scholarly journals Traffic accident analysis based on C4.5 algorithm in WEKA

2019 ◽  
Vol 272 ◽  
pp. 01035 ◽  
Author(s):  
Jiajia Li ◽  
Jie He ◽  
Ziyang Liu ◽  
Hao Zhang ◽  
Chen Zhang
Keyword(s):  
Traffic Safety ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Safety Management ◽  
Depth Information ◽  
Highway Traffic ◽  
Safety Issues ◽  
C4.5 Algorithm ◽  
Accident Data ◽  
The Impact

At present, China is in a period of steady development of highways. At the same time, traffic safety issues are becoming increasingly serious. Data mining technology is an effective method for analysing traffic accidents. In-depth information mining of traffic accident data is conducive to accident prevention and traffic safety management. Based on the data of Wenli highway traffic accidents from 2006 to 2013, this study selected factors including time factor, linear factor and driver characteristics as research indicators, and established the decision tree using C4.5 algorithm in WEKA to explore the impact of various factors on the accident. According to the degree of contribution of each variable to the classification effect of the model, various modes affecting the type of the accident are obtained and the overall prediction accuracy is about 80%.

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.

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 The impact of traffic flow structure on traffic safety: the case of Slovenian motorways

Transport ◽  
2016 ◽  
Vol 33 (1) ◽  
pp. 216-222 ◽  
Author(s):  
Marina Zanne ◽  
Aleš Groznik
Keyword(s):  
Traffic Safety ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Transport Infrastructure ◽  
Traffic Flows ◽  
Moving Vehicle ◽  
Public Road ◽  
Past Data ◽  
The Impact

Road traffic accident is an accident on a public road in which at least one moving vehicle has been involved and material damage or injury or death has occurred. Traffic accidents occur for various reasons, with one of them being the transport infrastructure and next the condition of traffic environment. Motorways are considered to be the safest roads, which have initially been planned as dedicated roads intended to be travelled only by personal cars, but the evolution of modal split of freight transport in Europe is causing the heterogeneity of traffic flows on these roads, which consequently affects the traffic safety. The aim of this paper is to explore the effects of changing volume and structure of traffic flows on road safety on Slovenian motorways. After the exhaustive analysis of past data, the paper provides different models for forecasting traffic safety on Slovenian motorways.

scholarly journals Exploring the Application of the Linear Poisson Autoregressive Model for Analyzing the Dynamic Impact of Traffic Laws on Fatal Traffic Accident Frequency

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Yue Zhang ◽  
Yajie Zou ◽  
Lingtao Wu ◽  
Jinjun Tang ◽  
Malik Muneeb Abid
Keyword(s):  
Traffic Safety ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Negative Binomial ◽  
Moving Average ◽  
Red Light ◽  
Dynamic Impact ◽  
Temperature And Precipitation ◽  
Accident Data ◽  
Poisson Autoregressive Model

Annual fatal traffic accident data often demonstrate time series characteristics. The existing traffic safety analysis approaches (e.g., negative binomial (NB) model) often cannot accommodate the dynamic impact of factors in fatal traffic accident data and may result in biased parameter estimation results. Thus, a linear Poisson autoregressive (PAR) model is proposed in this study. The objective of this study is to apply the PAR model to analyze the dynamic impact of traffic laws and climate on the frequency of fatal traffic accidents occurred in a large time span (from 1975 to 2016) in Illinois. Besides, the NB model, NB with a time trend, and autoregressive integrated moving average model with exogenous input variables (ARIMAX) are also developed to compare their performances. The important conclusions from the modelling results can be summarized as follows. (1) The PAR model is more appropriate for analyzing the dynamic impacts of traffic laws on annual fatal traffic accidents, especially the instantaneous impacts. (2) The law that allows motorcycles and bicycles to proceed on a red light following the rules applicable after a “reasonable period of time” leads to an increase in the frequency of annual fatal traffic accidents by 14.98% in the short term and 30.69% in the long term. The climate factors such as average temperature and precipitation concentration period have insignificant impacts on annual fatal traffic accidents in Illinois. Thus, the modelling results suggest that the PAR model is more appropriate for annual fatal traffic accident data and has an advantage in estimating the dynamic impact of traffic laws.

