New Intersection Crash Prediction Models for the Second Edition of the Highway Safety Manual

2021 ◽  
pp. 036119812110398
Author(s):  
Darren J. Torbic ◽  
Daniel Cook ◽  
Joseph Grotheer ◽  
Richard Porter ◽  
Jeffrey Gooch ◽  
...  
Keyword(s):  
Traffic Control ◽  
Prediction Models ◽  
Highway Safety ◽  
Crash Severity ◽  
Crash Prediction ◽  
Part C ◽  
Highway Safety Manual ◽  
Rural And Urban ◽  
Diamond Interchanges ◽  
Crash Prediction Models

The objective of this research was to develop new intersection crash prediction models for consideration in the second edition of the Highway Safety Manual (HSM), consistent with existing methods in HSM Part C and comprehensive in their ability to address a wide range of intersection configurations and traffic control types in rural and urban areas. The focus of the research was on developing safety performance functions (SPFs) for intersection configurations and traffic control types not currently addressed in HSM Part C. SPFs were developed for the following general intersection configurations and traffic control types: rural and urban all-way stop-controlled intersections; rural three-leg intersections with signal control; intersections on high-speed urban and suburban arterials (i.e., arterials with speed limits greater than or equal to 50 mph); urban five-leg intersections with signal control; three-leg intersections where the through movements make turning maneuvers at the intersections; crossroad ramp terminals at single-point diamond interchanges; and crossroad ramp terminals at tight diamond interchanges. Development of severity distribution functions (SDFs) for use in combination with SPFs to estimate crash severity as a function of geometric design elements and traffic control features was explored; but owing to challenges and inconsistencies in developing and interpreting the SDFs, it was recommended for the second edition of the HSM that crash severity for the new intersection configurations and traffic control types be addressed in a manner consistent with existing methods in Chapters 10, 11, and 12 of the first edition, without use of SDFs.

Safety Performance of Crossroad Ramp Terminals at Single-Point and Tight Diamond Interchanges

2021 ◽  
pp. 036119812110299
Author(s):  
Darren J. Torbic ◽  
Richard J. Porter ◽  
Jeff Gooch ◽  
Kristin Kersavage
Keyword(s):  
Urban Areas ◽  
Prediction Models ◽  
Single Point ◽  
Highway Safety ◽  
Safety Performance ◽  
Crash Prediction ◽  
Highway Safety Manual ◽  
Predictive Methods ◽  
Diamond Interchanges ◽  
Crash Prediction Models

Single-point diamond interchanges and tight diamond interchanges are two alternative interchange types that are considered in urban areas where right-of-way is usually limited. The Highway Safety Manual First Edition predictive methods for freeways and interchanges are capable of estimating the safety performance of freeway mainline, freeway-ramp terminal, and ramp proper segments associated with these interchange types. However, limited research has been conducted to predict and compare the safety performance of the crossroad ramp terminals for these two alternative interchange designs, as would be necessary for a performance-based approach to interchange alternatives analysis. Planners, designers, and safety managers would benefit from having tools to compare the safety performance of these crossroad ramp terminals to make more informed decisions about their use and application in the urban environment. Research was undertaken with the objective of developing new intersection crash prediction models for crossroad ramp terminals at single-point diamond interchanges and crossroad ramp terminals at tight diamond interchanges. In general, it was found that the crash prediction models for crossroad ramp terminals at single-point diamond interchanges predicted more crashes than the models for crossroad ramp terminals at tight diamond interchanges in higher volume conditions. The differences were primarily driven by the property-damage-only crash predictions. Comparisons of the crash prediction models suggested that the two sets of models appear compatible and provide reasonable results over the range of applicable traffic volume conditions.

Assessing Transferability of Highway Safety Manual Crash Prediction Models to Data from Italy

2014 ◽  
Vol 2433 (1) ◽  
pp. 129-135 ◽  
Author(s):  
Francesca Russo ◽  
Mariarosaria Busiello ◽  
Salvatore A. Biancardo ◽  
Gianluca Dell'Acqua
Keyword(s):  
Prediction Models ◽  
Highway Safety ◽  
Crash Prediction ◽  
Highway Safety Manual ◽  
Crash Prediction Models

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.

