A framework for corridor-level traffic safety network screening and its implementation using Business Intelligence. (January 2020)

• Record Type: Journal Article
• Authors: Veeramisti, Naveen; Paz, Alexander; Baker, Justin
• Is Part Of: Safety science. Volume 121(2020)
• Page Start: 100
• Page End: 110
• Publication Date: 2020-01
• Subjects: Traffic safety management -- Network screening -- Corridor screening -- Crash frequency -- Business intelligence; Industrial accidents -- Periodicals; Accident Prevention -- Periodicals; Safety -- Periodicals; Travail -- Accidents -- Périodiques; 363.11
• DOI: 10.1016/j.ssci.2019.08.042
• Languages: English
• ISSNs: 0925-7535

Abstract

Highlights: Corridor-level network screening is extremely important for traffic safety engineers. Existing methodologies enable network screening based on individual segments and intersections. Proposed methodology considers corridor-level network screening with combination of segments and intersections. A Business intelligence framework is implemented for corridor-level network screening and safety analytics for crash diagnostics. This framework addresses practical barriers that limit the use of state-of-the-art methods for traffic safety management. Abstract: Currently, there are both methodological and practical barriers that together preclude the use of theoretically sound approaches for network screening as part of a traffic safety management process. Methodological barriers include, among others, lack of a comprehensive framework for corridor-level network screening. Existing corridor screening methodologies use observed crash frequency as a performance measure. In practice, corridor-level screening is extremely important because traffic safety engineers prefer to deploy countermeasures and provide homogenous conditions throughout corridors to meet drivers' expectations and avoid confusion. On the other hand, practical barriers that limit the use of sound approaches for traffic safety include (1) significant data integration requirements, (2) a particular data schema is needed to enable analysis using specialized software, (3) time-consuming and intensive processes are involved, (4) substantial technical knowledge is needed, (5) visualization capabilities are limited, and (6) coordination across various data owners is required. This research proposes a systematic methodology for corridor-level network screening. The solution algorithm is implemented within a Business Intelligence (BI) platform to address, to the extent possible, the practical barriers listed above. BI provides methods and mechanisms to integrate and process data, generate advanced analytics, and visualize results by using intuitive and interactive web-based dashboards and maps. Experiments and results illustrate the advantage of using the proposed framework for corridor-level network screening implemented within a BI platform.