## 3 Materials and Methods
### Input Data
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Section** & **km from 0–18** & **km from 18–42** & **km from 42–64** \\ \hline Uphill & 6307 & 5513 & 4185 \\ Downhill & 6358 & 5622 & 3775 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Vehicle classification (VCL) scheme. In the same way, Table 4 displays the vehicle classification for the section located at Laguna Salada from kilometer 18 to 42. It is worth noting that this is no longer an urban area, but it does have recreational areas. The most prevalent vehicle with the highest traffic is the A2 light vehicle, accounting for 72% on the uphill and 70% on the downhill. Table 5 presents the vehicle classification for the section located in the mountainous area from kilometers 42 to 64. This section represents lower traffic. Nevertheless, it accounts for a daily circulation of four thousand vehicles, with 65% being light vehicles on the uphill and 68% on the downhill. With HDM-4 software, in addition to traffic and its characterization, vehicle information is inputted, including operating speeds, types of fuel used, and specific vehicle characteristics. As established previously, the emission models in HDM-4 are based on vehicle-specific fuel consumption; additionally, fuel consumption is dependent on vehicle characteristics, speed, and road conditions [82]. A travelling vehicle is associated with two types of speeds, namely the vehicle free speed and operating speed; free speed can be achieved on an uncongested road, and this is predicted using mechanistic models, \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multicolumn{3}{c}{**Uphill**} & \multicolumn{3}{c}{**Downhill**} \\ \hline
**VCL** & **Quantity** & \
\begin{tabular}{c} **Vehicle** \\ **Percentage** \\ \end{tabular} & **Vehicle Type** & **Quantity** &
\begin{tabular}{c} **Vehicle** \\ **Percentage** \\ \end{tabular} \\ \hline A2 & 3969 & 72 & A2 & 3935 & 70 \\ A\({}^{2}\) & 6 & 0.1 & A\({}^{2}\) & 34 & 0.6 \\ B2 & 55 & 1 & B2 & 56 & 1 \\ B3 & 127 & 2.3 & B3 & 135 & 2.4 \\ C2 & 474 & 8.6 & C2 & 522 & 9.3 \\ C3 & 72 & 1.3 & C3 & 79 & 1.4 \\ T3-S2 & 529 & 9.6 & T3-S2 & 557 & 9.9 \\ T3-S3 & 154 & 2.8 & T3-S3 & 163 & 2.9 \\ T3-S2-R4 & 127 & 2.3 & T3-S2-R4 & 141 & 2.5 \\ \hline Total & 5513 & 100 & Total & 5622 & 100 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Vehicle classification for Section 18+000 al 42+000. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multicolumn{3}{c}{**Uphill**} & \multicolumn{3}{c}{**Downhill**} \\ \hline
**VCL** & **Quantity** & \ \begin{tabular}{c} **Vehicle** \\ **Percentage** \\ \end{tabular}  & **Vehicle Type** & **Quantity** & \begin{tabular}{c} **Vehicle** \\ **Percentage** \\ \end{tabular}  \\ \hline A2 & 4730 & 75 & A2 & 4641 & 73 \\ A\({}^{2}\) & 25 & 0.4 & A\({}^{2}\) & 64 & 1 \\ B2 & 63 & 1 & B2 & 64 & 1 \\ B3 & 139 & 2.2 & B3 & 134 & 2.1 \\ C2 & 675 & 10.7 & C2 & 648 & 10.2 \\ C3 & 151 & 2.4 & C3 & 203 & 3.2 \\ T3-S2 & 372 & 5.9 & T3-S2 & 439 & 6.9 \\ T3-S3 & 76 & 1.2 & T3-S3 & 76 & 1.2 \\ T3-S2-R4 & 76 & 1.2 & T3-S2-R4 & 89 &and operating speed includes uphill speed, downhill speed, and the average round trip speed [83]. The equations for estimating this are described in [84]. The characterization of the vehicles and consumption and operating expenses were obtained from [85]. In order to calibrate the data related to the speed of the vehicles, a point speed study on the highway was carried out considering the methodology described in [86]. With this methodology, it is possible to obtain a representative sample of the vehicles that travel at a given point, as well as its speed characteristics under prevailing conditions of traffic and weather conditions at the time of carrying out the study, allowing speeds by user groups to be obtained. It is based on obtaining the arithmetic mean of the point speeds of the vehicles passing through a specific point. That is, a distribution of point velocities is obtained and, with it, the observed and accumulated frequency distribution.