Research On Impacts Of Urban Built Environment On Travelaccounting For Spatial Heterogeneity

Global climate change has become an important issue in the21stcentury, since theincreasing non-renewable energy consumption and greenhouse gas emissions have put ahuge threat on the global ecological environment. Urban carbon emissions are mainlyfrom industrial, architecture and transportation. With the increase of car ownership andcommuting distance due to the job-housing separation in large cities, the amount oftransportation carbon emission is sharply raising. How to reduce the urban transportenergy consumption and carbon emission has become a challenging practical problem.In contrast to the travel demand management measures such as traffic congestion toll,odd-and-even license plate rule and vehicle fuel tax, urban built environment plays apositive role on travel that is considered as an essential method to decrease the autodependency thereby reducing transport energy consumption and carbon emissions. Howto optimize the urban built environment to affect commuting travel demand, and thenreduce car ownership and promote switching to green travel, thereby reducing transportenergy consumption and carbon emissions, has become a hot issue among domestic andforeign scholars in the field of urban planning and related areas.To decrease auto dependency, it is necessary to make an effective urban planningwhose theoretical basis is to understand the relationship between built environment andtravel. This study reviews the impacts of built environment on travel qualitatively. Fromthe microscopic perspective of individual behavior, the analytical framework isproposed about car ownership-mode choice and travel distance to decrease autodependency. In this paper, spatial heterogeneity is incorporated into analyze the impactsof built environment on travel to reveal the mechanism between them.Spatial heterogeneity is incorporated into analyze the impacts of built environmenton household car ownership. The Bayesian hierarchical ordered probit model isestablished to characterize decision-making process and describe the spatialheterogeneity of household car ownership. Using the Washington, DC as empirical case,this paper analyzes the impacts of residential built environment on car ownership, andthen reveals the differences between ignoring and accouting for spatial heterogeneity.In order to systematically understand the impacts of residential and workplace builtenvironment on commuting mode choice, meanwhile describle the spatial heterogeneityof travel mode choice, this paper establishes the Bayesian hierarchical cross-classifieddiscrete choice model to reveal the impacts of residential and workplace builtenvironment on commuting mode choice based on commuting trip chain.It provides amethod to reveal the impacts of built environment in trip orgion and destination on travel mode choice. Using the Washington, DC as empirical case, this paper analyzesthe impacts of residential and workplace built environment on commuting mode choice,and then reveals the differences between ignoring and accouting for spatialheterogeneity of commuting mode choice.Considering commuting travel behavior is influenced by the built environmentboth in trip origin and destination, this paper integrates the workplace built environmentinto anlyze the impact of residential buitlt environment on commuting vehicle milestraveled. The Bayesian hierarchical cross-classified linear model is established as theanalytic method. Using the Washington, DC as empirical case, this paper analyzes theimpacts of residential and workplace built environment on commuting vehicle milestraveled, and then reveals the differences between ignoring and accouting for spatialheterogeneity of commuting vehicle miles traveled.This study systematically explores the impacts of built environment on carownership, commuting mode choice and vehicle miles traveled based on the empiricalresults in order to check the differences of significant factors and spatial heterogeneity.The explained degree of car “ownership-choice-travel” spatial heterogeneity due to thebuilt environment is discussed.This study integrates the latest achievements from urban planning, transportationscience, behavioral science, and system science. From the insight of micro-individualbehavior, this paper proposes the mathematical model to analyze the built environmenton car ownership, mode choice and vehicle mils travled. For one thing, it contributes tothe mechanism research between land use and travel which provides the analyticmodeling method. For another, it is helpful for practical projects to decrease autodependency, thereby reducing transport energy consumption and carbon emissionsthrough optimizing urban built environment.