Citation

Wang X, Yuan J, Schultz GG, Fang S. Accid. Anal. Prev. 2018; 113: 137-148.

Affiliation

School of Transportation Engineering, Tongji University, Shanghai 201804, China; Road and Traffic Key Laboratory, Ministry of Education, Shanghai 201804, China.

Copyright

(Copyright © 2018, Elsevier Publishing)

DOI

10.1016/j.aap.2018.01.029

PMID

29407661

Abstract

With rapid changes in land use development along suburban arterials in Shanghai, there is a corresponding increase in traffic demand on these arterials. To accommodate the local traffic needs of high accessibility and efficiency, an increased number of signalized intersections and accesses have been installed. However, the absence of a defined hierarchical road network, together with irregular signal spacing and access density, tends to deteriorate arterial safety. Previous studies on arterial safety were generally based on a single type of road entity, either intersection or roadway segment, and they analyzed the safety contributing factors (e.g. signal density and access density) on only that type of road entity, while these suburban arterial characteristics could significantly influence the safety performance of both intersections and roadway segments. Macro-level safety modeling was usually applied to investigate the relationships between zonal crash frequencies and demographics, road network features, and traffic characteristics, but the previous researchers did not consider the specific arterial characteristics of signal density and access density. In this study, a new modeling strategy was proposed to analyze the safety impacts of zonal roadway network features (i.e., road network patterns and road network density) along with the suburban arterial characteristics of signal density and access density. Bayesian Conditional Autoregressive Poisson Log-normal models were developed for suburban arterials in 173 traffic analysis zones in the suburban area of Shanghai.

RESULTS identified that the grid pattern road network with collector roads parallel to arterials was associated with fewer crashes than networks without parallel collectors. On the other hand, lower road network density, higher signal density and higher access density tended to increase the crash occurrence on suburban arterials.

Copyright © 2018 Elsevier Ltd. All rights reserved.

Language: en

Keywords

Access density; Conditional Autoregressive (CAR) model; Macro level safety modeling; Road network patterns; Signal density; Suburban arterials