Research on Road Capacity Improvement Based on Real-Time Road Condition Information and Cloud Model

Against the background of increasing urban traffic congestion, this paper aims to alleviate urban regional road congestion. Taking Beijing's road network as the research object, the real-time information of the road network was downloaded and extracted by using the Baidu road condition extraction program. The image representation index of traffic congestion is quantified and identified through the geographical information system. At the same time, the causes of traffic congestion are analyzed from multiple perspectives. The index system for improving the capacity is constructed by combining the index system of the road network structure, traffic planning and design, traffic operation organization and management, etc. The cloud model is applied to build a comprehensive model to enhance capacity, to analyze and find out the main indexes to improve capacity of regional road network, and to provide solutions for traffic congestion alleviation.