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

Author(s):  
Steven Y. Stapleton ◽  
Timothy J. Gates ◽  
Raul Avelar ◽  
Srinivas R. Geedipally ◽  
Ramin Saedi

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.

Author(s):  
Steven Y. Stapleton ◽  
Anthony J. Ingle ◽  
Meghna Chakraborty ◽  
Timothy J. Gates ◽  
Peter T. Savolainen

Safety performance functions (SPFs) were developed for rural two-lane county roadway segments in Michigan. Five years of crash data (2011 to 2015) were analyzed for greater than 6,500 mi of rural county roadways, covering 29 of Michigan’s 83 counties and representing all regions of the state. Three separate models were developed to estimate annual deer-excluded total and injury crashes on rural county roadways: 1) paved federal-aid segments, 2) paved non-federal-aid segments, and 3) paved and gravel non-federal-aid segments with fewer than 400 vpd. To account for the unobserved heterogeneity associated with differing county design standards, mixed effects negative binomial models with a county-specific random effect were utilized. Not surprisingly, the county segment SPFs generally differed from traditional models generated using data from state-maintained roadways. County federal-aid roadways general showed greater crash occurrence than county non-federal-aid roadways, the Highway Safety Manual (HSM) two-lane rural roadways model, and rural state highways in Michigan. County non-federal-aid paved roadways showed crash occurrence rates that were remarkably similar to the HSM base rural two-lane roadway model, whereas gravel roadways showed greater crash occurrence rates. The presence of horizontal curves with design speeds below 55 mph had a strong association with the occurrence of total and injury crashes across all county road classes. Increasing driveway density was also found to be associated with increased crash occurrence. However, lane width, roadway surface width, and paved shoulder width had little to no impact on total or injury crashes.


2021 ◽  
Author(s):  
Bishnu Prasad Parajuli

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.


2021 ◽  
Author(s):  
Bishnu Prasad Parajuli

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.


Author(s):  
Ghalia Gamaleldin ◽  
Haitham Al-Deek ◽  
Adrian Sandt ◽  
John McCombs ◽  
Alan El-Urfali

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.


Author(s):  
Ghalia Gamaleldin ◽  
Haitham Al-Deek ◽  
Adrian Sandt ◽  
Alan El-Urfali ◽  
Md Imrul Kayes ◽  
...  

Understanding how the type and location of intersections affect crashes is important to reduce these crashes effectively. This paper discusses the development of regional safety performance functions (SPFs) based on a new context classification system developed by the Florida Department of Transportation (FDOT). This classification system (which has not previously been used) categorizes intersections into eight different categories based on land use and other parameters, allowing SPFs to be developed for up to 32 different types of intersections. The Model Inventory of Roadway Elements (MIRE) 2.0 was used as the standard inventory for the data elements collected. Using MIRE 2.0 allows for the procedures conducted in this study to be easily implemented in other states. SPFs were developed for two intersection groups. First, a linear regression model was built to predict missing minor traffic volumes. This statistically significant model ( p-value < 0.05) had an adjusted R-square of 0.7648. Data were collected for over 25 potential predictor variables (including a regional variable for FDOT districts) and used to fit a negative binomial model to each studied intersection group. Some variables (such as major traffic volume) were significant for both groups, but each SPF had unique variables (such as speed limit and road width). Different regions were significant for each group, showing how crashes vary for different intersection types in different regions. By allowing for the development of SPF models for many intersection classifications, FDOT’s context classification system can be used by other agencies to identify crash-influencing factors better for different conditions.


Author(s):  
Srinivas R. Geedipally ◽  
Timothy J. Gates ◽  
Steven Stapleton ◽  
Anthony Ingle ◽  
Raul E. Avelar

Much of the earlier work on rural safety focused on state-maintained roadways and little is known about the safety performance of low-volume county-maintained roads. This study involved the estimation of safety performance for rural county roadways (paved and gravel). This was accomplished through the development of safety performance functions (SPFs) to estimate the number of annual crashes at a given highway segment, crash modification factors to determine the impacts associated with various roadway and geometric characteristics, and severity distribution functions (SDFs) to predict the crash severity. County road segment data were collected across a sample of 30 counties representing all regions of Michigan. Because of the overwhelming proportion of deer crashes, only non-deer-related crashes were considered. To minimize the influence of variability among counties, the random effect negative binomial model was used to develop SPFs. In addition, a multinomial logit model was used to develop SDFs. Paved county roadways showed approximately double the crash occurrence rate of typical state-maintained two-lane rural highways, and gravel roadways showed a substantially greater crash occurrence rate than paved county roadways across the equivalent range of traffic volumes. The economic analysis showed that it is beneficial to pave a gravel road when the traffic volume is greater than 600 vehicles per day. The random effect variable is significant in all the calibrated models, which shows that there is a considerable variability among counties that cannot be captured with the available variables. Not considering the random effects will result in biased estimation of crashes.


Inge CUC ◽  
2019 ◽  
Vol 15 (2) ◽  
pp. 66-77
Author(s):  
Kelly Andrea Rodríguez Polo ◽  
Santiago Henao Pérez

Introduction- Road safety is a global concern due to the fact that traffic accidents represent serious temporary and / or permanent damage to the health of those involved. On the other hand, the Bus Rapid Transit (BRT) systems carries a large volume of passengers and during their operation; they are involved in this problem. Objective- Accident prediction model implemented in the Highway Safety Manual 2010 or HSM is an alternative to evaluate the strategies that allow to reduce accidents in this type of systems. However, there is not specified safety performance functions (SPFs) developed for BRT systems. In the present work, the accident model of HSM is adapted by calibration of general SPFs expressions of the manual and also, SPFs were developed for BRTs installed on the central-line of main roads and use an exclusive lane of all other transport systems (both public or private) and mobility (e.g. bike paths). Method / Results - Crashes reports and traffic volumes data supplied by the Department of Transportation of Bogotá were used. The model was calibrated using the safety performance functions (SPFs) of the HSM and a specific developed functions for the BRT conditions. These SPFs were developed using a negative binomial model in roadway segments and intersections. Conclusions- Through the validation, it was found that the functions developed have a better fit than the established SPF of the HSM. The developed SPFs can be used as a tool to define safety performance guidelines of Bogotá's BRT corridors in the coming years.


2021 ◽  
Author(s):  
Tony Chiu

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.


2021 ◽  
Author(s):  
Tony Chiu

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.


Author(s):  
Subasish Das ◽  
Ioannis Tsapakis ◽  
Songjukta Datta

The Fixing America’s Surface Transportation Act (FAST Act) mandates a Highway Safety Improvement Program (HSIP) for all states that “emphasizes a data-driven, strategic approach to improving highway safety on all public roads that focuses on performance.” To determine the predicted crashes on a specific roadway facility, the most convenient and widely used tool is the first edition of Highway Safety Manual (HSM), which provides predictive models [known as safety performance functions (SPFs)] of crash frequencies for different roadways. Low-volume roads (LVRs) are defined as roads located in rural or suburban areas with daily traffic volumes of less than or equal to 400 vehicles per day (vpd). LVRs cover a significant portion of the roadways in the U.S. While much work has been done to develop SPFs for high-volume roads, less effort has been devoted to LVR safety issues. This study used 2013–2017 traffic count, and roadway network and crash data from North Carolina to develop six SPFs for three LVRs, which can be used to predict total crashes, as well as fatal and injury crashes. This study also performed a sensitivity analysis to show the influence of traffic volumes on expected crash frequencies. The SPFs developed in this study can provide guidance to state and local agencies with the means to quantify safety impacts on LVR networks.


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