Contribution to Accident Prediction Models Development for Rural Two-Lane Roads in Serbia

Over the last three decades numerous research efforts have been conducted worldwide to determine the relationship between traffic accidents and traffic and road characteristics. So far, the mentioned studies have not been carried out in Serbia and in the region. This paper represents one of the first attempts to develop accident prediction models in Serbia. The paper provides a comprehensive literature review, describes procedures for collection and analysis of the traffic accident data, as well as the methodology used to develop the accident prediction models. The paper presents models obtained by both univariate and multivariate regression analyses. The obtained results are compared to the results of other studies and comparisons are discussed. Finally, the paper presents conclusions and important points for future research. The results of this research can find theoretical as well as practical application.

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The Development of Data Warehouse to Support Data Mining Technique for Traffic Accident Prediction

E3S Web of Conferences ◽

10.1051/e3sconf/20187312007 ◽

2018 ◽

Vol 73 ◽

pp. 12007

Author(s):

Budiawan Wiwik ◽

Singgih Saptadi ◽

Ary Arvianto

Keyword(s):

Data Mining ◽

Data Warehouse ◽

Traffic Safety ◽

Traffic Accident ◽

Traffic Accidents ◽

Prediction Models ◽

Data Access ◽

Design Data ◽

Accident Prediction ◽

The World

Traffic accidents are one of the major health problems that cause serious death in the world and ranks 9th in the world. Traffic accidents in Indonesia ranks 5th in the world. One effort to improve traffic safety is to design traffic accident prediction models. Prediction models will utilize accident-related data in traffic through data mining processing. The data warehouse offers benefits as a basis for data mining. Building an effective data warehouse requires knowledge and attention to key issues in database design, data acquisition and processing, as well as data access and security. This study is the first step in the development of data mining accidents based prediction system. The output of this initial stage is the design of data warehouses that can provide periodic and incidental data to the data mining process, especially in the prediction of accidents. The method used to design data warehouse is Entity Relationship Diagram (ERD).

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Study on the influence of skid resistance on traffic safety of highway with a high ratio of bridges and tunnels

Transportation Safety and Environment ◽

10.1093/tse/tdab025 ◽

2021 ◽

Vol 3 (4) ◽

Author(s):

Yongjie Ding ◽

Danni Li ◽

Mingxuan Huang ◽

Xuejuan Cao ◽

Boming Tang

Keyword(s):

Correlation Analysis ◽

Traffic Safety ◽

Traffic Accident ◽

Traffic Accidents ◽

Prediction Models ◽

Back Propagation ◽

Weather Conditions ◽

High Ratio ◽

Skid Resistance ◽

The Relationship

ABSTRACT The safety of highways with a high ratio of bridges and tunnels is related to multiple factors, for example, the skid resistance of the pavement surface. In this study, the distribution of accidents under different conditions was calculated to investigate the relationship between the road skid resistance and the incidence of traffic accidents based on the traffic accident data of the Yuxiang highway. Statistical results show that weather conditions and road alignment may affect traffic accidents. The correlation analysis method was used to study the relationship between three factors and traffic accidents. The results show that road alignment, weather conditions and road skid resistance are related to the incidence of traffic accidents. The traffic accident prediction models were established based on back propagation neural network to verify the correlation analysis results. It is confirmed that road alignment, weather conditions and road skid resistance are the factors that affect traffic accidents.

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Effect of Traffic and Geometric Characteristics of Rural Two Lane Roads on Traffic Safety: a case study of Ilesha-Akure-Owo road, South-West, Nigeria

FUOYE Journal of Engineering and Technology ◽

10.46792/fuoyejet.v3i2.256 ◽

2018 ◽

Vol 3 (2) ◽

Cited By ~ 1

Author(s):

Monsuru O Popoola ◽

Oladapo S Abiola ◽

Simeon O Odunfa

Keyword(s):

Road Safety ◽

Traffic Accident ◽

Negative Binomial ◽

Prediction Models ◽

Negative Binomial Regression ◽

Accident Prediction ◽

Geometric Characteristics ◽

South West ◽

Binomial Regression ◽

Accident Data

Road safety engineering involves identifying influencing factors causing traffic crashes through accident data, carrying out detailed accident studies at different locations and implementing relevant remedial measures. This study was carried out to establish relationship between traffic accident characteristics (frequency and severity) and traffic and road design characteristics on a two-lane highway. Statistical models applied in traffic accident modeling are Poisson regression, Negative Binomial regression (NB), and Zero-Inflated Negative Binomial regression (ZINB).; Traffic flow and road geometry related variables were the independent variables of the models. Using Ilesha-Akure-Owo highway, South-West, Nigeria accident prediction models were developed on the basis of accident data obtained from Federal Road Safety Commission (FRSC) during a 4-year monitoring period extending between 2012 and 2015. Curve radius (CR), lane width (LW), shoulder factor (SF), access road (CHAR), average annual daily traffic (AADT), parentage heavy good vehicle (HGV) and traffic sign posted (TSP) were the identified effective factors on crash occurrence probability. Finally, a comparison of the three models developed proved the efficiency of ZINB models against traditional Poisson and NB models. Keywords— Traffic accidents. Single carriageway, accident prediction model, road geometric characteristics.

