Mobility as a Service and User Experience
Advances in communication and sensor technologies can support transport systems in which supply and demand are actively managed almost simultaneously.
Thus, the current pre-planned, static, fixed route, provider-led notion of public transport is set to change to a far more responsive, dynamic, flexible route, user-led paradigm – with significant societal benefits.
Research in this area spans the potential of smart motorways, contactless pay-as-you-go public transport, traffic generator-led transport provision, and dial-a-pod travel. Whilst some of these aspects of user-centred IM are already existent, others will see a revolution in how we travel and move goods. For instance, the Mobility as a Service (MaaS) model now being adopted is beginning to significantly change local travel, and looks likely to become far more widespread. Meanwhile the potential for seamlessly booking and travelling on journeys provided by multiple operators and using a whole range of transport modes – including, eventually, driverless taxi pods – will soon be realised, providing even more choice in how and when journeys are made.
Our researchers are exploring how these new transport technologies and systems could work – improving our daily routines and reducing the environmental impact of our journeys. We are investigating the challenges that cities will have in adapting to connected and automated mobility systems and helping them find ways to use the technologies to achieve cities' policy objectives. We conduct research into the mathematical basis of improved logistics systems.
Our research include:
- Using simulation models to forecast the impacts on cities of future intelligent mobility systems
- Analysis of normal driving and travel data to support the development of future intelligent mobility systems
- Development of quantitative methods to improve logistics and freight transport
- Improving the user experience through use of personal data
Research Projects
Developing Relevant Tools for Demand Responsive Transport (DRT for DRT)
Evaluation Study of Demand Responsive Transport Services in Wiltshire
Enhancing the rail experience for passengers with special needs
Using real time rainfall data to predict weather conditions to increase cycling and walking
Delivering better transport systems while reducing environmental impact
Understanding how we travel to improve our lives
Data to improve the customer experience (DICE)
REFLECT A feasibility study in experienced utility and travel behaviour