A Framework for Intersection Traffic Safety Screening with the Implementation of Complex Network Theory. (27th September 2020)

• Record Type: Journal Article
• Authors: Mi, Xueyu; Shao, Chunfu; Dong, Chunjiao; Zhuge, Chengxiang; Zheng, Yan
• Other Names: Chen Feng Academic Editor.
• Is Part Of: Journal of advanced transportation. Volume 2020(2020)
• Publication Date: 2020-09-27
• Subjects: Transportation -- Periodicals; 388.05
• DOI: 10.1155/2020/8824447
• Languages: English
• ISSNs: 0197-6729

Abstract

Abstract : The traffic safety screening could provide guidance for determining the use of resources for traffic safety improvements and is critical for the traffic management. To account for the impacts of traffic safety and the effects of intersection as a node in the roadway network, a framework with six indicators and four strategies is proposed for intersection traffic safety screening. The traffic flow has been incorporated into the process of developing three indicators from the perspective of the complex network theory to measure the node importance. For the assessment of traffic safety, other than the observed and estimated crash frequency and modified time-to-collision, a distance that describes the nonlane-based movements has been proposed from the perspective of traffic safety. A multilayer entropy-weighted VIKOR (MEW-VIKOR) approach is proposed to compute the ranking results, and four strategies have been developed to better account for the effects of the six indicators simultaneously. A roadway network with 28 intersections in Shenzhen has been adopted to verify the effectiveness of the proposed framework for intersection traffic safety screening. The results indicate that the proposed framework with two layers could represent the features of traffic safety and the characteristics of node importance and satisfy the expectation from the public, government, and research institutes. With an appropriate threshold setting, the ranking results are consistent with the intersection safety investigation and contribute significantly to the reduction of false-positive and false-negative cases in identifying the black spot intersections.