Safety Evaluation of Arterials under Signal Coordination Considering the Correlated Heterogeneity and Multivariate Spatial Correlation

Abstract

Signal-coordinated control systems have been widely implemented on urban arterials. By synchronizing consecutive intersections, signal coordination can significantly improve the throughput of vehicles along arterials. Considerable research has been dedicated to assessing the efficiency of coordinated signalization, while from a safety perspective there is a lack of necessary effort to identify the correlated heterogeneity between injury and property damage only (PDO) crashes. In this paper, the authors adopt a multivariate Poisson log-normal (MPLN) model to reveal the heterogeneous connectivity along coordinated arterials. In addition, spatial correlations of conditional autoregression (CAR) and multivariate conditional autoregression (MCAR) are added to the MPLN model for the purpose of calibrating the regressive results. With the surveyed arterials in Ann Arbor, Michigan, the case study shows that (1) the MPLN-MCAR model predicts the results more accurately compared to the MPLN-CAR and MPLN models, (2) the spatial correlation of injury crashes differs significantly from that of PDO crashes, and (3) there is a strongly correlated heterogeneity between injury and PDO crashes. The findings serve to provide effective countermeasures for safety planning, design, and management of signal-coordinated arterials.