# Exploring Hybrid-Multimodal Routing to Improve User Experience in Urban Trips
## 5 Results and Discussion
### Hybrid Multimodal Routing  
The models described in Section 4 were used to compare the route options for the trip flows that were identified according to the data reduction process. Filtering the trip flows to contain only the analyzed traffic scenarios (i.e., Low Peak, High Peak, and Weekend Peak), a total of 1654 trip flows were evaluated. Table 2 shows an overview of the characteristics of these scenarios, with the averages of trips/flow, duration, and length. The results were obtained for the three main outcomes of the model described in Section 4: (i) Generalized Time, (ii) Generalized Cost, and (iii) Opportunity Cost of Generalized Cost. Figure 9a,b show the modes Uber and Transit mean trips that were performed using those modes, while the Hybrid trips consider the mixture of these modes and the use of bicycles. Figure 9a shows the distribution of the Generalized Time for the main routing options in the three evaluated traffic scenarios. The Generalized Time is a User Experience metric, which outputs an amount of time that the users would perceive passed on average. In order to compute this metric, we use level-of-service and acceptability multipliers to the actual time elapsed. This way, we aim to convert all times elapsed in different modes to a single base in-vehicle time (IVT). Figure 9a shows that the QoE for hybrid routes obtained the best (i.e., smaller) values of medians. This means that, for most trips, the best option is the Hybrid; also, we observe that the distribution of the values is more concentrated for the Hybrid options, meaning more stability on the results. We also note that the variation of the obtained values increased according to the scenario; this is probably due to the resulting average trip length being greater for Low Peak and Weekend Peak than the High Peak. The Generalized Time is used to evaluate the Generalized Cost of a trip (see Figure 9b). The generalized time is used with the average income per hour of full-time year-round Americans [45]. This generalized time is added to the price of the trip to obtain its Generalized Cost (includes price, duration, and user experience). The Hybrid option is the best in terms of Generalized Cost. Because Uber options are more expensive, their values are higher than the Public Transportation ones. We observe the values of Hybrid to be under \begin{table}
\begin{tabular}{c c c c} \hline \hline  & **Trips/Flow** & **Duration** & **Length** \\ \hline High Peak Weekdays (18:00–24:00) & 5780 & 13.6 min & 1.87 km \\ Low Peak Weekdays (08:00–17:00) & 6453 & 13.7 min & 2.03 km \\ Weekend Peak Weekends (11:00–02:00) & 2378 & 15.6 min & 2.32 km \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Average flow characteristics for each scenario. Figure 9: Relative impact of different users’ profiles in the route evaluation. (a) Distribution of the Generalized Time of trips. (b) Distribution of Generalized Cost of trips. (c) Distribution of the Opportunity Cost. Public Transportation. This behavior is probably due to the number of bicycle trips that are cheaper than Public Transportation in New York. When considering the Generalized Cost medians, the average saving values are around USD 10.00, when comparing Hybrid with Uber, and USD 2.50 as compared to Public Transportation in all traffic scenarios. Figure 8(c) shows the distribution of Opportunity Cost of choosing an option of a trip w.r.t. the Generalized Cost. This data measures the amount of loss for the decision-maker due to selecting a trip among the available ones. A traditional option is an instance of Hybrid routing. Thus, invariably is the best option in this set, leading the Opportunity Cost to always be zero. The traditional options are not necessarily the best routes, which lead to the distribution of Uber and Public Public Transportation in Figure 8(c). Additionally, we consider that bicycle options are in the Hybrid group, causing a rise in the values for the common modes.