Envisioning the driverless city using backcasting and Q-methodology

Autor: Esther González-González, Rubén Cordera, Dominic Stead, Soledad Nogués
Přispěvatelé: Universidad de Cantabria, University of Cantabria, Department of Built Environment, Aalto-yliopisto, Aalto University
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Cities, 2023, 133, 104159
ISSN: 2019-1103
Popis: Despite the expected future introduction of autonomous vehicles in cities, very few studies have analysed the needs and challenges facing urban planning. This paper employs a combination of backcasting and Q-methodology to carry out participatory visioning for a future driverless city. This novel approach was used to elaborate shared visions of the desirable city among a group of 20 citizens and 10 practitioners. Views on 41 statements were analysed relating to urban design, society, environment, transport and mobility needs. Three main visions were identified. The first focuses on high-quality urban spaces and active mobility. The second vision is more futuristic and pro-social, consistent with the more imaginative and innovative stance of young people. The third vision is more conventional and closer to business-as-usual. The results suggest that there is some agreement on the future conditions and policies, especially on the need for environmentally friendly urban development and safe urban design. The article is premised on the belief that engaging stakeholders from different backgrounds, including citizens of various ages, can be enriching for urban planning since there is a wide variety of heterogeneous preferences across society. This requires a search for common ground when designing policy measures that satisfy multiple interests. This work is based on the research project: “InnovAtive Urban and Transport planning tOols for the implementation of New mObility systeMs based On aUtonomouS driving” — AUTONOMOUS (2020–2023) (PID2019-110355RB-I00), funded by the Spanish Ministry of Science and Innovation (MICINN)/ERDF (EU) under the National Plan for Scientific and Technical Research and Innovation 2017–2020.
Databáze: OpenAIRE