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ROAD SAFETY CAMPAIGNS TO REDUCE TRAFFIC ACCIDENTS FOR YOUNG ROAD USERS

ICCD ◽

10.33068/iccd.vol2.iss1.278 ◽

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.

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Calibration and Transferability of Accident Prediction Models for Urban Intersections

Transportation Research Record Journal of the Transportation Research Board ◽

10.3141/1784-08 ◽

2002 ◽

Vol 1784 (1) ◽

pp. 57-64 ◽

Cited By ~ 76

Author(s):

Bhagwant Persaud ◽

Dominique Lord ◽

Joseph Palmisano

Keyword(s):

Functional Form ◽

Prediction Models ◽

Research Effort ◽

Safety Performance ◽

Accident Prediction ◽

Unsignalized Intersections ◽

Safety Performance Functions ◽

Safety Design ◽

Accident Data ◽

Single Calibration

Accident prediction models, also known as safety performance functions, have several important uses in modern-day safety analysis. Unfortunately, calibration of these models is not straightforward. A research effort was undertaken that demonstrates the complexity of calibrating these models for urban intersections. These complexities relate to the specification of the functional form, the accommodation of the peculiarities of accident data, and the transferability of models to other jurisdictions. Toronto data were used to estimate models for three- and four-legged signalized and unsignalized intersections. Then the performance of these models was compared with that of models for Vancouver and California that were recalibrated for Toronto using a procedure recently proposed for the application in the Interactive Highway Safety Design Model (IHSDM). The results of this transferability test are mixed, suggesting that a single calibration factor as is currently specified in the IHSDM procedure may be inappropriate and that a disaggregation by traffic volume might be preferable.

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Research on Preventive Management of Freeway Traffic Accident

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.779-780.763 ◽

2013 ◽

Vol 779-780 ◽

pp. 763-768

Author(s):

Bing Li ◽

Jia Xin Liu

Keyword(s):

Traffic Accident ◽

Traffic Accidents ◽

Rapid Development ◽

Research Work ◽

Accident Prevention ◽

Future Research ◽

Freeway Traffic ◽

Traffic Police ◽

Preventive Work ◽

Countermeasures And Suggestions

With the rapid development of the freeway, preventive work of freeway traffic faces larger and larger test. This paper adopts 1561 cases of traffic accidents in the Jiliao-freeway in past 5 years to find out the factors that affect safety. The study found out some factors which cause freeway traffic accidents, they are time, weather, the number of patrol vehicles and monitoring, age and attribution of the accident driver. The paper studies the management problems and puts forward on the countermeasures and suggestions, especially the problem of freeway traffic police burnout. This problem which involves in freeway traffic accident prevention will reach a new level and lay the foundation for the future research work.

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Highway Traffic Accident Prediction Based on SVR Trained by Genetic Algorithm

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.433-440.5886 ◽

2012 ◽

Vol 433-440 ◽

pp. 5886-5889 ◽

Cited By ~ 1

Author(s):

Zhen Qi Yang

Keyword(s):

Genetic Algorithm ◽

Support Vector Regression ◽

Traffic Accident ◽

Traffic Accidents ◽

Regression Function ◽

Support Vector ◽

Highway Traffic ◽

Prediction Ability ◽

Accident Prediction ◽

Better Than

The multi researches and experiments show that the future highway traffic accident situation is shown by the highway traffic accident prediction. In the paper, support vector regression trained by genetic algorithm is presented in highway traffic accident prediction. In the method, genetic algorithm is used to train the parameters of support vector regression. Firstly, the regression function of support vector regression algorithm is introduced, and the parameters of support vector regression are optimized by genetic algorithm. The computation results between G-SVR and SVR can indicate that the prediction ability for highway traffic accidents of G-SVR is better than that of SVR absolutely.

