# Analyzing Demand with Respect to Offer of Mobility
## 7 Conclusions  
A model and tool, called DORAM, has been introduced in this paper. It allows to perform the analysis of public transportations offer with respect to the demand (taking into account a set of possible data sources), in a multi-modal and multi-operator context. More precisely, the formal mathematical model related to DORAM has been introduced, in order to analyze the mobility demand with respect to the public transport offer taking into account a range of contextual and operative data. The DORAM solution investigates how the demand is satisfied in terms of public transportation mobility by means of simulation tools and KPIs and the related evidence information with the aim of identifying crowded conditions on bus-stops and on the busses, that influence the experience of transportation. In the present work, we first analyzed the current status of a public transportation system by matching the service offer, in terms of public transportation means, and the \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Scenario** & \multicolumn{2}{c}{_ActualScen._} & \multicolumn{3}{c}{_Alternative Scenario_} \\ \hline
**Stop** & _Indipendenza_ **XXVII _Aprile_ & \multicolumn{2}{c}{_Indipendenza_ **XXVII _Aprile_} & \multicolumn{2}{c}{_[PERSON]_} \\ \hline
**Mobility Operator** & **ATAF** & **Busitalia** & **ATAF** & **Busitalia** & **ATAF** & **Busitalia** \\ \hline Lines & 9 & 20 & 27 & 20 & 2 & - \\ \hline Daily pick-ups & & 377 & 334\((-11.4\%\) compared to _Actual Scenario_) & & 65 & \\ \hline Daily drop-offs & & 407 & 362\((-11.05\%\) compared to _Actual Scenario_) & & 75 & \\ \hline \hline \end{tabular}
\end{table} 
Table 6: The comparison of Actual Scenario and Alternative Scenario. mobility demand. This allowed us to tune the model and identify the parameters that express the relationship of the mobility demand with the city context and census data. Then, we focused on creating alternative scenarios, where a set of changes are introduced in the current status of a public transportation system and comparing the available scenarios by quickly switching between them, with the aim of reducing the crowded conditions on busses and at bus-stops. While the computational model of DORAM is enriched by the usage of a wide range of data sources, investigating public transportation systems in DORAM is equipped with computing relevant KPIs (e.g., pickups and drop-offs at a stop) and related evidence information (e.g., the number of passing trips and lines, considering a stop). DORAM can suitably be used by urban decision-makers and mobility when deciding on a (set of) plans to improve the public transportation networks, especially in the presence of critical situations (e.g., overcrowded or blocking stops, overcrowded vehicles). DORAM model and solution has been validated on the basis of data collected on the field by major public transportation companies in the Florence Area, that are: ATAF and BUSITALIA. The DORAM tool demonstrated to be capable to identify critical problems without the needs of investing large amount of money for physical campaign of data collection. Moreover, DORAM solution performs what-if analysis by analyzing the impact of a (set of) change(s) of the Actual Scenario to see their effects in terms of people flows and matching demand/offer. Then, DORAM provides non-functional features such as (i) flexibility, by taking into account different data sources, (ii) fast-computability, quickly switch between different scenarios, and (iii) web-based interface that supports GTFS data and REST APIs for analysis results. DORAM is presently accessible from: [[https://www.snap4](https://www.snap4) city.org/odanalyzer/#b]([https://www.snap4](https://www.snap4) city.org/odanalyzer/#b) (accessed on 5 September 2022) and with more functionalities if you perform free registration on Snap4 City.org. Conceptualization, A.A., P.B. and P.N. ; methodology, A.A. and P.N. ; software, C.B., P.B. and P.N. ; validation, A.A., S.B., P.N. and M.P. ; formal analysis, A.A., S.B. and P.N. ; investigation, P.N. and M.P.