## 4 Results
### Routing Performance Evaluation
#### 4.4.4 Impact of Vehicular Mobility
The DSRC utilization of the proposed routing was lower than that of AODV at all speeds for the urban and rural mobility scenarios, while it was higher and lower at different speeds in the autobahn mobility scenario. Another observation that can be seen from Figure 19b is that the LTE utilization of Dijkstra was always higher than that of the proposed routing at all speeds in urban and autobahn scenarios, while at higher speeds (and at zero speed in the rural mobility scenario), it occurred otherwise. The increasing order of LTE utilization of both the proposed routing and Dijkstra at all speeds among different mobility scenarios is urban, rural, and autobahn. However, increasing order of cost is not the preceding order, since communication cost in routing is affected mostly by DSRC utilization, whose variation is exactly the same as the communication cost variation. The latency of routing using Dijkstra barely varies with speed in all mobility scenarios, as is evident from Figure 19c. Furthermore, under any mobility scenario, at any given speed, the increasing order of latency is the proposed routing, Dijkstra, and AODV. The latencies of each routing method are clearly separate from each other, as 95% CIs of latency of each routing technique do not overlap or intersect with each other for any speed in the urban and rural mobility scenarios. However, in the autobahn mobility scenario at lower speeds, 95% CIs of latency of routing techniques intersect, such that the latency gap is lower. Furthermore, for all routing techniques, the increasing order of latency among different mobility scenarios is rural, urban, and autobahn. For the rural mobility scenario, the latency of the proposed method is almost constant with speed, while the latency of AODV slightly increases with speed. In contrast, for the urban mobility scenario, a clear variation with speed cannot be observed for both the proposed routing method and AODV, as the latency tends to increase and decrease alternately with the increment of speed. However, for the autobahn mobility scenario, an increasing trend in latency for speeds in the range 0-50 km/h and a decreasing trend in latency for speeds greater than 50 km/h for the proposed routing can be observed, while an increasing trend in latency with speed for AODV can be observed. The increasing order of packet delivery ratio among all speeds for a given routing technique among different mobility scenarios is rural, urban, and autobahn, as evident from Figure 19d. The reason for the preceding order of packet delivery ratios is that, when the average number of neighbors in the network increases, the PDR also increases. Thus, the average number of neighbors in the network should be in increasing order of rural, urban, and autobahn. Furthermore, for a given mobility scenario at any speed, the increasing order of packet delivery ratio is Dijkstra, AODV, and proposed routing. Thus, the proposed routing technique yields the best PDR at any speed in any mobility scenario. However, the PDR gap between the proposed method and AODV is low, as evident from the intersecting 95% CIs of PDRs of those techniques in Figure 19d. Note that, for all mobility scenarios, the PDRs of all routing techniques except AODV in the urban mobility scenario increase from 0 to 50 km/h and then deteriorate when the speed is increased beyond 50 km/h. Thus, moderate speeds seem to have enhanced packet delivery ratios,while very low and high speeds have poor packet delivery ratios for the proposed routing framework and routing using Dijkstra. Overall, all four of the cost, channel utilization, latency, and PDR of each routing technique at all speeds among different mobility scenarios in increasing order are rural, urban, and autobahn. The underlying reasons for the above observations related to mobility are discussed in the discussion section.