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Conversion of Volunteer-Collected GPS Diary Data into Travel Time Performance Measures

Research Project 0-5176. Conducted for. Conversion of Volunteer-Collected GPS Diary Data into Travel Time Performance Measures. Training Workshop on the Use of GPS-TDG Software. PC : Terry Keener PD : Michael Chamberlain PI : Chandra R. Bhat Barbara Parmenter. Researchers

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Conversion of Volunteer-Collected GPS Diary Data into Travel Time Performance Measures

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  1. Research Project 0-5176 Conducted for Conversion of Volunteer-Collected GPS Diary Data into Travel Time Performance Measures Training Workshop on the Use of GPS-TDG Software PC : Terry Keener PD : Michael Chamberlain PI : Chandra R. Bhat Barbara Parmenter Researchers Siva Srinivasan Prabuddha Ghosh Aruna Sivakumar Aarti Kapur Stacey Bricka

  2. Presentation Overview • Background • Research Objectives • Conceptual Structure of GPS-TDG • Software Overview • Tutorial using Sample Data from Laredo • Preprocessing GPS streams • Basic Analysis • Enhanced Analysis • Querying and Aggregation

  3. Household Travel Surveys Data Travel Demand Models Understand Travel Needs: Generate Policy Actions Evaluate Impacts of Policy Actions Forecast Travel Demand Background: Collecting Travel Data

  4. Survey Implementation Enhancements PAPI CATI ETD / CASI GPS-Enhanced Background: Enhancing Travel Data Collection Survey Design Enhancements Trip diaries Activity diaries Time-use diaries

  5. Using GPS in Travel Surveys: Different Technologies Our focus In-Vehicle devices Purely passive Requiring additional active input Hand-held devices

  6. Advantages of GPS-based Data Collection • Passive Data Collection • Reduces respondent burden • Address under-reporting of trips • Address item non-response • Increased Spatial and Temporal Accuracy • Destination locations for non-frequent trips • Trip times and time-of-day of travel are not estimates • Additional Data • Trips missed in manual reporting • Route choice • Travel speeds

  7. Issues with Passive-GPS Data Collection • Data is collected in the form of navigational streams • Requires operational definitions of “trips” and “stops” • Requires substantial processing for converting into conventional trip-diary format • Equipment capabilities/accuracy/errors impacts trip identification • Trip purpose information unknown • Requires supplemental user input (en-route or via prompted recall) • Use of regional land-use and respondent demographics data for imputing trip purposes • Vehicle occupancy unknown • Requires supplemental user input

  8. GPS-based Travel Surveys: Summary • Substantial potential for using in-vehicle GPS technologies in travel surveys to enhance quality and quantity of data • Shifts considerable burden from the respondent to the analyst: Need to convert navigational streams from GPS devices to trip sequences

  9. Research Objectives Develop a GIS-based software to automate the process of converting the raw GPS navigational streams into the conventional trip-diary format Develop algorithm to identify vehicle trip characteristics from GPS navigational streams Implement the algorithm in GIS-based software to automate travel-diary extraction Aggregate the derived travel diaries to produce inter-zonal trip-tables by trip purpose and time of day Compute inter-zonal highway performance measures (i.e., travel times and speeds)

  10. Conceptual Overview of GPS-TDG

  11. GPS-TDG: Primary User Interface Menu Bar Preprocessing and help Data Area Display of derived travel diaries and query results Command Area Providing inputs, querying, and overall control

  12. Tutorial on Using GPS-TDG • View sample raw GPS streams • Preprocess GPS streams & view the results • Running the software in the Basic Analysis mode • Provide inputs • View and interpret results • Running the software in the Enhanced Analysis mode • Provide inputs • View and interpret results • Aggregation and Querying

