Citation

Fan Y, Zhang G, Ma J, Lee J, Meng T, Zhang X, Jiang X. Anal. Meth. Accid. Res. 2019; 21: 32-43.

Copyright

(Copyright © 2019, Elsevier Publishing)

DOI

10.1016/j.amar.2019.01.001

PMID

unavailable

Abstract

Many cities have adopted signal coordination schemes to improve the operational efficiency of arterials. Through providing a "green wave", the coordinated signals allow vehicles to pass consecutive intersections with fewer stops. Conventionally, studies focused mainly on the efficiency aspect of signal coordination. From a safety perspective, there are few studies devoted to investigating spatial heterogeneity and homogeneity simultaneously along arterials, particularly those with different traffic control and signal coordination schemes. Applying a joint negative binomial conditional auto-regression crash sum (JNBCS-CAR) model, this paper aims to comprehensively evaluate traffic safety on arterials with coordinated traffic signals. The performance of JNBCS-CAR is compared to those of traditional five ones (i.e., Poisson log-normal (PLN), negative binominal crash sum (NBCS), Poisson log-normal conditional auto-regression (PLN-CAR), negative binominal conditional auto-regression crash sum (NBCS-CAR), and hierarchical Poisson log-normal conditional auto-regression (HPLN-CAR)). Nine years of data are selected from the City of Ann Arbor (Michigan).

RESULTS indicate that (1) the JNBCS-CAR model outperforms other models in terms of the goodness-of-fit; (2) signalized intersections appear to have significant spatially heterogeneous effects on roadway segments under the scenario of signal coordination, while roadway segments do not have spatially heterogeneous effects on signalized intersections; and (3) there is a strong spatially homogeneous correlation among the coordinated intersections, but not among the segments. The findings serve to provide an accurate evaluation of the coordinated signalization from the safety perspective.

Language: en

Keywords

Crash prediction; Joint negative binominal conditional auto-regression crash sum model; Signal coordination; Spatial heterogeneity