Governments are increasingly committed to shrinking the environmental footprint of the urban transport sector. The European Union has set a 2050 target of zero carbon emissions from transport in cities. Lisbon is planning an extensive area at downtown with zero emissions, others like Copenhagen and Stockholm, becoming more aggressive in terms of banning combustion engines circulation. Singapore, aims in 2040 that the majority of vehicles, public and private will be electric. This will also contribute to improve the livability of the communities, that become also safer with reduced accident indexes, walkable, were people can cycle, promoting a healthier way of life, as well as, democratize access to a destinations via multiple modes of transport that matches the individual preferences.
Smart mobility can be perceived only as a perfect advanced combination of infrastructure & intermodal transport, taking individuals between two points as fast as possible. Smart mobility is much beyond that.
Smart mobility is what about by better communities. Better communities are safe, walkable, healthy places that promote sustainable and access to destinations by multiple modes and keep together human interaction and connections in a community. Promoting a healthier lifestyle, can be also achieved under the principle of government agencies cooperate under the principle of ecosystems. I’ve been working with some healthcare providers that are promoting a wellness education program. Mobility that invite walking and cycling that can help reverse the trend toward sedentary urban living. Connections are vital to the inner of a community, of a family. People need convenient access to schools, offices, and shopping, leisure areas, to go about their lives. Environmentally progressive cities with world-class public transport and cycling infrastructure, leading the change in decrease carbon footprint, which the majority of the households (75%) to be close to a carbon free public transport in 10 minutes.
Smart mobility can become a reality via the combination of the scenarious as follows, based on a spectrum of government agencies I am working with. At the heart of the concept of smart mobility is data. Data that is going to allow the citizens, a better commute and be on the forefront in terms of influencing the next stage of smart mobility in terms of public policy design.
Scenarios that enable smart mobility
Mobility as a service
The concept of mobility as a service (MaaS) is not about using an application to show travel options and itineraries. Carrying 10 different mobile applications one for each transport mode is not for certain the objetive.
The concept of MaaS is simple: bundling different transport modes, public and private to end-customer. This breaks traditional paradigms of owning a car, that is one of the biggest outcomes that a transport authority wants to influence. Hence, the development of MaaS is fostered by a new way of thinking that does not considers traffic flow as an isolated function but linked to society. And society is about people. And people have preferences. Hence MaaS is about incorporating a digital assistant that recognizes our preferences as an individual. Who we are.
That matchmaking process ensures the captures and learns all preferences of the traveler and his travel conditions in a mobility profile. A digital assistant demonstrates that the options combined his preferences concerning comfort, available budget, and time made available to meet business partners and share lunch or dinner, travel with the family to the park or go the airport. It will learn if and individual have more time to travel and want to be environmental friendly.
Traffic Accident Prevention / Traffic Flow Management
Proactive traffic enforcement and intervention should be based on an analysis on the collision data available to identify leading causes of accidents, the most prone locations, as well as, to predict the conditions for collision occurrence, data such as weather, geospatial information and social events data that can be obtained via a combination of datasets with existing sensor technology. Traffic collision should also be integrated into traffic flow management in order to ensure smooth travels and road safety.
Using a machine learning model is possible to aggregate historical data sets about regarding collisions, traffic intersection volumes, social events – national day, sports events – geospatial road segments, weather conditions. This way, it is possible to estimate collision probability map per road segment. The model is updated in real time and regenerates itself with real live data.
This information can be proactively shared with drivers, law enforcement authorities to redirect them in order to escape to points where there is a higher probability of accident and at the same time support decisions in terms of changes in traffic flow direction of infraestruture configuration. In the future with the introduction of autonomous vehicles (buses, automobiles) managed like a device with with traffic management systems, the value realization is much higher.
Asset integrity is one of the areas that evolved very much in the last 2 years. Despite the fact anomaly prediction models are well know, the key factor that enable the change is a combination of new hardware: drones with cameras, mixed reality devices like HoloLens, sensors and be able to run applications on real time using edge or fog technologies, that makes possible to localize issues, predict failure and integrate end to end the maintenance supply chain, spare parts, automatic routing based on issue taxonomy, crew availability based on estimarted risk.