Transportation Planning, Climate Change, and Decisionmaking Under Uncertainty

ravel demand forecasting as widely practiced today deals inadequately with uncertainty. Methods currently used to forecast travel at the regional level simplify the world for which they forecast by relying heavily on point estimates. Forecasts are developed through the application of sequences of independent models in which the outputs from one become inputs to others. The current transportation modeling process is demanding in the sense that it employs a great deal of data to a large number of interconnected models having many parameters. The complexity of the modeling process, however, does not extend to the accurate representation of complex economic and social phenomena, and point estimates of many quantities are used that make it difficult to analyze or even to represent the uncertainty that characterizes transportation systems and traveler decisionmaking. After summarizing the major characteristics of travel forecasting procedures and their limited treatment of uncertainty, this paper presents several methods by which forecasting has been done outside the field of transportation that include explicit consideration of uncertainty. Influence trees and influence diagrams, real options, adaptive management, and the use of scenarios in planning and policy making are described and their application to policymaking under uncertainty is explored. Methods that aim to achieve robustness and resiliency rather than to optimize system performance are also described. Such methods would help us try to create transportation systems that perform acceptably under a range of potential future conditions rather than to find a single system design that best meets a set of precisely specified set of evaluation criteria. Case studies are presented that illustrate the application of methods which incorporate decisionmaking under uncertainty. The applications of these methods that are summarized in this paper deal with cases outside of transportation, including military planning and planning for higher education systems. The cases are indicative of ways in which such methods might be applied in transportation and comments are offered regarding opportunities and difficulties that might be involved if such methods were extended to applications in the field of transportation.