Modelling the Safety Performance of Roadways for Specific Collision Types

Constant Factor ◽

Safety Performance ◽

Annual Average Daily Traffic ◽

Collision Type ◽

Binomial Regression ◽

The Individual ◽

Screening Approaches

Safety performance functions (SPFs) are rarely developed for specific accident types because this can be very lengthy especially when relevant data are unavailable. Because of this constraint, a factor is applied along with the SPF for all accident types to estimate the safety for specific accidents types. This factor is the proportion of the individual collision type in the entire population of all accidents. However, there is no reason to believe that this factor is a constant which is independent of Annual Average Daily Traffic (AADT). Accordingly, a constant factor and the proportion model are applied to the SPF for all accident types combined to estimate the SPF for specific accident types on both rural road segments and Two-Way Stop-Controlled (TWSC) intersections. The validity of these factors are tested using the state-of-the-art network screening approaches. Furthermore, a detailed investigation on Property Damaage Only (PDO) estimates is carried out on certain aspects of safety performance functions, using negative binomial regression. PDO estimates are then evaluated based on three different approaches.

Safety performance assessment of freeway interchanges, ramps and ramp terminals

10.32920/ryerson.14651721.v1 ◽

2021 ◽

Author(s):

Bishnu Prasad Parajuli

Keyword(s):

Negative Binomial ◽

Safety Performance ◽

Index Method ◽

Safety Improvement ◽

Binomial Regression ◽

Network Screening ◽

Traffic Volumes ◽

Functional Forms

Existing safety performance functions for mainline interchanges and ramps of Ontario freeways are updated using negative binomial regression. The functional forms of the updated models are different from the existing models. In addition, new safety performance functions for ramp terminal sites are developed. Network screening to identify sites in need of safety treatment has been illustrated using two different methods, one based on a potential for safety improvement (PSI) index and, the other based on an index of a high proportion of a specific accident type. A comparison for rankings for 3-legged signalized ramp terminals by the two methods indicates reasonably consistent results, with some key differences. The method of screening for high proportion of specific accidents can be a possible alternative to PSI index method where safety performance functions and/or traffic volumes are not available since, unlike the PSI Index method, it does not require these inputs.

Safety performance assessment of freeway interchanges, ramps and ramp terminals

10.32920/ryerson.14651721 ◽

2021 ◽

Author(s):

Bishnu Prasad Parajuli

Keyword(s):

Negative Binomial ◽

Safety Performance ◽

Index Method ◽

Safety Improvement ◽

Binomial Regression ◽

Network Screening ◽

Traffic Volumes ◽

Functional Forms

Existing safety performance functions for mainline interchanges and ramps of Ontario freeways are updated using negative binomial regression. The functional forms of the updated models are different from the existing models. In addition, new safety performance functions for ramp terminal sites are developed. Network screening to identify sites in need of safety treatment has been illustrated using two different methods, one based on a potential for safety improvement (PSI) index and, the other based on an index of a high proportion of a specific accident type. A comparison for rankings for 3-legged signalized ramp terminals by the two methods indicates reasonably consistent results, with some key differences. The method of screening for high proportion of specific accidents can be a possible alternative to PSI index method where safety performance functions and/or traffic volumes are not available since, unlike the PSI Index method, it does not require these inputs.

Regional Perspective of Safety Performance Functions and Their Application to Florida Intersections in Suburban Residential and Urban General Context Classification Categories

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/03611981211008447 ◽

2021 ◽

pp. 036119812110084

Author(s):

Ghalia Gamaleldin ◽

Haitham Al-Deek ◽

Adrian Sandt ◽

John McCombs ◽

Alan El-Urfali

Keyword(s):

