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There are many challenges associated with the physical movement of people within a city, whether this be too much traffic for finite road space leading to congestion the lack of an integrated public transport system (across rail, light rail, bus, tram, bike) Competition between providers that leads to a lack of centralised control and no ability to provide journey planning. External / Environmental effects (i.e. extreme weather) on the transport network and the knock on effect this has to network users. These challenges are compounded as the population utilizing the transport network increases.

Smart transport, through enhanced city insight looks to optimization of city transportation systems through smart sensing, modelling, and control. Through the ingestion of multiple sources of sensed data, it is possible to model the complex system of public and private transport systems across a city, and to improve how it operates. Multiple data sources, and in particular those from new media (twitter feeds, etc) can be harnessed in real-time to provide the increased insight necessary to reduce congestion and provide information services for travellers (for example, multi-modal route planning). Sophisticated analytic tools can help traffic controllers and the traveling public make better decisions and improve the functioning of the system for everyone.