Combining California Household Travel Survey data with harvested social media information to form a self-validating statewide origin-destination travel prediction method.

Combining California Household Travel Survey data with harvested social media information to form a self-validating statewide origin-destination travel prediction method.
PI: Kostas Goulias, UC Santa Barbara
$128,000

Abstract: In this research project we will fill a gap in empirically supported fusion of multiple sourced data to produce statewide travel patterns and large scale estimates of induced travel demand. In this way we can develop a baseline short- and long- distance travel inventory that includes statewide vehicle miles traveled (VMT). Then, a procedure will be created to monitor the evolution of travel in California using data from social media adjusted by region and correlated with land uses at fine geographic areas. This method addresses one of the most critical themes in UCCONNECT 2015-2016 RfP to understand induced travel demand. First, the development of a synthetic inventory of travel in our State provides the reference needed to monitor if change in travel will take place due to changing policies including land use patterns. This synthesis will use the data in the California Household Travel Survey, Origin-Destination data from the Statewide Travel Demand Model, and social media harvested data. Second, a conversion procedure will be created to transform harvested data from the web into origin-destination travel and trip lengths to produce estimates of VMT. This will be done by using an OD estimation method developed at UCSB supplemented with the findings of a small pilot test by researchers at UCSB in this proposed project. Third, an automated procedure to harvest data and convert them into travel predictions statewide will be created and then used to derive estimates of induced demand.

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