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MOBILE-WEB-BASE VOLUNTEERED GEOGRAPHIC INFORMATION APPLICATION AND GEOMETRIC ACCURACY ANALYSIS FOR TRAFFIC ACCIDENTS

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xliv-4-w3-2020-375-2020 ◽

2020 ◽

Vol XLIV-4/W3-2020 ◽

pp. 375-378

Author(s):

H. K. Sevinc ◽

I. R. Karas ◽

E. Demiral

Keyword(s):

Traffic Accident ◽

Traffic Accidents ◽

Geographic Information ◽

Google Earth ◽

Geographical Information ◽

Accuracy Analysis ◽

Geometric Accuracy ◽

Web Based ◽

Mobile Web ◽

Accident Data

Abstract. The users can contribute to geographic information through platforms such as Wikimapia and OpenStreetMap. They can also generate data by themselves with their applications in cyber worlds like Google Earth. This study is primarily designed to be a guide regarding Volunteered Geographical Information (VGI) and to evaluate the geometric accuracy of data collected from volunteers on application. The main purpose of this study is to present basic information about Volunteered Geographical Information (VGI), why users are tending to use VGI, the accuracy of the data entered by the user, to examine the examples of use in various fields, to learn about geographic information systems and to compare this phenomenon and also by developing a VGI application to examine the similarity between the actual data and the data collected from volunteer users. A mobile and web-based application have been developed to collect traffic accident data from volunteer users. The geometric accuracy analysis was performed by comparing the data collected with this application with the data obtained from the General Directorate of Security.

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TRAFFIC ANALYSIS ZONE LEVEL ROAD TRAFFIC ACCIDENT PREDICTION MODELS BASED ON LAND USE CHARACTERISTICS

International Journal for Traffic and Transport Engineering ◽

10.7708/ijtte.2019.9(4).03 ◽

2019 ◽

Vol 9 (4) ◽

Keyword(s):

Land Use ◽

Road Traffic Accident ◽

Traffic Accident ◽

Prediction Models ◽

Road Traffic ◽

Traffic Analysis ◽

Accident Prediction

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K-Means Clustering untuk Data Kecelakaan Lalu Lintas Jalan Raya di Kecamatan Pelaihari

Jurnal Teknologi Informasi dan Ilmu Komputer ◽

10.25126/jtiik.2018551113 ◽

2018 ◽

Vol 5 (5) ◽

pp. 613 ◽

Cited By ~ 1

Author(s):

Winda Aprianti ◽

Jaka Permadi

Keyword(s):

Data Mining ◽

Traffic Accident ◽

Traffic Accidents ◽

Distance Measure ◽

Data Traffic ◽

First Aid Training ◽

Accident Data ◽

Special Concern ◽

Clustering Data ◽

Minor Injuries

Kecelakaan lalu lintas di jalan raya masih menjadi penyumbang tingginya angka kematian di Indonesia, sehingga menjadi perhatian khusus bagi kepolisian di negara ini. Termasuk Kepolisian Resor (Polres) Tanah Laut, yang telah membuktikan perhatian tersebut dengan membentuk komunitas korban kecelakaan lalu lintas dan Pelatihan Pertolongan Pertama Gawat Darurat (PPGD). Tahapan awal pencegahan kecelakaan lalu lintas adalah dengan mengetahui faktor-faktor penyebab kecelakaan lalu lintas yang diperoleh melalui analisa data kecelakaan. Analisa tersebut dapat dilakukan dengan data mining, yaitu K-Means Clustering. K-Means Clustering mengelompokkan data menjadi beberapa cluster sesuai karakteristik data tersebut. Data kecelakaan lalu lintas dibagi menjadi 2 dataset, yakni dataset 1 dan dataset 2. Hasil cluster penerapan K-means clustering terhadap dataset 1 dan dataset 2 kemudian dilakukan pengujian silhoutte coefficient untuk mencari hasil cluster dengan kualitas terbaik. Pengujian silhoutte coefficient secara berurutan menghasilkan distance measure paling optimal yakni clustering dengan 4 cluster untuk dataset 1 dan clustering dengan 2 cluster untuk dataset 2. Selain memperoleh cluster dengan kualitas terbaik, penganalisaan data juga menghasilkan beberapa informasi kecelakaan lalu lintas yang sering terjadi, yakni faktor penyebab dan korban kecelakaan adalah pengemudi, umur korban adalah 9 sampai 28 tahun, dan keadaan korban kecelakaan adalah luka ringan. AbstractTraffic accidents on the highway are still contribute to the high mortality rate in Indonesia, which are becoming a special concern for the police. Including the Police of Tanah Laut Resort where prove themselves by established The Community of Traffic Accident Victims and Emergency First Aid Training. The first prevention of traffic accidents is knowing the factors causing traffic accidents which is obtained through the analysis of traffic accident’s data. It can be done through data mining, i.e. K-Means Clustering, which is clustering data into clusters according to characteristics of the data. Traffic accident data is divided into two datasets, namely dataset 1 and dataset 2. After obtaining the cluster results, the next step is to calculate silhoutte coefficient which is used to find the best quality cluster result. The result of testing silhoutte coefficient are clustering with 4 clusters for dataset 1 and clustering with 2 clusters for dataset 2. Analyzing data in this research also produces some information on traffic accidents that often occur, namely the causes and victims of accidents are drivers, the age of the victims is between 9 and 28 years old, and the circumstance of the accidents victims are minor injuries.

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