Predicting crash likelihood and severity on freeways with real-time loop detector data

Xu, Chengcheng; Tarko, Andrew P.; Wang, Weixu; Liu, Pan

doi:10.1016/j.aap.2013.03.035

Cited by 182 publications

(99 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…2011; Xu et al 2012;Abdel-Aty et al 2012;Xu et al 2013;Ahmed and Abdel-Aty 2013;Xu et al 2014). In these studies, several traffic flow related attributes, including, but not limited to, "absolute speed", "variation of speed", "speed difference between upstream and downstream loop detectors", "traffic density", "average occupancy", and etc.…”

Section: Accepted Manuscriptmentioning

confidence: 99%

Application of a Rule-Based Approach in Real-Time Crash Risk Prediction Model Development Using Loop Detector Data

Pirdavani

Pauw

Brijs

et al. 2015

Traffic Injury Prevention

View full text Add to dashboard Cite

Objectives: There is a growing trend in development and application of real-time crash risk prediction models within dynamic safety management systems. These real-time crash risk prediction models are constructed by associating crash data with the real-time traffic surveillance data (e.g. collected by loop detectors). The main objective of this paper is to develop a real-time risk model that will potentially be utilized within traffic management systems. This model aims to predict the likelihood of crash occurrence on motorways. Methods:In this study, the potential prediction variables are confined to traffic related characteristics. Given that the dependent variable (i.e. traffic safety condition) is dichotomous Conclusions:The findings of this study can be used to predict the likelihood of crash occurrence on motorways within dynamic safety management systems.

show abstract

Section: Accepted Manuscriptmentioning

confidence: 99%

Application of a Rule-Based Approach in Real-Time Crash Risk Prediction Model Development Using Loop Detector Data

Pirdavani

Pauw

Brijs

et al. 2015

Traffic Injury Prevention

View full text Add to dashboard Cite

show abstract

“…In doing so, the binary logistic regression modeling framework was utilized due to having only two possible outcomes-1 if BIM increases safety and 0 otherwise. This modeling framework has been utilized and presented in transportation safety literature [30][31][32][33], yet applying this econometric technique with regard to construction safety is scarce. With that in mind, to determine the probability that the outcome takes the value 1 (e.g., BIM increases safety), the following binary logit form applies [34]:…”

Section: Analysis Using Econometric Modellingmentioning

confidence: 99%

Opportunities for Using Building Information Modeling to Improve Worker Safety Performance

Alomari

Gambatese

Anderson

2017

Safety

View full text Add to dashboard Cite

Building information modelling (BIM) enables the creation of a digital representation of a designed facility combined with additional information about the project attributes, performance criteria, and construction process. Users of BIM tools point to the ability to visualize the final design along with the construction process as a beneficial feature of using BIM. Knowing the construction process in relationship to a facility's design benefits both safety professionals when planning worker safety measures for a project and designers when creating a project's design. Success in using BIM to enhance safety partly depends on the familiarity of project personnel with BIM tools and the extent to which the tools can be used to identify and eliminate safety hazards. In a separate, ongoing study, the authors investigated the connection between BIM and safety to document the opportunities, barriers, and impacts. Utilizing an on-line survey of project engineers who work for construction firms together with a comprehensive literature review, the study found those who use BIM feel that it aids in communication of project information and project delivery, both of which have been found to have positive impacts on construction site safety. Further, utilizing the survey results, the authors apply the binary logistic regression econometric framework to better understand the factors that lead to safety professionals believing that BIM increases safety in the work place. In addition, according to the survey results, a large percentage of the engineers who use BIM feel that ultimately it helps to eliminate safety hazards and improve worker safety. The study findings suggest that improvements in safety performance across the construction industry may be due in part to increased use of BIM in the construction industry.

show abstract

“…Earlier, Shankar et al (1996) stated that crash severity investigations had been historically limited to the localization of fatalities, even though the estimation of the other severity levels (i.e., property damage only-PDO -, possible injury, non-incapacitating injury) could help in understanding the benefits of safety-improvement projects. Seventeen years later, Xu et al (2013) again underlined that most influencing crashes along road segments. Data on crashes, traffic and the weather database of Turin's road network (Italy) were collected and used to calibrate and validate predictive models of crash severity.…”

Section: Introductionmentioning

confidence: 99%

“…Specifically, Theofilatos & Yannis (2014) pointed out that the few papers available mainly deal with roads operating under uninterrupted flow conditions, and recur mainly to logit modelling (Al-Ghamdi 2002, Golob et al 2008, Christoforou et al 2010, Jung et al 2010, Xu et al 2013, Yu & Abdel-Aty 2013. Earlier, Shankar et al (1996) stated that crash severity investigations had been historically limited to the localization of fatalities, even though the estimation of the other severity levels (i.e., property damage only-PDO -, possible injury, non-incapacitating injury) could help in understanding the benefits of safety-improvement projects.…”

Section: Introductionmentioning

confidence: 99%

The influence of pedestrian crossings features on driving behavior and road safety

Bichicchi¹,

Mazzotta²,

Lantieri³

et al. 2017

Transport Infrastructure and Systems

View full text Add to dashboard Cite

The paper deals with the identification of variables and models that can explain why a certain Severity Level (SL) may be expected in the event of a certain type of crash at a specific point of an urban road network. Two official crash records, a weather database, a traffic data source, and information on the characteristics of the investigated urban road segments of Turin (Italy) for the seven years from 2006 to 2012 were used. Examination of the full database of 47,592 crash events, including property damage only crashes, reveals 9,785 injury crashes occurring along road segments only. Of these, 1,621 were found to be associated with a dataset of traffic flows aggregated in 5 minutes for the 35 minutes across each crash event, and to weather data recorded by the official weather station of Turin. Two different approaches, a back-propagation neural network model and a generalized linear mixed model were used. Results show the impact of flow and other variables on the SL that may characterize a crash; differences in the significant variables and performance of the two modelling approaches are also commented on in the manuscript.of the research studies have been focused on the likelihood of a crash without considering the crash outcome severity.

show abstract

Predicting crash likelihood and severity on freeways with real-time loop detector data

Cited by 182 publications

References 38 publications

Application of a Rule-Based Approach in Real-Time Crash Risk Prediction Model Development Using Loop Detector Data

Application of a Rule-Based Approach in Real-Time Crash Risk Prediction Model Development Using Loop Detector Data

Opportunities for Using Building Information Modeling to Improve Worker Safety Performance

The influence of pedestrian crossings features on driving behavior and road safety

Contact Info

Product

Resources

About