Implementing Innovation in Planning Practice: The Case of Travel Demand Forecasting
Travel demand modeling is a core technology of transportation planning and has been so for half a century. This technology refers to the structured use of mathematical formulae and spatial data to forecast the likely travel impacts of possible transportation, land use, and demographic scenarios. Although this planning practice is pervasive, critics have long argued that is has been resistant to innovation. As the policy scenarios explored through modeling become increasingly complex, particularly in the face of climate change, the question arises of whether regional planning agencies will be able to change their practices through implementing innovation. This research addresses this question by examining the history of travel demand modeling as practiced at regional planning agencies, interviewing travel demand modeling experts, conducting detailed case studies of model practice evolution at two metropolitan planning organizations, the San Francisco Bay Area's Metropolitan Transportation Commission (MTC) and the capital region's Sacramento Area Council of Governments (SACOG), and analyzing the early impacts of California's groundbreaking climate change legislation on the modeling practiced in the Golden State. The findings suggest that far from being a static practice, travel demand modeling at regional agencies has advanced, particularly with public interest in exploring the impacts of major policy interventions. The nature of travel demand models does not naturally foster changes in practice; however, government action can structure the innovation process by establishing clear expectations of agency modeling capabilities to meet legislative mandates, providing resources for investments in new approaches, and creating forums for interagency interaction and information dissemination.