Pilot Testing of SHRP 2 Reliability Data and Analytical Products: Washington (2014) / Chapter Skim
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17 CHAPTER 3 Data Compilation and Integration 3.1 Test Site Selection Table 3.1 shows all the reliability products selected to test and their test objectives. Following the needs of testing all the products, the SHRP 2 L38D research team and its steering committee met and generated a list of candidate test sites.
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18 congestion, impacts to freight movement, military operations, and the overall economy. This test site is used for testing products of L05 and C11.
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19 the purpose of traffic management, the State of Washington is divided into six regions: Northwest, North Central, Eastern, South Central, Southwest, and Olympic. Relevant to this project, there are approximately 4,200 single or dual-loop detectors installed in the Northwest region that are used to monitor traffic conditions around the Seattle metropolitan area.
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20 Table: TrapData (Dual Loop) Columns Data Type Value Description SPEED smallint Average speed for each 20-second interval (e.g., 563 means 56.3 miles per hour)
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21 formatted, and stored in the STAR Lab Microsoft SQL Server databases using an automated computer program written in Microsoft Visual C#. For the pilot testing of SHRP 2 L02, L07, L08, and C11 products, traffic volume data along the Test Sites A, B, and D corridors were collected.
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22 © OpenStreetMap contributors Figure 3.1. Loop detectors in Northwest Washington State.
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23 Figure 3.2. Traffic flow map based on loop detector data.
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24 ALPR technology uses high-definition cameras, typically mounted on top traffic signal gantries and placed directly over the roadway so that the appropriate angle of sight can be achieved (Figure 3.4 shows a mounted ALPR camera)
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25 Table 3.5. ALPR Data Descriptions Columns Data Type Value Description Stamp Datetime Date and time of observation ID int Unique ID for each route, defined by a unique combination of location of origin and destination TravelTime int Travel time on the section in seconds Trips int Number of trips during observation period UpCount int Number of license plates read by upstream reader DownCount tinyint Number of license plates read by downstream reader Lanes Number of lanes Flag tinyint Error identification flag 3.2.3 Data Set C: INRIX Data INRIX is an international company for traffic analytics and data located in Kirkland, Washington.
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26 Table 3.6. INRIX Data Description Columns Data Type Value Description DateTimeStamp datetime 24-hour time in integer format as YYYYMMDD hh:mm:ss SegmentID varchar Unique ID for each segment-Traffic Message Channel (TMC)
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27 Table 3.7. TMC Code Examples TMC Roadway Direction Intersection Country Zip Start Point End Point Miles 114+05099 522 Eastbound 80th Ave King 98028 47.758321,122.249705 47.755733,122.23368 0.768734 114-05095 522 Westbound WA523/145th St King 98115 47.753417,122.27005 47.733752,122.29253 1.608059 3.2.4 Data Set D: Incident Data This data set was extracted from the WITS and describes the basic characteristics of traffic incidents.
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28 Table 3.9. Weather Data Description Columns Data Type Value Description name Varchar The weather station identifier timestamp Datetime 24-hour time in integer format as YYYYMMDD hh:mm:ss visibility Smallint Visibility in miles temp Smallint Temperature in degrees Fahrenheit dewtemp Smallint Dew point temperature wind_direction Smallint Direction wind is coming from in degrees; from the south is 180 wind_speed Smallint Wind speed in knots pcpd Smallint Total 6-hour precipitation at 00z, 06z, 12z and 18z; 3-hour total for other times.
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29 diagnostics and value thresholding, and then sensitivity issues are detected and corrected using a Gaussian Mixture Model algorithm. All loop detector quality control is completed according to the methodologies outline in Wang et al.
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30 Figure 3.6. Loop data quality control flow chart (Wang et al.
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31 1. Replacement by spatial interpolation, 2.
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32 following: (1) good, (2)
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33 Figure 3.7. GUI for freeway data quality control.
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34 minimal calculation effort and is often very accurate when the level of congestion remains stable. However, when the level of congestion changes quickly, the predicted segment travel times at the end of the route will be quite inaccurate.
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35 3.1 and 3.2) at that time and then sum them together to get the route travel time.
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36 Figure 3.8. Diagram of travel-based route travel time calculation.
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37 o Area-wide and section-level service patrol trucks (average number of patrol trucks per day) o Area-wide and section-level service patrol trucks per mile (average number of patrol trucks per day divided by centerline mile)
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38 sets, the STAR Lab DRIVE Net platform is used as a data repository, visualization, and analysis tool. Figure 3.9 shows an interface snapshot of DRIVE Net Version 3.0.
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39 Figure 3.10. Data acquisition methods for the DRIVE Net system (Wang et al.
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