## 3 Model Development
### Development of Multimodal Travel Demand Model (MTDM)  
Several studies, such as S6-5 Group [25], [PERSON] et al. [29], SIRDC [36], and [PERSON] et al. [45] similarly adopted the MTDM to forecast travel demands in the KKTP area. In this study, the MTDM was applied to forecast the travel demands in the KKTP transport network for 2016, 2026, and 2046. CUBE software (Version 5.0) [46] was used as the software development platform for the MTDM. In the trip generation step, the category analysis trip rates per capita per day, classified according to vehicle ownership classes--no vehicle, one motorcycle (MC), more than two MCs, one passenger car (PC), more than two PCs, one MC and one PC, and more than one MC and more than one PC [32]--were used to estimate the total trip production, while the multiple linear regression analysis method was employed to generate the trip attraction equations. In 2016, the total calculated trip generation was 656,500 trips per day. In 2026 and 2046, the total trip generation was predicted to be 860,670 and 1,518,130, respectively. The trip purposes of the trip generation step were divided into four categories: home-based work (HBW), home-based school (HBS), home-based other (HBO), and non-home-based (NHB). Based on the total trips made, 59%, 24%, 10%, and 7% of trips were associated with HBW, HBE, HBO, and NHB, respectively. In the trip distribution step, the well-known gravity model [25; 29; 45] was applied to predict the trip interchanges between zones [32]. In the modal choice step, the logit model was utilized to split the travel modes into either transit or private modes. The modal splits of the KKTP area in 2016 were as follows: motorcycle, MC (54%); passenger car, PC (32%); public transport, PT (9.0%), and walking and cycling (5.0%) [30; 32]. In the trip assignment step, an equilibrium approach was adopted to assign all trips to the KKTP highway and transit networks. In this step, the total travel demand (trips) comprises the internal trips derived from the household interview survey (HIS) and the external trips obtained from the roadside interview survey (RIS). The internal trips are composed of trips made by MC, PC, PT, walking, and cycling, while the external trips comprise PCs, MCs, buses, pick-up trucks, and other trucks.  
Finally, the predicted trips based on the MTDM were validated against the observed trip volumes on the six-screen lines for 16 validation sites, as shown in Table 2. The results of such validation clearly illustrate that the modeled trips were reasonably well fitted with the surveyed data, with an average root mean square (RMS) error of 5.5% [32], suggesting that the developed MTDM can predict multimodal travel demand.  
\begin{table}
\begin{tabular}{l c c c c} \hline \hline \multirow{2}{*}{**Screen Lines**} & \multirow{2}{*}{**Validating Points**} & \multicolumn{2}{c}{**Number of Traffic (PCU/hr)**} & \multirow{2}{*}{**RMS (\%)**} \\ \cline{3-3} \cline{5-5}  & & **Observed** & & **Modeled** \\ \hline SL1 Railway line & 4 & 15,652 & 14,330 & \(-\)8.4 \\ SL2 North–south (north) & 1 & 2252 & 2391 & 6.2 \\ SL3 North–south (south) & 2 & 4947 & 4987 & 0.8 \\ SL4 East–west (west) & 2 & 4949 & 4887 & \(-\)1.3 \\ SL5 East–west (west) & 2 & 6067 & 5248 & \(-\)13.5 \\ SL6 Cordon line (ring road) & 5 & 13,989 & 14,639 & 4.6 \\ \hline Total & 16 & 47,856 & 46,482 & 5.5 \\ \hline \hline \end{tabular}
\end{table}
Table 2: The results of model validation [32].