Smart Mobility aims at making mobility safer, more comfortable, better accessible (e.g. for the elderly) and to reduce environmental impact. Examples are Travelling Advice, Automated Driving, Speed Control, Platooning or Traffic Sign Recognition. While the technology for intelligent transport systems (ITS) develops fast, their application is limited to boundary conditions of technical capabilities and infrastructure. The trade-off between these aspects, the context and traffic participants’ behaviour, acceptance and abilities define to a large extend the success of smart mobility.
Sustainable development of transport solutions that use smart mobility need true understanding of the users involved and their use situations. Deficits in users’ understanding may cause counterproductive effects, like drivers who take increased speeding risks as they assume to be compensated by the ITS-application. For the development of smart mobility it is crucial to involve users, traffic participants and all stakeholders to ensure that an application will be effective, meaningful, ethically sound and practically usable.
The track Human Centred Design for Smart Mobility researches the interaction between technology, context and user to develop better transport applications. We develop methods to improve the balance between the capabilities of the technology and the ‘fit’ to human needs. An important focus is to avoid counterproductive effects and to add value through stakeholder involvement.
current projects
i-Cave
Integrated Cooperative Automated Vehicles. Human Factors of driver-vehicle cooperation of highly automated vehicles in urban environments. – STW project 2016-2020
Prautocol
Developing tools and methods to license drivers of automated vehicles in their role as supervisor. – commissioned research 2017-2019
Talking Traffic
Human Factors evaluation and design exploration of in-vehicle traffic light information. 2017
Driving automation interface design: supporting drivers' changing role
Design and evaluation of interfaces that provide directional cues on the place and importance of traffic elements that need attention. These interfaces are intended to support drivers in their role to supervise driving automation. – PhD project 2013-2016, co-funded by Ford Motor Cooperation.