Modern data sources and techniques for analysis and forecast of road accidents: A review

Afzaal, 2018, Real time traffic incident detection by using twitter stream analysis, 620 Ahmed, 2012, The viability of using automatic vehicle identification data for real-time crash prediction, IEEE Transactions on Intelligent Transportation Systems, 13, 459, 10.1109/TITS.2011.2171052 Ait-Mlouk, 2019, DM-MCDA: a web-based platform for data mining and multiple criteria decision analysis: a case study on road accident, SoftwareX, 10, 100323, 10.1016/j.softx.2019.100323 Ait-Mlouk, 2017, An improved approach for association rule mining using a multi-criteria decision support system: a case study in road safety, European Transport Research Review, 9, 40, 10.1007/s12544-017-0257-5 Akaike, 1987, Factor analysis and AIC, Psychometrika, 52, 317, 10.1007/BF02294359 Alkheder, 2017, Severity prediction of traffic accident using an artificial neural network, Journal of Forecasting, 36, 100, 10.1002/for.2425 Amin-Naseri, 2018, Evaluating the reliability, coverage, and added value of crowdsourced traffic incident reports from Waze, Transportation Research Record, 2672, 34, 10.1177/0361198118790619 Anantharam, 2015, Extracting city traffic events from social streams, ACM Transactions on Intelligent Systems and Technology, 6, 1, 10.1145/2717317 2019 Bao, 2019, A spatiotemporal deep learning approach for citywide short-term crash risk prediction with multi-source data, Accident Analysis and Prevention, 122, 239, 10.1016/j.aap.2018.10.015 Bao, 2017, Incorporating twitter-based human activity information in spatial analysis of crashes in urban areas, Accident Analysis and Prevention, 106, 358, 10.1016/j.aap.2017.06.012 Beshah, 2011, Pattern recognition and knowledge discovery from road traffic accident data in Ethiopia: implications for improving road safety Breslow, 1997 Cao, 2015, Cluster-based correlation of severe braking events with time and location, Journal of Intelligent Transportation Systems, 20, 187 Castro, 2016, Data mining on road safety: factor assessment on vehicle accidents using classification models, International Journal of Crashworthiness, 21, 104, 10.1080/13588265.2015.1122278 Chen, 2018, SDCAE: stack denoising convolutional autoencoder model for accident risk prediction via traffic big data Chen, 2016, Learning deep representation from big and heterogeneous data for traffic accident inference Chen, 2017, A convolutional neural network for traffic information sensing from social media text Çodur, 2015, An artificial neural network model for highway accident prediction: a case study of Erzurum, Turkey, Promet-Traffic-Transportation, 27, 217, 10.7307/ptt.v27i3.1551 D'Andrea, 2015, Real-time detection of traffic from twitter stream analysis, IEEE Transactions on Intelligent Transportation Systems, 16, 2269, 10.1109/TITS.2015.2404431 Dabiri, 2019, Developing a twitter-based traffic event detection model using deep learning architectures, Expert Systems with Applications, 118, 425, 10.1016/j.eswa.2018.10.017 Dacos Gov Co, 2019 Data Gov, 2019 Data. Gov. UK, 2019 Delen, 2006, Identifying significant predictors of injury severity in traffic accidents using a series of artificial neural networks, Accident Analysis and Prevention, 38, 434, 10.1016/j.aap.2005.06.024 De Oña, 2013, Analysis of traffic accidents on rural highways using latent class clustering and Bayesian networks, Accident Analysis and Prevention, 51, 1, 10.1016/j.aap.2012.10.016 Depaire, 2008, Traffic accident segmentation by means of latent class clustering, Accident Analysis and Prevention, 40, 1257, 10.1016/j.aap.2008.01.007 Fan, 2017, Context-aware big data analytics and visualization for city-wide traffic accidents Fan, 2015, Big data analytics and visualization with spatio-temporal correlations for traffic accidents Fawcett, 2017, A novel Bayesian