ◽  
Anton Kott
Keyword(s):  
Traffic Safety ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Insurance Companies ◽  
Road Traffic Accidents ◽  
Quality Of Data ◽  
Property Damage ◽  
Traffic Conflicts ◽  
Accident Data ◽  
Survey Results

The number of serious road traffic accidents is decreasing in all European countries. Based on the trends and directions in the past it may be predicted that in longer perspective the number of serious road traffic accidents will decrease remarkably. This will create a situation where it is more and more difficult to ensure the reliability of traffic safety analyses performed by statistical methods. There are two possibilities to decrease the problem: either to carry out in-depth investigations of serious road traffic accidents and/or investigate also Property Damage Only (PDO) traffic accidents and traffic conflicts in addition to serious traffic accidents. The key issue in using the PDO accident data is its precision. The present paper is attempting to enlighten the area, and assess the quality of data of PDO road traffic accidents collected by insurance providers by example of Estonia. The survey results show that in spite of certain shortcomings, the PDO road traffic accident data collected by insurance provider is valuable to be used in traffic safety analyses.

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 Identification of potential traffic accident hot spots based on accident data and GIS

2020 ◽  
Vol 325 ◽  
pp. 01005
Author(s):  
Hongge Zhu ◽  
Yuntong Zhou ◽  
Yanyan Chen
Keyword(s):  
Traffic Safety ◽  
Hot Spots ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Hot Spot ◽  
Geographic Information ◽  
Causality Analysis ◽  
Road Traffic Safety ◽  
Accident Data

The problem of road traffic safety has been widely concerned in recent years. The identification of traffic accident hot spots can effectively improve the road traffic safety and let the traffic managers formulate targeted improvement measures and suggestions. The traditional identification method of accident hot spot does not consider the spatial attribute of the accident, so it has some limitations in the identification of traffic accident hot area. Therefore, this paper first proposes a method to identify the hot spot of traffic accidents based on geographic information system (GIS). The mathematical model and machine learning model are used to explore the correlation between traffic accidents and spatial characteristics from macro and micro aspects. Finally, taking Beijing as an example, the feasibility of the research method is proved by using the accident data of Beijing in 2015 and the geographic information of Beijing. The research results of this paper can realize the spatial effective transformation of accident records, comprehensively consider the micro and macro attributes of the accident itself, realize the automatic and efficient identification of the accident hot spot. In addition, the causality analysis results between each attribute and the distribution of accident hot spots can help decision makers to formulate safety and sustainable road strategies.

scholarly journals Spatial and Temporal Distribution Analysis of Traffic Accidents Using GIS-Based Data in Harbin

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Meina Wang ◽  
Jing Yi ◽  
Xirui Chen ◽  
Wenhui Zhang ◽  
Tiangang Qiang
Keyword(s):  
Traffic Safety ◽  
Road Network ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Network Density ◽  
Road Traffic Accidents ◽  
Urban Centers ◽  
Accident Severity ◽  
Accident Data ◽  
Density Analysis

Road traffic safety is a social issue of widespread concern. It is important for traffic managers to understand the distribution patterns of road traffic accidents. To this end, this study examines the spatial and temporal patterns of road traffic accidents from both accident frequency and accident severity perspectives. Road traffic accident data from 2016 to 2018 in Harbin, China, were used for the analysis. First, the spatial localization of accidents was completed using geocoding, and the localized accident data were classified by season. Then, density analysis was performed both with and without considering road network density. The results of the density analysis showed that when road network density was considered, accidents were mainly distributed in urban centers, while accidents were more dispersed when road network density was not considered. Third, a cluster analysis considering accident severity found that low-severity accident clusters occurred mostly in urban centers. High-severity accident clusters were mostly present in suburban areas. Finally, the results of these two methods are shown by using the comap technique. Areas of the city with a high frequency and severity of crashes in each season were identified. This study will help traffic management to have a more visual and intuitive understanding of the urban traffic safety situation and to take targeted measures to improve it accordingly.

scholarly journals Application and Evaluation of a Non-Accident-Based Approach to Road Safety Analysis Based on Infrastructure-Related Human Factors

2022 ◽  
Vol 14 (2) ◽  
pp. 662
Author(s):  
Lorenzo Domenichini ◽  
Andrea Paliotto ◽  
Monica Meocci ◽  
Valentina Branzi
Keyword(s):  
Human Factors ◽  
Road Safety ◽  
Performance Measure ◽  
Evaluation Tool ◽  
Contributing Factors ◽  
Good Correspondence ◽  
Crash Data ◽  
Accident Data ◽  
Numerical Performance ◽  
Road Segments

Too often the identification of critical road sites is made by “accident-based” methods that consider the occurred accidents’ number. Nevertheless, such a procedure may encounter some difficulties when an agency does not have reliable and complete crash data at the site level (e.g., accidents contributing factors not clear or approximate accident location) or when crashes are underreported. Furthermore, relying on accident data means waiting for them to occur with the related consequences (possible deaths and injuries). A non-accident-based approach has been proposed by PIARC. This approach involves the application of the Human Factors Evaluation Tool (HFET), which is based on the principles of Human Factors (HF). The HFET can be applied to road segments by on-site inspections and provides a numerical performance measure named Human Factors Scores (HFS). This paper analyses which relationship exists between the results of the standard accident-based methods and those obtainable with HFET, based on the analysis of self-explaining and ergonomic features of the infrastructure. The study carried out for this purpose considered 23 km of two-way two-lane roads in Italy. A good correspondence was obtained, meaning that high risky road segments identified by the HFS correspond to road segments already burdened by a high number of accidents. The results demonstrated that the HFET allows for identifying of road segments requiring safety improvements even if accident data are unavailable. It allows for improving a proactive NSS, avoiding waiting for accidents to occur.

