# Benefits of Advanced Air Mobility for Society and Environment: A Case Study of Ohio
## 4 Benefit Factors
### BF-2: Safety Cost Reductions for Passengers  
The increasing number of traffic accidents is one of the leading causes of disability and fatality, putting significant economic and social strains on the affected commuters [38]. Traveling by eVTOL is expected to be safer than by car, and this benefit can help eVTOLs to gain a significant level of public acceptance as a ride-sharing alternative [39]. One of the most major transportation concerns is safety, and cost reductions in this area are generally used as the fundamental criterion for upgrading the infrastructure [39].  
_Vehicle Miles Traveled (VMT)_ refers to the total quantity of travel for all the roadway vehicles in a certain geographic region during a given time period. \(VMT_{US}\) is the forecasted \(VMT\) for USA (see Table 1), where \(VMT^{\prime}\) refers to the forecasted \(VMT\) for SMCO. Furthermore, \(P_{US}\) is the estimated population of USA for the next 11 years, which was taken from [40], and **P** is the forecasted population of SMCO. We acquired the historical \(VMT\) of USA data of 59 years and SMCO population data of 71 years from [41,42], respectively, to compute \(VMT_{US}\) and **P** using ARIMA (see Table 1), respectively. Then, these variables were used to determine \(VMT^{\prime}\):  
\[VMT_{i}^{\prime}=\frac{VMT_{US_{(i)}}}{P_{US_{(i)}}}\times P_{i}\qquad i\in\{ 2022,2023,...,2032(year)\}. \tag{4}\]  
According to Uber's report, the number of fatalities per 100 million passenger miles in ground transportation is denoted by \(A_{g}\), which equals to 0.6, whereas the number of fatalities per 100 million passenger miles in on-demand urban air transportation is denoted by \(A_{a}\), which is 0.3. So, based on the fatality rate per passenger mile, Uber aims to set eVTOLS's safety level as twice as driving a car [38]. \(F_{i}\) can be calculated using Equation (5), which refers to the additional number of fatality projected to occur in year \(i\) in SMCO's ground transportation relative to the on-demand urban air transportation:  
\[F_{i}=\frac{VMT_{i}^{\prime}}{10^{8}}\times(A_{g}-A_{a})\qquad i\in\{2022,2023,...,2032(year)\} \tag{5}\]  
The implementation of AAM infrastructure would allow \(F_{i}\) fatalities to be prevented in year \(i\) if all the people using ground transportation switch to the new urban air transportation, which is highly unlikely to occur in the next 11 years. **R** refers to the possible amount of reduction in the number of fatalities when AAM infrastructure is implemented in SMCO. According to NASA, eVTOL would carry 1 to 4 passengers per trip [43]. Therefore, the estimated number of passenger trips by eVTOL in year \(i\) can be calculated which is denoted by :  
\[D_{i}^{T}=\frac{D_{i}}{4}\qquad i\in\{2022,2023,...,2032(year)\}. \tag{6}\]  
The product of \(D_{i}^{T}\) and \(d_{1}\) (see Section 4.1) gives the number of miles traveled by the passengers in SMCO in year \(i\) using eVTOL. Then, by dividing this number by \(VMT_{i}^{t}\) (see Section 4.1), we obtained the ratio of vehicles miles traveled by eVTOL and existing ground transportation in SMCO, which was used to compute the \(\mathbf{R}\):  
\[R_{i}=\frac{D_{i}\times d_{1}}{VMT_{i}^{t}}\times F_{i}\qquad i\in\{2022,2023,...,2032(year)\}. \tag{7}\]  
Value of Statistical Life (VSL) is a measure of how much an individual is willing to pay to lower a specific degree of risk or how much risk an individual is ready to tolerate by not paying for the risk reduction. In Equation (8), the total cost reduction in year \(i\) for safety benefit (\(CR_{i}^{s}\)) was calculated using the values of \(\mathbf{VSL}\), which was forecasted (see Table 1) based on the past data taken from US DOT [44]:  
\[CR_{i}^{s}=R_{i}\times VSL_{i}\qquad i\in\{2022,2023,...,2032(year)\} \tag{8}\]