Key Technologies Research For Mobile Monitoring In Road Networks

With the rapid development of positioning technology, a large number of applications based on the location information of mobile objects appear in recent years, typically including traffic monitoring system and location-based service system. As the technology of mobile monitoring extends, number of updates to server grow rapidly, handling of these massive updates becomes a bottleneck in this field. The paper studies several key technologies of mobile monitoring in road networks with the view of reducing massive updates, including the appropriate proportion, temporal-spatial sampling methods and location update algorithms of mobile monitoring points.First, the paper reviews related researches in the field of traffic monitoring under road networks and summarizes the advantages and disadvantages of different traffic monitoring methods. For deficiencies in relevant research, the paper points out current issues traffic monitoring faces in road networks and the direction of future research.Then, the paper proposes calculation of appropriate proportion and temporal-spatial sampling methods of mobile monitoring points in road network traffic monitoring. Taking number of updates sent by mobile monitoring points, accuracy and timeliness of traffic monitoring into consideration, the paper first calculates the traffic parameters by sampling data from mobile monitoring points, comparing them with the corresponding real ones, then determines the appropriate proportion of mobile monitoring points. On this basis, it brings forward two sampling methods:temporal sampling and spatial sampling. Microscopic traffic simulation experiments show that the methods proposed in this paper can effectively reduce the updates between mobile monitoring points and traffic data center while ensuring the accuracy of traffic monitoring.Finally, an enhanced vector-based location update algorithm of mobile monitoring in road networks is proposed which is aimed at reducing location updates between mobile monitoring points and the server. Utilizing the characteristics of road network, enhanced vector-based location update algorithm makes use of dealing with wrong GPS positioning, minimum position correction, maximum position correction and horizontal correction to reduce the number of updates which mobile monitoring points send to the server, at the same time, it uses probability update algorithm to further decrease the number of updates. Experimental results show that enhanced vector-based location update algorithm is superior to vector-based location update algorithm in number of updates, accuracy, scalability and stability.In summary, the paper studies the existing main problems of mobile monitoring applications in road networks and proposes calculation of appropriate proportion, sampling methods and enhanced vector-based location update algorithm of mobile monitoring points. Experimental results verify its feasibility and effectiveness.