# Evaluation of Accuracy of Traffic Flow Generation in SUMO
## 4 Results  
In Figure 5, forecasted traffic data are shown from Monday to Sunday vertically, and the last row of each section shows the simulated traffic status. In the 8 road sections, sections 2-4 can represent normal traffic situation in a city, the difference between workdays and weekends are obvious: on weekends, the red and yellow situations (represent traffic jam and slow traffic flow) are apparently less. What is more, in these three sections, peak periods are also outstanding, particularly am 8 and 17 o'clock, the roads carry more traffic pressure. Since ActivityGen does not offer a weekend mode, the simulated traffic is imitating workdays. Therefore, the results of the simulation are simultaneously close to the forecasted traffic situation on workdays is expectable. In road sections 2-4, the result of the traffic scenario is quite persuasive.  
Besides normal road sections, we want to check the accuracy of simulated traffic in special extremely crowded public locations. Therefore, we selected one road section in front of a train station (section 1), two in front of two hospitals separately (sections 5 and 6), and two in densely populated resident areas (sections 7 and 8). Due to the differences in medical systems, family doctors are not common in China, people go to hospitals directly no matter whether they have a serious aliment or not. Moreover, because of cultural differences, people prefer to go to the hospital with their family or friends, which means, half of the people in the hospital are neither medical staff nor patients. All these reasons make hospitals a traffic intensive area, no matter where the hospital is located. In sections 5 and 6 of Figure 5, we can notice that the yellow parts (represent slow traffic) of predicted traffic last longer comparing to normal situations (sections 2-4), and there is no apparent difference between workdays and weekends. The simulation result differs from 6 to 20 o'clock. In addition, actual afternoon rush hour is later than simulated, and also later than normal situations like sections 2-4, this can be explained by going to the hospital after work.  
For some cities, the train station is the busiest area of the city, which is also the case in the Jianghan Zone. In road section 1, traffic jam continues 10 h every day, which shows a relatively large difference from the simulated traffic. The reason could be the passenger flow. Normally the number of passengers leaving from Hankou train station is over 70,000 per day, on special national holidays, the number can be over 140,000 [24]. Nevertheless, the simulation model just considers the working staff of the train station, which are significantly less than the passengers are.  
Sections 7 and 8 are example road sections of two dense residential areas. Section 7 is at the edge of residential belts, also connecting the way to Yangtze River, but at the same time, Section 8 is in the middle of a group of dense residential areas and this road section is the only way, which must be passed for several residential quarters. These two sections show longer and heavier jam situations than normal traffic. The simulated traffic status has roughly met the forecasted traffic status from AutoNavi, based on the results from these two sections, we are glad to see ActivityGen can simulate traffic flow in residential areas.