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Traffic Risk Mining From Heterogeneous Road Statistics

Koichi Moriya, Shin Matsushima, Kenji Yamanishi
2018 IEEE transactions on intelligent transportation systems (Print)  
In this paper, we propose a novel framework for mining traffic risk from such heterogeneous data. Traffic risk refers to the possibility of occurrence of traffic accidents.  ...  At present, a large amount of traffic-related data is obtained manually and through sensors and social media, e.g., traffic statistics, accident statistics, road information, and users' comments.  ...  We propose a framework for mining traffic risk information from heterogeneous datasets consisting of traffic statistics (number of accidents, traffic volume, roadway information, brake data, and social  ... 
doi:10.1109/tits.2018.2856533 fatcat:ry45zqgblvginj7ywxbsthl5ry

Traffic accident segmentation by means of latent class clustering

Benoît Depaire, Geert Wets, Koen Vanhoof
2008 Accident Analysis and Prevention  
They also acknowledge extensive comments from the reviewers.  ...  From a statistical point of view, data mining can also be considered as a computer automated exploratory data analysis of (usually) large complex data sets (Friedman, 1997) .  ...  Sometimes building separate models for different traffic accident types shows that certain risk factors are not statistically significant for all traffic accident types.  ... 
doi:10.1016/j.aap.2008.01.007 pmid:18606254 fatcat:n252bc2n6zgxfiymfybd2yqlry

Density-based clustering for road accident data analysis

Abdullah S. Alotaibi
2018 International Journal of Advanced and Applied Sciences  
In this research paper, we discover factors behind road traffic accidents problem solving by data mining algorithms together with DBSCAN and Parallel Frequent mining algorithm.  ...  Now days, Road accidents due to traffic are increasingly being recognized as key issue for transportation agencies as well as common people.  ...  (FPTi, Pi, A Framework of proposed method Table 1 : 1 1970-2017 road accident statistical data Year Road accidents Road accidental deaths Accident risk Road accidental injuries Fatality  ... 
doi:10.21833/ijaas.2018.08.014 fatcat:mqgeypeblfg4jmdgrwjglszxfy

Amphetamine-type stimulant use and the risk of injury or death as a result of a road-traffic accident: A systematic review of observational studies

Amie C. Hayley, Luke A. Downey, Brook Shiferaw, Con Stough
2016 European Neuropsychopharmacology  
We performed a systematic review to evaluate existing evidence regarding the association between amphetamine use and the risk of injury or death due to road traffic accidents.  ...  This is the first review to synthesise evidence regarding the association between amphetamine-type substance use and the risk of injury or death due to a road traffic accident.  ...  Heterogeneity between studies was initially evaluated with the I 2 statistic as a measure of the proportion of total variation in estimates due to heterogeneity, where I 2 values of 25%, 50%, and 75% correspond  ... 
doi:10.1016/j.euroneuro.2016.02.012 pmid:27006144 fatcat:yrnekoujwjg6vkueviemipgpl4

Evaluation of the Impact of Spatial and Environmental Accident Factors on Severity Patterns of Road Segments

Maen Qaseem Ghadi, Árpád Török
2020 Periodica Polytechnica Transportation Engineering  
The practical objective of the article is to assist specialists in identifying risk patterns both from a spatial and casualty point of view.  ...  Several studies have examined a wide range of accident risk factors affecting road safety.  ...  The investigated data describes the main traffic, road geometric and accident parameters from the year 2013 to 2015.  ... 
doi:10.3311/pptr.14692 fatcat:vivmbeap6zhrbfok3556ihdxl4

Evaluating the Effect of Roadway and Development Factors on the Rural Road Safety Risk Index

Shahriar Afandizadeh, Shahab Hassanpour
2020 Advances in Civil Engineering  
Secondly, it aimed to develop a rural road safety risk index based on K-means clustering and Gaussian models.  ...  As roadway and development factors are identified as the most effective factors contributing to road traffic accidents, investigating these factors could lead to reducing the accident frequency rate.  ...  According to several studies, statistical and data mining techniques are proper for analyzing the road accident data [21] [22] [23] [24] . Lee et al.  ... 
doi:10.1155/2020/7820565 fatcat:jkbxss4s7bgvbeld54qkcmzipy

Crash risk analysis for Shanghai urban expressways: A Bayesian semi-parametric modeling approach

Rongjie Yu, Xuesong Wang, Kui Yang, Mohamed Abdel-Aty
2016 Accident Analysis and Prevention  
For the purpose of unveiling crash occurrence mechanisms and further developing Active Traffic Management (ATM) control strategies to improve traffic safety, this study developed disaggregate crash risk  ...  In order to construct more flexible and robust random effects to capture the unobserved heterogeneity, Bayesian semi-parametric inference technique was introduced to crash risk analysis in this study.  ...  Three variables were found to affect crash risk, which are all from upstream traffic detectors.  ... 
doi:10.1016/j.aap.2015.11.029 pmid:26847949 fatcat:co57466xqbcqlcbfg4rcl36we4

Geographical Detection of Traffic Accidents Spatial Stratified Heterogeneity and Influence Factors

Yuhuan Zhang, Huapu Lu, Wencong Qu
2020 International Journal of Environmental Research and Public Health  
However, road factors, lighting, topography, etc., only have a certain impact on fatalities.  ...  The purpose of this paper is to investigate the existence of stratification heterogeneity in traffic accidents in Shenzhen, what factors influence the casualties, and the interaction of those factors.  ...  In order to narrow this gap, the Traffic Management Research Institute of the Ministry of Public Security launched a pilot data-mining activity of traffic accidents in Shenzhen, which have provided traffic  ... 
doi:10.3390/ijerph17020572 pmid:31963135 pmcid:PMC7013890 fatcat:n5hrbzjsgjhatb4ugyddxqgdeq