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 Highway Traffic Accident Influence Area Based on Vehicle Bypass Decision-Making Index

2017 ◽  
Vol 2017 ◽  
pp. 1-8
Author(s):  
Zhenjun Zhu ◽  
Yang Lu ◽  
Jun Zeng ◽  
Hongsheng Chen
Keyword(s):  
Decision Making ◽  
Traffic Flow ◽  
Traffic Accident ◽  
Road Network ◽  
Traffic Accidents ◽  
Highway Traffic ◽  
Selection Probability ◽  
The Road ◽  
Influence Area ◽  
The Impact

In order to reduce the impact of highway traffic accidents on surrounding road networks, accident influence area should be determined reasonably. According to the relationship between vehicle bypass decision-making index and threshold under accident condition, the vehicles’ route choice behavior at upstream of the accident spot can be divided into two types: bypass and nonbypass. Under nonbypass condition, the method of using traffic wave theory was put forward to determine the upstream influence area. Under bypass condition, the total number of bypass vehicles is determined based on bypass decision-making index being greater than bypass threshold. Assignment algorithms based on routes were proposed. Using improved Logit model to get the selection probability and the traffic flow of each route, then traffic flow of surrounding links could be obtained. At last, the road network influenced by the accident could be determined by comparing with the level of service of each link under normal condition. The paper takes Beijing-Kunming highway as an example, and the results show that the road network formed by the influenced links was highway traffic accident influence area. Comparing with the actual survey results, correctness of the calculation method is verified. Therefore, the analytical method based on bypass decision-making is applicable to determining highway accident influence area.

scholarly journals Development of road infrastructure safety management system according to updates of EU Directive 96/2008/EC

2021 ◽  
Vol 1 (1) ◽  
pp. 35-41
Author(s):  
Fadila Kiso ◽  
Ajdin Džananović ◽  
Samira Šabanović-Karičić
Keyword(s):  
Traffic Safety ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Safety Management ◽  
Traditional Approach ◽  
Preventive Action ◽  
New Approach ◽  
Road Infrastructure ◽  
The Road ◽  
Eu Directive

The traditional approach to the analysis of traffic accidents has mostly involved identifying omissions in vehicles and drivers, which led to the occurrence of a traffic accident. However, more recent EU directives dealing with this area emphasize infrastructure failures that may be the real cause of the accident. This approach refers to preventive action, ie the design of such infrastructure that will, in case of failure of the driver, "forgive" the driver his mistake and prevent the occurrence of a traffic accident or reduce the consequences of a traffic accident. To achieve this, a completely new approach to the problem is needed, ie to build, reconstruct and regenerate the road infrastructure according to its real function from the aspect of traffic safety. The realization of these concepts in our area implies primarily the education of all entities that have contact with road infrastructure (designers, managers, auditors, etc.), with emphasis on the fact that savings on the material are significantly less than the savings achieved by reducing the number of accidents, with injured faces and fatalities.

Traffic Safety Diagnostics and Application of Countermeasures for Rural Roads in Burkina Faso

2003 ◽  
Vol 1846 (1) ◽  
pp. 39-43 ◽  
Author(s):  
Dominique Lord ◽  
Hamidou Mamadou Abdou ◽  
Antoine N’Zué ◽  
Georges Dionne ◽  
Claire Laberge-Nadeau
Keyword(s):  
Burkina Faso ◽  
Traffic Safety ◽  
Safety Management ◽  
Highway Traffic ◽  
Network Efficiency ◽  
Rural Roads ◽  
Staff Members ◽  
Accident Data ◽  
The Government

