To validate our proposal, we must calculate the threshold for the alpha, beta and road resolution parameter. Anyway, we leave to the users the option to modify each one of them depending on their criteria. To carry out our validations, we used the mixed map of Figure 4.10 that combines all the usual characteristics that can be found in any map such as curves, highways and Manhattan-style areas.
In Figure 4.11(a), we took a snapshot of the scenario using αt = 10. The red
point describes the position of the vehicle in a specific time-stamp while the blue road represents the road to which this vehicle belongs. In this specific case the threshold for alpha is αt= 10 degrees and the real alpha between segments A and B is α = 90
degrees. This means that this red point (the vehicle) can interchange packets with any vehicle found in the green roads F and G. These green roads F and G are considered related to the blue road A since both angles ( ~A ] ~F ) and ( ~A ] ~G) are lower than αt.
4.4 Validation and tuning of parameters
On the contrary, the red point (the vehicle) cannot send nor receive packets from any vehicle found on roads B, E, C and D since all the angles ( ~A ] ~B), ( ~A ] ~E), ( ~A ] ~D) and ( ~A ] ~C) are 90 degrees, which is higher than αt.
In Figure 4.11(b), we took a snapshot of the scenario using αt= 100. In this case,
we are making an error as we will explain later. Between roads A and B, α = 90◦, then α < αt meaning that the red point can send or receive packets from any vehicle found
in roads B, E, C and D. However, this is an error because between roads (A and B) or (A and E) or (A and C) or (A and G) an obstacle is found. So this αt= 100 would not
be a proper threshold value of α for this scenario.
Now, we take another piece of our mixed map where αtwill take the following values:
10, 20 and 60 degrees.
In Figure 4.12(a), αtis 10 degrees. The red point represents the vehicle in a specific
time-stamp, the blue road H means that this red point belongs to this road and the green roads G, A and E mean that any vehicle in road H can interchange packets with any vehicle found on roads G, A and E. Notice that the angle α between roads H and D is higher than 10 degrees and therefore, any vehicle found in road D cannot interchange packets with any vehicle found on road H due to the presence of an obstacle which is a true situation.
In Figure 4.12(b), αtis 20 degrees. Here, no changes happen with respect to Figure
4.12(a). However, in Figure 4.12(c), αtis 60 degrees and here we see another mistake
due to that vehicles found in roads D and B can send or receive packets to or from any vehicle found on road H knowing that there is an obstacle between roads H and D as well as between roads H and B.
Related to βt(β threshold), we took 2 pieces of our mixed map, one is similar to a
curve shape as in Figure 4.13 and the other is a kind of S-shaped curve which is shown in Figure 4.14. The reason to take these special curves is that if with these kind of curves βtis calculated showing no or little errors in detecting if two nodes in the same
transmission range and in the same road can actually see each other or not, thus for any other simple curves with this βtno errors will be committed.
As we go increasing beta, see Figs. 4.13(a), 4.13(b) and 4.13(c), the visibility between the red point (vehicle) and any node found in next lines will decrease.
Taking another S-shape group of curves, shown in Figs. 4.14(a), 4.14(b) and 4.14(c), we see that as we go passing from line to line in the road, β is coming higher rapidly due to presence of such a sharp curve.
4.4.1
Alpha threshold
To obtain which is the proper range of values for the threshold αt, we carried out many
simulations with different values of αt, using many snapshots of the vehicles’ positions in
different time-stamps. We analysed if all the vehicles in a specific road would see or not other vehicles in other roads within their transmission range throughout simulation. For each αttested, we concluded if using that threshold αtthe blocking buildings would be
(a) αt= 10 degrees (b) αt= 100 degress Figure 4.11: αtvalues
(a) αt= 10 degrees (b) αt= 20 degrees (c) αt= 60 degrees Figure 4.12: αtfrom 10 to 60 degrees
detected or not. After many tests, αt= 20◦ showed to be an optimal value for different
generic city maps like the one shown in Figure 4.10. Therefore, any α angle lower than 20◦ means that nodes found on those roads will be able to send and receive packets without any problem caused by a blocking building.
4.4 Validation and tuning of parameters
(a) βt= 40 degrees (b) βt= 50 degrees (c) βt= 60 degrees Figure 4.13: βtfrom 40 to 60 degrees
(a) βt= 40 degrees (b) βt= 50 degrees (c) βt= 60 degrees Figure 4.14: βtfrom 40 to 60 degrees
4.4.2
Beta Threshold
After many simulations, we obtained that βt = 60◦ was the optimal threshold value
below which all the blocking buildings located in curved roads were detected. Basically, β depends on how long and how curved is the road. The longer and curvier the road, the higher the value of β should be.
4.4.3
Road Resolution
After making many tests varying the road resolution value, we got that using a road resolution equal to 1m produced a good trade-off between precision and processing time.
4.4.4
Transmission Range
Here, we just put the transmission range value of each vehicle. This value as we have explained before will allow us to make a pre-filter step of the number of nodes to be analysed. The reason is that it has no sense to check nodes that are outside the transmission range of the node under study.
quickly find out which are the actual neighbours of a node with which the node is in LOS (i.e., both nodes could actually communicate) in every moment. In the following, we will validate our proposal.