In recent years, research has been conducted on dynamic map systems, which are information and communication platforms that manage vehicle sensor information and run applications. However, there is a concern about scalability in the dynamic map system, which operates on a cloud on the Internet, when the number of vehicles that transmit and receive sensor information increases. Therefore, it is considered that the application load can be distributed by distributing multiple edge servers geographically and having the information managed in the cloud by the edge servers. However, the edge server that controls the vehicle information and the edge server that receives the data do not always match depending on the actual radio wave conditions. Therefore, some applications are difficult to manage, such as intersection collision danger warning and merging arbitration when edge servers are assigned in the same way as base stations that receive data from vehicles. Such an application should receive all vehicle data for the target road area. Therefore, we divide the area on the road where a vehicle travels as "lane section ID" and assign an edge server to each lane section ID on the basis of that area. In addition, we implemented a dynamic map system that connects vehicles and edge servers by linking multiple edge servers. This enables the edge server to aggregate vehicle data without being affected by radio traffic conditions. We evaluated the scalability of the dynamic map system and verified the effectiveness of the load balancing mechanism using multiple edge servers.

Research and development on connected cars equipped with communication functions is being conducted, and dynamic maps are being researched and developed as an information and communication platform for cooperative automatic driving. There is a concern about scalability when dynamic maps are constructed on a cloud server to aggregate a wide range of vehicle information. The problem can be alleviated by deploying edge servers that divide the geographic area where vehicles travel and manage each of them. The IP addresses of the edge servers need to be resolved on the basis of the location information of the moving vehicles. Using TCP improves reliability but reduces efficiency because the vehicles move. In this study, we developed a novel method for accessing edge servers that achieves higher reliability and efficiency by adopting UDP using anycast for transmission from vehicle to edge server and implementing a retransmission function. The effectiveness of this access method was verified by using a vehicle driving simulation.

Research and development on connected cars equipped with communication functions is being conducted, and dynamic maps are being researched and developed as an information and communication platform for cooperative automatic driving. There is a concern about scalability when dynamic maps are constructed on a cloud server to aggregate a wide range of vehicle information. The problem can be alleviated by deploying edge servers that divide the geographic area where vehicles travel and manage each of them. The IP addresses of the edge servers need to be resolved on the basis of the location information of the moving vehicles. Using TCP improves reliability but reduces efficiency because the vehicles move. In this study, we developed a novel method for accessing edge servers that achieves higher reliability and efficiency by adopting UDP using anycast for transmission from vehicle to edge server and implementing a retransmission function. The effectiveness of this access method was verified by using a vehicle driving simulation.