Intelligent travel planning: How data is secure in the mobility system of the future

Artificial Intelligence (AI) is changing our mobility. AI systems can make traffic more sustainable and relieve the burden on roads and railways. Intelligent apps for route planning, for example, will enable individual, time-saving and thus resource-saving travel in the future. However, such travel assistants require large amounts of data, including sensitive personal data - a challenge for data protection. How data security and data management can be guaranteed for AI-based travel assistants is shown in the new white paper by Plattform Lernende Systeme. Conclusion: It is crucial for the success of digitally connected mobility that both providers and users handle data responsibly.

Congestion on roads and public transport in Germany is increasing, people are travelling longer and longer distances to work on average, and the resulting greenhouse gas emissions are high. An intelligent travel assistant could adapt travel routes to the personal needs of travellers and make the transport system faster and more resource-efficient. "The use of intelligent travel assistants promotes a sustainable future-oriented mobility system and is therefore of great interest to society. However, their success depends on people's trust in the AI-based applications. Data security and informational self-determination must therefore be safeguarded," says Tobias Hesse, head of the Cooperative Systems Department at the German Aerospace Center and also head of the "Mobility and Intelligent Transport Systems" working group of Plattform Lernende Systeme.

The white paper "Safe travel with AI" identifies the risks of AI-based route planning and shows possible solutions. Using the example of the fictitious environment scenario "Intelligently connected on the road" of the Learning Systems Platform, the authors illustrate how a virtual AI travel assistant on the smartphone or laptop can function in the near future. The intelligent apps bundle offers for existing means of public or individual transport in the background and take into account the personal needs of the traveller, such as physical impairments, safety concerns or preferred seat. They combine the means of transport in such a way that the best possible travel route is created for the individual usage behaviour and the desired route. The travel assistant learns independently with each use and improves its recommendations for the next trip planning.

Data security and responsible handling

In order for an AI-based travel assistant to deliver the best possible results, it needs access to additional data from different sources, such as the traffic situation or the weather, in addition to information about the traveller's personal preferences. The white paper shows that secure digital mobility platforms play a key role in connecting different modes of transport. The intelligent travel assistant itself should not hold any data. Rather, it is part of a system architecture that voluntarily networks several data holders, such as mobility companies or weather services. "On the one hand, the more information people give to the intelligent travel assistant, the better the offers can be tailored to their individual preferences. On the other hand, it is precisely this personal data that represents a gateway for misuse. One risk in particular is that this data is insufficiently pseudonymised or anonymised and can be linked to the traveller," says Jörn- Müller Quade, head of the "IT Security, Privacy, Legal and Ethical Framework" working group of Plattform Lernende Systeme and professor of cryptography and security at the Karlsruhe Institute of Technology (KIT). People should therefore be educated more about how AI systems work and how to handle them, so that they can handle their data responsibly and make reflective decisions, the white paper says.

Data protection and legal compliance must already be considered in the design of an AI system. The so-called "privacy by design" principle should ensure from the outset that cyber risks are already avoided in the development of the data platforms and intelligent travel assistants and that the necessary trade-offs between data use and data protection are suitably technically implemented. According to the authors, the level of IT security required also varies depending on the type of platform and the data collected on it.

The data platform operator is responsible for establishing data protection measures such as data economy and anonymisation or pseudonymisation mechanisms. The experts recommend agreeing on technical and contractual security rules for the use of the mobility platform with the data holders and continuously checking compliance with them through independent certification and audits.

About the white paper

The white paper Secure and safe travel with AI was written by members of the working groups IT Security, Privacy, Legal and Ethical Framework as well as Mobility and Intelligent Transport Systems of the Plattform Lernende Systeme. The executive summary (in English) can be found here.

Further information:

Linda Treugut / Birgit Obermeier
Press and Public Relations

Lernende Systeme – Germany's Platform for Artificial Intelligence
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