Meso Safety Analysis of Major Arterials: The Impact of Intersection Spacing and Network Connection Compatibility

Abstract

With the increase in high-density road network construction in many urban areas, neither macro- nor micro-level safety analysis can fully explain the impact of network characteristics on safety. This study employed a meso-level analysis unit, which combines intersections with adjacent road segments, to investigate the safety impact of intersection spacing and network connection compatibility along 19 major arterials in Suzhou, China. Three main intersection spacing characteristics, the density of intersection spacing (DOIS), the standard deviation of intersection spacing (SDOIS), and the variation of intersection spacing (VOIS), were used to represent the interaction between arterials and other roads in the network. This study introduced the concept of hierarchical differences to quantitatively analyze the safety effects of connections between roads with different accessibility and mobility functions. To manage the hierarchical structure of the data (which has both within-arterial and between-arterial correlations), a two-level hierarchical negative binomial conditional autoregressive model was adopted to examine the safety effects of network characteristics at the meso level. The results showed the existence of unobserved heterogeneities among the selected arterials. The SDOIS and VOIS were found to have positive effects on crash frequency (more crashes on units with higher SDOIS and VOIS), while the DOIS was negatively associated with crash frequency. The meso units with moderately compatible network connections were found to have more crashes than those with compatible connections, while the units with the highest hierarchical differences had fewer crashes. The results from this study are expected to provide suggestions on potential safety hazard screening and crash prevention.

Keywords

safety Bayesian methods crash analysis crash data crash frequency general

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