scholarly journals Safety performance functions in Dedicated Bus Lane of BRT on Caracas Avenue Corridor at Bogotá city

Inge CUC ◽  
2019 ◽  
Vol 15 (2) ◽  
pp. 66-77
Author(s):  
Kelly Andrea Rodríguez Polo ◽  
Santiago Henao Pérez
Keyword(s):  
Traffic Accidents ◽  
Negative Binomial ◽  
Central Line ◽  
Safety Performance ◽  
Transport Systems ◽  
Accident Prediction ◽  
Highway Safety Manual ◽  
Safety Performance Functions ◽  
Traffic Volumes ◽  
Bus Lane

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.

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

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 ◽  
Safety Performance Functions ◽  
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.

Roadway Context Classification Approach for Developing Regional Safety Performance Functions for Florida Intersections

2020 ◽  
Vol 2674 (2) ◽  
pp. 191-202
Author(s):  
Ghalia Gamaleldin ◽  
Haitham Al-Deek ◽  
Adrian Sandt ◽  
Alan El-Urfali ◽  
Md Imrul Kayes ◽  
...  
Keyword(s):  
Classification System ◽  
Negative Binomial ◽  
Safety Performance ◽  
P Value ◽  
Department Of Transportation ◽  
Florida Department ◽  
Safety Performance Functions ◽  
Traffic Volumes ◽  
Road Width ◽  
Data Elements

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.

scholarly journals Safety performance assessment of freeway interchanges, ramps and ramp terminals

2021 ◽  
Author(s):  
Bishnu Prasad Parajuli
Keyword(s):  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Safety Performance ◽  
Index Method ◽  
Safety Improvement ◽  
Binomial Regression ◽  
Safety Performance Functions ◽  
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 Functions for Low-Volume Rural Stop-Controlled Intersections

2019 ◽  
Vol 2673 (5) ◽  
pp. 660-669 ◽  
Author(s):  
Steven Y. Stapleton ◽  
Timothy J. Gates ◽  
Raul Avelar ◽  
Srinivas R. Geedipally ◽  
Ramin Saedi
Keyword(s):  
Negative Binomial ◽  
Unobserved Heterogeneity ◽  
Random Effect ◽  
Negative Binomial Regression ◽  
Safety Performance ◽  
Cross Sectional ◽  
Minor Road ◽  
Safety Performance Functions ◽  
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.

scholarly journals Safety performance assessment of freeway interchanges, ramps and ramp terminals

2021 ◽  
Author(s):  
Bishnu Prasad Parajuli
Keyword(s):  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Safety Performance ◽  
Index Method ◽  
Safety Improvement ◽  
Binomial Regression ◽  
Safety Performance Functions ◽  
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.

scholarly journals The variability of urban safety performance functions for different road elements: an Italian case study

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Paolo Intini ◽  
Nicola Berloco ◽  
Gabriele Cavalluzzi ◽  
Dominique Lord ◽  
Vittorio Ranieri ◽  
...  
Keyword(s):  
Negative Binomial ◽  
Prediction Models ◽  
Safety Performance ◽  
Common Trends ◽  
Main Research ◽  
Pavement Markings ◽  
Italian Case ◽  
Sight Distance ◽  
Safety Performance Functions ◽  
Urban Safety

Abstract Background Urban safety performance functions are used to predict crash frequencies, mostly based on Negative Binomial (NB) count models. They could be differentiated for considering homogeneous subsets of segments/intersections and different predictors. Materials and methods The main research questions concerned: a) finding the best possible subsets for segments and intersections for safety modelling, by discussing the related problems and inquiring into the variability of predictors within the subsets; b) comparing the modelling results with the existing literature to highlight common trends and/or main differences; c) assessing the importance of additional crash predictors, besides traditional variables. In the context of a National research project, traffic volumes, geometric, control and additional variables were collected for road segments and intersections in the City of Bari, Italy, with 1500 fatal+injury related crashes (2012–2016). Six NB models were developed for: one/two-way homogeneous segments, three/four-legged, signalized/unsignalized intersections. Results Crash predictors greatly vary within the different subsets considered. The effect of vertical signs on minor roads/driveways, critical sight distance, cycle crossings, pavement/markings maintenance was specifically discussed. Some common trends but also differences in both types and effect of crash predictors were found by comparing results with literature. Conclusion The disaggregation of urban crash prediction models by considering different subsets of segments and intersections helps in revealing the specific influence of some predictors. Local characteristics may influence the relationships between well-established crash predictors and crash frequencies. A significant part of the urban crash frequency variability remains unexplained, thus encouraging research on this topic.

Safety Performance Functions for Rural Two-Lane County Road Segments

2018 ◽  
Vol 2672 (52) ◽  
pp. 226-237 ◽  
Author(s):  
Steven Y. Stapleton ◽  
Anthony J. Ingle ◽  
Meghna Chakraborty ◽  
Timothy J. Gates ◽  
Peter T. Savolainen
Keyword(s):  
Negative Binomial ◽  
Unobserved Heterogeneity ◽  
Strong Association ◽  
Random Effect ◽  
Safety Performance ◽  
Federal Aid ◽  
Rural County ◽  
Design Standards ◽  
Safety Performance Functions ◽  
Lane County

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.

