TRB Special Report 288, Metropolitan Travel Forecasting: Current Practice and Future Direction, examines metropolitan travel forecasting models that provide public officials with information to inform decisions on major transportation system investments and policies. The report explores what improvements may be needed to the models and how federal, state, and local agencies can achieve them. According to the committee that produced the report, travel forecasting models in current use are not adequate for many of today's necessary planning and regulatory uses.

A history of urban travel demand modeling (UTDM) and its enormous influence on American life from the 1920s to the present. For better and worse, the automobile has been an integral part of the American way of life for decades. Its ascendance would have been far less spectacular, however, had engineers and planners not devised urban travel demand modeling (UTDM). This book tells the story of this irreplaceable engineering tool that has helped cities accommodate continuous rise in traffic from the 1950s on. Beginning with UTDM’s origins as a method to help plan new infrastructure, Konstantinos Chatzis follows its trajectory through new generations of models that helped make optimal use of existing capacity and examines related policy instruments, including the recent use of intelligent transportation systems. Chatzis investigates these models as evolving entities involving humans and nonhumans that were shaped through a specific production process. In surveying the various generations of UTDM, he delves into various means of production (from tabulating machines to software packages) and travel survey methods (from personal interviews to GPS tracking devices and smartphones) used to obtain critical information. He also looks at the individuals who have collectively built a distinct UTDM social world by displaying specialized knowledge, developing specific skills, and performing various tasks and functions, and by communicating, interacting, and even competing with one another. Original and refreshingly accessible, Forecasting Travel in Urban America offers the first detailed history behind the thinkers and processes that impact the lives of millions of city dwellers every day.

Forecasting Urban Travel presents in a non-mathematical way the evolution of methods, models and theories underpinning travel forecasts and policy analysis, from the early urban transportation studies of the 1950s to current applications throughout the

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.

The most common method for producing regional or metropolitan area travel forecasts in the United States is to apply the following four modeling steps sequentially: trip generation; trip distribution; mode choice; and, route assignment. This traditional 4-step process passes output from one step to the next as input. While the process has produced forecast results sufficiently accurate for many types of long range transportation planning, it is commonly found that some of the outputs of the process are not consistent with inputs to earlier steps. The research undertaken in this project focused on methods to ensure that link speeds used in each step of the travel forecasting process are consistent with the final speeds estimated in the final step of the process. As a product of this research, a final report was prepared to provide guidance in the application of feedback.