Negative Binomial ◽

Regression Tree ◽

Influential Factors ◽

Safety Performance ◽

General Context ◽

Boosted Regression Tree ◽

Traffic Volumes ◽

Intersection Types ◽

The Individual

Safety performance functions (SPFs) are essential tools to help agencies predict crashes and understand influential factors. Florida Department of Transportation (FDOT) has implemented a context classification system which classifies intersections into eight context categories rather than the three classifications used in the Highway Safety Manual (HSM). Using this system, regional SPFs could be developed for 32 intersection types (unsignalized and signalized 3-leg and 4-leg for each category) rather than the 10 HSM intersection types. In this paper, eight individual intersection group SPFs were developed for the C3R-Suburban Residential and C4-Urban General categories and compared with full SPFs for these categories. These comparisons illustrate the unique and regional insights that agencies can gain by developing these individual SPFs. Poisson, negative binomial, zero-inflated, and boosted regression tree models were developed for each studied group as appropriate, with the best model selected for each group based on model interpretability and five performance measures. Additionally, a linear regression model was built to predict minor roadway traffic volumes for intersections which were missing these volumes. The full C3R and C4 SPFs contained four and six significant variables, respectively, while the individual intersection group SPFs in these categories contained six and nine variables. Factors such as major median, intersection angle, and FDOT District 7 regional variable were absent from the full SPFs. By developing individual intersection group SPFs with regional factors, agencies can better understand the factors and regional differences which affect crashes in their jurisdictions and identify effective treatments.

Evaluation of Strategies to Mitigate Culvert-Involved Crashes

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/0361198121992070 ◽

2021 ◽

pp. 036119812199207

Author(s):

Hitesh Chawla ◽

Megat-Usamah Megat-Johari ◽

Peter T. Savolainen ◽

Christopher M. Day

Keyword(s):

Negative Binomial ◽

Cost Effective ◽

Negative Binomial Regression Model ◽

Promising Alternative ◽

Roadside Safety ◽

Adverse Conditions ◽

Traffic Characteristics ◽

Annual Average Daily Traffic ◽

Binomial Regression

The objectives of this study were to assess the in-service safety performance of roadside culverts and evaluate the potential impacts of installing various safety treatments to mitigate the severity of culvert-involved crashes. Such crashes were identified using standard fields on police crash report forms, as well as through a review of pertinent keywords from the narrative section of these forms. These crashes were then linked to the nearest cross-drainage culvert, which was associated with the nearest road segment. A negative binomial regression model was then estimated to discern how the risk of culvert-involved crashes varied as a function of annual average daily traffic, speed limit, number of travel lanes, and culvert size and offset. The second stage of the analysis involved the use of the Roadside Safety Analysis Program to estimate the expected crash costs associated with various design contexts. A series of scenarios were evaluated, culminating in guidance as to the most cost-effective treatments for different combinations of roadway geometric and traffic characteristics. The results of this study provide an empirical model that can be used to predict the risk of culvert-involved crashes under various scenarios. The findings also suggest that the installation of safety grates on culvert openings provides a promising alternative for most of the cases where the culvert is located within the clear zone. In general, a guardrail is recommended when adverse conditions are present or when other treatments are not feasible at a specific location.

Estimation of safety performance functions for urban intersections using various functional forms of the negative binomial regression model and a generalized Poisson regression model

Accident Analysis & Prevention ◽

10.1016/j.aap.2020.105964 ◽

2021 ◽

Vol 151 ◽

pp. 105964

Author(s):

Muhammad Wisal Khattak ◽

Ali Pirdavani ◽

Pieter De Winne ◽

Tom Brijs ◽

Hans De Backer

Keyword(s):

Regression Model ◽

Negative Binomial ◽

Negative Binomial Regression Model ◽

Poisson Regression Model ◽

Generalized Poisson ◽

Binomial Regression ◽

Functional Forms ◽

Generalized Poisson Regression

Geographically weighted negative binomial regression applied to zonal level safety performance models

Accident Analysis & Prevention ◽

10.1016/j.aap.2017.06.011 ◽

2017 ◽

Vol 106 ◽

pp. 254-261 ◽

Cited By ~ 21

Author(s):

