The evaluation process for some roads safety strategies, especially innovative ones, may be challenging, as prior information may be non-existent. This challenge could be addressed with the use of surrogate measures, such as traffic conflicts. Statistical models relating crashes to conflicts are fundamental to this application. The aim of the paper’s research was to investigate some key issues related to the development and application of crash–conflict models. Among the issues addressed are the model specification, the very definition of conflicts, model transferability, and application of the models for estimating crash modification factors (CMFs). Issues are addressed with a case study in which traffic conflicts identified from both time to collision and post encroachment time are generated from the microsimulation of four-legged signalized intersections. These conflicts, in addition to the speed of conflicting vehicles, are used to explore the improved statistical relationships between the frequency of crashes and surrogate measures. Transferability of the models to another jurisdiction is also investigated. The results indicate that the inclusion of the speed variable along with conflicts provides stronger relationships than those with conflicts as a standalone variable. In particular, the results confirm the viability of estimating CMFs with the improved models. The transferability investigation results indicate that it is reasonable to apply the models to the other jurisdiction with caution. Importantly, where such an application is valid, a key conclusion is that calibration of the models would not be necessary to estimate CMFs and apply them to estimate the potential safety impact of a contemplated treatment.
<p>Evaluating the impacts of planned or implemented road safety treatments could be challenging as limited information on crash effects may be accessible. Thus, surrogate measures for safety assessments could be considered as an alternative approach in evaluating the effects of various road safety treatments. The main objective of this study was to investigate various approaches for developing crash prediction models for four-legged signalized intersections in the City of Toronto based on simulated traffic conflicts, including the speed of conflicting vehicles, a variable that has received little emphasis in previous research. A safety evaluation of these intersections with automated vehicles (AVs) was conducted and the transferability of the models to two Canadian jurisdictions was investigated. Results indicate that the safety of intersections may improve with the presence of AVs in cautious operation mode and that these types of models may be transferred for use with caution in other jurisdictions. The primary outcome of this study was the establishment of improved relationships between surrogate safety measures and crashes to swiftly evaluate planned or implemented road safety treatments with and without the presence of AVs.</p>
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.
<p>Evaluating the impacts of planned or implemented road safety treatments could be challenging as limited information on crash effects may be accessible. Thus, surrogate measures for safety assessments could be considered as an alternative approach in evaluating the effects of various road safety treatments. The main objective of this study was to investigate various approaches for developing crash prediction models for four-legged signalized intersections in the City of Toronto based on simulated traffic conflicts, including the speed of conflicting vehicles, a variable that has received little emphasis in previous research. A safety evaluation of these intersections with automated vehicles (AVs) was conducted and the transferability of the models to two Canadian jurisdictions was investigated. Results indicate that the safety of intersections may improve with the presence of AVs in cautious operation mode and that these types of models may be transferred for use with caution in other jurisdictions. The primary outcome of this study was the establishment of improved relationships between surrogate safety measures and crashes to swiftly evaluate planned or implemented road safety treatments with and without the presence of AVs.</p>
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