Services for Intelligent Mobility Management

Project: Research council

Project Details

Description

We are in a period of unprecedented technological change in which the convergence of a range of underlying technologies in the domains of computing, communications, positioning and navigation, pervasive sensing and modelling and analysis are fundamentally changing the way we can organise our lives and undertake our business. These types of changes will have major implications for many aspects of travel behaviour and for the operation of transport systems. Whilst there is much speculation regarding the exact nature of these impacts, history strongly suggests that it is unlikely to be productive to attempt to predict in detail the impact of such disruptive technologies. What is clear, however, even from existing experience, is that scale of these impacts will be profound. At the same time that this technological driver accelerates, there is in parallel a growing recognition that powerful drivers are at work within the transport domain itself. Many parts of the transport system are already operating at or near capacity for most of the day, with in most cases little or no scope for significant capacity expansion. In addition, there are increasingly urgent environmental objectives associated with substantial reductions in CO2 and other environmental emissions, as highlighted for example by the recent publication of the Stern Report. Policy makers are increasingly be drawn to the conclusion that these objectives can only be achieved if we bring about a step change both in the underlying patterns of travel demand and the efficiency and effectiveness with which the transport network is operated and managed. This step change is likely to be one that involves policy interventions that makes travel both more expensive and more difficult than at present. The transport domain thus finds itself at the focal point of two distinct but strongly interacting and reinforcing drivers - one technological and one policy. As a result, the decision making process confronting individuals, businesses and network managers will in the future become substantially more challenging - technology will provide more ways of doing things and policy interventions are likely to substantially change the balance of costs and benefits associated with invoking different options. In both dimensions, the exact path of change will be unpredictable. The fundamental challenge that arises is how best to harness the capabilities of the new digital economy to support decision making in this new and complex environment. The overall aim of the SIMM research cluster is to explore the research challenges associated with how to exploit the capabilities of the digital economy to promote and enable the development of new services to support and improve the decision making capability of travellers, transport network managers and the wider community.The SIMM research cluster is a partnership of 12 academic groups and 3 industrial organisations with active research and business interests in the development of the digital economy and its relationship to transport. The consortium spans 4 key technical areas of direct relevance to the digital economy in a transport context; computing, communications, positioning and navigation and transport modelling. In addition, the industrial partners provide a range of domain experience that compliments the academic experience.Through a series of workshops and conferences, backed by web based interaction and resources the SIMM cluster will establish new academic research collaborations, bringing together new disciplinary combinations and establishing between individuals the relationships of mutual understanding and trust necessary to underpin successful collaboration. These collaborations, which will include extensive interaction with stakeholders, will define, scope and prioritise research challenges and develop specific research proposals, which will be taken forward to a variety of funding bodies.
StatusFinished
Effective start/end date1/04/0831/03/09

Funding

  • Engineering and Physical Sciences Research Council

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