Before–after studies in highway safety

Lord, Dominique; Qin, Xiao; Geedipally, Srinivas Reddy

doi:10.1016/b978-0-12-816818-9.00003-2

Cited by 3 publications

(5 citation statements)

References 29 publications

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“…There has been extensive literature focusing on calibration methods applied on HSM-SPFs ( 30 ). For instance, Lord et al ( 31 ) conducted a research study with respect to the existing calibration method in the HSM and attempted to assess when the models should be recalibrated and when region-specific CFs are recommended. Moreover, Shahdah et al ( 32 ) utilized simulated crash data and proposed an integrated CMF to obtain more promising results concerning prediction reliability.…”

Section: Literature Reviewmentioning

confidence: 99%

Developing Economic Loss-Based Thresholds for Improving Context-Specific Crash Prediction Models

Koloushani

Abazari

Khayamim

et al. 2023

Transportation Research Record: Journal of the Transportation R

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Negative binomial-based safety performance functions (SPFs) have been extensively used by United States Department of Transportation professionals for predictive crash analysis. Recently, the Florida Department of Transportation (FDOT) has developed a context classification approach and incorporated it into crash prediction models, which has the potential to significantly enhance their accuracy and reliability. The additional modeling contexts and parameters make it more challenging to diagnose and remedy modeling problems, however. Particularly for roadway segments with low annual average daily traffic (AADT), short lengths, or low counts of severe crashes, the SPF models significantly underestimate the actual number of crashes. This uncertainty in SPF predictions can lead FDOT practitioners to reach misleading conclusions, such as failing to detect sites with genuinely high crash rates. This project intends to establish thresholds for certain SPF parameters to ensure reliable crash predictions are obtained across various context classes. For this purpose, we (a) developed a functional statistical model that quantifies economic loss relative prediction errors as a function of AADT volume and (b) calculated the minimum context-specific AADT threshold for each segment length group, roadway category, context classification, and crash severity combination. Employing the developed AADT thresholds confirmed up to 89% reduction in SPF prediction errors for the most represented context class. In light of the results obtained, we are able to conclude that context-specific AADT thresholds perform well in significantly reducing prediction errors for the thresholded segments and contexts on Florida roadways.

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Section: Literature Reviewmentioning

confidence: 99%

Developing Economic Loss-Based Thresholds for Improving Context-Specific Crash Prediction Models

Koloushani

Abazari

Khayamim

et al. 2023

Transportation Research Record: Journal of the Transportation R

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“…The fatal (K) and incapacitating-injury (A) crash percentages are found to be quite low. This imbalance in the data may introduce a bias in the crash prediction (26,27). To handle this issue, the fatal (K) and incapacitating-injury (A) crashes were combined as KA (severe) crash severity.…”

Section: Variable Descriptionmentioning

confidence: 99%

Multivariate Approach to Peak-Period Models for Crash Types and Severities in Variable Speed Systems on Freeways

Hasan,

Abdel-Aty,

Mahmoud

2023

Transportation Research Record: Journal of the Transportation R

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According to current research, safety performance functions (SPFs) based on traditional annual average daily traffic are less suitable for addressing crash risk in traffic-management strategies that typically operate for short time intervals (e.g., peak period). Variable speed limit (VSL)/variable advisory speed (VAS) is a traffic-management strategy which is deployed to achieve speed harmonization typically during the peak hours of weekdays. However, peak-period SPFs for VSL/VAS-implemented freeways considering different crash types and severity levels are still unexplored. Therefore, in this study the multivariate Poisson lognormal (MVPLN) method was applied to estimate the different crash-type and severity-level models. The results showed that by addressing correlations among different crash types and severity levels, MVPLN models outperformed individual univariate Poisson lognormal crash-type and -severity models. From the developed models, several traffic- and roadway-related attributes—such as volume, average speed, standard deviation of speed, segment type (merge, diverge, and weaving), higher number of lanes, and so forth—could be identified as the potential crash-risk factors. Also, the proposed models were successful in capturing the spatial effects of segments (differences between segments downstream and upstream of the location of interest) on crash frequency. Further, the implementation of VSL/VAS strategy was found to be effective in reducing rear-end crashes in the crash-type model as well as property-damage-only (PDO) and C (non-incapacitating) crash severity levels in the crash-severity model. Policymakers and practitioners could benefit from this study in incorporating safety aspects into developing VSL/VAS algorithms.

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“…e segment length and AADT were transferred to the natural logarithm values to fit in the generalized linear regression [19,26]. e classification of IRI (international roughness) is based on the FHWA recommendations, where 95 in/mile (1.5 m/km) is the upper threshold of "good" ride quality, 170 in/mile (2.7 m/km) is the upper threshold for "acceptable" ride quality, and IRI beyond 170 in/mile (2.7 m/km) is classified as "poor" ride quality [27,28].…”

Section: Data Compilation and Descriptionmentioning

confidence: 99%

“…As a result, the proportion of roadway segments in "poor" conditions was higher than expected. In addition, some research found that such data filtering may also help handle the unbalanced feature of crash data [26].…”

Section: Data Compilation and Descriptionmentioning

confidence: 99%

“…Since the zero counts in this study are not dominating (625 divided by 1,811, which is 34.5%), the differences between the HNB and ZINB models are not apparent for this case study. However, the zero-state hypothesis in the zero-inflated count models has been criticized by researchers and is not widely accepted in the analysis of crash frequency [26,44,45].…”

Section: Comparisons Andmentioning

confidence: 99%

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Statistical Safety Performance Models considering Pavement and Roadway Characteristics

Liu

et al. 2022

Journal of Advanced Transportation

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Transportation agencies build statistical models and predict the average crash frequency to identify hazardous road sections and make informed decisions to reduce crashes. In this paper, safety performance models (SPFs) were built and evaluated considering various pavement and roadway characteristics, including pavement friction, which is seldom available for analysis. Four count data models—Poisson model, negative binomial (NB) model, hurdle-NB model (HNB), and zero-inflated NB (ZINB) model—were built based on roadway characteristics and crash data provided by the Oklahoma Department of Transportation (ODOT). Pavement friction, roadway geometry, surface condition characteristics, and traffic exposure were considered the contributing factors to traffic crashes. Established models were compared in terms of the goodness-of-fit, zero inflation, and statistical significance of factors. The HNB model exhibited promising fitting performance with a manageable number of influencing variables. Coefficients in the HNB model suggest that adequate pavement friction and the presence of shoulders can significantly reduce the crash frequency and thus improve roadway safety performance. Potential issues of the statistical models, such as unobserved heterogeneity and multicollinearity, were also discussed. The relation between roadway infrastructure characteristics (including pavement friction) and roadway safety revealed in this study could assist in choosing the proper statistical model for better decision-making and selecting appropriate preventive treatments for improved roadway safety.

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Before–after studies in highway safety

Cited by 3 publications

References 29 publications

Developing Economic Loss-Based Thresholds for Improving Context-Specific Crash Prediction Models

Developing Economic Loss-Based Thresholds for Improving Context-Specific Crash Prediction Models

Multivariate Approach to Peak-Period Models for Crash Types and Severities in Variable Speed Systems on Freeways

Statistical Safety Performance Models considering Pavement and Roadway Characteristics

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