The government of Burkina Faso has recently been making important macroeconomic changes to encourage the economic growth of the country. To maintain this growth, the government has implemented a transportation program to improve road network efficiency and safety. A 2000 study to improve the safety of rural roads in Burkina Faso is described. The primary objectives were to assess traffic safety problems and propose countermeasures to reduce the number and severity of collisions on rural roads. Many rural roads were evaluated on site; all accident data and important socioeconomic variables were collected; and key staff members from various governmental and private agencies were interviewed. The study has shown that traffic safety problems in Burkina Faso are multidimensional, involving inefficient traffic safety management and policy, inadequate road networks, untrained drivers, and defective vehicles. Several traffic safety countermeasures have been proposed for immediate, short-, and long-term application. The most important countermeasures are to create a new institutional framework for improving traffic safety management and train the key personnel responsible for implementing these countermeasures. For the short term, the counter-measures mainly relate to roadway infrastructure improvements and better enforcement tools. For the long term, the countermeasures include a review of current highway traffic laws and their application, evaluation of existing countermeasures, and driver training improvement.

Identification of Urban Traffic Accident Hotspot Zones Using GIS: A Case Study of Dhaka Metropolitan Area

2020 ◽  
Vol 3 (1) ◽  
pp. 36-42
Author(s):  
Arif Ahmad ◽  
Khandaker Hossain ◽  
Mallik Hossain
Keyword(s):  
Spatial Patterns ◽  
Metropolitan Area ◽  
Traffic Safety ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Safety Management ◽  
Road Traffic ◽  
Urban Traffic ◽  
Traffic Information ◽  
Gis Technology

The issue of traffic safety becomes increasingly prominent and has attracted widespread attention from researchers and policy makers. Dhaka, the capital of Bangladesh, is the most vulnerable city both in terms of total number of accidents and accident rates. GIS technology has been widely applied to urban traffic information and safety management. This paper presents a geospatial analysis to identify the road traffic accident (RTA) hotspot zones in Dhaka Metropolitan Area (DMA). ‘Spatial analysis’ and ‘spatial statistics tools’ are used to examine spatial patterns of accident data. A systematic comparison of identified hotspot zones using Local Moran’s-I Statistic, Getis-Ord Gi* statistic and Kernel Density Estimation (KDE) carried out to examine spatial patterns of high cluster of traffic accidents. These analyses revealed a total 22 hotspot zones in DMA during the years 2010-2012. This kind of research would help generating new parameters for reducing road traffic accidents in Dhaka Metropolitan Area.

Study on Road Traffic Safety Evaluation Based on Improved Bayes Model

2011 ◽  
Vol 97-98 ◽  
pp. 489-493
Author(s):  
Yao Ping Li ◽  
Jian Lin Li ◽  
Bin Li ◽  
Li Wei Hu
Keyword(s):  
Traffic Safety ◽  
Empirical Bayes ◽  
Safety Management ◽  
Road Traffic ◽  
Safety Evaluation ◽  
Road Traffic Safety ◽  
Accident Probability ◽  
Probability Prediction ◽  
Accident Data ◽  
The Impact

he traditional safety evaluation methods are mostly based on historical accident data, which belong to the macroscopical level and have obvious defects in traffic safety management. This paper established accident Probability Density Function by using Kernel Density Estimation (KDE), proposed Accident Probability Prediction (APP) model based on Empirical Bayes (EB) method for considering the impact of accident location characteristics and historical data. The paper also established the method for road traffic safety micro-evaluation by adopting Traffic Accident Probabilities of Equivalent ten thousand Cars (TAPEC) indicator, and a comparative evaluation was conducted by the proposed method against cumulative frequency curve method. Through analyzing accident data collected from the G301, the results show that the proposed method is more reliable and can access to the transformation priorities of potentially dangerous road sections. So it can provide theoretical basis for checking the dangerous sections and improving accident prevention and response.

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