Planning policies for the driverless city using backcasting and the participatory Q-Methodology

Abstract

Autonomous vehicles (AVs) can potentially bring about major changes in cities. Anticipatory planning approaches may provide valuable opportunities for fostering desirable transitions and pre-empting undesirable impacts. This research employs a combination of two methods to define the key policies to support a transition to the desirable driverless urban futures: the backcasting approach and the participatory Q-method. The combination of these techniques aims to identify different viewpoints about policies with the purpose of determining more effective and more acceptable options. The article analyses viewpoints from 20 citizens and 10 experts. The results point to the existence of two main viewpoints about the most and least desirable policies. The first viewpoint centres around increasing pedestrian mobility and promoting a more compact city. The second viewpoint centres around expanding transit-oriented development (TOD) and new networks of green spaces. Meanwhile, support for regulation-oriented policies to discourage the use of private motorised vehicles was relatively low. This research not only sheds light on the different viewpoints on the policies to achieve more desirable urban visions, it also illustrates the tensions and disagreements that may arise in the process of policy-making.