A Comparative Analysis on Performance of Severe Crash Prediction Methods

2018 ◽  
Vol 2672 (30) ◽  
pp. 109-119 ◽  
Author(s):  
Raul E. Avelar ◽  
Karen Dixon ◽  
Sruthi Ashraf
Keyword(s):  
Prediction Models ◽  
Distribution Functions ◽  
Safety Performance ◽  
Future Research ◽  
Alternative Analysis ◽  
Crash Prediction ◽  
Explanatory Variables ◽  
Safety Performance Functions ◽  
Comprehensive Comparison ◽  
Crash Prediction Models

The objective of this paper is to compare the performance and tradeoffs between two alternative analysis methods for developing crash prediction models for severe crashes: a direct estimation of severe crashes using frequency models, and an indirect but popular approach of combining frequency of total crashes models and some form of severity distribution functions (SDFs). The researchers conducted a comprehensive comparison of these modeling methods to illustrate the strengths and weaknesses of each alternative, and to inform future research that intends to develop such models. An examination of the theoretical characteristics of the modeling approach is presented and discussed. The performance of the two modeling alternatives is compared using two different datasets. The results of those comparisons showed very similar performances by both techniques. Finally, a sensitivity analysis is presented to explore how the performance of these techniques vary by degree of dispersion and observed correlation levels of total and severe injury crashes (KAB; injury scale in which K = fatal [killed], A = incapacitating injury, B = nonincapacitating injury) with potential explanatory variables. The results from these analyses tended to favor the use of SDFs in combination with total crashes safety performance functions (SPFs), as the prediction tended to show reduced dispersion under most conditions. However, performance of the KAB SPF model outperformed the combination of SDF and SPF for total crashes when KAB and non-KAB crashes had a common predictor but with effects in opposite directions.

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.

scholarly journals International transferability of macro-level safety performance functions: a case study of the United States and Italy

2019 ◽  
Vol 1 (1) ◽  
pp. 68-78 ◽  
Author(s):  
Jaeyoung Lee ◽  
Mohamed Abdel-Aty ◽  
Maria Rosaria de Blasiis ◽  
Xuesong Wang ◽  
Ilaria Mattei
Keyword(s):  
United States ◽  
Prediction Models ◽  
The United States ◽  
Safety Performance ◽  
Macro Level ◽  
Safety Performance Functions ◽  
The Usa ◽  
Good Potential ◽  
Using Data ◽  
Crash Prediction Models

Abstract Safety performance functions (SPFs), or crash-prediction models, have played an important role in identifying the factors contributing to crashes, predicting crash counts and identifying hotspots. Since a great deal of time and effort is needed to estimate an SPF, previous studies have sought to determine the transferability of particular SPFs; that is, the extent to which they can be applied to data from other regions. Although many efforts have been made to examine micro-level SPF transferability, few studies have focused on macro-level SPF transferability. There has been little transferability analysis of macro-level SPFs in the international context, especially between western countries. This study therefore evaluates the transferability of SPFs for several states in the USA (Illinois, Florida and Colorado) and for Italy. The SPFs were developed using data from counties in the United States and provincias in Italy, and the results revealed multiple common significant variables between the two countries. Transferability indexes were then calculated between the SPFs. These showed that the Italy SPFs for total crashes and bicycle crashes were transferable to US data after calibration factors were applied, whereas the US SPFs for total and bicycle crashes, with the exception of the Colorado SPF, could not be transferred to the Italian data. On the other hand, none of the pedestrian SPFs developed was transferable to other countries. This paper provides insights into the applicability of macro-level SPFs between the USA and Italy, and shows a good potential for international SPF transferability. Nevertheless, further investigation is needed of SPF transferability between a wider range of countries.

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.

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.

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.

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.

Effectiveness of Consistency Measures in Crash Prediction Models for Two-Lane Highways in Palestine

2018 ◽  
Vol 43 (10) ◽  
pp. 5645-5656 ◽  
Author(s):  
Khaled Al-Sahili ◽  
Mohammed Dwaikat ◽  
Sameer Abu-Eisheh ◽  
Wael Alhajyaseen
Keyword(s):  
Prediction Models ◽  
Crash Prediction ◽  
Crash Prediction Models

Calibration of Predictive Models for Estimating Safety of Ramp Design Configurations

2005 ◽  
Vol 1908 (1) ◽  
pp. 88-95 ◽  
Author(s):  
Dominique Lord ◽  
James A. Bonneson
Keyword(s):  
Predictive Models ◽  
Prediction Models ◽  
Free Flow ◽  
Flow Loop ◽  
Local Conditions ◽  
Crash Prediction ◽  
Calibration Process ◽  
Low Costs ◽  
Crash Prediction Models ◽  
Transportation Agencies

The goal for the calibration process is to use predictive models developed with data collected from other jurisdictions and apply them to the jurisdiction of interest by adapting the models for local conditions and characteristics. Given the large costs associated with data collection, this process is often the only method available to transportation agencies for estimating the safety of different transportation facilities. Thus, recalibrating models produced from other jurisdictions allows agencies to produce their own models at relatively low costs. The objective for the research was to recalibrate a set of crash prediction models for different ramp design configurations. The ramp design configurations addressed included diagonal ramps, non-free-flow loop ramps, free-flow loop ramps, and outer connection ramps. A total of 44 ramps located in and around Austin, Texas, were used in the calibration process. The results of the study showed that more crashes occur on exit ramps than entrance ramps by a ratio of about 6 to 4. The results also showed that the non-free-flow ramp experiences twice as many crashes as other types of ramp. Similarly, more crashes occur on rural than urban ramps.

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