The National Academies Press

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From page 175... ... 175 This appendix provides an overview of the weather and incident data requirements needed to run a SHRP 2 Project L08 travel time reliability analysis. It also provides basic data collection and analysis guidance for data-rich agencies wishing to make their analyses more precise by including high-detail, facility-specific weather and incident statistics in their reliability analyses. Read the entire page →
From page 176... ... 176 Acquisition and processing of Weather data Weather Data Sources The ideal weather data set would include a year's worth of 15-min weather reports collected near the facility being studied. In the likely case that 15-min weather data are not available, hourly weather reports published by the Federal Highway Administration's (FHWA) Read the entire page →
From page 177... ... 177 Figure D.1. Screenshot of CLARUS interactive weather data map. Read the entire page →
From page 178... ... 178 as simple as setting filters and counting observations. If not, the precipitation rate column can be used to determine whether there was rainfall or snowfall. Read the entire page →
From page 179... ... 179 apply (e.g., severe cold with light snow) , the analyst should choose the weather type with the highest capacity reduction. Read the entire page →
From page 180... ... 180 Acquisition and Processing of Incident Data Both SHRP 2 Project L08 computation engine spreadsheets include default values for incident statistics as part of their methodology, but their approach differs. The urban streets methodology simply asks for an annual crash rate and uses hard-coded default values, but the freeways methodology allows the user to substitute defaults with facility-specific values. Read the entire page →
From page 181... ... 181 SHRP 2 Project L08 Urban Street Type Similar to its treatment of weather events, the SHRP 2 L08 project methodology has a simple, user-friendly approach to crash data input. In this case, the only requirement is yearly crash frequency by segment. Read the entire page →
From page 182... ... 182 Urban Streets Computational Engine and Freeways Computational Engine. Figure D.4 represents the overall process for both existing and future facility evaluations and for both data-rich and datapoor agencies. Read the entire page →
From page 183... ... 183 Figure D.4. Incident data processing schematic. Read the entire page →
From page 184... ... 184 Table D.9. National Defaults for Incident Data from SHRP 2 Project L08, Freeways Incident Type Incident Type Distribution (%) Read the entire page →
From page 185... ... 185 Each of the methods above requires a different set of inputs for traffic and geometry information. Depending on the facility type being evaluated, the HSM or HERS methods may be applicable. Read the entire page →
From page 186... ... 186 Table D.11. Crash Prediction Methods Facility Type Crash Prediction Tool Comments Urban Arterials Single-vehicle crashes Use HSM Equation 12-13 Multiple-vehicle driveway-related crashes Use HSM Equation 12-16 Vehicle–pedestrian crashes Use HSM Equation 12-19 Vehicle–bicycle crashes Use HSM Equation 12-20 Intersection crashes are combination of the following predictions: Vehicle–vehicle crashes for intersections Use HSM Equation 12-21 Use HSM Equation 12-20 Vehicle–pedestrian crashes for signalized intersections Use HSM Equation 12-28 Use HSM Equation 12-29 Vehicle–pedestrian crashes for stop-controlled intersections Use HSM Equation 12-30 Vehicle-Bicycle Crashes Use HSM Equation 12-31 Option 2: Arterial Crash Prediction by HERS Models (Chapter 5) Read the entire page →
From page 187... ... 187 Table D.12. Incident Occurrence Probabilities for Each Month Month Freeway Having Incidents No Incidents January 0.9032 0.0968 February 0.8839 0.1161 March 0.9194 0.0806 April 0.9000 0.1000 May 0.8871 0.1129 June 0.8750 0.1250 July 0.9113 0.0887 August 0.8871 0.1129 September 0.9000 0.1000 October 0.7903 0.2097 November 0.8417 0.1583 December 0.8790 0.1210 Total 0.8815 0.1185 Table D.13. Read the entire page →
From page 188... ... 188 Table D.14. Average, Median, and Standard Deviation of Incident Type Probabilities Facility Type Incident Distribution (%) Read the entire page →
From page 189... ... 189 Table D.15. Lane Closure Type Distribution by Incident Type Facility Type Incident Type Statistic Lane Closure Distribution (%) Read the entire page →
From page 190... ... 190 Table D.16. Lane Closure Type by Crash Severity Facility Type Crash Severity Distribution (%) Read the entire page →
From page 191... ... 191 Table D.17. Incident Duration by Incident Type and Lane Closure Type Facility Type Incident Type Statistic Incident Duration (min) Read the entire page →
From page 192... ... 192 References AASHTO. Highway Safety Manual. Read the entire page →

From page 175...

... 175 This appendix provides an overview of the weather and incident data requirements needed to run a SHRP 2 Project L08 travel time reliability analysis. It also provides basic data collection and analysis guidance for data-rich agencies wishing to make their analyses more precise by including high-detail, facility-specific weather and incident statistics in their reliability analyses.