This paper studies the difference in Vehicle Miles Traveled (VMT) and length of vehicle trips taken in the state of California by Place Type. Place Types are a measurement of urban form composed of built environment variables ranging from dense, accessible urban places to sparsely populated, remote rural places. This study is a further development of the study of Place Types and influence of the built environment on travel patterns. This paper finds that VMT and trip length are consistently lower for more urbanized Place Types. Difference in VMT and trip length is statistically significant for all Place Types, with Urban Centers having 64% lower daily VMT than Rural Places, 47% lower daily VMT than Suburban Places, and 34% lower daily VMT than Urban Places. Urban Centers additionally have 50% shorter trips than Suburban Places, and 72% shorter trips than Rural Places. This study also analyzed trends in travel using 2010 and 2040 modeled data and found that while individual VMT and trip length decreases, overall VMT increases. A linear regression model was fitted to VMT and trip length by Place Type to quantify the association between Place Types and travel. Outcomes variables of VMT per capita, Work, Shopping, and Other trip lengths had the best fit, with R-squared values of 0.1797, 0.2119, 0.171, and 0.171, respectively. Given the limitations of Place Types as a predictor variable, additional analysis of per capita VMT, Work, Shopping, and Other trip lengths by LEND index score was conducted. Fitting a polynomial model to the aforementioned outcome variables achieved R-squared values of 0.2477, 0.3275, 0.2817, and 0.267, respectively. This study further quantifies the association that Place Types and the built environment has with individual travel patterns and behavior, and measures change in VMT and trip length between different Place Types. By extension, Place Types also influence CO2 and GHG emissions, with more compact/efficient Place Types having significantly lower CO2 emissions than sprawling Place Types. This information may be used to support local efforts to further develop in-fill areas and reduce car dependency by demonstrating the reduction in vehicle travel as places and neighborhoods urbanize.