A Data Driven Approach to State Transportation Investment Decisions: A Transportation Project Investment and Evaluation Resource (T-Pier)

16445402016Final ReportPDFTech ReportContract # DTRT12GUTC12Highway planningInvestmentsDecision makingPlanning methodsinvestment decision makingnetwork designbi-level programmingAdministration and ManagementPlanning and ForecastingTransportation (General)GeorgiaUnited StatesNational Center for Transportation Systems Productivity and Management (U.S.)Welch, Timothy FKumar, AmitGeorgia Institute of Technology. Center for Quality Growth and Regional DevelopmentNational Center for Transportation Systems Productivity and Management (U.S.)United States. Department of Transportation. Office of the Assistant Secretary for Research and TechnologyUS Transportation CollectionOne of the challenges for transportation decision makers is to select link improvement or capacity expansion in the network under the constraint of budget such that various objectives of the decision maker, for example, total system travel time is minimized, social welfare (consumer surplus) is maximized, or total system emission is minimized, while accounting for the route choice behavior of users. Such type of investment decision-making involves the need to considering two entities, i.e., decision makers and road users, which make the decision-making process difficult. One of the approaches to addressing this two-hierarchical problem is by using bi-level programming built upon numerical methods and application algorithms such that optimal investment decisions are made in a network design problem. To test the approach, the model is applied to small and medium size example networks and the optimum results are presented. The data that was incorporated include the budget, cost function, time period of investments, modal network, free flow travel times by link, number of lanes and capacity by link, and origin destination matrices of the network. The results from the study has potential to efficiently make capacity expansion decision making for transportation planning and applications