# Research on the Impact of Flexible Working Hours on Reducing Traffic Delays in the City
## 3 Results and Discussion
### Limitations of the Study  
This article describes the impact of flexible WHs and peak-hour traffic on a specific example of a small district town. It can be assumed that similar improvements in traffic conditions will occur in other cities with approximately the same peak-hour traffic intensity. For comparison, cities where intersection surveys were conducted in the last five years were selected. The following figure (Figure 20) presents a graph showing the percentage of vehicles passing through the intersection during the morning and afternoon peak hours relative to the total load between 6:00 and 10:00 and between 14:00 and 18:00. The graph in the previous figure shows that during the morning peak hour, 12.31% to 13.73% of the total traffic load passes through the intersections, while during the afternoon peak hour, this percentage ranges from 13.73% to 17.47%. The total load is defined as the sum of vehicles recorded between 6:00 and 10:00 and between 14:00 and 18:00. In some cases, data for the afternoon peak hours were not available. Based on this comparison, it can be assumed that if a similar traffic load distribution is observed in other cities, the traffic flow characteristics will behave similarly. It should be kept in mind that the outputs presented in this article are only the results of a microscopic simulation conducted on traffic light-controlled intersections in the town of Topol'cany. However, traffic-related problems are faced by almost every city, and these problems will only grow with the increasing \begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Inters.**} & \multirow{2}{*}{**Var.**} & \multicolumn{3}{c}{**Morming Period 530–12:00**} & \multicolumn{3}{c}{**Afternoon Period 12:00–18:30**} & \multicolumn{3}{c}{**7:15–8:15**} & \multicolumn{3}{c}{**8:15-9:15**} \\  & & **Time** & **MaxDT** & **LoS** & **Time** & **MaxDT** & **LoS** & **MaxDT** & **LoS** & **MaxDT** & **LoS** \\ \hline K1 & 0 & 10:30– & 30.1 & B & 14:15– & 33.4 & B & 29.9 & B & 27.8 & B \\ K1 & 1 & 09:30– & 29.7 & B & 15:30– & 31.5 & B & 27.5 & B & 27.8 & B \\ K1 & 2 & 08:30– & 29.7 & B & 15:30– & 33.2 & B & 25.7 & B & 29.7 & B \\ \hline K2 & 0 & 07:15– & 56.4 & D & 13:45– & 50.9 & D & 56.4 & D & 53.2 & D \\ K2 & 1 & 08:15– & 64.2 & D & 13:45– & 55.4 & D & 48.3 & C & 64.2 & D \\ K2 & 2 & 08:15– & 70.7 & E & 13:45– & 54.8 & D & 42.1 & C & 70.7 & E \\ \hline K3 & 0 & 09:15– & 27.8 & B & 13:45– & 24.2 & B & 24.1 & B & 20.7 & B \\ K3 & 1 & 09:15– & 25.6 & B & 16:00– & 24.7 & B & 20.9 & B & 20.8 & B \\ K3 & 2 & 07:30– & 23.7 & B & 16:30– & 25.1 & B & 23.5 & B & 22.6 & B \\ \hline K4 & 0 & 07:00– & 24.6 & B & 13:30– & 20.2 & B & 23.9 & B & 13.6 & A \\ K4 & 1 & 07:00– & 23.0 & B & 13:15– & 21.2 & B & 21.1 & B & 15.8 & A \\ K4 & 2 & 07:00– & 22.3 & B & 13:00– & 19.7 & A & 17.9 & A & 17.7 & A \\ \hline K5 & 0 & 08:45– & 94.1 & E & 13:45– & 80.7 & E & 72.0 & E & 75.2 & E \\ K5 & 1 & 08:45– & 103.7 & F & 13:30– & 73.3 & E & 66.9 & D & 88.3 & E \\ K5 & 2 & 08:45– & 144.6 & F & 13:00– & 66.6 & D & 55.9 & D & 109.8 & F \\ \hline \hline \end{tabular} MaxDT—maximum delay time; LoS—Level of Service.  
\end{table} 
Table 6: Simulation results—comparison of different solution variants. Source: processed by authors. number of individual cars. From the results of traffic surveys, it is obvious that the traffic peak in Slovak cities accounts for 12% to 17.5% of the 8-h intensity. During the traffic peak, people most acutely feel traffic-related problems. Verification of simulation results with real data is not possible due to a lack of data--there is no exact number of workers whose WHs have changed to flexible formats. However, the simulation outputs indicated under what conditions such a change could benefit the traffic situation in the area in question. This article clearly states that flexible WHs can contribute to improving traffic conditions.