hierarchical model for road safety hotspot prediction, Accident Analysis and Prevention, 99, 262, 10.1016/j.aap.2016.11.021 Fraley, 1998, How many clusters? which clustering method? answers via model-based cluster analysis, The Computer Journal, 41, 578, 10.1093/comjnl/41.8.578 Gey, 2005, Model selection for CART regression trees, IEEE Transactions on Information Theory, 51, 658, 10.1109/TIT.2004.840903 Ghosh, 2017, Bayesian prediction of the duration of non-recurring road incidents Gu, 2016, From twitter to detector: real-time traffic incident detection using social media data, Transportation Research Part C: Emerging Technologies, 67, 321, 10.1016/j.trc.2016.02.011 Gutierrez-Osorio, 2019, Characterizing road accidents in urban areas of Bogota (Colombia): a data science approach Halim, 2016, Artificial intelligence techniques for driving safety and vehicle crash prediction, Artificial Intelligence Review, 46, 351, 10.1007/s10462-016-9467-9 Hashmienejad, 2017, Traffic accident severity prediction using a novel multi-objective genetic algorithm, International Journal of Crashworthiness, 22, 425, 10.1080/13588265.2016.1275431 Jain, 2000, Data clustering: a review, ACM Computing Survey, 31, 264, 10.1145/331499.331504 Janssen, 2012, Benefits, adoption barriers and myths of open data and open government, Information Systems Management, 29, 258, 10.1080/10580530.2012.716740 Kaplan, 2013, Cyclist-motorist crash patterns in Denmark: a latent class clustering approach, Traffic Injury Prevention, 14, 725, 10.1080/15389588.2012.759654 Kononen, 2011, Identification and validation of a logistic regression model for predicting serious injuries associated with motor vehicle crashes, Accident Analysis and Prevention, 43, 112, 10.1016/j.aap.2010.07.018 Krishnaveni, 2011, A perspective analysis of traffic accident using data mining techniques, International Journal of Computer Applications, 23, 40, 10.5120/2896-3788 Kumar, 2016, A data mining approach to characterize road accident locations, Journal of Modern Transportation, 24, 62, 10.1007/s40534-016-0095-5 Kumar, 2015, A data mining framework to analyze road accident data, Journal of Big Data, 2, 10.1186/s40537-015-0035-y Kumar, 2015, Analyzing road accident data using association rule mining Kumar, 2016, Analysis of hourly road accident counts using hierarchical clustering and cophenetic correlation coefficient (CPCC), Journal of Big Data, 3, 10.1186/s40537-016-0046-3 Kumar, 2012, Analysis of Bayes, neural network and tree classifier of classification technique in data mining using WEKA, Computer Science and Information Technology (CS & IT), 2, 359 Kunt, 2011, Prediction for traffic accident severity: comparing the artificial neural network, genetic algorithm, combined genetic algorithm and pattern search methods, Transport, 26, 353, 10.3846/16484142.2011.635465 Li, 2020, Real-time crash risk prediction on arterials based on LSTM-CNN, Accident Analysis and Prevention, 135, 105371, 10.1016/j.aap.2019.105371 Lin, 2015, A novel variable selection method based on frequent pattern tree for real-time traffic accident risk prediction, Transportation Research Part C: Emerging Technologies, 55, 444, 10.1016/j.trc.2015.03.015 Lu, 2017, A model of traffic accident prediction based on convolutional neural network Lu, 2018, Using Adverse weather data in social media to assist with city-level traffic situation awareness and alerting, Applied Sciences, 8, 10.3390/app8071193 Ma, 2006, Crash modeling using clustered data from Washington state: prediction of optimal speed limits Moghaddam, 2011, Prediction of accident severity using artificial neural networks, International Journal of Civil Engineering, 9, 41 Mohamed, 2013, A clustering regression approach: a comprehensive injury severity analysis of pedestrian-vehicle crashes in New York, US and Montreal, Canada, Safety Science, 54, 27, 