17 October 2013
Enhancing Travel Experiences with Public Transport Systems
12:30pm - 13:45pm
Traditionally, the reliability and efficiency of public transport services has been considered most important to guarantee a high uptake of public transport systems. Over the recent years, innovation in public transportation is increasingly focusing on information technology to make the usage of public transport system more attractive. The availability of novel sources of transport data such as digital travel records or real-time quality-of-transport information paves the way for novel user-centric transport information systems which can provide additional layers of travel experiences and guidance to users. In this seminar talk, we give an overview about the research activities carried out in the European research project GAMBAS for the design of personalised transport applications, aimed to accommodate the information and mobility needs of transport users more effectively. First, we show how data mining approaches can be applied to uncover patterns of transport usage from digital travel histories to inform the behaviour of intelligent transport applications. Then, we report on the experiences and insights we gained from a user study in Milton Keynes focused on the evaluation of user interface designs for representing qualitative attributes of transport system on mobile applications. Finally, we discuss the development of a prototype application for the city of Madrid where an integrated transport information system is built consisting of a mobile travel application and system components contributed by different European Universities and the local transport authority of Madrid.
Stefan Foell and Reza Rawassizadeh are Research Associates at the Open University, where they explore the design of mobile information systems for public transport as part of the European Research project GAMBAS.
Before joining the Open University, Stefan Foell was a PhD student at the University of Stuttgart, where he developed stochastic user models and methods for predicting changes in the context of mobile users. His current research interests span across urban data analysis and prediction, smart city applications and mobile systems.
Reza Rawassizadeh holds a Ph.D. of Computer Science from University of Vienna. Before joining the OU, he worked as a senior researcher in Research Studio Austria and analysed human behaviours in the context of various media such as mobile phones and social networks. Currently he works on UI design and UX studies for mobile transport applications.
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