TU Wien Informatics

20 Years

Researchers create personal mobility assistant for road users

  • 2015-09-23

Successful results of the three-year EU project SIMPLI-CITY

SIMPLI-CITY smart phone app
SIMPLI-CITY smart phone app
Picture: SIMPLI-CITY

Researchers from the Faculty of Informatics co-developed a “personal mobility assistant” (PMA) during the course of the three-year EU Framework 7 project “SIMPLI-CITY – The Road User Information Systems of the Future”, which was coordinated by TU Wien. The project was initiated in order to solve the problem of information overflow that impacts many traffic participants. “Bundling all mobility-related features helps road users significantly” summarizes Stefan Schulte (Distributed Systems Group, Institute of Information Systems), leader of the research project.

Using the road with fewer distractions

People can and do use a variety of information sources during their time on the road. These sources vary in content and technical aspects, which often renders their (simultaneous) use time-consuming and distracting. Since data are heterogeneous and provided through different apps, websites or software services, retrieval is inconvenient – the user needs to search for the relevant information in several places and transfer it manually, often via text input. While using mobility apps, car drivers can find themselves in critical or dangerous situations because their attention is divided. The personal mobility assistant helps avoid such situations through easy usage and integration of data from many different sources.

The PMA combines mobility-related data such as information about traffic, parking spaces or charging stations for electric cars with user data such a personal calendar and presents them in a secure and non-distracting manner. The user can install the assistant on his or her smartphone and control the associated apps through touch or voice commands. The output is multi-modal as well, including written text and synthesized voice.

Solving problems ahead of time

As the project comes to an end with September 2015, results show that SIMPLI-CITY has been very successful. It has led to more than thirty scientific publications and a feasibility study which now explores potential commercial utilization of the research. Car manufacturers have already realized that mobile apps and services will become an essential part of the “product” mobility. “The efforts undertaken by the automobile industry and large IT companies such as Google and Apple show that SIMPLI-CITY has recognized an important trend at an early stage,” explains Schahram Dustdar (Head of Distributed Systems Group, Institute of Information Systems), scientific leader of the project. According to a survey by the market research company Gartner, 250 million vehicles will be connected to the internet by the year 2020. In 2014 alone, more than 1.2 billion smart phones were sold worldwide and many of them were subsequently used in cars. This demonstrates the immense market potential for mobility-related apps.

Data integration saves time and effort

Within the SIMPLI-CITY project, researchers at TU Wien and TU Darmstadt focused on developing methods for data integration from heterogeneous sources. “The app revolution in the mobile phone market has shown that many innovative apps are provided by third party suppliers. Therefore, our goal was to make mobile data integration easier for software engineers,” says Stefan Schulte. Software engineers with access to a homogeneous data model and the option to transform data do not need to work with different data formats and communication protocols and are thus able to save time and effort.

In SIMPLI-CITY, access to different data sources is realized through an abstraction layer. This layer retrieves external data through various protocols and automatically translates them into a homogeneous format. Data can be saved in time-variant versions for future use or analysis. One of the project partners utilizes this feature in order to generate recommendations for driving behavior based on live data from the car and saved data from previous drives. The user can also compare his or her own driving behavior with other drivers through social networks. The aim is to create an incentive system based on the comparison with friends in order to reduce the ecological footprint.

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