Influences of built environment characteristics and individual factors on commuting distance: A multilevel mixture hazard modeling approach

被引:69
作者
Ding, Chuan [1 ]
Mishra, Sabyasachee [2 ]
Lu, Guangquan [1 ]
Yang, Jiawen [3 ]
Liu, Chao [4 ]
机构
[1] Beihang Univ, Beijing Key Lab Cooperat Vehicle Infrastruct Syst, Sch Transportat Sci & Engn, Beijing 100191, Peoples R China
[2] Univ Memphis, Dept Civil Engn, Memphis, TN 38152 USA
[3] Peking Univ, Sch Urban Planning & Design, Shenzhen 518055, Peoples R China
[4] Univ Maryland, Natl Ctr Smart Growth Res, College Pk, MD 20742 USA
基金
中国博士后科学基金; 中国国家自然科学基金;
关键词
Built environment; Commuting distance; Land use; Spatial heterogeneity; Multilevel hazard model; RESIDENTIAL SELF-SELECTION; TRAVEL BEHAVIOR; LAND-USE; TIME; CHOICE; STOP; CONNECTIVITY; IMPACTS;
D O I
10.1016/j.trd.2017.02.002
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Concerns over transportation energy consumption and green-household gas (GHG) emissions have prompted a growing body of research into the influence of built environment on travel behavior. Studies on the relationship between land use and travel behavior are often at a certain aggregated spatial unit such as traffic analysis zone (TAZ), spatial issues occur among individuals clustered within a zone because of the locational effects. However, recognition of the spatial issues in travel modeling was not sufficiently investigated yet. The object of this study is twofold. First, a multilevel hazard model was applied to accommodate the spatial context in which individuals generate commuting distance. Second, this research provides additional insights into examine the effects of socio-demographics and built environment on commuting distance. Using Washington metropolitan area as the case, the built environment measures were calculated for each TAZ. To estimate the model parameters, the robust maximum likelihood estimation method for a partial function was used, and the model results confirmed the important roles that played by the TAZ and individual level factors in influencing commuting distance. Meanwhile, a comparison among the general multilevel model, single level and multilevel hazard models was conducted. The results suggest that application of the multilevel hazard-based model obtains significant improvements over traditional model. The significant spatial heterogeneity parameter indicates that it is necessary to accommodate the spatial issues in the context of commuting distance. The results are expected to give urban planners a better understanding on how the TAZ and individual level factors influence the commuting distance, and consequently develop targeted countermeasures. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:314 / 325
页数:12
相关论文
共 40 条
[1]   Hazard-Based Analysis of Travel Distance in Urban Environments: Longitudinal Data Approach [J].
Anastasopoulos, Panagiotis Ch ;
Bin Islam, Mouyid ;
Perperidou, Dionysia ;
Karlaftis, Matthew G. .
JOURNAL OF URBAN PLANNING AND DEVELOPMENT-ASCE, 2012, 138 (01) :53-61
[2]   Urban land uses, socio-demographic attributes and commuting: A multilevel modeling approach [J].
Antipova, Anzhelika ;
Wang, Fahui ;
Wilmot, Chester .
APPLIED GEOGRAPHY, 2011, 31 (03) :1010-1018
[3]   The spatial analysis of activity stop generation [J].
Bhat, C ;
Zhao, HM .
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL, 2002, 36 (06) :557-575
[4]   A comprehensive analysis of built environment characteristics on household residential choice and auto ownership levels [J].
Bhat, Chandra R. ;
Guo, Jessica Y. .
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL, 2007, 41 (05) :506-526
[5]   A continuous-time model of departure time choice for urban shopping trips [J].
Bhat, CR ;
Steed, JL .
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL, 2002, 36 (03) :207-224
[6]   A Broader Context for Land Use and Travel Behavior, and a Research Agenda [J].
Boarnet, Marlon G. .
JOURNAL OF THE AMERICAN PLANNING ASSOCIATION, 2011, 77 (03) :197-213
[7]   Examining the impacts of neighborhood design and residential self-selection on active travel: a methodological assessment [J].
Cao, Xinyu .
URBAN GEOGRAPHY, 2015, 36 (02) :236-255
[8]   Disentangling the influence of neighborhood type and self-selection on driving behavior: an application of sample selection model [J].
Cao, Xinyu .
TRANSPORTATION, 2009, 36 (02) :207-222
[9]   Effects of built environments on vehicle miles traveled: evidence from 370 US urbanized areas [J].
Cervero, Robert ;
Murakami, Jin .
ENVIRONMENT AND PLANNING A-ECONOMY AND SPACE, 2010, 42 (02) :400-418
[10]   Role of the built environment on mode choice decisions: additional evidence on the impact of density [J].
Chen, Cynthia ;
Gong, Hongmian ;
Paaswell, Robert .
TRANSPORTATION, 2008, 35 (03) :285-299