Marcos José Timbó Lima Gomes ◽

Flávio Cunto ◽

Alan Ricardo da Silva

Keyword(s):

Negative Binomial ◽

Safety Performance ◽

Performance Models ◽

Binomial Regression

The Cycle of Violence Revisited: Childhood Victimization, Resilience, and Future Violence

Journal of Interpersonal Violence ◽

10.1177/0886260516651090 ◽

2016 ◽

Vol 34 (6) ◽

pp. 1261-1286 ◽

Cited By ~ 16

Author(s):

Kevin A. Wright ◽

Jillian J. Turanovic ◽

Eryn N. O’Neal ◽

Stephanie J. Morse ◽

Evan T. Booth

Keyword(s):

Protective Factors ◽

Negative Binomial ◽

Future Research ◽

Cycle Of Violence ◽

Childhood Victimization ◽

Adult Health ◽

Violent Offending ◽

Binomial Regression ◽

The Individual

The individual and social protective factors that help break the cycle of violence are examined. Specifically, this study investigates (a) the individual and social protective factors that reduce violent offending among previously victimized children, and (b) whether certain protective factors are more or less important depending on the type and frequency of childhood victimization experienced. Data on young adults from Wave III of the National Longitudinal Study of Adolescent to Adult Health are used ( N = 13,116). Negative binomial regression models are estimated to examine the protective factors that promote resiliency to violent offending among individuals who reported being physically and sexually victimized as children. Results indicate that a number of individual and social protective factors reduce violent offending in young adulthood. With a few exceptions, these factors are specific to the type, frequency, and comorbidity of abuse experienced. The results suggest a number of promising approaches to break the cycle of violence among previously victimized children. Future research should move beyond explaining the cycle of violence to examine how the cycle may be broken.

Safety Performance Functions for Low-Volume Rural Stop-Controlled Intersections

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/0361198119840348 ◽

2019 ◽

Vol 2673 (5) ◽

pp. 660-669 ◽

Cited By ~ 2

Author(s):

Steven Y. Stapleton ◽

Timothy J. Gates ◽

Raul Avelar ◽

Srinivas R. Geedipally ◽

Ramin Saedi

Keyword(s):

Negative Binomial ◽

Unobserved Heterogeneity ◽

Random Effect ◽

Safety Performance ◽

Cross Sectional ◽

Minor Road ◽

Traffic Volumes ◽

Low Volume

This study involved the development of safety performance functions for rural, low-volume, minor road stop-controlled intersections in Michigan. Facility types included three-leg stop-controlled (3ST) and four-leg stop-controlled (4ST) intersections under state or county jurisdiction and were sampled from each of Michigan’s 83 counties. To isolate lower-volume rural intersections, major roadway traffic volumes were limited to the range of 400–2,000 vehicles per day (vpd). Data were compiled from several sources for 2,023 intersections statewide. These data included traffic crashes, volumes, roadway classification, geometry, cross-sectional features, and other site characteristics covering the period of 2011–2015. Random effects negative binomial regression models were specified for each stop-controlled intersection type considering factors such as driveway density, lighting presence, turn lane presence, and intersection skew, in addition to volume. To account for the unobserved heterogeneity between counties, mixed effects negative binomial models with a county-specific random effect were utilized. Furthermore, unobserved temporal effects were controlled through the use of a year-specific random effect. Separate models were developed for fatal/injury crashes, property damage crashes, and select target crash types. The analysis found that skew angles of greater than five degrees led to significantly greater crash occurrence for both 3ST and 4ST intersections, while greater than two driveways near the intersection led to significantly greater angle crashes at 4ST intersections. Other factors were found to have little impact on crash occurrence. Comparison with the Highway Safety Manual (HSM) base models showed that the HSM models over-predict crashes on 4ST intersections and 3ST intersections with volumes between 1,200 and 2,000 vpd.