Developing a Statewide Truck Trip Management System

Trucking has become increasingly important to the economies of both the nation and to the State of Kansas. Rail has shifted from moving general commodities to long-haul unit trains leaving the general commodity movement as well as special high-value products to the trucking industry. For the most part, rail service is no longer provided to the individual local grain elevators. Two issues have emerged. One is the construction of roadways to handle the increased loads and the other is the possibility of interruption of service due to either natural disasters or to terrorist acts. In order to have a clear picture of the movements of trucks throughout the state, one must have data about the origins and destinations of these trucks. Interviewing a meaningful sample would be very costly to both the collecting agency and to the traveling public. Stopping trucks entering or leaving the state as well as at numerous internal locations is not feasible. Therefore a means of developing a simulated trip table to analyze the truck loading and route seems to be the only practical approach. Computer software has been developed to refine a starting trip table so that the resulting assigned traffic closely matches the actual counts that have been taken at numerous locations throughout the state. This research involved using two approaches. One was to refine a total trip table, regardless of the origin or destination of the trips. The other was to estimate the through trips, then subtract those trips from their respective state line counts. The remainders were then distributed to internal zones using a gravity model approach. This produced the external-local trips, which along with the through trips, were subtracted from each link of the state system over which they were assigned by the traffic assignment program. The weighted average speed limits were used to determine the minimum times for the assignment. Another gravity model was used to provide a first estimate of the trips between all of the internal zones within the state. The refinement process used the reduced counts to estimate the internal trips. The comparison of the two scenarios showed that the refinement model could provide a single trip table (Scenario 1) which, when assigned to the state network, closely reproduces the counts. However, the refined trip table did not provide realistic through and external-local trips which would be a concern when testing a road closure. The second scenario (Scenario 2) did not provide as good an assignment as the first but did provide the methodology for further refinement.


  • English

Media Info

  • Media Type: Web
  • Edition: Final Report
  • Features: Appendices; Figures; Tables;
  • Pagination: 43p

Subject/Index Terms

Filing Info

  • Accession Number: 01155369
  • Record Type: Publication
  • Report/Paper Numbers: K-TRAN: KSU-07-4
  • Contract Numbers: C1606
  • Created Date: Apr 23 2010 10:55AM