01030702

Component

https://doi.org/10.3141/1950-08

http://scholar.google.com...rive&publication_year=2006

This paper describes a research project conducted at Madrid Polytechnic University with the objective of refining the negative binomial accident prediction models that had been developed previously for two-lane rural roads in Spain. Cumulative scaled residuals plots were used to identify the value ranges of annual average daily traffic (AADT) where the model over- or underestimated accident frequencies. They were also used to determine whether the calibration sample contained redundant information for some values of the explanatory variables that was detrimental to the model-fitting process. On the basis of the results of these analyses, two approaches were explored to refine the models. First, a random reduction of the sample size was tried to mitigate the effect of redundancies in the statistical information. Second, the sample was stratified, and independent models were fitted for the regions of AADT values where the cumulative residuals plot showed moderate fluctuations. These processes reduced considerably the amount of over- and underestimation of the models, which indicates that in some cases they may be a valid tool to refine accident prediction models and to overcome the lack of flexibility in the functional forms commonly used in multivariate regression modeling.

01030706

English

pp 65-72

2006

Transportation Research Record: Journal of the Transportation Research Board

0309099595

Print

Figures (3) ; References (28) ; Tables (4)

Annual average daily traffic; Calibration; Crash risk forecasting; Multivariate analysis; Regression analysis; Rural highways; Two lane highways

Negative binomial; Sample size

Spain

Data and Information Technology; Highways; Safety and Human Factors; I81: Accident Statistics

TRIS, TRB

Mar 3 2006 10:20AM

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• Calibration of Safety Prediction Models for Planning Transportation Networks
• Comparison of Two Negative Binomial Regression Techniques in Developing Accident Prediction Models
• Describing the Evolution in the Number of Highway Deaths by Decomposition in Exposure, Accident Risk, and Fatality Risk
• Effects of Sample Size on Goodness-of-Fit Statistic and Confidence Intervals of Crash Prediction Models Subjected to Low Sample Mean Values
• Use of Propensity Score Matching Method and Hybrid Bayesian Method to Estimate Crash Modification Factors of Signal Installation
• Using Macrolevel Collision Prediction Models in Road Safety Planning Applications
• Using the Rural Two-Lane Highway Draft Prototype Chapter