Spatio-Temporal Clustering of Road Accidents in Kelantan, Malaysia

Wan Fairos Wan Yaacob, Shahirah Binti Ibrahim, Ainin Sorfina Afizan, Nur Azreen Faizul Azran, Syerina Azlin Md Nasir, Norazlina Che Harun
2021 International Journal of Academic Research in Business and Social Sciences  
The findings from this study can be used by the authorities in preventing and reducing the statistics of road accident cases in Kelantan and can be further utilized by the other states in Malaysia.  ...  Analysis of spatio-temporal is utilized to identify the hotspot areas of high-risk road accidents by mapping spatio-temporal heterogeneity road accidents' cases of ten districts in Kelantan by day.  ...  This research received no specific grant from any funding agency in the public, commercial, or not-for profit sectors.  ... 
doi:10.6007/ijarbss/v11-i9/11036 fatcat:kg5ui7dbx5ehfbwrfap34sdfce

Traffic Accidents Analysis using Self-Organizing Maps and Association Rules for Improved Tourist Safety

Andreas Gregoriades, Andreas Christodoulides
2017 Proceedings of the 19th International Conference on Enterprise Information Systems  
risks.  ...  Raw accident obtained from Police records, underwent pre-processing and subsequently was integrated with secondary traffic-flow data from a mesoscopic simulation.  ...  . >160 Km/h and traffic flow i.e. greater than the capacity of the road section) were discovered and were excluded from the dataset.  ... 
doi:10.5220/0006356204520459 dblp:conf/iceis/GregoriadesC17 fatcat:i7zpwwwywrblvnsspcbi3ed4tm

Analyzing Factors Associated with Fatal Road Crashes: A Machine Learning Approach

Ali J. Ghandour, Huda Hammoud, Samar Al-Hajj
2020 International Journal of Environmental Research and Public Health  
Road traffic injury accounts for a substantial human and economic burden globally. Understanding risk factors contributing to fatal injuries is of paramount importance.  ...  In this study, we proposed a model that adopts a hybrid ensemble machine learning classifier structured from sequential minimal optimization and decision trees to identify risk factors contributing to  ...  The LRAP database compiles national traffic data by crowdsourcing reported road crashes in Lebanon from social media consolidated mainly from three credible sources: Traffic Management Authority, Civil  ... 
doi:10.3390/ijerph17114111 pmid:32526945 fatcat:bbtjun6dezgdjch5kkvvhgg3zm

A Novel Approach to Assessing Road-Curve Crash Severity

Andry Rakotonirainy, Samantha Chen, Bridie Scott-Parker, Seng Wai Loke, Shonali Krishnaswamy
2014 Journal of Transportation Safety & Security  
Text mining is a novel methodology to improve knowledge related to risk and contributing factors to road-curve crash severity.  ...  the increased risk of crash on road-curves.  ...  Data mining techniques Data mining is a process of knowledge discovery from large data sets by combining methods from statistics and artificial intelligence.  ... 
doi:10.1080/19439962.2014.959585 fatcat:pq3tqr6zvrfcxclaoe33izwjvu


Muneer A.S. Hazaa, Faculty of Computer Sciences and Information Systems, Thamar University, Thamar, Yemen., Redhwan M.A. Saad, Mohammed A. Alnaklani, Faculty of Engineering and Architecture, Ibb University, Ibb, Yemen., Faculty of Computer Sciences and Information Systems, Thamar University, Thamar, Yemen.
2019 International Journal of Software Engineering and Computer Systems  
In addition, this paper proposed a model for predicting traffic accidents based on dataset obtained from the Directorate General of Traffic Statistics, Ibb, Yemen.  ...  There are several methods used in the process of forecasting traffic accidents such as classification, assembly, association, etc.  ...  (Perone, 2015) , predicted the risk of traffic accidents in the city of Porto Alleger, Brazil.  ... 
doi:10.15282/ijsecs.5.1.2019.6.0056 fatcat:s6tx4xrw5fgxznvnpe35u576xe

Application of Principal Component Analysis for Outlier Detection in Heterogeneous Traffic Data

Pritam Saha, Nabanita Roy, Deotima Mukherjee, Ashoke Kumar Sarkar
2016 Procedia Computer Science  
Level-of-service (LOS) measures of two-lane highways exhibit incompatibility if the prevailing traffic is heterogeneous in character.  ...  However, heterogeneity in the traffic mix results in the presence of significant proportion of outliers in the data set, which can distort the results and render into misleading or useless outcomes.  ...  They share the same road space and thereby, exhibit heterogeneity in the traffic mix because of large speed differential among them.  ... 
doi:10.1016/j.procs.2016.04.105 fatcat:hyglssrwirf27mdjytjzhmy4bi

Method of Identifying Low Performance Vehicles in Heterogeneous Traffic on Two-Lane Highways

Pritam Saha, Antaripa Bhadra, Nagendra S. Reddy, Ashoke Kumar Sarkar
2013 Procedia - Social and Behavioral Sciences  
This paper demonstrates a method of identifying low performance vehicles in heterogeneous traffic on two-lane highways.  ...  These vehicles in turn affect the traffic performance and therefore considered as low performance vehicles.  ...  Unlike homogeneous traffic stream, the heterogeneous behaviour is commonly characterized by lack of lane discipline and increased risk ability of driver population.  ... 
doi:10.1016/j.sbspro.2013.11.146 fatcat:w4v3fi6x4bglbkxingsxm6wcna
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