Investigating the impacts of built environment on vehicle miles traveled and energy consumption: Differences between commuting and non-commuting trips

《Investigating the impacts of built environment on vehicle miles traveled and energy consumption: Differences between commuting and non-commuting trips》

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关键字: Built environment; VMT; Energy consumption; Multiple-group SEM; Commuting trip; RESIDENTIAL SELF-SELECTION; LAND-USE; MODELING APPROACH; URBAN FORM; NONWORK TRAVEL; BEHAVIOR; TRANSIT; PATTERNS; TRANSPORTATION; STRATEGIES

作者单位: [Ding, Chuan; Wang, Yunpeng] Beihang Univ, Sch Transportat Sci & Engn, Beijing Key Lab Cooperat Vehicle Infrastruct Syst, Beijing 100191, Peoples R China. [Liu, Chao] Univ Maryland, Natl Ctr Smart Growth Res, College Pk, MD 20742 USA. [Zhang, Yi] Shanghai Jiao Tong Univ, Sch Naval Architecture Ocean & Civil Engn, Shanghai 200240, Peoples R China. [Yang, Jiawen] Peking Univ, Sch Urban Planning & Design, Shenzhen 518055, Peoples R China. Zhang, Y (reprint author), Shanghai Jiao Tong Univ, 800 Dongchuan Rd, Shanghai 200240, Peoples R China. E-Mail: cding@buaa.edu.cn; cliu8@umd.edu; darrenzhy@sjtu.edu.cn; yangiw@pkusz.edu.cn; ypwang@buaa.edu.cn

摘要: This research contributes to the understanding of the impacts of the built environment on vehicle miles traveled (VMT) and energy consumption by considering the mediating effects from vehicle type and travel speed. Meanwhile, whether the relationships among the built environment, VMT and energy consumption vary between commuting and non-commuting trip was examined by applying the multiple-group structural equation model (SEM). The primary travel data used in the research is drawn from the National Household Travel Survey (NHTS) Baltimore Add-on data. In this study, the built environment was measured for each residential location based on various external sources. By controlling for the socio-demographic factors, the model results show that the effects of the built environment on travel speed, VMT and vehicle energy consumption significantly vary between commuting and non-commuting trips. For the two different travel types, the direct, indirect, and total effects of the built environment measurements on VMT and vehicle energy consumption were discussed. The model results confirmed the important roles played by the built environment in influencing VMT and vehicle energy consumption. The results are expected to give urban planners and policy makers a better understanding on how the built environment factors can impact the VMT and energy consumption, and consequently develop more effective and targeted countermeasures.