Real-Time Information for Improved Efficiency of Commercial Vehicle Operations

Intelligent Transportation Systems (ITS) harness advanced communications and computation technologies in order to make transportation systems more efficient. This work is concerned with the application of ITS to commercial vehicle operations and freight mobility; it identifies and investigates potential uses of real-time information for the efficient management of carrier operations. In truckload and less-than-truckload operations, carriers typically know only a portion of the loads that must be moved more than a few hours before the moves must take place. Therefore, the assignment of an available driver to a load takes place in real-time or shortly after the request is received. The load acceptance decision made by a carrier must also be executed in real-time, and may have a significant impact on the carrier's ability to accept other loads requested in the near future. In this context vehicle to load assignments as well as the sequence in which loads are to be served may be revisited as demands unfold and traffic network conditions change. Because of the speed with which decisions must be made, the number of possible choices and the fact that the system is changing dynamically and often, unpredictably, locally oriented decision rules offer a promising alternative to approaches seeking global optimality or those which take into account long term or forecast information. The main hypotheses examined are, that real-time information on vehicle locations and demands can increase the efficiency of carrier fleet operations with respect to measures of trucking company profitability and responsiveness to customer requests, and, that real-time operational strategies perform well, compared to those requiring less real-time information, under certain conditions with respect to fleet size, level of demand and service deadlines. Operational strategies which take advantage of real-time information and, which include methods to perform load acceptance, assignment and re-assignment are examined both analytically, and in simulation framework developed to test these and related strategies under a variety of operating assumptions. Quantitative estimates of the benefits of real-time information for vehicle assignment and routing decisions for trucking operations are developed.