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Title: Crash Severity Effects of Adaptive Signal Control Technology: Insights from Pennsylvania and Virginia
Accession Number: 01698149
Record Type: Component
Abstract: Adaptive signal control technology (ASCT) is an intelligent transportation systems (ITS) technology that optimizes signal timings in real time to improve corridor flow. While several past studies have examined the impact of ASCT on crash frequency, little is known about its effect on injury severity outcomes. This paper used ordered probit models to estimate the injury severity outcomes resulting from ASCT deployment using 8 years of crash data from 42 intersections in Pennsylvania and 11 years of crash data from 49 intersections in Virginia. A unique aspect of this data was the availability of before and after deployment characteristics for two different ASCT technologies. The estimation results revealed that both ASCT systems were associated with a reduced propensity for injury crashes. The best fit model also revealed a similar trend towards reductions in severe crashes. This model performed well on validation data with low forecast error of 0.301 and was also observed to be spatially transferable. These results encourage the consideration of ASCT deployments at intersections with high crash severities and have practical implications for aiding agencies in making future deployment decisions about ASCT.
Supplemental Notes: This paper was sponsored by TRB committee ANB20 Standing Committee on Safety Data, Analysis and Evaluation.
Report/Paper Numbers: 19-04637
Language: English
Corporate Authors: Transportation Research BoardAuthors: Pagination: 8p
Publication Date: 2019
Conference:
Transportation Research Board 98th Annual Meeting
Location:
Washington DC, United States Media Type: Digital/other
Features: References; Tables
TRT Terms: Geographic Terms: Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management
Source Data: Transportation Research Board Annual Meeting 2019 Paper #19-04637
Files: TRIS, TRB, ATRI
Created Date: Dec 7 2018 9:47AM
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