2019
DOI: 10.1016/j.aap.2018.12.022
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Real-time crash prediction models: State-of-the-art, design pathways and ubiquitous requirements

Abstract: Proactive traffic safety management systems can monitor traffic conditions in real-time, identify the formation of unsafe traffic dynamics, and implement suitable interventions to bring unsafe conditions back to normal traffic situations. Recent advancements in artificial intelligence, sensor fusion and algorithms have brought about the introduction of a proactive safety management system closer to reality. The basic prerequisite for developing such a system is to have a reliable crash prediction model that ta… Show more

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Cited by 124 publications
(34 citation statements)
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“…High temporal resolution traffic data allows the precise identification of traffic conditions at the time of each accident. As accidents are rare events, obtaining large sample sizes of accidents with corresponding traffic volume data is difficult [50]. Large traffic volume datasets increase the likelihood that an accident can be paired with volume data, increasing the final sample size of accidents useable for analysis.…”
Section: Relationship Between Traffic Volume and Accident Frequencymentioning
confidence: 99%
See 1 more Smart Citation
“…High temporal resolution traffic data allows the precise identification of traffic conditions at the time of each accident. As accidents are rare events, obtaining large sample sizes of accidents with corresponding traffic volume data is difficult [50]. Large traffic volume datasets increase the likelihood that an accident can be paired with volume data, increasing the final sample size of accidents useable for analysis.…”
Section: Relationship Between Traffic Volume and Accident Frequencymentioning
confidence: 99%
“…Large traffic volume datasets increase the likelihood that an accident can be paired with volume data, increasing the final sample size of accidents useable for analysis. Hossain et al [50] note that only 30 studies in their comprehensive review had sample sizes larger than 500. Comparing this to n = 1629 in this study highlights another point where additional detail was able to be captured.…”
Section: Relationship Between Traffic Volume and Accident Frequencymentioning
confidence: 99%
“…The ability to monitor traffic conditions in real-time and act to reduce accident prone conditions before they can fully develop is the ultimate goal, with models being critical tools to obtain a predictive understanding of accident risk. A comprehensive review of real-time crash prediction models has recently been presented by Hossain, Abdel-Aty, Quddus, Muromachi and Sadeek [19]. Most models reviewed use empirical, multidimensional methods with different approaches of factor pre-selection.…”
Section: Applicationsmentioning
confidence: 99%
“…Most models reviewed use empirical, multidimensional methods with different approaches of factor pre-selection. Models showed a dominance of Bayesian approaches, suggesting an importance of using informative priors in these models [19]. Performance increases in models are thus based on our understanding of causative factors.…”
Section: Applicationsmentioning
confidence: 99%
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