Evaluation of Safety Performance Functions Based on Experimental Design Using a Cross-Validation Method

2017 ◽  
Vol 2636 (1) ◽  
pp. 62-72 ◽  
Author(s):  
Jung-Han Wang ◽  
Mohamed A. Abdel-Aty ◽  
Jaeyoung Lee
Keyword(s):  
Goodness Of Fit ◽  
Cross Validation ◽  
Safety Performance ◽  
Major Road ◽  
Highway Safety Manual ◽  
Annual Average Daily Traffic ◽  
Minor Road ◽  
Safety Performance Functions ◽  
The One ◽  
Leave One Out

The Highway Safety Manual (HSM) Part C provides a series of safety performance functions (SPFs) for different roadway conditions. The SPFs suggested in the HSM are formulated on the basis of exposure variables: the logarithms of the annual average daily traffic (AADT) on the major road and on the minor road under the base condition. In this research, data from 7,802 intersections in Florida were collected and processed. These intersections were categorized into seven types based on area type (rural or urban), number of legs (three or four), and number of approaches controlled by stop signs. Twenty-two SPF formulations, including the one suggested by the HSM, were developed for each intersection type for examination of the goodness-of-fit measures of the SPFs. In addition, the goodness of fit of each model of the 22 SPFs in each category was examined with 10-fold leave-one-out cross-validation (LOOCV). With a comparison of the delta values generated with the LOOCV method, it is suggested that the SPF with the logarithm of the total entering vehicle volume and the ratio of the AADT on the minor road and the AADT on the major road are important. In addition, the SPFs with the AADT on the major road and the AADT on the minor road and their logarithmic transformations are also important. Therefore, it is suggested that the future HSM compare these two SPF formulations—as suggested in the current research, along with the original SPF formulation in the manual—and select the one with the best model fit on the basis of the delta value using LOOCV.

scholarly journals Crash Prediction Models for Horizontal Curve Segments on Two-Lane Rural Roads in Thailand

2021 ◽  
Vol 13 (16) ◽  
pp. 9011
Author(s):  
Nopadon Kronprasert ◽  
Katesirint Boontan ◽  
Patipat Kanha
Keyword(s):  
Prediction Models ◽  
Safety Performance ◽  
Horizontal Curve ◽  
Crash Frequency ◽  
Rural Roads ◽  
Crash Prediction ◽  
Road Crashes ◽  
Highway Safety Manual ◽  
Safety Performance Functions ◽  
Crash Prediction Models

The number of road crashes continues to rise significantly in Thailand. Curve segments on two-lane rural roads are among the most hazardous locations which lead to road crashes and tremendous economic losses; therefore, a detailed examination of its risk is required. This study aims to develop crash prediction models using Safety Performance Functions (SPFs) as a tool to identify the relationship among road alignment, road geometric and traffic conditions, and crash frequency for two-lane rural horizontal curve segments. Relevant data associated with 86,599 curve segments on two-lane rural road networks in Thailand were collected including road alignment data from a GPS vehicle tracking technology, road attribute data from rural road asset databases, and historical crash data from crash reports. Safety Performance Functions (SPFs) for horizontal curve segments were developed, using Poisson regression, negative binomial regression, and calibrated Highway Safety Manual models. The results showed that the most significant parameter affecting crash frequency is lane width, followed by curve length, traffic volume, curve radius, and types of curves (i.e., circular curves, compound curves, reverse curves, and broken-back curves). Comparing among crash prediction models developed, the calibrated Highway Safety Manual SPF outperforms the others in prediction accuracy.

Calibration and Transferability of Accident Prediction Models for Urban Intersections

2002 ◽  
Vol 1784 (1) ◽  
pp. 57-64 ◽  
Author(s):  
Bhagwant Persaud ◽  
Dominique Lord ◽  
Joseph Palmisano
Keyword(s):  
Functional Form ◽  
Prediction Models ◽  
Research Effort ◽  
Safety Performance ◽  
Accident Prediction ◽  
Unsignalized Intersections ◽  
Safety Performance Functions ◽  
Safety Design ◽  
Accident Data ◽  
Single Calibration

Accident prediction models, also known as safety performance functions, have several important uses in modern-day safety analysis. Unfortunately, calibration of these models is not straightforward. A research effort was undertaken that demonstrates the complexity of calibrating these models for urban intersections. These complexities relate to the specification of the functional form, the accommodation of the peculiarities of accident data, and the transferability of models to other jurisdictions. Toronto data were used to estimate models for three- and four-legged signalized and unsignalized intersections. Then the performance of these models was compared with that of models for Vancouver and California that were recalibrated for Toronto using a procedure recently proposed for the application in the Interactive Highway Safety Design Model (IHSDM). The results of this transferability test are mixed, suggesting that a single calibration factor as is currently specified in the IHSDM procedure may be inappropriate and that a disaggregation by traffic volume might be preferable.

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