# UAV-Assisted Hybrid Scheme for Urban Road Safety Based on VANETs
## 3 UAV Assisted (UAVa) Reactive Protocol Strategy
### UAVa's Design Approach
#### 3.2.2 Route Discover Metrics  
In this section, some of the metrics used in the UAVa routing mechanism are discussed in detail. Accumulate and Distribute Real-Time Data: We propose an innovative idea that can accumulate and distribute current-time data as well as take immediate steps to prevent congestion at the road intersections. This section will describe our proposed mechanism for current-time information-sharing between nodes to RSUs and UAVs at intersections. The analysis of complexity and intensity demonstrates that the proposed current-time traffic data accumulation and sharing mechanism can transfer information in current-time to the entire network between RSUs, UAVs, and vehicles. We have already mentioned that traffic information stored in RSU memory is divided into two classes. One is static data, containing all information about traffic networks, and previous congestion history; nodes can download static information through V2R communications and reduce measurement errors. Static traffic data are updated between RSUs after a definite period of time. For dynamic traffic data,such as unexpected traffic collisions or congestions, RSU's current-time information accumulation and sharing mechanism will immediately transmit these dynamic current-time traffic data over the traffic network instead of periodically updating them. For our proposed model, the current-time traffic information-sharing mechanism for RSU's is broadcast. The broadcasting technique for information sharing has excellent performance. Moreover, our proposed current-time traffic information-sharing mechanism encompasses the entire transmitted traffic network, which likely to be useful for other nodes on the road segments. RSU Setup Process: In our proposed system, all RSUs are connected via existing cellular networks because of reducing RSU setup costs. There is no need to create a new network setup for RSUs. We are using a carry and forward mechanism in our model to reduce the cost of creating a new RSU network. We proposed to place RSUs at an intersection. One intersection to another intersection distance could be 5 km to 10 km, and make a wired or wireless connection between RSU to RSU quite impossible because urban area obstacles are so high. To remove those redundancies, we proposed all of our RSUs be connected with the existing cellular network. We assume that all RSUs and UAVs are equipped with a single omnidirectional antenna with unitary gain. Nowadays, cellular technology is well developed and 5G systems are in our hands. We proposed a different and unique idea for avoiding congestion before it occurs. It is known that issue prevention is better than regulation. Route Discover and Selection Process: To discover the shortest path from the source to the destination, at first from the source, all the directly connected route distances need to be determined using a digital city map. These distances are the shortest curved metric distance from the source to the destination, where a curve metric distance is a distance determined by using [PERSON]'s famous greedy algorithm based on the geometric shape of the road segments by. As shown in Figure 3, there are several road segments and road intersections, assume source intersection (IBZ1) and the destination intersection (IBX1). Hence, the shortest curve metric distance of IBZ1 means selecting the shortest route of these road segments in terms of distance. Using [PERSON]'s famous greedy algorithm, we can choose the shortest route from source intersection to destination intersection. According to this [PERSON]'s algorithm, we can calculate the shortest route in our designed model after applying the shortest route as Distance (v) = (IBZ1 + ICZ1 + ICY1 + ICX1 + IBX1 = 5 + 2.75 + 1.75 + 2 = 11.5 km). The proof of [PERSON]'s algorithm is derived from the acceptance of the number of visited intersections in Table 1.