# Traffic Simulation of Future Intelligent Vehicles in Duisburg City Inner Ring
## 4 Results and Discussion
### Comparison of Different Traffic Demand Sources  
Figures 5 and 6 show the traffic volume determined with the simulation settings presented in the last section and the average speed at the four verification points. The red lines represent the real data recorded by the induction loops. The blue lines show the simulation results from Section 3.2 and the black lines represent the simulation results from Section 3.1. From left to right, the four figures represent the four verification points from V1 to V4, respectively. In order to reduce the interference of different lane choices, the traffic volume is the sum of different lanes on the same road.  
As can be seen in Figure 5, the blue lines are closer to the red lines than the black lines. That means, for the number of vehicles in the simulation, the simulation using induction loops data as the source of traffic demand has better results than the simulation using the OD matrix data. The reason could be that the OD matrix data only contains the trips that start or end in the range of the inner ring, and the trips passing by this area are not included. For V2 and V3, the difference between actual traffic volume and the OD matrix generated traffic volume is more significant than V1 and V4. The reason could be that most vehicles passing intersection 723 do not need to enter the inner ring area. This location of the intersection also proves that it bears more out-of-region traffic.  
For the average velocity comparison in Figure 6, the simulation results using OD matrix data as traffic demand are closer to the real data at 24 h for a day. In contrast, the average speeds of simulation using induction loops data and OD matrix data are similar; sometimes lower than the real data, and sometimes higher. The zero average speed represents that there is no vehicle passing the verification point during this hour. The two simulations use the same traffic scenario and the same network file. Hence, the speed limit of the roads is also the same.  
Figure 5: Traffic volume of the verification points. (Red lines, real data; blue lines: simulation of intersection loops data; black lines: simulation of OD matrix data).  
Figure 6: Average velocity of different hours in the verification points. (Red lines, real data; blue lines: simulation of intersection loops data; black lines: simulation of OD matrix data).  
The deviation of the detector simulation data and the real data in traffic volume is \(\sigma~{}=\) 37.43, which is better than the deviation of the OD matrix simulation data and the real data, which is \(\sigma=\) 129.20. Regarding velocity, the deviation of the detector's data is \(\sigma=\) 7.44, and therefore slightly better than the deviation of the OD matrix, which is \(\sigma~{}=\) 8.72. According to the comparison of simulation results, the simulation using induction loops data have a more realistic result than the simulation using the OD matrix in the aspect of traffic volume. The reason might be that the induction loops data record every vehicle passing by, but the OD matrix data only generates the vehicles that depart or end their journey at the selected area. In the next section, the induction loops data are also used as the traffic demand source for the simulation of vehicles with different degrees of automation.