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The goal of this study is to provide additional insights to the linkages between built environment, travel behavior(travel purpose and travel mode choice) and travel energy consumption for reducing tr...ansportation related fuel consumption and emissions. This paper applies Linear Regression Model(LRM) analysis to examine the influence of built environment attributes; "5Ds"(Density, Diversity, Design, Destination accessibility and Distance to transit) and socio-demography on non-motorized travel, motorized travel and energy consumption for five different travel purposes( work, study, business, private and return home) at both trip origin and trip destination. The analysis result shows that people travel a long distance for work and private purpose whereas for business purpose they travel a shorter distance. The result identifies that increase of travel energy consumption is mainly due to work trip. Reduction of energy consumption is found possible even though work origin is far from CBD; by promoting higher density(D 1) and better transit accessibility(D5) at work origin. Also, found that higher land use mix(D3) at work destination has no direct effect on energy consumption but has direct effects on the increase of non-motorized travel which ultimately effect indirectly on travel energy consumption reduction .show more
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