Lead Presenter Biography

Thomas Rossi, a Principal of Cambridge Systematics, is an internationally recognized expert in travel demand modeling. He has been doing this for more than 40 years but still acts alike he’s young (or perhaps he is just immature). Tom has led or overseen the development of many activity-based and trip-based models throughout the country--not too many to count, but he has lost count. He has been an expert advisor to federal agencies and metropolitan planning organizations in the development of travel models and survey data collection efforts. For 30 years, Tom has worked with the U.S. Department of Transportation to conduct research and develop and teach training courses in travel demand modeling. He is a past chair of the Transportation Research Board’s Transportation Demand Forecasting Committee. Tom has been to all but three of the predecessor conferences to this one, but he has good excuses. He is very happy to visit Indianapolis, which had been the largest U.S. city he had never been to. He will buy a drink for the first person to guess his new largest unvisited city (one guess per person!).

Co-Authors

Presentation Description

The New York Metropolitan Transportation Council (NYMTC) maintains one of the largest metro area travel demand models in the world. This model was recently updated to reflect the ways in which travel is rapidly changing in the vibrant, diverse New York metropolitan area. It is being used for a variety of planning analyses in the region, including air quality conformity analysis, long-range plan development, transportation investment studies, and policy analyses. The validation of this model is a very challenging effort, requiring a wealth of travel behavior, demographic, and transportation system data from a vast variety of sources.

The model region has over 22 million in population spread over three states and 28 counties. These people make over 60 million trips on an average weekday. Visitors to the region make another million trips, and there are another four million daily truck trips. Over 30% of personal trips are made by modes other than private auto, including transit, ferry, taxi, ridesharing services, and active transportation modes. The non-auto mode share is even higher in New York City.

The model validation, which uses a 2019 base year, is much more challenging than similar efforts in other regions, not only due to the size of and nature of travel in the region, but also due to the number of different validation data sources. These include travel behavior data from household, establishment, and transit surveys; ridership data from three major and numerous smaller transit operators, traffic counts from three states, and passively collected data from location-based service (LBS) data. These sources include data collected using a multitude of different methods, at different points in time, and with different sampling rates. Combining these disparate data sets into a consistent set of data that can be used for model validation is a difficult but critical task.

This presentation will describe how the data sets were processed and analyzed and how a successful validation of this large model was accomplished. We will discuss how the various types of data were analyzed for consistency and prioritized for use in validation. A particular focus will be on how the LBS data have been used to help the model produce reasonable origin-destination and time of day patterns for resident tours and trips as well as for the visitor model component.

While most planning jurisdictions in the U.S. do not have the same level of geographic and travel diversity as the New York region, all model developers need to deal with a variety of data sources that have inconsistencies such as those described here. This presentation should help provide advice and guidance for planners dealing with this issue. 

Presentation File