Influence Of Urban Spatial Characters On Green Travel Behavior With Emerging Travel Modes

China is in the process of rapid urbanization,and the travel demand of residents continues to grow with high speed.With the gradual integration of various emerging travel modes,such as ride-hailing service,bike-sharing system and new energy vehicles,the relationship between urban space and travel behavior is constantly changing.How to control and guide the travel demand and further promote green travel through scientific and reasonable urban planning and management is a prominent issue that needs to be solved under the goal of sustainable development.Based on the comprehensive use of urban big data,this paper portrays the urban space characteristics from different perspectives.Based on different emerging travel modes,the study empirically analyzes how the urban space characteristics with different attributes affect the green travel behavior of residents and provides relevant suggestions on how to promote green travel through urban planning.Specifically,the main research work and conclusions are listed as follows:(1)Using the individual trips data from Chengdu,China,this dissertation employed gradient boosting decision trees(GBDT)method to examines the influence of built environment on travel distance of ride-hailing trips at a disaggregated level.The results show that,among the built environment variables,population density at origin position is the most crucial factor in predicting travel distance,however there is a nonlinear effect.The asymmetric effects show that the same built environment variables have different influence on the travel distance between origin and destination locations under different spatiotemporal scenarios.The findings of the threshold effect of built environment on the travel distance provide a quantitative basis for urban planning at different stages of urban development.(2)Using the eye-level greenery view index(GVI)extracted from street view images and the Normalized Difference Vegetation Index(NDVI)extracted from remote sensing image,the influence of perceived urban greenness on free floating bikesharing system(FFBS)usage is explored in Beijing.It is found that in the global model,as the GVI of a location increases by one unit,the average usage of FFBS at that location will grow by 1.003 times.However,NDVI is negatively associated with the usage of FFBS.The spatial distribution of urban functions is further delineated using POI data to investigate the heterogeneity.Compared to the global model,GVI presents a negative impact during the morning peak hours in the single function area business service(P)and the mixed function area of public-business service(P-B),while in the mixed function area of residential-business(R-B),GVI presents a negative impact overall.The study reveals the spatiotemporal heterogeneity of greenness perception on active travel modes,which has important implications for improving the quality of urban spaces and streets,and thus motivating residents to adopt active travel modes.(3)Using vehicles sale data of 290 Chinese cities from 2016 to 2019,this dissertation tries to explore the influence of the urban population agglomeration on NEVs adoption.Applying high spatial resolution population distribution data,this study delineates the indicator of agglomeration of economic activity and investigate its influence on adoption shares of NEVs.The results of the two-stage least squares(2SLS)regressions indicate that for every 1% increase in the spatial agglomeration of economic activity,the adoption shares of battery electric vehicles will increase by 0.73%and the sales share of hybrid electric vehicles will increase by 0.46%.It is also found that the associations between agglomeration and adoption shares of NEVs are influenced by urban size and temperature.Our findings shed light on the policymaking to promote the adoption of NEVs and improve sustainable urban management.By expanding the dimensions of urban spatial characteristics and enriching the theoretical mechanism of Space-Behavior interaction,this dissertation tries to use the multi-source urban data to provides theoretical and empirical evidence for traffic demand management from the perspective of spatial planning.The findings can help urban policymakers to establish green oriented spatial planning policies to promote the adoption of sustainable travel behavior.