## 1 Introduction
Noise impacts are expected to be more severe near the take-off and landing areas. Existing noise concerns focus on traffic noise during the night and early morning; noise from UAM could pose a more notable obstacle in the future as electric vehicles become more mainstream (potentially causing a reduction in overall ambient noise, making UAM more noticeable) [4]. Design of transport network, whether land, sea, or air, is a complex problem spanning many disciplines that would also encounter many real-world issues. There are many \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Category** & **Road Type** & **Road Name (Section)** & **Extension (km)** \\ \hline \multirow{8}{*}{Rush hour congestion} & \multicolumn{3}{c}{Seoul outer ring expressway (Gyeyang} \\  & IC—Jungdong IC—Ahnhyun IC), west coast expressway (Ansan JC—West Seoul TG), 2 nd Gyeongin expressway (Gwangmyeong IC—Jhik JC), etc. & 75.3 \\  & \multicolumn{3}{c}{Ganghyceponuk-ro (Seengan Large} \\  & Bridge—Donghore Large Bridge), internal & \\  & beltway (Yeonhee IC—Hongjilmun tunnel entrance), Donghun main road (Jungnang & 84.5 \\  & Bridge—Wolgye Bridge), Olympic daero & \\  & \multicolumn{3}{c}{(Gayang Large Bridge–Yequi Downstream} \\  & IC), etc. & 159.8 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Major congestion zones. barriers and challenges, such as noise, to operate UAM. The Booz Allen Hamilton report [4] explored market size and potential barriers to UAM by focusing on three potential markets--airport shuttle, air taxi, and air ambulance. The barriers and challenges were also stratified according to their applicability or potential mitigation through technology as well as market maturity. In an immature market, the technology challenges are high cost of service, weather conditions, high density operations, battery technology, and environmental impacts, particularly noise. On the other hand, the non-technology challenges are infrastructure constraints, competition, and public perception [4]. For the UAM study, key metrics from the perspective of operators (e.g., number of flights, potential revenue, and operating costs), passengers (e.g., number and distribution), non-flying public (e.g., flight patterns, potential noise impacts), and infrastructure providers (e.g., number, location, and capacity of vertiports) should be calculated and tracked. However, in this study, only vertiport location selection and noise analysis were performed without considering all these factors [4]. To select vertiport locations, [PERSON] et al. [5] came up with the idea of using highway cloverleaf interchanges, coastlines, river barges, and private infrastructures as UAM ground infrastructure locations. Also, [PERSON], who collaborated with Uber, selected sites for their design in the Dallas/Fort Worth area, which is a primary launch market for Uber Air because of its high commuting population between cities, the high demand of air shuttle, and its existing helicopter routes for navigation [6]. [PERSON] et al. [7] used census data from San Francisco and Los Angeles to collect commuting locations and commuting time. Using this data, 10, 20, and 40 vertiport locations were selected, solving an integer program that maximizes potential time savings compared to driving. [PERSON] et al. [8] conducted an eVTOL study for small package delivery and also formulated and solved the optimization formula for maximizing the package demand served. Therefore, they derived one to eight vertiports positions. [PERSON] et al. [9] proposed an iterative constrained clustering algorithm with the multimodal transportation warm-start technique. Using NYC taxi records, 10 to 85 vertiport locations were suggested, including large facilities and small stops. [PERSON] et al. [10] defined three different UAM networks with different numbers of vertiports in the Munich Metropolitan region. Each network has 24, 74, and 130 vertiports, representing low, medium, and high-density networks. [PERSON] et al.