Integrate FRATIS with existing drayage order management systems to reduce human data entry errors and improve efficiency.

Evaluation of a drayage optimization tool proof of concept.

Date Posted
09/14/2018
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Identifier
2018-L00835

Enhancement of Cross-Town Improvement Project (C-TIP) Drayage Optimization Proof of Concept - Los Angeles/Long Beach, California

Summary Information

This project evaluated the deployment of a drayage optimization tool designed to use Freight Advanced Traveler Information System (FRATIS) data and Corridor Optimization for Freight (COfF) algorithms to improve trucking operations by reducing the number of unproductive truck drayage trips (short-haul freight movement) in the Los Angeles/Long Beach area of California.



The project conducted from July through October 2017 included participation from five motor carriers and one drayage company. In addition to a quantitative analysis of truck drayage performance with and without the optimization planning tool, lessons learned from experience were collected to support future FRATIS deployments.

Lessons Learned

Integrating FRATIS with existing order management systems reduces human data entry errors. Using FRATIS, an entire set of daily orders can be entered in about the same amount of time it would take to enter a single order without the system. This high level of functionality played a critical role in supporting participants’ increased use of the tool and also served to greatly reduce the potential for data entry human errors.



Having accurate order data is critical to perform successful route optimization. FRATIS reduces potential for disruption by not allowing invalid orders to be entered into the optimization algorithm which forces team members to address potential data issues before and during deployment.



Methods for assigning orders to drivers are highly dynamic and are customized to the individual needs and requirements of different companies, leading to different user expectations of FRATIS. The following categories of data elements were common, but data definitions were likely to vary between companies.

  • Number of imports available for pickup at terminals.
  • Number of empty containers ready to be returned.
  • Length of the trip, such as a short- or long-haul move.
  • Type of cargo, such as dry or refrigerated cargo.
  • Chassis ownership, such as whether the trucking company owns the chassis or if it belongs to a chassis pool.
  • Driver’s preferences.
  • Customer requests and priorities.



Offer multimedia trainings through a range of different delivery approaches. Allow users to become familiar with the FRATIS interface and formulate questions prior to training.



It is challenging to effectively optimize empty returns given there are many uncertainties characterizing this particular drayage activity. One issue faced by many drayage companies is determining where to return empty containers. This creates a series of costly problems, such as where and how to find storage for empty containers and paying per diem charges if empty containers are not returned on time.



When assigning orders, dispatchers must consider drivers’ preferences for specific routes. over 80 percent of the drivers in the Los Angeles/Long Beach region are owner operators and serve as independent contractors. This adds complexity to solving the routing problem. To address this problem, dispatchers often present drivers with alternative assignments to choose from once the optimization is run.



Real-time dynamic planning requires real-time data updates. Among the many ever-changing factors are stop time at pickup and drop-off locations, equipment availability at intermodal facilities and marine terminals, waiting times and turn times at marine terminals, traffic conditions, road closures, and others.



Drivers currently use many mobile applications; adding an additional one can create challenges. Both trucking managers and dispatchers expressed concerns about how use of the Driver Mobile Application might affect drivers’ safety and productivity (although the application was designed to lock when the driver is in motion).

Goal Areas
System Engineering Elements

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