Bayesian estimation of conflict-based safety performance functions

Sacchi, Emanuele; Sayed, Tarek

doi:10.1080/19439962.2015.1030807

Cited by 36 publications

(15 citation statements)

References 25 publications

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“…A large number of studies on crash prediction models were mainly carried out from the aspects of crash frequency estimation and the crash severity prediction at the macro level (e.g., yearly, monthly) [3][4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Predicting Crash Frequency for Urban Expressway considering Collision Types Using Real-Time Traffic Data

Zhang

et al. 2020

Journal of Advanced Transportation

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Current studies on traffic crash prediction mainly focus on the crash frequency and crash severity of freeways or arterials. However, collision type for urban expressway crash is rarely considered. Meanwhile, with the rapid development of urban expressway systems in China in recent years, traffic safety problems have attracted more attention. In addition, the traffic characteristics are considered to be a potentially important predictor of traffic accidents; however, their impact on crashes has been controversial. Therefore, a crash frequency predicting model for urban expressway considering collision types is proposed in this study. The loop detector traffic data and historical crash data were aggregated based on the similarities of the traffic conditions 5 minutes before crash occurrence, among which crashes were divided by collision type (rear-end collision and side-impact collision). The impact of traffic characteristics along with weather variables as well as their interactions on crash frequency was modelled by using negative binomial regression model. The results indicated that the influence of traffic and weather factors on two collision types shared similar trend, but different level. For rear-end collisions, crash frequency increased with lower average speed and high traffic volume under low speed limit. And when the speed limit is high, higher average speed coupled with larger volume increases the probability of crash. Higher average speed and traffic volume increase the probability of side-impact collisions, without being affected by the speed limit. The findings of the present study could help to determine efficient safety countermeasures aimed at improving the safety performance of urban expressway.

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Section: Introductionmentioning

confidence: 99%

Predicting Crash Frequency for Urban Expressway considering Collision Types Using Real-Time Traffic Data

Zhang

et al. 2020

Journal of Advanced Transportation

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“…The first approach has been criticized due to its reactive nature and the fact that it cannot provide early warning information to empower authorities to take action prior to accidents. Thus, there has been a shift towards using leading indicators, such as unsafe behaviors, to more effectively measure the regulatory alignment and secure traffic safety goals [19,20].…”

Section: Introductionmentioning

confidence: 99%

An Investigation into Unsafe Behaviors and Traffic Accidents Involving Unlicensed Drivers: A Perspective for Alignment Measurement

Boulagouas

Herrero

Chaib

et al. 2020

IJERPH

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Road traffic plays a vital role in countries’ economic growth and future development. However, traffic accidents are considered a major public health issue affecting humankind. Despite efforts by governments to improve traffic safety, the misalignment between the policy efforts and on-ground infringements, distractions and breaches reflect the regulatory failure. This paper uses the Bayesian network method to investigate unsafe behaviors and traffic accidents involving unlicensed drivers as a perspective for the regulatory alignment assessment. The findings suggest that: (1) unlicensed drivers are more likely to have unsafe driving behaviors; (2) the probability of being involved in a severe traffic accident increases when the drivers are unlicensed and decreases in the case of licensed drivers; (3) young drivers are noticeably more likely to engage in unsafe behaviors, usually leading to serious injuries and deaths, when their driving licenses are invalid; (4) women are more likely to engage in right-of-way violations and to have collisions with no serious injuries, contrary to unlicensed men drivers, who are involved in other types of traffic accidents resulting in serious injuries.

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“…However, no specific data from a reference population were available for this evaluation. Hence, a conflict-based SPF recently developed for signalized intersection approaches for metropolitan Vancouver, British Columbia, Canada, was used as a reference model (4). Its functional form is given in the following equation:…”

Section: Ba Study By Eb Methodsmentioning

confidence: 99%

“…Moreover, traffic conflicts can provide insight into the failure mechanism that leads to road collisions (1). In fact, traffic conflict data can be modeled from a statistical point of view as nonnegative, discrete, and rare events in a way similar to that in which collision data are modeled (4). As such, it is possible to adopt and transfer the statistical methodologies used for crash-based road safety analysis to conflict-based analysis.…”

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confidence: 99%

Traffic Conflict–Based Before–After Study with Use of Comparison Groups and the Empirical Bayes Method

Reyad

Sacchi

Ibrahim³

et al. 2017

Transportation Research Record: Journal of the Transportation R

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Road safety evaluations mainly rely on the analysis of crash data that are challenged by well-recognized availability and quality issues. The statistical models used to predict the safety level of road sites—that is, safety performance functions—have recently been successfully developed with the use of traffic conflict observations instead of crashes. As such, it is possible to adopt and transfer the statistical techniques used in crash-based road safety analysis to conflict-based analysis. The use of statistically rigorous techniques in crash-based before-and-after (BA) studies is essential for evaluation of the effectiveness of road safety countermeasures. In particular, the use of Bayesian methods, such as the empirical Bayes (EB) technique, is vital to control for confounding factors that can operate simultaneously with the countermeasure and may affect road safety performance. The main objective of this paper was to estimate the treatment effectiveness of two traffic signal (visibility) improvement projects in the city of Edmonton, Alberta, Canada, with a conflict-based BA study using the comparison group and the EB methods. More than 300 h of video data with traffic conflict observations was automatically collected and analyzed by computer vision techniques for two treatment intersections and two control (untreated) intersections before and after the signal improvement projects. The results of the comparison group method showed a statistically significant 24% reduction in the average number of rear-end conflicts per hour, whereas the EB method showed a statistically significant 24.5% reduction in the average number of total conflicts per hour.

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Bayesian estimation of conflict-based safety performance functions

Cited by 36 publications

References 25 publications

Predicting Crash Frequency for Urban Expressway considering Collision Types Using Real-Time Traffic Data

Predicting Crash Frequency for Urban Expressway considering Collision Types Using Real-Time Traffic Data

An Investigation into Unsafe Behaviors and Traffic Accidents Involving Unlicensed Drivers: A Perspective for Alignment Measurement

Traffic Conflict–Based Before–After Study with Use of Comparison Groups and the Empirical Bayes Method

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