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By 2050, about two-thirds of the world’s people are expected to live in urban areas. But, the economic viability and sustainability of city centers is threatened by problems related to transport, such as pollution, congestion, and parking. Much has been written about automated vehicles and demand responsive transport. The combination of these potentially disruptive developments could reduce these problems. However, implementation is held back by uncertainties, including public acceptance, liability, and privacy. So, their potential to reduce urban transport problems may not be fully realized. We propose an adaptive approach to implementation that takes some actions right away and creates a framework for future actions that allows for adaptations over time as knowledge about performance and acceptance of the new system (called ‘automated taxis’) accumulates and critical events for implementation take place. The adaptive approach is illustrated in the context of a hypothetical large city

Dynamic adaptive policymaking for the sustainable city: The case of automated taxis