Qing Shen

The Influence of Street Environments on Fuel Efficiency: Insights from Naturalistic Driving

Authors: Wang, X. G., C. Liu, L. Kostyniuk, Q. Shen, and B. Shan.
Synopsis: Fuel consumption and greenhouse gas 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. Ourresearch applied structural equation modeling 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.


Changing Urban Growth Patterns in a Pro-Smart Growth State: The Case of Maryland, 1973-2002

Authors: Qing Shen, Chao Liu, Joe Liao, Feng Zhang, Chris Dorney (2007)
Synopsis: This paper presents a study of recent urban growth patterns in the state of Maryland, which is known as a leader in the current smart growth movement. Five research questions are addressed in this study. First, what have been the trends in urban growth and land use in Maryland for the past 30 years? Second, to what extent have recent urban development patterns in Maryland matched the typical characterization of sprawl? Third, how have the intensity of urban land uses and the physical forms of urban growth in this state varied among its counties? Fourth, have the smart growth initiatives, especially the “Smart Growth Area Act,” significantly affected urban development patterns? Fifth, does the effectiveness of smart growth initiatives vary significantly across local jurisdictions? To answer these research questions, we measure, analyze, and model urban development patterns in Maryland using land use and land cover (LULC) and demographic data for 1973, 1992, 1997, 2000, and 2002. By calculating several important indicators of urban development patterns, we find that for the past three decades population densities have continued to decrease for the state as a whole. However, this trend has slowed since 1997, when the state implemented the smart growth programs. The land conversion rate has somewhat decreased, which indicates that smart growth initiatives have helped, in a limited way, curtail the growing demand for urban land and residential space. Further, we find that the patterns of urban growth and land use have generally become slightly less fragmented and more continuous since 1997. Additionally, we find significant variations in urban development patterns among local jurisdictions. In general, higher densities, higher levels of compactness, and lower levels of fragmentation are observed in the more urbanized counties. Moreover, by estimating a series of logit models of land conversion, we find that Maryland’s “Smart Growth Area Act” has generally increased the probability of land use change from non-urban to urban for areas designated as “Priority Funding Areas.” The effectiveness of this program, however, varies significantly across the counties. We discuss the implications of these findings and identify the directions for future research.


Reexamining ICT Impact on Travel Using the 2001 NHTS Data for Baltimore Metropolitan Area

Authors: Feng Zhang, Kelly J. Clifton, Qing Shen (2005)
Synopsis: This paper presents an empirical examination of the relationship between information and communications technology (ICT) and travel. The primary research objective is to examine the effects of several indicators of ICT usage on three measures of travel outcomes. The ICT indicators include the frequency of Internet use, the number of mobile phones, and the presence of a telephone at home for business purposes. The travel outcomes examined are vehicle miles traveled (VMT), total daily trips, and daily walking trips. Using the 2001 national household travel survey (NHTS) data for Baltimore metropolitan area, a linear regression model is estimated for VMT and two Poisson regression models are estimated for, respectively, total daily trips and daily walking trips. The empirical results suggest simultaneous existence of substitution and complementarity interactions between ICT and travel, with complementarity as the dominant form. Implications of the research findings are discussed.