Back from the future. A backcasting on autonomous vehicles in the real city
Abstract
Backcasting is a scenario-building technique that can help decision-makers face uncertain and complex dynamics. For this reason, backcasting is often mentioned as suitable to deal with the transition to autonomous driving. However, at present the applications of backcasting to this transition in real-world cases are quite few. The article presents a backcasting carried out in the city of Turin (Italy), aimed at defining a policy pathway to steer the transition to autonomous driving towards objectives of sustainability and liveability of the city and its neighbourhoods. It reflects on this exercise and highlights some critical issues for backcasting that emerged from its application to autonomous vehicles (AVs). The transition to AVs displays some issues that proved to challenge the effectiveness and the potentialities of implementation of backcasting. These are mainly related to: factors and levels of uncertainty, contextualization of the vision, involvement of relevant stakeholders, definition of the policy pathway. Nevertheless, the exercise showed that some solutions can be adopted to deal with these challenges, in terms of definition of background socioeconomic scenarios, combination of a range of participatory techniques, integration of collaborative and think-tank methodologies, reference to mid-term planning tools. These solutions can support further backcasting exercises for AVs.
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