# Efficient Traffic Flow Guidance Feedback Strategy Considering Drivers' Disobedience in ITS
## 4 Simulation Results and Discussion
### Simulation Results and Analysis
The mean congestion lasts nearly half the time of the entire duration. The next simulation corresponds to the case where the system uses SVM before sending instructions to drivers. The goal is to see what the road situation will be during congestion if the system uses SVM to pre-filter the drivers and then gives instructions to the filtered drivers. At first, the traffic created congestion on the road. The waiting queue became longer as vehicles kept entering the route. When dynamic weighted vehicle density surpasses the threshold, the system launches SVM and then instructs the drivers labeled as \"obeying instructions\" to change routes. Some of the newly arriving vehicles will not enter the original route, and the number of vehicles exiting the route is greater than those entering the route; thus, the congestion was reduced or eliminated. When the dynamic weighted vehicle density went down, the route was not regarded as congested. More vehicles would enter the original route, and the vehicle density would re-increase; the procedure of the pre-filtering of drivers and the delivery of instructions would be implemented once again. Figure 3a shows the mean velocity of the vehicles on the route when SVM is implemented. We observe a cycle of the change in the mean velocity. Thanks to the driver pre-filtering and instruction delivery procedures, the mean velocity could be maintained at a high level, where the peak of the mean velocity is nearly 15 m/s. In Figure 3b, we observe that the number of stopped vehicles on the original route increased multiple times because of the traffic light. Nevertheless, the peak number of stopping vehicles did not surpass 18, thanks to the instructions given by the ITS framework. Figure 3c shows that the vehicle flux went up and down multiple times, just like the cycle shown in the figure of mean velocity. Figure 2: _Cont._  
The third simulation is related to the case where instructions are given by the system without SVM. The goal is to see what will happen to the road situation during congestion if instructions are given to drivers directly by the system and no SVM or other pre-filtering procedures are implemented. As explained before, during this study, it was not possible to perform a real test, and it is not easy to simulate what a driver will do in real life when he or she receives an instruction, so two methods to simulate the drivers' reactions are proposed. In this part, the simulation was realized by combining principal component analysis and \(k\)-means. At first, the traffic lights created congestion on the road. The waiting queue became longer as vehicles kept entering the route. When dynamic weighted vehicle density surpasses the threshold, the system sends instructions to the newly arriving 30 drivers to change routes. Some of these drivers will follow the instruction, while others will not. This leads to the situation that some of the newly arriving vehicles will not enter the original route, and the number of vehicles exiting the route is greater than those entering the route; the congestion is hence reduced or eliminated. When the dynamic weighted vehicle den  
Figure 2: Results of no route guidance strategy. (**a**) Mean velocity without instruction; (**b**) Number of stopping vehicles; (**c**) Vehicle flux. sity went down, the route was not regarded as congested; more vehicles would enter the original route, the vehicle density would re-increase, and the procedure of the delivery of instructions would be implemented once again. Figure 3: Results of instruction with SVM. (**a**) Mean velocity without instruction; (**b**) Number of stopping vehicles; (**c**) Vehicle flux. Figure 4a shows the mean velocity of the vehicles on the route when SVM is not implemented. We can observe a cycle of change in the mean velocity. Because of the instruction delivery procedure, the congestion would still be eliminated, but with less efficiency.