Building adaptive smart transport governance using citizen-centric data

With the increasing popularity of the concept “smart city”, many cities have adopted smart governance to address complex socio-economic and spatial issues in urban areas. Smart transport governance is applying innovations in the process of collective decision making in response to the technological and other changes in smart transport development. Governing smart transport, as a key priority in smart cities, faces old and new challenges such as managing complex uncertainties, considering alternative futures, involving citizens and correct analysis of their needs, as well as changing roles of governance. Robust theoretical and practical understandings of smart transport governance are useful for planners and policymakers to address these challenges and transform the urban mobility system towards accessible, sustainable, and innovative futures. This PhD research explores the complexities in smart transport governance from theoretical, methodological, and practical aspects with a special focus on citizens’ needs. Four gaps in theory, methods, and practice are addressed in six chapters. In Chapter 2, a systematic literature review is performed to enhance the theoretical understanding of smart transport governance and its linkage with complexity theory in cities (CTC) and urban data science (UDS). A citizen-centric adaptive governance framework is proposed. Using the proposed framework to understand specific issues in smart transport governance, Chapters 3-5 conduct empirical studies. Chapter 3 first assesses the existing smart transport governance and development, using a new evaluation framework. Within English metropolitan areas, Greater London ranks first in smart transport development. Chapter 4 zooms into Greater London and applies novel methods to understand citizens’ activity-travel patterns with uncertainties. Typical activity-travel patterns before COVID-19 and the emerging self-organising changes when COVID-19 first hit London are identified. To supply quick insights into the pandemic’s impact on different sub-systems, Chapter 5 senses the public opinion towards different transport sub-systems through real-time social media big data. Dynamic behavioural changes and potential opportunities for smart transport transitions are found. The outcomes of this research support the idea that CTC and UDS can enhance existing smart transport governance in terms of adaptive planning, robust analysis, and citizen involvement. We have identified and discussed emerging technologies and abrupt crises that add complexity to the urban transport sector on its way to transforming into smart transport. Adaptive understanding with the help of citizen-centric data is crucial for planning uncertain futures. Despite some limitations, the studies can provide theoretical and practical implications for smart transport governance in an increasingly complex world. The study also shows significant potential for future development and further applications of the adaptive governance framework.

Name dc:type.qualificationname

Doctor of Philosophy (PhD)

Level dc:type.qualificationlevel

Doctoral

Grantor dc:publisher.institution

University of Cambridge

Year dc:date.issued

2022

Author dc:creator

• Chen, Yiqiao

Advisors dc:contributor.advisor

• Silva, Elisabete
• Reis, Jose

• smart city
• smart transport
• adaptive governance
• urban data science
• complexity theory in cities

Licence

• https://www.rioxx.net/licenses/all-rights-reserved/

Language dc:language

eng

Author Identifier

0000-0003-3575-5553

OAI identifier oai:identifier

oai:www.repository.cam.ac.uk:1810/346365