Drayage optimization algorithms may not apply equally in different operating scenarios, it is important to develop a deep understanding of the environment in which a solution will be deployed in advance of deploying an algorithm or prototype.

Prototype deployment and results in the execution of the Freight Advanced Traveler Information System Small-Scale Testing Program in Dallas-Fort Worth.

Date Posted

Freight Advanced Traveler Information System (FRATIS) - Dallas-Fort Worth (DFW) Prototype: Final Report

Summary Information

This report summarizes the prototype deployment and results in the execution of the Freight Advanced Traveler Information System (FRATIS) Small-Scale Testing program in the Dallas-Fort Worth (DFW) region of Texas (FRATIS DFW). The purpose of the FRATIS DFW prototype was to demonstrate a small-scale implementation of the USDOT’s FRATIS bundle of applications. At the conceptual level, these included an intermodal drayage optimization application and a freight-specific travel planning and performance application. The DFW region was selected due to the size of the area (the fourth largest metropolitan area in the United States) and the prevalence of dray traffic in the region due to the presence of multiple Class I rail terminals and the many container yards, distribution centers and warehouses that network with these entities. At the highest level, the performance goals for the overall FRATIS bundle of applications included:

  • Reducing the number of bobtail trips by 10 percent
  • Reducing terminal queue time by 20 percent
  • Reducing travel time by 15 percent
  • Reducing fuel consumption by 5 percent
  • Reducing criteria pollutants and greenhouse gas emissions by 5 percent each.

Lessons Learned

During the testing phase, the FRATIS development team identified and documented the following lessons learned and opportunities for expansion and improvement:

  • The optimization program was the focus of the prototype, limiting the ability to broaden other applications. While the drayage optimization program had success in a prior deployment, conditions in Dallas were different and many changes had to be made to the algorithm. A better approach would have been for the prototype teams to evaluate the participating drayage company workflows prior to the start of the prototype and assess whether the program was best suited for optimizing the work. It is also likely that the work and effort in making the program a success went on for too long prior to moving on to a different solution.
  • Automating certain functions of the prototype increased usage. Drayage companies are consistently trying to do more with less, such operational priorities will ultimately supersede temporary participation in a voluntary pilot. Automation of functions is in closer alignment with the priorities of drayage firms.
  • Including vendors/providers had pros and cons. A software provider was instrumental in creating the proper dynamic queries to capture the correct baseline data and input data for the drayage optimization programs. They also provided critical insight into troubleshooting issues with the input data. Integration with an existing software package also expedited deployment. However, implementation of some features and functionalities were limited by this relationship and that software provider was not specifically defined as a subcontractor.
  • The dynamic routing solution needs the right environment – a regional carrier may benefit more from this type of solution. The participating drayage companies felt that the dynamic routing, traffic, navigation, and weather information was somewhat helpful, but neither felt it was an application they would continue using after the pilot. Feedback from participants suggests that this type of information was better suited to drivers on regional routes, where they may be less familiar with the routes between frequently visited facilities.
  • The "right" stakeholders are critical to test success. The right stakeholder is one open to the benefits a technology may provide and can apply said technology within their organization to realize the highest level of benefits possible. Stakeholders must also be open to changing operational preferences, as the fewer constraints on the technology, the more opportunity it has for success.