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Clustering Algorithms to Analyze the Road Traffic Crashes
[article]
2021
arXiv
pre-print
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Points To Identify the Clustering Structure (OPTICS) to overcome them. ...
Comparative performance analysis based on real-life data on the recorded cases of road accidents in North Carolina also show more effectiveness and efficiency achieved by these algorithms. ...
ACKNOWLEDGMENT We would like to thank the Institute of Energy, Environment, Research, and Development (IEERD, UAP) and the University of Asia Pacific for financial support. ...
arXiv:2108.03490v1
fatcat:hstmyqxotzg7jjgnrhh552l2r4
Identify Road Clusters with High-Frequency Crashes Using Spatial Data Mining Approach
2019
Applied Sciences
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The conceptualization of crash–road spatial relationships is established using crash spatial aggregation algorithm. ...
The first step, preprocessing, is to store the roads and crashes in a spatial database. The second step is to describe the conceptualization of road–road and crash–road spatial relationships. ...
Methods
Crash Spatial Aggregation Algorithm To find the RCHC, we should aggregate crashes in roads as the count of traffic crashes on the road. ...
doi:10.3390/app9245282
fatcat:umageu4apzao3dadjkmzkr7hqe
The impact of vehicle moving violations and freeway traffic flow on crash risk: An application of plugin development for microsimulation
2017
PLoS ONE
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This paper presents the use of the Aimsun microsimulation program to simulate vehicle violating behaviors and observe their impact on road traffic crash risk. ...
A Fuzzy C-mean Clustering algorithm was developed to identify high risk states in different road segments over time. ...
Introduction Vehicle moving violations are a major cause of traffic crashes and road fatalities, contributing to 75% of road crashes in China [1] , 50% of all fatal crashes in Europe [2] , and 56% of ...
doi:10.1371/journal.pone.0184564
pmid:28886141
pmcid:PMC5590972
fatcat:nytn2avrenf5fj2b4nas5z5q54
A Parallel FP-Growth Mining Algorithm with Load Balancing Constraints for Traffic Crash Data
2022
International Journal of Computers Communications & Control
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for massive amounts of traffic crash data; then, according to the results of the coupling mechanism among the crash precursors, the causes of freeway traffic crashes were identified and revealed. ...
This improved algorithm makes full use of Hadoop cluster resources and is more suitable for large traffic crash data sets mining while retaining the original advantages of conventional association rule ...
The authors' contributions are as follows: Yang Yang (Conceptualization, Methodology, Formal analysis, Investigation, Validation, Writing-original draft, Writing-review & editing, Funding acquisition, ...
doi:10.15837/ijccc.2022.4.4806
fatcat:leltkuljzbeibkz5lvafass4pe
Mining of the Correlations for Fatal Road Accident using Graph-based Fuzzified FP-Growth Algorithm
2020
International Journal of Engineering and Advanced Technology
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FP Growth Algorithm, Support Vector Machine (SVM) Cluster classification models and simple C-means clustering Algorithm formed Association laws. ...
The findings suggest that the algorithm proposed is more efficient and faster than the algorithm of the previous research. ...
To identify problems, the program collects data for the analyzes of road safety crashes and assesses counter-measures to reduce injury and property damage arising out of crashes. ...
doi:10.35940/ijeat.e9526.069520
fatcat:xkhni744xbczbhjcsqfo25llhq
Predicting Freeway Traffic Crash Severity Using XGBoost-Bayesian Network Model with Consideration of Features Interaction
2022
Journal of Advanced Transportation
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This research aims to explore the influence of road and environmental factors on the severity of a freeway traffic crash and establish a prediction model towards freeway traffic crash severity. ...
In the field of freeway traffic safety research, there is an increasing focus in studies on how to reduce the frequency and severity of traffic crashes. ...
impact of objective factors on traffic crashes and established a cumulative logistic model to analyze their impact on the severity of traffic crashes. rough the goodness of fit and prediction accuracy ...
doi:10.1155/2022/4257865
fatcat:s27fxkjvqvdpvkyryfg4pdgk3u
Integration of Probability and Clustering Based Approaches in the Field of Black Spot Identification
2018
Periodica polytechnica. Civil engineering
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The objective of the paper is to define a complex methodology to analyze black spot locations of road infrastructure network combining the benefit of both; Empirical Bayes method and K-mean clustering ...
In the first step, K-mean algorithm is used to define homogeneous accident clusters. ...
Empirical Bayesian After applying K-mean clustering to divide the road into segments based on the similarity of the analyzed accidents, as described in section 2, it is required now to evaluate the level ...
doi:10.3311/ppci.11753
fatcat:umuqzherlbanpoajiwmuo2jigq
Traffic Accident Data Profiling and Clusteringwith Data Mining Process
2012
IOSR Journal of Computer Engineering
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The significance of the study lies on the profiling of clusters of traffic roads in terms of accident related data and the degree in which these accident characteristics are perceptive between the different ...
