Analysis The Influencing Factors of Urban Traffic Flows by Using Emerging Urban Big Data

Keywords: traffic flow, urban big data, spatial Durbin model
Abstract Type: Virtual Paper Abstract

Abstract

Urban traffic analysis has acted an important role in the process of urban development, which can provide insights for urban planning, traffic management and resource allocation. This re-search applies spatial Durbin model to analyse traffic flow distributions via various factors in the urban areas and traffic flow data. We include road characteristics, socio-demographics and surrounding environments such as land use, nearby points of interest and Google Street View images. The results show that the built environment within an area has more significant impact on urban traffic flow, than the nearby location. Areas with more young and white dwellers are associated with more traffic flows. Major roads connected between and within cities and towns also show heavier traffic flows. With the influence of COVID-19, residents prefer to spend their daily life in the nearby locations rather than long distance travel. Therefore, the development of 20-minute city can act an important role in contribution to the active travel and achieve net-zero carbon target in the future.