Some Limitations of the Models in the Highway Safety Manual to Predict Run-off-Road Crashes

2013 ◽  
Vol 2377 (1) ◽  
pp. 38-48
Author(s):  
Shaw-Pin Miaou
Keyword(s):  
Prediction Models ◽  
Highway Safety ◽  
Roadside Safety ◽  
Highway Safety Manual ◽  
Run Off ◽  
Section Design ◽  
Single Vehicle ◽  
Crash Modification Factors ◽  
Model Equations ◽  
Crash Prediction Models

Crash-prediction models in the current edition of the Highway Safety Manual (HSM) have been developed to predict crash frequency by collision type and severity level for specific types of roadways and sites. Each model is made up of three major components: safety performance functions (SPFs), crash modification factors, and calibration factors. The objective of this study was to identify the limitations of the prediction models in estimating single-vehicle, run-off-road (SVROR) crashes for roadside safety analyses and suggest needed changes and developments. The paper presents a review of the state of the models in HSM and focuses on SPFs. Data from FHWA's safety effects of cross-section design for two-lane roads database were used to gain insight about the characteristics of SVROR crashes and total crashes, and to identify the limitations of the current models in predicting the frequency, type, and severity of SVROR crashes. Three major areas of limitations of SPFs are discussed: (a) assumptions involved in development, (b) variables that are potentially important to roadside design but not considered, and (c) statistical bias and uncertainty of the model equations.

Maximizing Safety Improvement Benefits in Crash Prediction Models with Accident Modification Factors

2005 ◽  
Vol 1908 (1) ◽  
pp. 9-18 ◽  
Author(s):  
Mohamadreza Banihashemi ◽  
Michael Dimaiuta
Keyword(s):  
Optimization Model ◽  
Optimization Problem ◽  
Prediction Models ◽  
Linear Optimization ◽  
Mathematical Optimization ◽  
Highway Safety ◽  
Expected Number ◽  
Crash Prediction ◽  
Safety Improvement ◽  
Crash Prediction Models

A linear optimization model that maximizes the safety benefits of improve-ments on an existing highway within specific budget constraints is presented. This model works in conjunction with crash prediction models that predict the expected number of crashes for highways by using a base model and productive accident modification factors (AMFs). The base model predicts the expected number of crashes for a base highway. The AMFs modify the prediction on the basis of the actual characteristics of the highway. If there were multiple alternative improvements for several highway features, then there would be many combined alternatives, each with a certain cost and a certain degree of improvement in highway safety. The proposed model uses linear optimization to find the combined alternative that has the best safety improvement within the available budget. The mathematical optimization model is studied in a general form as well as a detailed form in the context of an existing crash prediction model, the crash prediction module of the interactive highway safety design model. The procedure for building the optimization problem is described. A C programming code was developed to build the linear optimization problem. A test case study is defined, and the problem is built and solved by using the CPLEX optimization solver. The variation of the safety measures versus improvement costs is studied, and the results are discussed.

Preliminary Analysis of Light Rail Crashes in Denver, Colorado

2012 ◽  
Vol 2275 (1) ◽  
pp. 12-21 ◽  
Author(s):  
Pamela M. Fischhaber ◽  
Bruce N. Janson
Keyword(s):  
Traffic Control ◽  
Preliminary Analysis ◽  
Prediction Models ◽  
Hazard Index ◽  
Traffic Signals ◽  
Control Device ◽  
Light Rail ◽  
Crash Prediction ◽  
Grade Crossing ◽  
Grade Crossings

This paper presents a preliminary analysis of light rail crashes at at-grade crossings in Denver, Colorado, based on Regional Transportation District data for 1999 through 2009. Differences in design and operation of at-grade crossings are discussed for light rail versus common carrier railroad (railroad). The differences appear to warrant the development of separate crash prediction and hazard index models because models developed for railroad at-grade crossing operations may not accurately predict the number and severity of crashes at light rail at-grade crossings. In addition, the models developed for railroads do not predict crashes at crossings for some traffic control device types such as traffic signals. The lack of information for crossings controlled by traffic signals in the railroad crash prediction equations is one reason why equations specific to light rail may need to be developed. This study identifies patterns in light rail crossing crash data that warrant further investigation and support the development of crash prediction models and hazard index equations specific to light rail at-grade crossing configurations and operations.

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