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 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 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 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.

Traffic accident and emission reduction through intermittent release measures for heavy fog weather

2015 ◽  
Vol 29 (25) ◽  
pp. 1550148 ◽  
Author(s):  
Jing Shi ◽  
Jin-Hua Tan
Keyword(s):  
Traffic Safety ◽  
Emission Reduction ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Driving Simulator ◽  
Emission Characteristics ◽  
Driving Behaviors ◽  
Ca Model ◽  
Reduce Emissions

Heavy fog weather can increase traffic accidents and lead to freeway closures which result in delays. This paper aims at exploring traffic accident and emission characteristics in heavy fog, as well as freeway intermittent release measures for heavy fog weather. A driving simulator experiment is conducted for obtaining driving behaviors in heavy fog. By proposing a multi-cell cellular automaton (CA) model based on the experimental data, the role of intermittent release measures on the reduction of traffic accidents and CO emissions is studied. The results show that, affected by heavy fog, when cellular occupancy [Formula: see text], the probability of traffic accidents is much higher; and CO emissions increase significantly when [Formula: see text]. After an intermittent release measure is applied, the probability of traffic accidents and level of CO emissions become reasonable. Obviously, the measure can enhance traffic safety and reduce emissions.

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 ESTIMATION OF THE TRAFFIC ACCIDENTS COSTS IN SERBIA BY USING DOMINANT COSTS MODEL

Transport ◽  
2012 ◽  
Vol 26 (4) ◽  
pp. 433-440 ◽  
Author(s):  
Boris Antić ◽  
Milan Vujanić ◽  
Krsto Lipovac ◽  
Dalibor Pešić
Keyword(s):  
Traffic Safety ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Economic Effects ◽  
Decision Makers ◽  
Gdp Per Capita ◽  
Crucial Importance ◽  
Per Capita ◽  
The Republic ◽  
Official Data

This paper presents estimation of the traffic accident costs in Serbia, based on original dominant costs model. Dominant costs model uses human capital approach and this model is developed for simple and quick calculation of the traffic accidents costs, because other simple methods as 1 million rules, are not suitable for estimation of the traffic accident costs in the countries with a low GDP per capita. Knowing the costs of traffic accidents is of crucial importance for establishing traffic safety to the level defined by the size of costs made as a consequence of unsafely. So, politicians, decision makers and stakeholders in the field of traffic safety often need quick estimation of the traffic accident costs and economic effects of the particular measures which are applied for decreasing the number and severity of traffic accidents. The estimation of the level of the traffic accidents costs in Serbia, based on the official data (from the Ministry of Interior of the Republic of Serbia) about traffic accidents in Serbia for 2008 is shown in this paper and the comparison between predicted and calculated value of the traffic accident costs for 2009 is also presented.

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 Expressway Traffic Accidents Involving Human Injuries and Fatalities in Ethiopia: Negative Binomial Regression Model

2021 ◽  
Author(s):  
Yesuf Abdela Mustefa ◽  
Addis Belayhun
Keyword(s):  
Regression Model ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Negative Binomial ◽  
Road Traffic ◽  
Weather Condition ◽  
Negative Binomial Regression ◽  
Negative Binomial Regression Model ◽  
Level Of Education ◽  
Binomial Regression

Abstract Background: Road traffic accident is a major public health as well as economic challenge that rated the eighth leading cause of death. The severity became higher in developing countries. Ethiopian is among the most confronted countries in the world. We utilized the Ethiopian Toll Roads Enterprise data to provide insights and model significant determinants of accidents involving injuries and fatalities. Besides utilizing recent dataset, we applied the most appropriate but forwent statistical model. Moreover, we examined the significance of the effects of drivers’ age and gender that have not been the cases in the literatures.Methods: We made descriptive insights available on the basis of graphs from integrated traffic accident and flow datasets. We tested for the presence of over-dispersion in a total of 1824 observations of accident data recorded from September, 2014 to December, 2019 for inferential analysis. Finally, we modeled the effects of significant variables on the number of injuries using the negative binomial regression model. Results: we found that the number of injuries in accidents were significantly determined by type of vehicles, ownership status of vehicles, accident time weather condition, driver-vehicle relationship, drivers’ level of education, and drivers’ age.Conclusions: Heavy trucks were more likely to cause more number of injuries than medium or small vehicles. Hot and windy weather conditions were associated with higher probability of the number of injuries. The likelihood of the number of injuries were lower when drivers are owner of the vehicle; drivers level of education is above secondary school; and the age of the driver is between 18 and 23 years old. Moreover, due concern needs to be given for traffic road rules.