  13. Sample Raw GPS Stream (GeoLogger) RECTYPE,GPS_ID,HH_ID,Veh_ID,GMT_DATE,GMT_TIME,LOC_DATE,LOC_TIME,LAT_RAW,LONG_RAW,ELEV_RAW,VELOCITY,HEADING,HDOP,SATS 5,272,1005402,1,03/25/02,12:40:37,03/25/02,06:40:37,27.59705,-99.47217,00179,0.00,000,01.7,05 5,272,1005402,1,03/25/02,12:40:38,03/25/02,06:40:38,27.59705,-99.47217,00179,0.00,000,01.7,05 5,272,1005402,1,03/25/02,12:40:39,03/25/02,06:40:39,27.59705,-99.47217,00180,0.00,000,01.7,05 5,272,1005402,1,03/25/02,12:40:40,03/25/02,06:40:40,27.59705,-99.47217,00180,0.00,000,01.7,05 5,272,1005402,1,03/25/02,12:40:41,03/25/02,06:40:41,27.59705,-99.47217,00180,0.00,000,01.7,05 5,272,1005402,1,03/25/02,12:40:42,03/25/02,06:40:42,27.59705,-99.47217,00180,0.00,000,01.7,05 5,272,1005402,1,03/25/02,12:40:43,03/25/02,06:40:43,27.59705,-99.47218,00179,0.00,000,01.7,05 5,272,1005402,1,03/25/02,12:40:44,03/25/02,06:40:44,27.59705,-99.47218,00179,0.00,000,01.7,05 5,272,1005402,1,03/25/02,12:40:45,03/25/02,06:40:45,27.59707,-99.47218,00179,0.00,000,01.7,05 5,272,1005402,1,03/25/02,12:40:46,03/25/02,06:40:46,27.59707,-99.47218,00178,0.00,000,01.7,05 5,272,1005402,1,03/25/02,12:40:47,03/25/02,06:40:47,27.59707,-99.47218,00178,0.00,000,01.7,05 5,272,1005402,1,03/25/02,12:40:48,03/25/02,06:40:48,27.59707,-99.47218,00177,0.00,000,01.7,05 5,272,1005402,1,03/25/02,12:40:49,03/25/02,06:40:49,27.59707,-99.47220,00177,0.00,000,01.7,05 5,272,1005402,1,03/25/02,12:40:50,03/25/02,06:40:50,27.59707,-99.47220,00177,0.00,000,01.7,05 5,272,1005402,1,03/25/02,12:40:51,03/25/02,06:40:51,27.59707,-99.47220,00176,0.00,000,01.7,05 5,272,1005402,1,03/25/02,12:40:52,03/25/02,06:40:52,27.59707,-99.47220,00176,0.00,000,01.7,05 5,272,1005402,1,03/25/02,12:40:53,03/25/02,06:40:53,27.59707,-99.47220,00176,0.00,000,01.7,05 5,272,1005402,1,03/25/02,12:40:54,03/25/02,06:40:54,27.59707,-99.47220,00176,0.00,000,01.7,05 5,272,1005402,1,03/25/02,12:40:55,03/25/02,06:40:55,27.59707,-99.47220,00176,0.00,000,01.7,05 5,272,1005402,1,03/25/02,12:40:56,03/25/02,06:40:56,27.59707,-99.47220,00175,0.00,000,01.7,05

  14. Running the Preprocessor Select the directory containing the raw streams Select the target directory for writing the processed streams

  15. Sample Processed GPS Stream HREC,HDOP=5.0,Min Satellites=3 GREC,272,1005402,1,1017060037000,27.59705,-99.47217,0.00,000,0 GREC,272,1005402,1,1017060038000,27.59705,-99.47217,0.00,000,0 GREC,272,1005402,1,1017060039000,27.59705,-99.47217,0.00,000,0 GREC,272,1005402,1,1017060040000,27.59705,-99.47217,0.00,000,0 GREC,272,1005402,1,1017060041000,27.59705,-99.47217,0.00,000,0 GREC,272,1005402,1,1017060042000,27.59705,-99.47217,0.00,000,0 GREC,272,1005402,1,1017060043000,27.59705,-99.47218,0.00,000,0 GREC,272,1005402,1,1017060044000,27.59705,-99.47218,0.00,000,0 GREC,272,1005402,1,1017060045000,27.59707,-99.47218,0.00,000,0 GREC,272,1005402,1,1017060046000,27.59707,-99.47218,0.00,000,0 GREC,272,1005402,1,1017060047000,27.59707,-99.47218,0.00,000,0 GREC,272,1005402,1,1017060048000,27.59707,-99.47218,0.00,000,0 GREC,272,1005402,1,1017060049000,27.59707,-99.47220,0.00,000,0 GREC,272,1005402,1,1017060050000,27.59707,-99.47220,0.00,000,0 GREC,272,1005402,1,1017060051000,27.59707,-99.47220,0.00,000,0 GREC,272,1005402,1,1017060052000,27.59707,-99.47220,0.00,000,0 GREC,272,1005402,1,1017060053000,27.59707,-99.47220,0.00,000,0 GREC,272,1005402,1,1017060054000,27.59707,-99.47220,0.00,000,0 GREC,272,1005402,1,1017060055000,27.59707,-99.47220,0.00,000,0

  16. Basic Analysis Click button, navigate to directory containing pre-processed GPS streams and select Click button, navigate to appropriate input files, and select Leave blank to use default algorithm parameters Provide file name to store the derived travel diaries Click to run the trip detection after providing all inputs

  17. Basic Analysis: Results

  18. Enhanced Analysis Click button, navigate to appropriate input files, and select Additional inputs for enhanced analysis Progress bar

  19. Enhanced Analysis: Results

  20. Querying and Aggregation: Options Input: a file containing derived travel diaries Aggregation criteria Filtering criteria

  21. Querying and Aggregation: Results Overall aggregation summary

  22. Querying and Aggregation: Results Trip table and inter-zonal performance measures (over entire day and all trip purposes)

  23. Querying and Aggregation: Results Trip table and inter-zonal performance measures (PM peak, all trip purposes)

  24. Querying and Aggregation: Results Trip table and inter-zonal performance measures (entire day, home-based work trips)

  25. Thank You!

  26. Structure of GPRMC Streams

  27. Structure of GeoLogger Streams

  28. Algorithm Parameters

  29. Conceptual Overview of Process Module Accept inputs Read in data for first/next vehicle Scan GPS stream until a potential trip is detected Compute trip characteristics Perform reasonableness checks Potential trip passes checks Potential trip fails checks Write trip to output file Check if end of GPS stream is reached for the current vehicle No Yes Check if there are any more vehicles in the database Yes No Trip diary extraction complete

  30. Attributes Characterizing Each Trip in the Derived Travel Diary Database

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