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.

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.

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.

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.

scholarly journals The Development of Safety Performance Functions for Roundabouts in Amman, Jordan

2019 ◽  
Vol 296 ◽  
pp. 01006 ◽  
Author(s):  
Diana AL- Nabulsi ◽  
Khair Jadaan
Keyword(s):  
Urban Areas ◽  
Developed Countries ◽  
Safety Performance ◽  
Statistical Tool ◽  
Crash Frequency ◽  
Road Crashes ◽  
Design Variables ◽  
Safety Performance Functions ◽  
Strong Relation ◽  
Pedestrian Crossing

It is now well established that crash occurrences at roadway segments or intersections are associated with a large variety of factors. Safety Performance Functions (SPF) are statistical models developed to predict crash frequencies for various design variables. In Jordan, almost half of all road crashes occur at intersections, mostly in urban areas. There is a significant number of roundabouts throughout Amman which is increasing without evaluating their safety performance. To assess safety benefits of this kind of intersections, transportation professionals need the powerful statistical tool; the SPF. This study aims to develop SPFs for roundabouts in Amman. The models consider the crash frequency, traffic volume and geometric features of all the studied 20 roundabouts. The developed SPFs were statistically significant (R^2 = 0.91) .The findings of the study revealed that crash frequency has a strong relation with the AADT, roundabout entry angle-degrees, entry path radius, splitter radius, pedestrian crossing structure, inscribed diameter, central diameter, circulating width, entry width, number of circle legs. The developed SPFs are evaluated through a comparison with others from developed countries.

Calibration of the Highway Safety ManualGiven Safety Performance Functions for RuralMultilane Segments and Intersections in Kansas

2017 ◽  
Author(s):  
Syeda Rubaiyat Aziz ◽  
Sunanda Dissanayake
Keyword(s):  
Safety Evaluation ◽  
Highway Safety ◽  
Safety Performance ◽  
Regression Coefficients ◽  
Local Conditions ◽  
Crash Prediction ◽  
Highway Safety Manual ◽  
Satisfactory Level ◽  
Safety Performance Functions ◽  
Predictive Methods

The Highway Safety Manual (HSM) provides models and methodologies for safety evaluation and prediction of safety performance of various types of roadways. However, predictive methods in the HSM are of limited use if they are not calibrated for local conditions. In this study, calibration procedures given in the HSM were followed for rural segments and intersections in Kansas. Results indicated that HSM overpredicts fatal and injury crashes and underpredicts total crashes on rural multilane roadway segments in Kansas. Therefore, existing safety performance functions (SPFs) must be adjusted for Kansas conditions, in order to increase accuracy of crash prediction. This study examined a way to adjust HSM calibration procedures by development of new regression coefficients for existing HSM-given SPF. Final calibration factors obtained through modified SPFs indicated significant improvement in crash prediction for rural multilane segments in Kansas. Additionally, obtained calibration factors indicated that the HSM is capable of predicting crashes at intersections at satisfactory level.

Highway Safety Manual Calibration: Assessing Alternate Definitions of the Calibration Factor

2018 ◽  
Vol 2672 (30) ◽  
pp. 99-108 ◽  
Author(s):  
Mahdi Rajabi ◽  
Jennifer Harper Ogle ◽  
Patrick Gerard
Keyword(s):  
Goodness Of Fit ◽  
Prediction Models ◽  
Highway Safety ◽  
Calibration Factor ◽  
Crash Frequency ◽  
Calibration Process ◽  
Highway Safety Manual ◽  
Safety Performance Functions ◽  
Safety Studies ◽  
Using Data

The publication of the Highway Safety Manual (HSM) in 2010 established crash frequency prediction as the essential safety measure for safety studies. However, given that the models were developed using a single state’s data, the HSM recommends calibration of the prediction models using data from the jurisdiction where they will be applied. This calibration process has been conducted in several states and many questions have been raised as a result. This paper is intended to investigate different definitions and criteria for the calibration factors, and provide recommendations for practitioners on which definition to use. In addition to the calibration factors in the HSM and previously published definitions, two other calibration factor equations are proposed and compared using multiple goodness of fit measures. Whereas each definition may outperform others in certain measures, in this study, it is recommended to use the definition that maximizes the likelihood between predicted and observed crashes. The idea is to follow the same concept in both state-specific safety performance functions development and calibration process, which is maximizing the likelihood of predicted and observed crashes.

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

Analyzing road design risk factors for run-off-road crashes in the Netherlands with crash prediction models

2014 ◽  
Vol 49 ◽  
pp. 121.e1-127 ◽  
Author(s):  
J.W.H. (Jan Hendrik) van Petegem ◽  
Fred Wegman
Keyword(s):  
Risk Factors ◽  
The Netherlands ◽  
Prediction Models ◽  
Crash Prediction ◽  
Road Crashes ◽  
Road Design ◽  
Run Off ◽  
Crash Prediction Models

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.

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