Applying data mining process to model traffic accident data records helped in obtaining the characteristics of drivers' behaviour, road condition and weather condition that are connected with different ...
Conclusion In this study, the association algorithm was used on a data set of traffic accidents to profile the two clusters of traffic roads. ...
doi:10.9790/0661-0621422
fatcat:gneg334awvd3fdk3xbyotppppe
Applying machine learning and geolocation techniques to social media data (Twitter) to develop a resource for urban planning
2021
PLoS ONE
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Using a spatial clustering algorithm, we are able to locate portions of the road network (<1%) where 50% of the crashes identified occurred. ...
The research project scraped 874,588 traffic related tweets in Nairobi, Kenya, applied a machine learning model to capture the occurrence of a crash, and developed an improved geoparsing algorithm to identify ...
We appreciate comments from anonymous reviewers and participants at the ACM COMPASS Conference and the Netmob Conference. ...
doi:10.1371/journal.pone.0244317
pmid:33534801
fatcat:rasxqeyd7jf2niluergc5fyowm
A Review on Injury Severity in Traffic System using Various Data Mining Techniques
2014
International Journal of Computer Applications
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The objective of this study is to evaluate a set of variables that contribute to the degree of injury severity in traffic crashes. ...
The study on road traffic accident causes can identify the key factors rapidly, efficiently and provide instructional methods to the traffic accidents prevention and road traffic accidents reduction, which ...
Hence many previous studies have used models with ordered structure to analyze risk factors and their effect on severity of injuries sustained in traffic crashes. ...
doi:10.5120/17506-8056
fatcat:xyjjamkcgvbzhciemn6aahox6m
A clustering regression approach: A comprehensive injury severity analysis of pedestrian–vehicle crashes in New York, US and Montreal, Canada
2013
Safety Science
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The methodologies used in this research are described in the third section: a clustering algorithm and injury severity regression model are applied to the whole dataset and to each cluster. ...
Since pedestrians are vulnerable road users and suffer more in road crashes, it is important to understand the factors affecting pedestrian injury severity levels. ...
With respect to traffic control, signalized traffic control represents approximately 92.0 % of the crashes in this cluster. ...
doi:10.1016/j.ssci.2012.11.001
fatcat:hetsxq2uz5gwxkamm4bjl4eckm
Spatial point analysis of road crashes in Shanghai: A GIS-based network kernel density method
2011
2011 19th International Conference on Geoinformatics
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As road crashes are constrained to a one-dimensional space, this paper analyzes the spatial distribution of road crashes with a GIS-based network-constrained kernel density method. ...
Different bandwidths may be considered for different types of traffic crashes. ...
ACKNOWLEDGMENT The authors would like to thank Mr. Lei Fang for his valuable comments and other help. ...
doi:10.1109/geoinformatics.2011.5980938
fatcat:wb2freuo65a4nmirtbp24nep54
Urban Traffic Accident Features Investigation to Improve Urban Transportation Infrastructure Sustainability by Integrating GIS and Data Mining Techniques
2023
Sustainability
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To our knowledge, this is the first time in which these three methods are applied simultaneously for analyzing traffic accidents. ...
To decrease the frequency of accidents, it is crucial to analyze accident data to determine the relationship between accidents and causes, especially for serious accidents. ...
The authors refer to this cluster as "Single-vehicle motorbike crashes". ...
doi:10.3390/su16010107
fatcat:fv4kcxtzlfgobivwohp52uj5dm
Modeling Crash Severity and Collision Types Using Machine Learning
2022
Zenodo
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Theoretically, the traffic collision type and crash severity type can be correlated, and thus, it is intuitive to model them simultaneously. ...
Similar clustering approach was also tested at the county-level to understand the spatial behavior and thus transferability of the MLC approach to other key cities in the state. ...
Acknowledgements The authors would like to thank Transportation Consortium of South-Central States (Tran-SET) for providing the essential platform and financial support to make this research possible. ...
doi:10.5281/zenodo.6615740
fatcat:inknswzafra6dlyh24gsvwt6o4
What You Eat Matters Road Safety: A Data Mining Approach
2016
Indian Journal of Science and Technology
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Background/Objectives: To assess the influence of dietary habit on driving performance of a driver and its impact on road traffic accident to ensure road safety. ...
Findings: The result indicates that driver's dietary habit can be one of the factors to road traffic accident along with driver's license type and status, gender and type of road. ...
The authors in 3 suggested a new real time crash prediction model using Bayesian Network as a modeling method and clustering method to find out road accidents which share the same crash risk factor by ...
doi:10.17485/ijst/2016/v9i15/92119
fatcat:ykknwlk3pbbsnhyexfyoon4k6q
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