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Data Collection Through New On-The-Road Technologies: The Need for Validation

Data Collection Through New On-The-Road Technologies: The Need for Validation. David Harkey University of North Carolina Highway Safety Research Center Traffic Records Forum July 2003 Denver, Colorado. Overview of Presentation. Roadway Inventory: Needs and Methods

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Data Collection Through New On-The-Road Technologies: The Need for Validation

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  1. Data Collection Through New On-The-Road Technologies: The Need for Validation David Harkey University of North Carolina Highway Safety Research Center Traffic Records Forum July 2003 Denver, Colorado

  2. Overview of Presentation • Roadway Inventory: Needs and Methods • Major Missing Element: Alignment • History of Recent HSIS Efforts • Results from New HSIS Study • Conclusions UNC Highway Safety Research Center Highway Safety Information System

  3. Roadway Inventories • Inventory databases exists in all State DOTs • Used for planning, operations and maintenance • Range of data elements • geometrics (roadways, intersections and interchanges) • traffic control/operations (segment speed limits, intersection TCD, signal timings) UNC Highway Safety Research Center Highway Safety Information System

  4. Roadway Inventory Collection • Manual methods • In-field acquisition (surveys, observational runs with DMI or GPS technology) • In-office acquisition (video logs, aerial photos, satellite images) • Automated Methods • Instrumented Vans (video logs, pavement conditions, sign inventory, geometrics) UNC Highway Safety Research Center Highway Safety Information System

  5. Alignment Data • Very few states have curvature and grade data • Only 2 of the 9 HSIS states have good horizontal curvature data • Known relationship between curvature and safety UNC Highway Safety Research Center Highway Safety Information System

  6. HSIS Research Focus • Improve upon the alignment data available for safety analyses • Automated methods using instrumented vehicles ARAN - Automatic Roadway Analyzer Roadware Group, Inc. UNC Highway Safety Research Center Highway Safety Information System

  7. History of HSIS Efforts • 1996/97 - MN Data Collection and Analysis • 4 2-lane roads with 50+ curves over 21 miles • Poor Results - Consistency and Accuracy • 1999 - Re-analysis of MN Data with algorithm developed for CT DOT • Dramatic improvement in consistency and accuracy UNC Highway Safety Research Center Highway Safety Information System

  8. New HSIS Effort • Evaluate the CT DOT algorithm that uses ARAN data • Repeatability (Consistency) • between multiple runs on the same segment of roadway • Accuracy - Comparison to “ground truth” • As determined from ground surveys UNC Highway Safety Research Center Highway Safety Information System

  9. Data Collection Tasks • Site Selection • approximately 50 miles distributed by number of lanes and level of curvature • ARAN Data Collection • 5 passes in each direction on every route • azimuth data acquired every 4 meters • Survey Alignments • CT DOT task from ground surveys segments UNC Highway Safety Research Center Highway Safety Information System

  10. Data Processing • Horizontal Curve Classification and Display System (PLV-HC Software) • Develop alignments from raw data • Make post-processing adjustments • Remove unresolved (unknown) segments at the end of a run • Convert spirals to tangents and arcs (split the difference in length) • Remove “true” outliers (not be more than 1 in the group of 5 runs) UNC Highway Safety Research Center Highway Safety Information System

  11. PLV-HC Software UNC Highway Safety Research Center Highway Safety Information System

  12. PLV-HC Software UNC Highway Safety Research Center Highway Safety Information System

  13. PLV-HC Software UNC Highway Safety Research Center Highway Safety Information System

  14. Visual Confirmation • Video log produced for each run • Allowed for the removal of induced curves UNC Highway Safety Research Center Highway Safety Information System

  15. Example Analysis (Rte 190) Initial Best-Fit Alignment Log Analysis 1 Log Analysis 2 Log Analysis 3 Log Validation 1 Log Validation 1 Rev Analysis 1 Rev Analysis 2_QC QC_Harkey QC_Van Dine Rev Validation 1 Rev Validation 2 Rev Analysis 3 UNC Highway Safety Research Center Highway Safety Information System

  16. Example Analysis (Rte 190) Adjustment 1 - removal of unknowns (unresolved segments) Log Analysis 1 Log Analysis 2 Log Analysis 3 Log Validation 1 Log Validation 1 Rev Analysis 1 Rev Analysis 2_QC QC_Harkey QC_Van Dine Rev Validation 1 Rev Validation 2 Rev Analysis 3 UNC Highway Safety Research Center Highway Safety Information System

  17. Example Analysis (Rte 190) Adjustment 2 - Conversion of Spirals to Arcs and Tangents Log Analysis 1 Log Analysis 2 Log Analysis 3 Log Validation 1 Log Validation 1 Rev Analysis 1 Rev Analysis 2_QC QC_Harkey QC_Van Dine Rev Validation 1 Rev Validation 2 Rev Analysis 3 UNC Highway Safety Research Center Highway Safety Information System

  18. Example Analysis (Rte 190) Kappa Statistics for Log Direction 0.64 0.91 0.91 3 Analyses 0.51 0.83 0.89 2 Validations 0.66 0.87 0.913 Analyses + 2 Validations Kappa Statistics for Reverse Direction 0.83 0.85 0.87 3 Analyses 0.72 0.89 0.84 2 Validations 0.79 0.89 0.893 Analyses + 2 Validations 0.91 0.91 0.89 Quality Control Analysis (H&Y) 0.91 0.93 0.92 Quality Control Analysis (H&Y&D) UNC Highway Safety Research Center Highway Safety Information System

  19. Consistency Kappa Statistics • 11 sites (22 sets of results - log and rev) • K > 0.90 9 sets • 0.90 > K > 0.75 8 sets • K < 0.75 5 sets UNC Highway Safety Research Center Highway Safety Information System

  20. Example Analysis (Rte 190) Accuracy Assessment Log Analysis 1 Log Analysis 2 Log Analysis 3 Log Validation 1 Log Validation 1 Survey K = 0.92 UNC Highway Safety Research Center Highway Safety Information System

  21. Accuracy Kappa Statistics • 11 sites (log direction only) • K > 0.90 2 sites • 0.90 > K > 0.75 4 sites • K < 0.75 5 sites UNC Highway Safety Research Center Highway Safety Information System

  22. Conclusions • Are the results consistent? • 77 percent of the directional groups met the threshold • Are the results accurate? • 55 percent of the sites met the threshold • Neither consistent nor accurate enough UNC Highway Safety Research Center Highway Safety Information System

  23. Conclusions • Need to conduct individual arc analysis • variation in length and radius across multiple runs • variation in PCs and PTs • differences with survey results • Critical to validate the results of any automated data acquisition technology UNC Highway Safety Research Center Highway Safety Information System

  24. For the Latest Info Visit the HSIS web site www.hsisinfo.org UNC Highway Safety Research Center Highway Safety Information System

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