Experimental design, data collection and model development to forecast vehicle modes of operation

Researchers have identified and quantified shortcomings of existing mathematical models for predicting emissions from motor vehicles, especially with regard to sensitivity to the operating modes of vehicles. In response, major efforts are underway to develop a new generation of emissions models. However, in current regional modeling practice, there are no tools for forecasting vehicle activity modes that are needed as input to this new generation of models. Other options available for forecasting activity are crude and are not sensitive to changes in traffic conditions brought about by current and emerging transportation planning alternatives. In order to address this shortcoming, researchers at Georgia Institute of Technology, University of California at Davis, San Jose University and California Polytechnic University in San Luis Obispo are developing a method to forecast modes of vehicle activity. This paper describes the current research to define the data needs, collect the data with a variety of available instrumentation, post-process the data from differing instrumentation into a compatible data base, estimate models to answer research questions, and address problems regarding the forecasting of vehicle modes of operation on freeways.