Commuting patterns in Sub-Saharan African cities are evolving in tandem with rapid levels of historical urbanization. Yet, our understanding of how the prevailing urban spatial structures shape travel patterns is limited. This study explores the land-use-travel nexus in the Kumasi metropolis in Ghana, by focusing on work commuting. It uses newly available land-use datasets to present TAZ-level analysis of the distribution of land-use activity types. From a survey of a representative sample of 1158 workers, the characteristics of commuters and their travel patterns are examined. The analyses reveal a unique structure for the urban system, that is polycentric in both morphological and functional dimensions, but with a relatively stronger centre (i.e. CBD). Overall, home-work commute flows strongly reflect the prevailing spatial structure. Residence in suburban neighbourhoods; non-home-based employment locations; home-work distance exceeding 0.3 km; and relatively higher-incomes influence motorized transport choice and car-use for work journeys. Walking to work is strongly associated with lower-income levels, residence in historical-core neighbourhoods and home-based employment. The paper contributes to conceptualizing, theorising and understanding the spatial structure-travel nexus at the intra-urban scale by focusing on a previously unexplored urban context. The implications of the findings for integrated urban development and transportation planning are highlighted.
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Autonomous Vehicles (AVs) have the potential to make motorized transport safer and more sustainable, by integrating clean technologies and supporting flexible shared-mobility services. Leveraging this new form of transport to transform mobility in cities will depend fundamentally on public acceptance of AVs, and the ways in which individuals choose to use them, to meet their daily travel needs.
Empirical studies exploring public attitudes towards automated driving technologies and interest in AVs have emerged in the last few years. However, within this strand of research there is a paucity of theory-driven and behaviourally consistent methodologies to unpack the determinants of user adoption decisions with respect to AVs. In this paper, we seek to fill this gap, by advancing and testing four conceptual frameworks which could be deployed to capture the range of possible behavioural influences on individuals’ AV adoption decisions.
The frameworks integrate socio-demographic variables and relevant latent behavioural factors, including perceived benefits and perceived ease of use of AVs, public fears and anxieties regarding AVs, subjective norm, perceived behavioural control, and attitudinal factors covering the environment, technology, collaborative consumption, public transit and car ownership.
We demonstrate the utility and validity of the frameworks, by translating the latent variables into indicator items in a structured questionnaire, and administering it online to a random sample of adult individuals (n = 507). Using the survey data in confirmatory factor analyses, we specify and demonstrate scale reliability of indicator items, and convergent and discriminant validity of relationships among latent variables.
Ultimately, we advance four measurement models. These theory-grounded measurement models are intended for application in research aimed at understanding and predicting (a) AV interest and adoption intentions, and (b) user adoption decisions regarding three different AV modes: ownership, sharing and public transport.