Cars vs Bikes: Intelligent Transport in EC Policy Documents

This paper is concerned with intelligent transport and smart mobility and considers the digital cultures emerging at the intersection of The Internet of Things, datafication and transport/mobility. Specifically, the research shows the intense bias of policies in these areas towards the automobile and other motorised modes, rather than towards more active and sustainable modes such as the bicycle. For this, the paper draws on recent academic concepts to develop a conceptual framework and then present results of an empirical analysis of international policies. Increasingly only those modes of transport/mobility are ‘visible’ in the socio-economic context that have data at their heart, i.e. are smart/intelligent – underlining the significance of this research. The conceptual framework draws on three areas of research (policy is considered across). The digital/data culture element of the framework is informed by critical data studies, including Kitchen’s understanding of data ‘doing’ work in the world and Andrejevic’s work on data divides. The transport/mobility element of the framework draws on more techno-centric perspectives around ‘Intelligent Transport’ (Perallos, Hernandez-Jayo, Onieva, & Zuazola, 2016) often used in policy documents, as well as more critical ‘Smart Mobility’ (Büscher, et al. 2012) perspectives that consider political, social and embodied aspects of mobile people and societies in the digital/data age. It also builds on the ‘Smart Velomobility’ concept (Behrendt, 2016). The methodology details the compiling of the archive of 39 relevant 2014-2018 EU policy papers, including those published under the themes transport, internet of things and smart cities – as all these areas consider aspects of intelligent transport/smart mobility. It also details the key word search protocol and NVIVO approach for analysing the documents. Results analyse and compare the use of keywords across the 39 documents, plus provide a detailed analysis of four documents. Overall, smart mobility is equated with the automotive industry across documents, and cars are the most prominent example of IoT given around transport. On the rare occasion that cycling is mentioned, only shared bike schemes are noted, whereas discussions of cars include both individual and shared use. The conversation around active modes such as walking and cycling is not integrated with conversations around the IoT– while those are strongly integrated with conversations around cars. The discussion and conclusion shows that not inclusing sustainable modes of transport such as cycling in the context of smart technologies such as IoT means they lack policy visibility and are less likely to receive associated funding, underlining the significance of the findings.