Study On The Impact Of Urban Built Environment On Road Travel Time

Most of the existing researches on road travel time estimation and prediction are based on traffic flow theory or data-driven method.These methods are often unable to analyze the key factors that affect road travel time.More importantly,being restricted to the local built environment attributes and the data of the study region,results obtained in a region are difficult to apply directly to the other regions.Previous studies have confirmed that there is a close relationship between urban built environment and travelers’ travel behavior,the urban built environment attributes have an important impact on travelers’ travel behavior,such as travel destination,travel mode,travel frequency,and travel route,which will ultimately affect the travel time of the road network.Therefore,it’s necessary to identify the key factors that influence road travel time from the perspective of urban built environment.In addition,due to the existence of spatial heterogeneity,the impacts of urban built environment on the road travel time of different regions are differently.In view of this,this paper selects a typical trunk road in Shenzhen as a research object.Then both the global regression model and geographically weighted regression(GWR)model are used to quantitatively analyze the impact of urban built environment on road travel time based on the taxi GPS data,land use data,and road network data.When using the global regression model with interactive items,the study route is divided into 397 small sections by 25 meters first,then the average speed of each section is taken as the dependent variable,the built environment attributes and passenger ratio of taxi(the ratio of the number of taxi samples in the passenger state to the number of taxi samples in the whole state)are taken as the main independent variables.Moreover,the interaction between the nearest intersection type and the main independent variables will be considered.Based on the results of global regression model,the existence of spatial heterogeneity is proved,and then the key independent variables that affect road travel time are selected as the explanatory variables in the GWR model.By embedding the spatial positions of the variables into the regression parameters,the GWR model can effectively describe the spatial heterogeneity of the effect of urban built environment on road travel time.The results show: There is an interaction between the urban built environment and the nearest intersections of the road sections,as well as the passenger ratio of taxi;The global regression model shows that the number of parking lots,passenger ratio of taxi,distance from nearest intersection,and speed limit are positively correlated with the road average travel speed.The number of bus stops and distance from nearest school are negatively associated with the road average travel speed.On the contrary,in the GWR model,due to the existence of spatial heterogeneity,each factor has both positive and negative correlation with the road average travel speed;Due to the bus lane and bus bay stop,the transit will not have a negative impact on road travel time,what’s more,when using the taxi data to estimate the road travel time,it will reduce the road travel time.The results of this study can provide decision-making basis for traffic planning and management departments to adjust the attributes of urban built environment to improve the efficiency of road network operation.