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.

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.

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 Contribution to Accident Prediction Models Development for Rural Two-Lane Roads in Serbia

2016 ◽  
Vol 28 (4) ◽  
pp. 415-424 ◽  
Author(s):  
Draženko Glavić ◽  
Miloš Mladenović ◽  
Aleksandar Stevanovic ◽  
Vladan Tubić ◽  
Marina Milenković ◽  
...  
Keyword(s):  
Multivariate Regression ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Prediction Models ◽  
Future Research ◽  
Practical Application ◽  
Accident Prediction ◽  
Accident Data ◽  
Road Characteristics ◽  
The Relationship

Over the last three decades numerous research efforts have been conducted worldwide to determine the relationship between traffic accidents and traffic and road characteristics. So far, the mentioned studies have not been carried out in Serbia and in the region. This paper represents one of the first attempts to develop accident prediction models in Serbia. The paper provides a comprehensive literature review, describes procedures for collection and analysis of the traffic accident data, as well as the methodology used to develop the accident prediction models. The paper presents models obtained by both univariate and multivariate regression analyses. The obtained results are compared to the results of other studies and comparisons are discussed. Finally, the paper presents conclusions and important points for future research. The results of this research can find theoretical as well as practical application.

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.

Accident Prediction Models With and Without Trend: Application of the Generalized Estimating Equations Procedure

2000 ◽  
Vol 1717 (1) ◽  
pp. 102-108 ◽  
Author(s):  
Dominique Lord ◽  
Bhagwant N. Persaud
Keyword(s):  
Generalized Estimating Equations ◽  
Prediction Models ◽  
Estimating Equations ◽  
Temporal Correlation ◽  
Expected Number ◽  
Accident Prediction ◽  
Site Characteristics ◽  
Accident Data ◽  
A Site ◽  
Generalized Estimating

Accident prediction models (APMs) are useful tools for estimating the expected number of accidents on entities such as intersections and road sections. These estimates typically are used in the identification of sites for possible safety treatment and in the evaluation of such treatments. An APM is, in essence, a mathematical equation that expresses the average accident frequency of a site as a function of traffic flow and other site characteristics. The reliability of an APM estimate is enhanced if the APM is based on data for as many years as possible, especially if data for those same years are used in the safety analysis of a site. With many years of data, however, it is necessary to account for the year-to-year variation, or trend, in accident counts because of the influence of factors that change every year. To capture this variation, the count for each year is treated as a separate observation. Unfortunately, the disaggregation of the data in this manner creates a temporal correlation that presents difficulties for traditional model calibration procedures. An application is presented of a generalized estimating equations (GEE) procedure to develop an APM that incorporates trend in accident data. Data for the application pertain to a sample of four-legged signalized intersections in Toronto, Canada, for the years 1990 through 1995. The GEE model incorporating the time trend is shown to be superior to models that do not accommodate trend and/or the temporal correlation in accident data.

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.

scholarly journals TRAFFIC COLLISION TIME SERIES ANALYSIS (A CASE STUDY OF KARAJ–QAZVIN FREEWAY)

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 941-948 ◽  
Author(s):  
R. Sanayei ◽  
A. R. Vafainejad ◽  
J. Karami ◽  
H. Aghamohammadi
Keyword(s):  
Time Series ◽  
Correlation Function ◽  
Prediction Models ◽  
Ar Model ◽  
Periodic Pattern ◽  
Accident Prediction ◽  
Auto Correlation ◽  
Accident Data ◽  
Auto Correlation Function ◽  
Simulation Results

Abstract. The application of Auto-correlation Function (ACF) and Partial Auto-correlation Function (PACF) in recent years has been improved in analyzing big traffic data, modelling traffic collisions and decreasing processing time in finding collision patterns. Accident prediction models for short and long time can help in designing and programming traffic plans and decreasing road accidents. Based on the above details, in this paper, the Karaj-Qazvin highway accident data (1097 samples) and its patterns from 2009 to 2013 have been analyzed using time series methods.In the first step, using auto correlation function (ACF) and partial auto correlation function (PACF), the rank of time series model supposed to be autoregressive (AR) model and in the second stage, its coefficients were found. In order to extract the accident data, ArcGIS software was run. Furthermore, MATLAB software was used to find the model rank and its coefficients. In addition, Stata SE software was used for statistical analysis. The simulation results showed that on the weekly scale, based on the trend and periodic pattern of data, the model type and rank, ACF and PACF values, an accurate weekly hybrid model (time series and PACF) of an accident can be created. Based on simulation results, the investigated model predicts the number of accident using two prior week data with the Root Mean Square Error (RMSE) equal to three.

scholarly journals Effect of Traffic and Geometric Characteristics of Rural Two Lane Roads on Traffic Safety: a case study of Ilesha-Akure-Owo road, South-West, Nigeria

2018 ◽  
Vol 3 (2) ◽  
Author(s):  
Monsuru O Popoola ◽  
Oladapo S Abiola ◽  
Simeon O Odunfa
Keyword(s):  
Road Safety ◽  
Traffic Accident ◽  
Negative Binomial ◽  
Prediction Models ◽  
Negative Binomial Regression ◽  
Accident Prediction ◽  
Geometric Characteristics ◽  
South West ◽  
Binomial Regression ◽  
Accident Data

Road safety engineering involves identifying influencing factors causing traffic crashes through accident data, carrying out detailed accident studies at different locations and implementing relevant remedial measures. This study was carried out to establish relationship between traffic accident characteristics (frequency and severity) and traffic and road design characteristics on a two-lane highway. Statistical models applied in traffic accident modeling are Poisson regression, Negative Binomial regression (NB), and Zero-Inflated Negative Binomial regression (ZINB).; Traffic flow and road geometry related variables were the independent variables of the models. Using Ilesha-Akure-Owo highway, South-West, Nigeria accident prediction models were developed on the basis of accident data obtained from Federal Road Safety Commission (FRSC) during a 4-year monitoring period extending between 2012 and 2015. Curve radius (CR), lane width (LW), shoulder factor (SF), access road (CHAR), average annual daily traffic (AADT), parentage heavy good vehicle (HGV) and traffic sign posted (TSP) were the identified effective factors on crash occurrence probability. Finally, a comparison of the three models developed proved the efficiency of ZINB models against traditional Poisson and NB models. Keywords— Traffic accidents. Single carriageway, accident prediction model, road geometric characteristics.

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