Developing a GPS-based truck freight performance measure platform.

Details

• Creators:
  McCormack, Edward ; Ma, Xiaolei ; Klocow, Charles ; Curreri, Anthony ; Wright, Duane
• Corporate Creators:
  University of Washington. Department of Civil and Environmental Engineering
• Corporate Contributors:
  Washington (State). Department of Transportation ; Washington State Transportation Center
• Subject/TRT Terms:
  • Global Positioning System
  • Freight transportation
  • Freight traffic
  • Truck traffic
  • Trucking Trucking--Washington (State)--Puget Sound Area--Data processing
  • Trucking--Washington (State)--Puget Sound Area--Evaluation
  • Freight and freightage--Washington (State)--Puget Sound Area--Data processing
  • Freight and freightage--Washington (State)--Puget Sound Area--Evaluation
  • Global Positioning System
• Publication/ Report Number:
  TNW2010-02;WA-RD 748.1
• Resource Type:
  Research Paper
• Geographical Coverage:
  Washington
• Edition:
  Final research report.
• Corporate Publisher:
  Transportation Northwest (TransNow) UTC
• Abstract:
  Although trucks move the largest volume and value of goods in urban areas, relatively little is known about their travel ; patterns and how the roadway network performs for trucks. Global positioning systems (GPS) used by trucking ; companies to manage their equipment and staff and meet shippers’ needs capture truck data that are now available to the ; public sector for analysis. The Washington State Department of Transportation (WSDOT), Transportation Northwest ; (TransNow) at the University of Washington (UW), and the Washington Trucking Associations (WTA) have partnered on ; a research effort to collect and analyze GPS truck data from commercial, in-vehicle, truck fleet management systems used ; in the central Puget Sound region. The research project is collecting commercially available GPS data and evaluating ; their feasibility to support a state truck freight network performance monitoring program. WSDOT is interested in using ; this program to monitor truck travel times and system reliability, and to guide freight investment decisions. ; The success of the truck freight performance measurement program will depend on developing the capability to ;  efficiently collect and process GPS devices’ output ;  extract useful truck travel time and speed, roadway location, and stop location information and ;  protect the identity of the truckers and their travel information so that business sensitive information is ; not released. ; While earlier studies have evaluated commercial vehicles’ travel characteristics by using GPS devices, these ; researchers did not have access to commercial fleet data and had to estimate corridor travel speeds from a limited number ; of portable GPS units capable of making frequent (1-to-60-second) location reads (Quiroga and Bullock 1998, Greaves ; and Figliozzi 2008, Due and Aultman-Hall 2007). This read frequency permitted a fine-grained analysis of truck ; movements on specific segments of the road network but did not provide enough data points to reliably track regional or ; corridor network performance. ; This research project is taking a different approach. The data analyzed in this project are drawn from GPS devices ; installed to meet the trucking sector’s fleet management needs. So the truck locations are collected less frequently (typically every 5 to 15 minutes) but are gathered from a much larger number of trucks over a long period of time. The ; researchers are collecting data from 2,000 to 3,000 trucks per day for one year in the central Puget Sound region. ; This report discusses the steps taken to build, clean, and test the data collection and analytic foundation from which the ; UW and WSDOT will extract network-based truck performance statistics. One of the most important steps of the project ; has been to obtain fleet management GPS data from the trucking industry. Trucking companies approached by WSDOT ; and the UW at the beginning of the study readily agreed to share their GPS data, but a lack of technical support from the ; firms made data collection difficult. The researchers overcame that obstacle by successfully negotiating contracts with ; GPS and telecom vendors to obtain GPS truck reads in the study region. The next challenge was to gather and format the ; large quantities of data (millions of points) from different vendors’ systems so that they could be manipulated and ; evaluated by the project team. Handling the large quantity of data meant that data processing steps had to be automated, ; which required the development and validation of rule-based logic that could be used to develop algorithms. ; Because a truck performance measures program will ultimately monitor travel generated by trucks as they respond to ; shippers’ business needs, picking up goods at origins (O) and dropping them off at destinations (D), the team developed ; algorithms to extract individual truck's O/D information from the GPS data. The researchers mapped (geocoded) each ; truck’s location (as expressed by a GPS latitude and longitude) to its actual location on the Puget Sound region’s roadway ; network and to traffic analysis zones (TAZs) used for transportation modeling and planning. ; The researchers reviewed truck freight performance measures that could be extracted from the data and that focused on ; travel times and speeds, which, analyzed over time, determine a roadway system's reliability. Because the fleet ; management GPS data from individual trucks typically consist of infrequent location reads, making any one truck an ; unreliable probe vehicle, the researchers explored whether data from a larger quantity of trucks could compensate for ; infrequent location reads. To do this, the project had to evaluate whether the spot (instantaneous) speeds recorded by one ; truck’s GPS device could be used in combination with spot speeds from other trucks on the same portion of the roadway ; network. ; The utility of spot speeds and the GPS data in general was evaluated in a case study of a three-week construction ; project on the Interstate-90 (I-90) bridge. The accuracy of the spot speeds was then validated by comparing the results ; with speed data from WSDOT's freeway management loop system (FLOW). ; The researchers also explored methods for capturing regional truck travel performance. The approach identified zones ; that were important in terms of the number of truck trips that were generated. Trucks’ travel performance as they traveled ; between these economic zones could then be monitored over time and across different times of day.
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• Format:
  PDF
• Funding:
  DTRT07-G-0010
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/18003/dot_18003_DS1.pdf
• File Type:
  [PDF - 4.01 MB]
• Collection(s):
  University Transportation Centers ; US Transportation Collection
• Main Document Checksum:
  urn:sha-512:21053d034c78265f3c7236c5d211ad74f48a807cbacf367fb9ee312926dda13dd430de20562abb89f2a14af46b29ea923cc3ce73338194db7d14bbfa4f4d1112