AI-research project started for sustainable mobility

Together with the Center for Applied Intelligent Systems Research (CAISR) at Halmstad University represented by Slawomir Nowaczyk, Professor of Machine Learning, we just signed a two-year project called FREEDOM to conduct research and development on how to turn connected vehicles to sustainable mobility using AI. The project is partially funded by Vinnova, Sweden’s innovation agency within the call Fordonsstrategisk forskning och innovation, Effektiva och uppkopplade transportsystem. We are very excited to start this collaboration, find new insights, and create digital services that will help shape sustainable mobility offers for car makers.

A data-driven approach can visualize mobility patterns and give new insights

Awareness of travel patterns of vehicles and people makes it possible to create new services for assisting the end-user in changing their habits. Such data can, for example, help end-users make better informed decisions to choose the optimal route or the best time to travel, to find car-sharing opportunities, or to select the most effective vehicle engine. All of this is based on the analysis of past driving patterns and comparing them to driving patterns of other people in similar situations.

By focusing on the data-driven approach, it is our goal to identify common patterns of mobility and quantify the crucial factors affecting the efficiency of the whole system. This is really a great opportunity for us to create and offer new data-driven services that support the automotive industry in their sustainability journey.

Why is this important?

Passenger cars account for nearly 41% of the global CO2 emissions from the transport sector, making them one of the most significant challenges facing cities today. It is also an excellent opportunity. Cities around the world have begun to recognize these opportunities and are busy transitioning from the current fossil-fuel dependency to a future built on efficiency and renewable energy.

We are witnessing a shift in attitude towards solutions that both protect the planet and improve people’s lives. However, such disruption is not easy. The cities and their transportation systems have become so complex that most people lack the knowledge of what, in their specific situation, can and should be done. Innovative transport solutions require accurate insights as input to decision-makers, and the FREEDOM project aims to make those data-based insights more accessible.

Slawomir Nowaczyk, professor of Machine Learning at fellow project partners Halmstad University: ”Using vehicle data in the right way has huge potential, which we aim to explore—to decouple pollution and CO2 emissions from the mission of providing necessary mobility for all. Many different actors will benefit from the data of millions of connected vehicles once it is analyzed in the FREEDOM project."

The two crucial dimensions of connected car data

Connected car data is a surprisingly untapped resource, and machine learning based on it is a crucial tool for making many of these mobility initiatives sustainable. Machine learning algorithms will help develop services that lead to sustainable and efficient resource utilization, while at the same time being realistic in terms of convenience and cost.

Mobility data/connectivity data is characterised by two critically essential dimensions:

• spatial, namely the locations or routes (for example, which street a vehicle is parked on) and
• temporal, namely the times or durations (when does it stand still, or how long is it moving around).

Slawomir Nowaczyk again: ”Graph Neural Networks (GNNs) is an emerging and promising field of machine learning, at the intersection of deep neural networks and graph theory, that is uniquely suitable to address both these aspects. The FREEDOM project gives us a unique opportunity to apply cutting-edge scientific solutions to a crucial societal challenge."

Using connected car data in a wider scope will pave the way

To make a significant contribution to the goal of sustainable mobility will require the meeting and cross-pollination of the following: technology development, studies of user motives, needs and prime movers, and value creation for different stakeholders—commercially as well as socially and environmentally.

This requires focus on the interrelation between technical development and social context so that users’ actual needs, worries and hopes can be met by technology, thus transforming habits and creating a willingness to act. Action that leads to climate positive scenarios and at the same time gives business value to the OEM.

An important output of the project are the interviews and observation studies with users about mobility preferences, hopes and fears concerning changing to electrified mobility, changing driving styles and everyday practices, since sustainability is not a property of an object. Objects in isolation cannot be sustainable. Instead, it is an emergent feature of complete systems. It is not so much about the parts, but how the parts work together to enable effective overall outcomes.

Research and practice are often either technology-driven or characterized by user studies and design. This unique combination of quantitative and qualitative research will be the foundation for the FREEDOM project, one that secures a solid contribution to sustainable mobility.

If you want to know more about the project or get involved, please feel free to contact me at Natalie Lucca. For more on the work we do, visit our website and read other articles on the WirelessCar blog!