Open Access
Methodology for fitting and updating predictive accident models with trend [forthcoming]
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TLDR
This paper addresses a number of methodological issues that arise in seeking practical and efficient ways to update PAMs, whether by re-calibration or byRe-fitting, including the choice of distributional assumption for overdispersion, and considerations about the most efficient and convenient ways to fit the required models.Abstract:
Reliable predictive accident models (PAMs) have a variety of important uses in traffic safety research and practice They are used to help identify sites in need of remedial treatment, in the design of transport schemes to assess safety implications, and to estimate the effectiveness of remedial treatments The PAMs currently in use in the UK are now quite old; the data used in their development was gathered up to 30 years ago Many changes have occurred over that period in road and vehicle design, in road safety campaigns and legislation, and the national accident rate has fallen substantially It seems unlikely that these aging models can be relied upon to provide accurate and reliable predictions of accident frequencies on the roads today This paper addresses a number of methodological issues that arise in seeking practical and efficient ways to update PAMs Models for accidents on rural single carriageway roads have been chosen to illustrate these issues, including the choice of distributional assumption for overdispersion, the choice of goodness of fit measures, questions of independence between observations in different years, and between links on the same scheme, the estimation of trends in the models, the uncertainty of predictions, as well as considerations about the most efficient and convenient ways to fit the required models, given the considerable advances that have been seen in statistical computing software in recent yearsread more
Citations
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Sample-Size Guidelines for Recalibrating Crash Prediction Models: Recommendations for the Highway Safety Manual
TL;DR: Sample-size guidelines were prepared based on the coefficient of variation of the crash data that are needed for the calibration process and they can be used for all facility types and both for segment and intersection prediction models.
Model-Based Versus Data-Driven Approach for Road Safety Analysis: Do More Data Help?
TL;DR: Two popular techniques from the two approaches are compared: negative binomial models for the parametric approach and kernel regression for the nonparametric counterpart, and it is shown that the kernel regression method outperforms the model-based approach for predictive performance, and that performance advantage increases noticeably as data available for calibration grow.
Confidence and prediction intervals for generalised linear accident models
TL;DR: In this article, the authors describe how confidence intervals (for example, for the true accident rate at given flows) and prediction intervals can be produced using spreadsheet technology, which can be used for estimating the number of accidents at a new site with given flows.
Journal ArticleDOI
A simulation analysis to explore when using a calibration function is preferred over a scalar factor for calibrating safety performance functions
TL;DR: In this article , the authors compare the performance of a scalar calibration factor and a calibration function for different ranges of data characteristics (i.e., sample mean and variance) as well as the sample size.
References
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Confidence and prediction intervals for generalised linear accident models
TL;DR: In this article, the authors describe how confidence intervals (for example, for the true accident rate at given flows) and prediction intervals can be produced using spreadsheet technology, which can be used for estimating the number of accidents at a new site with given flows.
Applying the Generalized Waring model for investigating sources of variance in motor vehicle crash analysis
TL;DR: In this article, a new type of model based on the Generalized Waring (GW) distribution is proposed for traffic safety analysis, which can be used for a wide variety of purposes, including establishing relationships between variables and understanding the characteristics of a system.
Exploration of a method to validate surrogate safety measures with a focus on vulnerable road users
Aliaksei Laureshyn,Carl Johnsson,Tanja Kidholm Osmann Madsen,Andras Varhelyi,Maartje de Goede,Åse Svensson,Nicolas Saunier,Wouter van Haperen +7 more
TL;DR: This work presents a methodological approach for a large-scale validation study of surrogate safety indicators focusing on vulnerable road users with only one site analyzed so far and presents the exploration of the data and of the performance of the technical tools used in the study.
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