Extending transportation system capacity flexibility model
Continuing economic growth and lag in infrastructure expansion has made transportation a vital concern in the nation's agenda. This increase in future traffic will continue to result in increased congestion and greater inefficiencies throughout the nation's transportation system. Therefore, the three papers presented are an extension of prior capacity work by dealing with 2 important questions. One is to consider flexibility and the other is to connect it to concepts of resource uses, resource limitations, and economic and practical capacity. ^ The first paper develops measures of transportation system flexibility for accommodating changing demands and traffic patterns. This study builds on the prior capacity model and extends it to analyze capacity flexibility. MAXCAP and ADDVOL models were developed to measure system flexibility utilizing the concept of reserve capacity. Capacity flexibility is measured by comparing the MAXCAP and ADDVOL estimated capacity of different routing options in the transportation systems. The measures and routing options are vi implemented and tested on a doublestack containerized freight rail network. ^ The second paper will consider how system parameters, resource uses and resource limitations could impact the economic and practical capacity of the transportation system. These resources and system parameters include speed, energy, and demand pattern shifts, which were not included in the previous models. The CMCAP Model was developed to estimate economic and practical capacity of the transportation system. CMCAP model results are used as a metric to compare changes in system parameters and how they effect the overall system capacity. ^ The last paper attempts to optimize the speed profile of a train route to minimize energy consumption. This is sought in a manner that makes possible generalization to a variety of different rail lines, train types, and other conditions. These rules are derived using an analytic approximation to fuel consumption that is widely used for line haul railroad freight and passenger trains powered by diesel-electric locomotives. The rules are then tested using a standard train performance and fuel consumption simulator. The results indicate that the rules do in fact yield lower fuel consumption than speed profiles that deviate from the rules. ^
Engineering, Civil|Engineering, System Science
David J Chang,
"Extending transportation system capacity flexibility model"
(January 1, 2003).
Dissertations available from ProQuest.