SOME TRAFFIC SAFETY ISSUES AT UNREGULATED PEDESTRIAN CROSSINGS IN THE CITY

2021 ◽  
Vol 5 (12(81)) ◽  
pp. 26-32
Author(s):  
V. Volkov ◽  
E. Nabatnikova ◽  
E. Lebedev
Keyword(s):  
Traffic Safety ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Hourly Interval ◽  
Safety Issues ◽  
The Road ◽  
Probability Estimates ◽  
Mode Of Transport ◽  
Speed Mode

The groups of participants of the pedestrian and automobile flows, whose actions cause the greatest danger to the occurrence of conflict situations in the zone of unregulated transition, are identified. The factors determining the likelihood of a traffic accident at an unregulated transition are systematized, for which probability estimates of the occurrence of road traffic accidents are calculated. As an estimated parameter, the hazard coefficient of a conflict point of an unregulated transition is proposed, which is determined by the ratio of the probability of a traffic accident in the real-time hourly interval to the average annual probability of a traffic accident reduced to the hourly interval. The dependences of the hazard ratio of an unregulated transition are established on the most significant factors: the speed mode of transport in the area before the transition and the state of the road surface.

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.

Regression Analysis of Rural Road Traffic Accidents Causes

2011 ◽  
Vol 97-98 ◽  
pp. 1042-1045 ◽  
Author(s):  
Chuan Jiao Sun ◽  
Ru Yue Bai ◽  
Yuan Yuan Yu
Keyword(s):  
Regression Analysis ◽  
Traffic Safety ◽  
Road Traffic Accident ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Lower Grade ◽  
The Road ◽  
Rural Road ◽  
Safety Awareness

9238 traffic accidents data are collected in rural road of China. Through the data analysis, the main causes of rural road traffic accident are presented. The external environment, the participant features, road features and accident characteristics are involved. The regression analysis in SPSS is applied to find the relationship between the accident features. Overall, the rural road traffic accident was mainly due to in the rural area there are mass travel mode, lower grade roads, poorer safety awareness of traveler and the road is lack of traffic safety facilities and so on.

scholarly journals Comparative Study of Machine Learning Classifiers for Modelling Road Traffic Accidents

2022 ◽  
Vol 12 (2) ◽  
pp. 828
Author(s):  
Tebogo Bokaba ◽  
Wesley Doorsamy ◽  
Babu Sena Paul
Keyword(s):  
Machine Learning ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Real Life ◽  
Support Vector ◽  
Road Traffic Accidents ◽  
Machine Learning Classifiers ◽  
Reduction Techniques ◽  
Learning Classifiers ◽  
Accident Data

Road traffic accidents (RTAs) are a major cause of injuries and fatalities worldwide. In recent years, there has been a growing global interest in analysing RTAs, specifically concerned with analysing and modelling accident data to better understand and assess the causes and effects of accidents. This study analysed the performance of widely used machine learning classifiers using a real-life RTA dataset from Gauteng, South Africa. The study aimed to assess prediction model designs for RTAs to assist transport authorities and policymakers. It considered classifiers such as naïve Bayes, logistic regression, k-nearest neighbour, AdaBoost, support vector machine, random forest, and five missing data methods. These classifiers were evaluated using five evaluation metrics: accuracy, root-mean-square error, precision, recall, and receiver operating characteristic curves. Furthermore, the assessment involved parameter adjustment and incorporated dimensionality reduction techniques. The empirical results and analyses show that the RF classifier, combined with multiple imputations by chained equations, yielded the best performance when compared with the other combinations.

scholarly journals PEDESTRIAN TRAFFIC CONDITIONS OF RURAL ROADS AND BUILT-UP AREAS: THE ANALYSIS OF THE EXISTING SITUATION AND POSSIBILITIES OF IMPROVING TRAFFIC CONDITIONS

2010 ◽  
Vol 2 (3) ◽  
pp. 60-66
Author(s):  
Nemunas Abukauskas ◽  
Egidijus Skrodenis
Keyword(s):  
Traffic Safety ◽  
Road Safety ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Rural Roads ◽  
Traffic Conditions ◽  
Foreign Countries ◽  
Pedestrian Traffic ◽  
Main Activity

The results of lengthy thorough investigations into traffic safety situation show that the percentage of pedestrians getting involved in road traffic accidents on Lithuanian roads is significantly higher (more than 33 % of the total number of injury and fatal accidents) than that compared to the other European Union member-states. The article studies traffic safety problems and their factors causing the largest influence on the occurrence of these accidents. Considering valuable experience gained by foreign countries, investigation was carried out to establish general and main factors causing insufficient road safety conditions and significance of these factors to road safety. The article also shows the main activity improving road safety in Lithuania and discusses the effectiveness of strategic and local (temporary and long term) measures to improve conditions for pedestrian road safety.

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