Attard, M; Haklay, ME; Capineri, C; (2015) Knowledge co-production, VGI and the implications on future transport systems. Presented at: WCTR SIG G3 Conference on Climate Change Targets and Urban Transport Policy, Valletta, Malta.

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Abstract

The capacity of the transport system to support the growing mobility needs of populations have been pushed to the limit in most cities and the approach of governments to resolve the problem has been to increase capacity (where this is possible) and repeat what has been the practice so far (Banister, 2007). This however has resulted in congested networks, unhealthy living conditions due to pollution, and infrastructures that are both unequal in dealing with particular groups within the population as well as costly to build and maintain. Miller (2013) contends the need to identify new capabilities (instead of capacity) of the transport infrastructure in order to increase efficiency and increase capacity without extending the existing infrastructure. In 2003 Susan Kenyon and Glen Lyons (working on earlier work by Lyons, 2001) described the potential of information to influence travel choices. Specifically they identified integrated traveller information to help make transport decisions. Both the transport industry and the research community supported this thesis with many cities developing multimodal information systems to support sustainability-oriented decisions (Kramers, 2014). Fast forward to today where the potential of information is not only to be integrated across different modes (e.g., cooperative transport systems) but also be user generated, real time and available on smart phones anywhere. User generated information play today an important role in sectors such as politics, businesses and entertainment, and presumably this phenomena would extend to transport in revealing people’s preferences for mobility (Gal-Tzur et al., 2014) and therefore be useful as tools for decision making and support. The widespread availability of smart phone technology and the growing coverage of ubiquitous data communication networks in urban areas are causing a dramatic transformation in the way information is produced and consumed (Manovich, 2009). It has also offered new opportunities for what are termed cooperative transport systems supported by smart phone apps and crowdsourcing through social media such as the successful community based traffic and navigation app Waze (www.waze.com), bought by Google for $1.3 billion (Rushe, 2013); Moovit for transit planning (www.moovitapp.com); community car sharing programmes such as Zipcar (www.zipcar.co.uk); and more recently peer-to-peer vehicle and ride sharing systems such as Getaround (www.getaround.com) and Uber (www.uber.com). Some of these systems are already being branded by Lanzendorf (2014) as Mobility 2.0, however many of which would not be so successful if not enough users actively participate and generate information (knowledge co-production). It is this revolution in the potential of data-driven planning, management and use of transport systems that has led Winter et al. (2011) to call for a new interdisciplinary field called computational transportation science, defined as a science concerned with the study of transportation systems where people interact with information systems (e.g., interfaces for driver assistance, or integrated transport information); where systems monitor and interpret traffic (e.g., mining for activity patterns, or crowd-sourcing to monitor events); or where systems manage the traffic (e.g., control of traffic flow at traffic lights, or toll management). It is the second objective that is of particular interest to our research here. In particular, its impact on the traveller and the potential of governments to use crowd-sourced information and social media effectively for sharing information, creating opportunities for collaboration, enhancing government responsiveness, planning and governance to achieve sustainability and climate change goals (related studied included Panagiotopoulos et al., 2014; Bertot et al., 2012). This article reflects on (i) the impact of technologies on travellers, particularly the information that is co-produced through crowdsourcing and VGI techniques (ii) its potential for supporting and achieving sustainable mobility goals, and (iii) what role exists for governments (if any at all) in the use of user generated information. A review of the literature and existing technology informs this article and the aim is to propose further research into these growing technologies as well as increasing participation through the development of VGI and Citizen Science for travel and transport.

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