Three papers on measuring the reliability and flexibility of transportation system capacity

An extensive review of' empirical traffic data collected over the last several decades indicates the trend of increasing traffic congestion due to surging freight traffic volume and downsizing of transportation infrastructure. A critical issue for continuing of economic and social growth is having an adequate “system level” capacity of transportation systems. Furthermore, the stability of transportation capacity should be well understood and assessed to deal with traffic congestion, since transportation systems are not fixed over time and are constantly impacted by changes in operating conditions.; In view of the current situation, this research seeks to address vital aspects of characterizing system capacity, which measures the maximum possible traffic throughput of a transportation system over a time period under stochastic conditions. This research measures the reliability and flexibility of system capacity. Reliability is concerned with the stability of the internal network environment, while flexibility deals with the uncertainty of the external environment. First, an overview of previous research related to defining and measuring the capacity, reliability and flexibility of transportation systems is conducted (Paper I). A comprehensive look at performance measures reveals shortcomings in the modeling of the system capacity reliability and flexibility. Thereafter, the reliability of system capacity, defined as the probability of accommodating a certain traffic demand under stochastic environments, is characterized and approximated with three proposed heuristic approaches (Paper II). Procedures for proposed Monte Carlo, Scenario-Based, and Dual-Based algorithms are described. Then, a conceptual definition of system capacity flexibility is developed in order to measure the ability of a transportation system to expand its system capacity to accommodate various traffic demands in uncertain environmental conditions (Paper III).; Finally, these algorithms are applied to the freight transportation network in order to demonstrate their effectiveness. Numerical results showing the benefit and effectiveness of these algorithms are provided and discussed in each paper. In summary, this research illustrates that analytical algorithms measuring system capacity reliability significantly reduces computation time over the Monte Carlo simulation, and system capacity of a transportation system can be improved significantly by following an effective implementation approach for flexibility enhancements based on the dual principle of linear programming.