Fuel consumption and greenhouse gas (GHG) emissions in the transportation sector are a result of a "three legged stool": fuel types, vehicle fuel efficiency, and vehicle miles travelled (VMT). While there is a substantial body of literature that examines the connection between the built environment and total VMT, few studies have focused on the impacts of the street environment on fuel consumption rate. Our research applied Structural Equation Modelling (SEM) to examine how driving behaviors and fuel efficiency respond to different street environments. We used a rich naturalistic driving dataset that recorded detailed driving patterns of 108 drivers randomly selected from the Southeast Michigan region. The results show that, some features of compact streets such as lower speed limit, higher intersection density, and higher employment density are associated with lower driving speed, more speed changes, and lower fuel efficiency; however, other features such as higher population density and higher density of pedestrian-scale retails improve fuel efficiency. The aim of our study is to gain further understanding of energy and environmental outcomes of the urban areas and the roadway infrastructure we plan, design, and build and to better inform policy decisions concerned with sustainable transportation.