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Title: Data Analytics and Pattern Recognition Methods for Work Zone Simulator Studies
Accession Number: 01622853
Record Type: Component
Abstract: This research presents a driving simulator based study to evaluate a driver’s response to alternate work zone sign configurations. This study has compared the Manual on Uniform Traffic Control Devices (MUTCD) configurations against Missouri Department of Transportation (MoDOT) alternate configurations. Study participants within target populations, chosen to represent a range of Missouri drivers, have attempted four work zone scenarios as part of a driving simulator experience. The test scenarios simulated both right and left work zone lane closures with both the CLM and MoDOT alternatives. Drivers’ merging patterns were measured against demographic characteristics of test populations. Statistical data analysis was used to investigate the effectiveness of the alternate configurations employed under different scenarios. The results of this simulation study were compared to the results from a previous MoDOT field study. Pattern recognition and data analytics suggest a correlation between age and gender with the location of merging for the simulated scenarios. Based on results it is observed that the drivers merge earlier with the MoDOT alternative sign than they do with the MUTCD sign. This suggests that MoDOT alternative sign is safer. Also, this observation is in line with the observations of Field study.
Supplemental Notes: This paper was sponsored by TRB committee AHB40 Standing Committee on Highway Capacity and Quality of Service.
Monograph Title: Monograph Accession #: 01618707
Report/Paper Numbers: 17-01023
Language: English
Corporate Authors: Transportation Research Board 500 Fifth Street, NW Authors: Moradpour, SamarehLong, SuzannaQin, RuwenKonur, DincerLeu, MingPagination: 12p
Publication Date: 2017
Conference:
Transportation Research Board 96th Annual Meeting
Location:
Washington DC, United States Media Type: Digital/other
Features: Figures; References; Tables
TRT Terms: Identifier Terms: Subject Areas: Highways; Operations and Traffic Management; Safety and Human Factors
Source Data: Transportation Research Board Annual Meeting 2017 Paper #17-01023
Files: TRIS, TRB, ATRI
Created Date: Dec 8 2016 10:17AM
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