10.1016/j.ssci.2012.11.001 Moriya, 2018, Traffic risk mining from heterogeneous road statistics, IEEE Transactions on Intelligent Transportation Systems, 19, 3662, 10.1109/TITS.2018.2856533 Nguyen, 2016, TrafficWatch: real-time traffic incident detection and monitoring using social media Ozbayoglu, 2016, A real-time autonomous highway accident detection model based on big data processing and computational intelligence Pandhare, 2017, Real time road traffic event detection using twitter and spark Park, 2016, Highway traffic accident prediction using VDS big data analysis, The Journal of Supercomputing, 72, 2815, 10.1007/s11227-016-1624-z Powers, 2011 Ren, 2017, A deep learning approach to the citywide traffic accident risk prediction Roshandel, 2015, Impact of real-time traffic characteristics on freeway crash occurrence: systematic review and meta-analysis, Accident Analysis and Prevention, 79, 198, 10.1016/j.aap.2015.03.013 Salas, 2017, Traffic event detection framework using social media Salas, 2018, Incident detection using data from social media Scott-Parker, 2017, Young driver risky behaviour and predictors of crash risk in Australia, New Zealand and Colombia: same but different?, Accident Analysis and Prevention, 99, 30, 10.1016/j.aap.2016.11.001 Shi, 2015, Big data applications in real-time traffic operation and safety monitoring and improvement on urban expressways, Transportation Research Part C: Emerging Technologies, 58, 380, 10.1016/j.trc.2015.02.022 Sinnott, 2015, Accident black spot identification and verification through social media Sun, 2016, Big data mobile services for New York City taxi riders and drivers Taamneh, 2017, Data-mining techniques for traffic accident modeling and prediction in the United Arab Emirates, Journal of Transportation Safety and Security, 9, 146, 10.1080/19439962.2016.1152338 Tiwari, 2017, Performance evaluation of lazy, decision tree classifier and multilayer perceptron on traffic accident analysis, Informatica, 41, 39 The Global Goals, 2017 Veljković, 2014, Benchmarking open government: an open data perspective, Government Information Quarterly, 31, 278, 10.1016/j.giq.2013.10.011 Wang, 2017, Real-time traffic event detection from social media, ACM Transactions on Internet Technology, 18, 1 Wang, 2019, Crash prediction based on traffic platoon characteristics using floating car trajectory data and the machine learning approach, Accident Analysis and Prevention, 133, 105320, 10.1016/j.aap.2019.105320 Wang, 2016, Enhancing traffic congestion estimation with social media by coupled hidden markov model World Health Organization, 2015 Wu, 2008, Top 10 algorithms in data mining, Knowledge and Information System, 14, 1, 10.1007/s10115-007-0114-2 Xiong, 2017, A new framework of vehicle collision prediction by combining SVM and HMM, IEEE Transactions on Intelligent Transportation System, 19, 1 You, 2017, Real-time crash prediction on freeways using data mining and emerging techniques, Journal of Modern Transportation, 25, 116, 10.1007/s40534-017-0129-7 Yuan, 2018, Approach-level real-time crash risk analysis for signalized intersections, Accident Analysis and Prevention, 119, 274, 10.1016/j.aap.2018.07.031 Yuan, 2017, Predicting traffic accidents through heterogeneous urban data: a case study Zhang, 2011, Fundamentals of association rules in data mining and knowledge discovery, WIREs Data Mining and Knowledge Discovery, 1, 97, 10.1002/widm.10 Zhang, 2018, A deep learning approach for detecting traffic accidents from social media data, Transportation Research Part C: Emerging Technologies, 86, 580, 10.1016/j.trc.2017.11.027 Zheng, 2019, Traffic accident's severity prediction: a deep-learning approach-based CNN network, IEEE Access, 7, 39897, 10.1109/ACCESS.2019.2903319 Zheng, 2014, Driving risk assessment using cluster analysis based on naturalistic driving data, 2584