# Information Fusion in Autonomous Vehicle Using Artificial Neural Group Key Synchronization
## 3 Proposed Methodology
RSUs will send the request to the key sharing unit, and if authentication is satisfactory, new ATs will be returned, as shown in Figure 4. In this scenario, the delay is still present, exactly as it was in Figure 2. Still, with the proposed architecture, average requests for upgrading keys may be much decreased, resulting in a lower average delay for upgrading keys. The driving path prediction may be used to forecast the passing regions in the following time frame for single vehicle, which can help optimize this architecture. Figure 4: Proposed an area-based key sharing system for cars and RSUs. When this design is first implemented, there is no way of knowing which key pools each vehicle should download. Assuming that the inbuilt computer of a vehicle has small memory space, requests for ATs related with unshared zones cannot be ignored. The proposed key sharing method, must be utilized in collaboration with the present requests and responses-based key sharing system. The supplemental techniques are queries to PKI servers for key updates. If the zones related with previously-shared keys are \(R\), and the entire areas one car actually crossed are \(M\), then It may be deduced that if \(R\subseteq M\), that refers to a single car, has keys for all of the passing areas, no requests for key updates will be made. If \(M\subseteq R\), the car will require the old key upgrading mechanism as a backup for acquiring new ATs in zones where previously-shared keys are not available. As a result, while delay cannot be prevented in this situation, requests are still minimized. Apparently, if \(R=\{\ \}\), the vehicle will have to seek AT updates in all areas it has gone through. As a result, if the vehicle goes through one area in less than 10 min, there may be additional update requests. To summarize, to decrease the number of requests for ATs, it is critical to predict each vehicle's traveling areas and previously-shared appropriate keys. The potential traveling areas for one vehicle in the following span of time may then be estimated using a destination and path assumptions method. Because this article is not about smart path or endpoint prediction, this paper presume a variable for the success ratio of path prediction in Section 5 and look at alternative efficiency assessment outcomes. There will always be borders between neighboring regions since the design is dependent on geography. The key pair that is currently in use needs to be upgraded as per the GPS position as a vehicle crosses a boundary between two neighboring areas. There will be a period of time when connectivity is inaccessible owing to the changeover of the keys in this instance. In this architecture, this article built a border zone between two nearby regions in which both keys are permitted to utilize for automobiles and RSUs. After just a vehicle travels from region \(j\) to region \(j+1\), there is indeed a region where both keys are available, as shown in Figure 5. The keys utilized for the next passing area will have precedence if the navigation system recognizes which area the car will be in next. If the vehicle is traveling from Area \(j\) to Area \(j+1\), for example, Key \(j+1\) will have greater priority than Key \(j\) as illustrated in Figure 5. Keys pertaining to preceding regions would have a smaller impact due to the lack of a defined priority based on the path prediction. Setting border zones has the primary purpose of maintaining connectivity by minimizing time delays caused by key flipping. This design is based on the validation of one-time slot's starting phase. After their genuine ID has been validated, the cars and RSUs will get the necessary shared key from the key sharing hub. During each time frame, a monitoring mechanism should be implemented to keep an eye on the abuse of the keys or other odd actions, such as sending misinformation to the MITS in one region.