scholarly journals ROAD SAFETY CAMPAIGNS TO REDUCE TRAFFIC ACCIDENTS FOR YOUNG ROAD USERS

ICCD ◽  
2019 ◽  
Vol 2 (1) ◽  
pp. 601-606
Author(s):  
Widodo Budi Dermawan ◽  
Dewi Nusraningrum
Keyword(s):  
School Environment ◽  
Road Safety ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Road Traffic ◽  
School Administrators ◽  
Road User ◽  
The Road ◽  
Road Users ◽  
Accident Data

Every year we lose many young road users in road traffic accidents. Based on traffic accident data issued by the Indonesian National Police in 2017, the number of casualties was highest in the age group 15-19, with 3,496 minor injuries, 400 seriously injured and 535 deaths. This condition is very alarming considering that student as the nation's next generation lose their future due to the accidents. This figure does not include other traffic violations, not having a driver license, not wearing a helmet, driving opposite the direction, those given ticket and verbal reprimand. To reduce traffic accident for young road user, road safety campaigns were organized in many schools in Jakarta. This activity aims to socialize the road safety program to increase road safety awareness among young road users/students including the dissemination of Law No. 22 of 2009 concerning Road Traffic and Transportation. Another purpose of this program is to accompany school administrators to set up a School Safe Zone (ZoSS), a location on particular roads in the school environment that are time-based speed zone to set the speed of the vehicle. The purpose of this paper is to promote the road safety campaigns strategies by considering various campaign tools.

scholarly journals PENENTUAN BIAYA KECELAKAAN LALU LINTAS: STUDI KASUS LOMBOK TIMUR

2018 ◽  
Vol 1 (3) ◽  
pp. 128
Author(s):  
Andyka Kusuma ◽  
Tri Tjahjono ◽  
Nuzul Achjar
Keyword(s):  
Traffic Safety ◽  
Human Development Index ◽  
Traffic Accident ◽  
Analytical Approach ◽  
Traffic Accidents ◽  
Price Index ◽  
Consumer Price Index ◽  
Potential Losses ◽  
The Cost ◽  
The City

Traffic accident cost analysis is needed to predict potential losses of nation due to the emergence of traffic accident victims. The cost of traffic accidents in Indonesia is based on the characteristics of the City of Bandung in 2003, and it is shown that the cost of traffic accidents can vary according to regional characteristics. This study tries to compare the analytical approach in Bandung in 2003 with the Consumer Price Index and Human Development Index approaches for an area with medium accessibility, namely East Lombok, West Nusa Tenggara Province. The location of traffic accidents greatly influences the cost of traffic accidents, because the costs on inter-city roads are relatively higher compared to those on roads in the city. This study shows that the cost of traffic accidents is related to accessibility of health facilities. This analysis can be developed for all regions in Indonesia, so that it can be used as a reference for traffic stakeholders in assessing the performance of the traffic safety programs implemented. Analisis biaya kecelakaan lalu lintas diperlukan untuk memprediksi potensi kerugian negara akibat timbulnya korban kecelakaan lalu lintas. Biaya kecelakaan lalu lintas di Indonesia dibangun berdasarkan karakteristik kota Bandung tahun 2003, dan diperlihatkan bahwa biaya kecelakaan lalu lintas dapat bervariasi sesuai dengan karakteristik wilayah. Penelitian ini mencoba membandingkan pendekatan analisis di Bandung tahun 2003 dengan pendekatan Indeks Harga Konsumen dan Indeks Pembangunan Manusia untuk suatu wilayah dengan aksesibilitas menengah, yakni Lombok Timur, Provinsi Nusa Tenggara Barat. Lokasi kecelakaan lalu lintas sangat mempengaruhi biaya kecelakaan lalu lintas, karena biaya di jalan antar kota relatif lebih tinggi dibandingkan dengan biaya di jalan dalam kota. Penelitian ini meperlihatkan bahwa biaya kecelakaan lalu lintas terkait dengan aksesibilitas fasilitas kesehatan. Analisis ini dapat dikembangkan untuk semua wilayah di Indonesia, sehingga dapat dijadikan acuan bagi pemangku kepentingan lalu lintas dalam menilai kinerja program keselamatan lalu lintas yang dijalankan.

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