Design And Implementation Of Traffic Guidance System Based On Edge Computing

With the advancement of induction theory and related technologies,the degree of informatization of expressways is increasing day by day.The large amount of data transmission demand brought by information construction makes the transmission network overwhelmed,and the long-distance transmission of data will bring high delay,making it difficult to meet some services that require high delay,such as the Internet of Vehicles,realtime warning,etc.The disadvantages of the traditional centralized processing mode are becoming more and more obvious.Applying edge computing technology to traffic guidance,a large number of data processing tasks are delegated to edge nodes,and through the coordination and cooperation between edge nodes and the cloud,less bandwidth occupancy,lower service delay,and higher reliability are achieved.The key technologies for the design and implementation of the traffic guidance system based on edge computing are studied.With the task allocation between the edge nodes and the cloud center as the core,in the edge computing scenario,the traffic information collection scheme,guidance information release scheme and Path induction implementation.The AI algorithm is used to analyze the video collected by the camera to obtain traffic flow information and traffic incident information,and the combined Kalman filter is used to perform data fusion on the structured traffic information collected by the field equipment.In the realization of path induction,the heuristic BPR road resistance function is improved,taking into account the influence of real-time traffic flow and traffic events,and on this basis,the Dijkstra algorithm is used to calculate the optimal driving path.The research background,significance and current research status of the traffic guidance system based on edge computing are analyzed,and the shortcomings of the current research are put forward.Then,the system requirements are analyzed around the four roles of system administrator,road user,edge node,and cloud center.On this basis,the overall design of the structure and function of the system is carried out.Next,the information collection function required for traffic guidance is realized,and the joint Kalman filter algorithm for data fusion of road traffic data obtained by different collection methods is designed and its realization effect is verified.The design of the resistance function is based on the road resistance information combined with Dijkstra to realize the path guidance function,and the realization of the traffic guidance function is carried out from the release of the outside guidance information and the inside guidance.Finally,the actual deployment of the system is carried out,and the system is tested from two aspects of system function and system performance.