Estimates of countermeasure effects using crash-traffic conflict analysis

摘要

Obtaining accurate estimates of countermeasure effects is one of the major challenges faced in safety research. Before-and-After evaluation methods based on observed historical crashes have been used traditionally to estimate these effects, and one of the main problems in conducting such evaluation is having insufficient data (e.g., too few sites and crashes) to provide a reliable basis for countermeasure evaluation. Recently surrogate safety measures based on high risk vehicle interactions and traffic conflicts have been used to provide a more causal perspective on lack of safety at a given site and mix of traffic conditions. The traffic conflict approach, however, has been criticized for lacking as formal link to observational crashes, which are viewed as being the only verified of transportation system failure. This paper presents a framework for estimating countermeasure effects that is based on an empirically defined relationship between crashes and high risk vehicle interactions or conflicts. Conflicts are established for a given traffic situation using VISSIM micro-simulation. The performance of the proposed model is compared to a conventional empirical Bayesian Before-and-After approach to evaluate the effectiveness of changing left turn signal from permissive to protected-permissive for a sample of signalized intersections in Toronto. The results are promising in that they demonstrate how inferences drawn from both crash experience and traffic conflict analysis can be used to provide a better understanding of how countermeasures introduced at a given site can enhance safety.