Urban mobility challenges from use cases and how they can be addressed by Disruptive Technologies - Part 5/5 - Conclusions
Despite their specific peculiarities such as organisational approaches, problems faced and mobility needs to be satisfied, the cities of Amsterdam, Bilbao Helsinki and Messina have some commonalities in terms of potential application of disruptive technologies that can help their respective decision-makers.
The main aspect that emerged is related to the need of data, as a vital element to perform any activity; in this sense, it is important to underline that here the need is related to the easiness of accessing the data, that many times is scattered, or represented using a different data structures with non-uniform standards.
Access to the data drives to another common point among the four cities, that is the exploitation of the possibilities offered by simulation tools, in particular, to forecast and predict the impact of decisions (such as the building of a new road, the creation of an LTZ, etc.) on traffic and mobility, not necessarily for what concerns the use of private cars and public transportation, but also the adoption of vehicles for light mobility, for instance, bikes.
The third common point is data visualisation. Accessed data and results obtained from simulations and data analysis must be visualised in an easy-to-understand manner, this includes not only the data visualisation per se, but also the possibility of creating customisable dashboards in which the decision-makers can arrange the information they need and represent it according to their needs.
From the result here summarised, it is possible to clearly identify a chain of needs with their corresponding solutions.
The first link of the chain is the need of accessing data. Here tools facilitating the connection to data sources and the integration with existing IT systems can offer a valuable solution to overcome information silos and to build a unique data-access point to available data, allowing also the harmonisation of the data according to common and well-defined data models and highlight the relevant information reducing the time to find it.
The second link of the chain is the analysis of the data made accessible through the previous step and the execution of the simulation. Here it is important to highlight that beyond the possibility to perform analysis and simulation, the availability of tools that simplify and reduce the time needed to set them up play a key role. In this sense pre-packaged simulations ready to use that guide the users in their setup and tools that allow the creation of customised KPIs and indicators represent an advantage for the decision-makers.
The third and final link of the chain is the data visualisation. Here, tools (e.g. Wizards) guiding the users in the creation of charts, graphs, map layers, etc. give the opportunity to speed up the decision making process by reducing the time of interpreting and understating the information. At the same time, the possibility to visualise different data in the same view through customisable dashboards offers the chance of obtaining a bird's-eye view on the information that is relevant for each decision-makers, according to its specific needs.
Taking into account the results here reported, a final consideration can be made; even if cities could be characterised by a different IT maturity level, the most disruptive technology that could be applied to effectively improve the decision-making processes is not a single technology, but a combination of disruptive technologies, that glued together unlock their respective potentialities and benefits.