Driving Innovation within the Transportation Industry
What is the MIT FreightLab?
The MIT FreightLab mission is to drive innovation into the freight transportation industry in order to reduce cost, minimize risk, and increase the level of service. Freight transportation is subject to highly volatile demand and costs that are typically outside of a firm’s ability to control or even influence. This is compounded by a dominant design in terms of how freight is historically procured and managed. FreightLab research focuses on working with companies to develop and implement real-world solutions to these challenges.
FreightLab objectives are to develop innovations in freight transportation planning and operations and drive them into practice. Recently, we have developed methods for forecasting both short term spot-market rates and longer-term contract rates. We are exploring alternative contract forms between shippers and carriers that increase the level of trust in the relationship and yield better results for both parties. Working with a wide range of shippers, carriers, and third-party providers, the freight lab team develops and delivers better ways to design, procure, and manage large-scale freight transportation systems.
In the U.S. truckload (TL) industry, shippers and motor carriers face major challenges as a result of uncertainties in the amount and timing of demand for capacity, availability of trucks at the time and locations needed, and external market conditions.
We analyze shipment data for assessing the impact of natural disasters on freight movement. Our focus is on North-Atlantic hurricanes that make landfall in the contiguous USA. Quantifying the impact of natural disasters on the truckload industry can help shippers know what costs to expect, what routes to avoid, how to procure and position relief goods.
The Driver Initiative looks to uncover new insights and identify specific opportunities to improve the effectiveness, efficiency, and quality of life of American over-the-road truck drivers through an analysis of individual driver actions and behavior using ELD and other related data
The project aims at predicting long haul truckload spot market rates in continental USA for the near future. Accurate forecasting of transportation costs is a key step in logistical planning. It helps buyers and sellers
of transportation services make better decisions at all stages of a supply chain.
This continuing project examines how truckload transportation rates are impacted by different policies, procedures, and network characteristics. Various econometric techniques were employed to quantify these impacts. Additionally, the projects uncovered actions that both shippers and carriers can take to reduce overall transportation cost.
The future rarely moves in predictable, incremental ways. Often seemingly small changes in technology, demographics, regulations, economics, or a myriad of other factors have dramatic and unintended impacts on how companies source, manufacture, distribute and operate in general. These non-linear impacts are very difficult to predict using traditional forecasting methods and techniques since they, by definition, do not follow any historical patterns.
The design, procurement, and management of a global ocean transportation (GOT) network is a challenging task. By definition, the network spans multiple continents, involves a variety of business units, and can impact and influence operations from procurement to final assembly. Additionally, the ocean carrier industry has particular pressures in terms of market structure, levels of competitiveness, and transparency (or lack thereof) of pricing and service levels. While the ocean carrier market appears to be global on the surface, in reality most of its activities are directed at supporting specific trade lanes.
This project explored the use of a variety of different transportation relationships between shippers and carriers to improve overall performance. Specifically, working with several different retailers and manufacturers, developed an approach for determining the optimal assignment of for-hire and private fleet assets across a freight transportation network while considering the uncertainty of demand for truckloads.
This research initiative addresses how shippers (buyers) should procure transportation services from truckload (TL) motor carriers (suppliers). TL carriers operate over irregular routes moving directly from origin to destination without any intermediate stops. A significant portion of a TL carrier’s costs is due to the repositioning of empty vehicles (deadheading) from the destination of one load to the origin of the follow-on load.
Our Partners & Sponsors
Dr. Chris Caplice
Dr. David Correll
Dr. Francisco Jauffred
Updates from the Lab
The Scenario Planning Toolkit is designed to help transportation planners in any organization design, plan, and run a Scenario Planning Workshop. There are two types of material contained here: Guidebooks and Workshop Collateral.
The U.S. DOT Volpe Center welcomed Chris Caplice, PhD, Executive Director of the Massachusetts Institute of Technology’s Center for Transportation & Logistics (CTL), as the second speaker in the Transportation in the Age of Artificial...
This animated video can be used to help an audience understand what Scenario Planning is. It complements (and can replace) the Introduction to Scenario Planning PPT.