Connected, computed, collective: Smart Mobilities

The 'smart' in 'Smart Transport' usually refers to technologies, not people. From cars designed to be 'stackable', through signs that monitor parking spaces, to 'automatic cruise control' systems that 'intelligently' control distances through vehicle-to-vehicle and vehicle-to-infrastructure communication: technologies are key to smart transport. And it is true, people — armoured with status symbol cars and stuck in traffic — often do not behave intelligently, raging at other drivers and pedestrians, taking risks that endanger themselves and others. However, underestimating human intelligence could be a damaging oversight and missed opportunity for transport designers. In this chapter we examine several related aspects of human sense-making practices on the move and explore how these could be productively integrated with smart transport. Starting with a comparison of a 'view from above' and a 'view from on the ground', key aspects of the social logics of our mobile societies become visible. Then, new technologies are already an integral part of the social organisation of mobilities — with some socio-technical innovations that form a kind of parallel universe to the intelligent transport solutions envisaged by engineers and traffic planners. We discuss such 'alternate smart mobilities' through some utopian visions of 'collective intelligence' (Levy 1997) and its more mundane manifestations, including micro-coordination and an emergent digital economy of mobilities, based on crowdsourcing, community sensing, and data mashups. These 'bottom-up' innovations could come together productively with the pervasive 'qualculation' (Thrift 2004) that underpins traffic shaping and other engineering and design efforts around 'intelligent transport systems' (ITS) (COM 2008). Moreover, such a convergence of social and technological innovation could counteract the threat of 'Orwellian' surveillance that is part of a potentially Faustian bargain for more efficiency, convenience, sustainability and security in transport (Dennis and Urry 2009). We conclude with suggestions for mixed mobile research methods that can inform innovation.