Moving vision zero programs forward: What pedestrian-focused countermeasure combinations work best and where? A dynamic copula-based time-series approach

Vision Zero stands out as one of the most promising systemic safety action plans. A crucial step to ensure the successful implementation of Vision Zero is to continuously assess the efficiency of the implemented treatments. Traditionally, this is achieved using before-and-after analyses or cross-sectional studies. However, the applicability of these approaches can be limited in assessing Vision Zero initiatives, which usually involve installing multiple treatments at a location, leading to a significant interdependency between treatments. This study proposes a dynamic R-vine copula-based time series model to evaluate the efficiency of treatments implemented as a part of Vision Zero. The proposed approach enables the accurate assessment of the treatments, understanding of their long-term impacts, and identifying the most effective combination of treatments at a location. The study also investigated the association between location characteristics and the performance of treatments. The proposed framework was applied to the City of Toronto at the macro-level (neighbourhood level) and focused on pedestrian-related treatments. Collision data and the implemented countermeasures were obtained from Toronto's Vision Zero Mapping Tool. The results show that the combination of speed limit reduction, leading pedestrian intervals (LPI), and community safety zones was the most frequent combination in terms of efficiency. Enforcement and speed limit reduction were the most effective combination in neighbourhoods with high school density, while LPI was effective in neighbourhoods with high densities of subway stations, and office density, especially when integrated with speed limit reduction and community zones. Driver feedback signs were effective in neighbourhoods with a high density of intersections, but only when combined with automated enforcement, community safety zones, and speed limit reduction. The results of the study would assist decision-makers in selecting the most effective treatment in a neighbourhood based on the neighbourhood characteristics and the countermeasures that are already installed.