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The study builds on previous rumble strip safety evaluations by providing some Canadian-specific experience and in the process offering some definitive insights into differences in safety effects between installations on curved and tangent segments. An empirical Bayes before–after study estimated crash modification factors (CMFs) for installing edge line rumble strips (ELRS) and centerline rumble strips (CLRS), separately and in combination, on two-lane rural roads in Ontario. Separate CMFs were estimated for ELRS and CLRS for curved and tangent segments. The estimated CMFs indicate that rumble strips can be beneficial, except for CLRS on curved segments, and especially if applied in combination on tangents. The results also indicate that edge line and dual rumble strips are more effective on curved segments, so priority should be given to their application on such segments. It is noteworthy that dual application is more safety effective than either CLRS or ELRS, for tangents and overall. [ABSTRACT FROM AUTHOR]

This paper describes an economical method for obtaining speeds, flows and densities from low quality time-lapse film that is unsuitable for the more common data reduction techniques, most of which require vehicle tracking. The method is developed from some very basic ideas and is illustrated in a description of a recent application--a study involving 16-mm time lapse film coverage of a 1400 m long freeway segment in Toronto, Canada. Average speeds were comparable to those obtained by tracking individual vehicles. [ABSTRACT FROM AUTHOR]

Crash modification factors (CMFs) for road safety treatments are usually obtained through observational models based on reported crashes. Observational Bayesian before-and-after methods have been applied to obtain more precise estimates of CMFs by accounting for the regression-to-the-mean bias inherent in naive methods. However, sufficient crash data reported over an extended period of time are needed to provide reliable estimates of treatment effects, a requirement that can be a challenge for certain types of treatment. In addition, these studies require that sites analyzed actually receive the treatment to which the CMF pertains. Another key issue with observational approaches is that they are not causal in nature, and as such, cannot provide a sound "behavioral" rationale for the treatment effect. Surrogate safety measures based on high risk vehicle interactions and traffic conflicts have been proposed to address this issue by providing a more "causal perspective" on lack of safety for different road and traffic conditions. The traffic conflict approach has been criticized, however, for lacking a formal link to observed and verified crashes, a difficulty that this paper attempts to resolve by presenting and investigating an alternative approach for estimating CMFs using simulated conflicts that are linked formally to observed crashes. The integrated CMF estimates are compared to estimates from an empirical Bayes (EB) crash-based before-and-after analysis for the same sample of treatment sites. The treatment considered involves changing left turn signal priority at Toronto signalized intersections from permissive to protected-permissive. The results are promising in that the proposed integrated method yields CMFs that closely match those obtained from the crash-based EB before-and-after analysis., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

This paper examines the temporal transferability of the zonal accident prediction models by using appropriate evaluation measures of predictive performance to assess whether the relationship between the dependent and independent variables holds reasonably well across time. The two temporal contexts are the years 1996 and 2001, with updated 1996 models being used to predict 2001 accidents in each traffic zone of the City of Toronto. The paper examines alternative updating methods for temporal transfer by imagining that only a sample of 2001 data is available. The sensitivity of the performance of the updated models to the 2001 sample size is explored. The updating procedures examined include the Bayesian updating approach and the application of calibration factors to the 1996 models. Models calibrated for the 2001 samples were also explored, but were found to be inadequate. The results show that the models are not transferable in a strict statistical sense. However, relative measures of transferability indicate that the transferred models yield useful information in the application context. Also, it is concluded that the updated accident models using the calibration factors produce better results for predicting the number of accidents in the year 2001 than using the Bayesian approach.