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Urban Science
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Advances in Urban Planning and the Digitalization of City Management
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Advances in Urban Planning and the Digitalization of City Management

A special issue of Urban Science (ISSN 2413-8851).

Deadline for manuscript submissions: 31 March 2026 | Viewed by 4967

Special Issue Editors

Prof. Dr. Cezar Scarlat

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Guest Editor
Doctoral School of Entrepreneurship, Business Engineering & Management, National University of Science and Technology POLITEHNICA Bucharest, Splaiul Independentei 313, 060042 Bucharest, Romania
Interests: technology entrepreneurship; business geolocation; technology-based decisions on business location and urban transportation; city development strategy; digital transformation and digitalization; smart city; city management; public administration
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Alexandru-Ionuţ Petrişor

E-Mail Website
Guest Editor
1. Doctoral School of Urban Planning, Ion Mincu University of Architecture and Urbanism, 10014 Bucharest, Romania
2. Department of Architecture, Faculty of Architecture and Urban Planning, Technical University of Moldova, 2004 Chisinau, Moldova
3. National Institute for Research and Development in Constructions, Urbanism and Sustainable Spatial, Development URBAN-INCERC, 21652 Bucharest, Romania
Interests: environmetrics; systems ecology; spatial ecology; geostatistics; urban ecology; landscape ecology; land cover and use; land cover and use changes; sustainable spatial development
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Modern urban planning makes use of digital technologies to the extent where it is impossible to separate the two. Data-driven approaches to planning are now the order of the day. Digital twins and smart cities are no longer simple concepts, but realities and well-defined standards. Recently, artificial intelligence has been applied in many fields, including urban planning. The question that remains unanswered, and is addressed by the current issue, is whether a city can be managed under current settings, and what challenges are facing those managing the city or planning for it in the new digital world. Additional questions are whether urban management can make use of or benefit from new technologies, and how? Since we are witnessing a new reality, we are also seeking for prospects related to the dynamics of new trends and to determine, overall, how to plan for a city in the digital age.

This Special Issue aims to collect answers to these questions from urban science theory, but mostly from practice. We invite urban planners and city managers to reflect upon the answers and provide grassroots examples wherever possible.

Original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

  • Opportunities and challenges for urban digitalization;
  • The digitalization of city administration and management;
  • AI-assisted decisions for city management;
  • The digitalization of city public services;
  • The digitalization of health and education services;
  • The digitalization of city transport networks;
  • Urban mobility, autonomous vehicles, and transportation issues;
  • Geospatial technologies and databases for city management;
  • Emergency management in urban agglomerations;
  • The city and citizens: managing the city and utilities for citizens;
  • The city and its businesses;
  • The city and energy issues, as well as smart energy grids;
  • Managing a smart, green, and sustainable city;
  • City development strategies: the city of the future;
  • Urban development: horizontal and vertical cities, the air, and underground;
  • Outer space and city issues.

We look forward to receiving your contributions.

Prof. Dr. Cezar Scarlat
Prof. Dr. Alexandru-Ionuţ Petrişor
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Urban Science is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • geospatial technology
  • urban planning in the digital era
  • AI in urban planning
  • digital twin
  • digital transformation
  • urban management
  • city management
  • urban mobility
  • utility networks and energy grids
  • smart and sustainable city

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (3 papers)

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Research

17 pages, 3487 KB  
Article
Vehicle Connectivity and Dynamic Traffic Response to Unplanned Urban Events
by Javad Sadeghi, Cristiana Botta, Brunella Caroleo and Maurizio Arnone
Urban Sci. 2025, 9(10), 409; https://doi.org/10.3390/urbansci9100409 - 2 Oct 2025
Viewed by 362
Abstract
Integrating advanced technologies, such as Connected Autonomous Vehicles (CAVs) and Connected Vehicles (CVs), represents new strategies and solutions in urban mobility, particularly during unexpected urban events. Vehicle connectivity facilitates real-time communication between vehicles and infrastructure, enhancing traffic management by enabling dynamic rerouting to [...] Read more.
Integrating advanced technologies, such as Connected Autonomous Vehicles (CAVs) and Connected Vehicles (CVs), represents new strategies and solutions in urban mobility, particularly during unexpected urban events. Vehicle connectivity facilitates real-time communication between vehicles and infrastructure, enhancing traffic management by enabling dynamic rerouting to minimize delays and prevent bottlenecks. This study employs the SUMO (Simulation of Urban Mobility) microsimulation to analyze the impact of dynamic rerouting strategies during urban disruptions within the IN2CCAM project’s Turin Living Lab. The Living Lab integrates simulation with real-world testing, including autonomous shuttle operations, to evaluate new mobility solutions. In the initial phase, offline simulations examine street, lane, and intersection closures along shuttle routes to assess how penetration levels of CVs and CAVs influence mobility. The results indicate that higher connectivity penetration improves traffic flow, with the greatest benefits observed at increased levels of autonomous vehicles. These findings highlight the potential of dynamic routing strategies, supported by vehicle connectivity and autonomous driving technologies, to enhance urban mobility and effectively respond to real-time traffic conditions. Additionally, this work demonstrates the capabilities and flexibility of SUMO for simulating complex urban traffic scenarios. Full article
(This article belongs to the Special Issue Advances in Urban Planning and the Digitalization of City Management)
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20 pages, 2641 KB  
Article
Artificial Intelligence for Urban Planning—A New Planning Process to Envisage the City of the Future
by Romano Fistola and Rosa Anna La Rocca
Urban Sci. 2025, 9(9), 336; https://doi.org/10.3390/urbansci9090336 - 27 Aug 2025
Cited by 1 | Viewed by 3003
Abstract
Assuming that Artificial Intelligence (AI) is changing the approach to urban planning issues, this study investigates whether changes will start to occur at a theoretical level or if technological innovations will mostly be endured rather than used with full knowledge. The authors observed [...] Read more.
Assuming that Artificial Intelligence (AI) is changing the approach to urban planning issues, this study investigates whether changes will start to occur at a theoretical level or if technological innovations will mostly be endured rather than used with full knowledge. The authors observed that technological innovation often occurs without a unifying theoretical framework to provide knowledge and a basis for its adoption. The first use of technology in urban management dates to the late 1950s, and it has recently regained attention within the scientific literature; however, a significant deficiency still exists regarding the definition of a theoretical framework for its use. Focusing on the use of AI in urban and regional planning, this study aims to address this gap by outlining theoretical observations that can guide the integration of AI into new approaches for the management of urban transformations. The enormous impact that the rapid and pervasive spread of AI is having on all human activities necessitates the definition of new educational and disciplinary processes, especially in fields like urban planning, which rely on the high potential of such technology for envisioning future scenarios. It is therefore essential to assume that AI will also modify the management of urban and territorial transformations. This study aims to suggest a framework for scholarly debate on the need to define new historical–disciplinary dimensions by appropriately using AI in the phases of urban planning, avoiding the risk of passively accepting AI’s potential by delegating the development of urban planning tools to artificial reasoning. Building on these premises, this study first provides a thorough and critical literature review regarding the use of AI in urban planning and then proposes a methodological framework. The final section discusses the possibilities and limitations of this approach, thereby contributing to the scientific debate on defining a theoretical framework for the adoption of AI within urban and regional planning processes. Full article
(This article belongs to the Special Issue Advances in Urban Planning and the Digitalization of City Management)
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19 pages, 3306 KB  
Article
AI-Driven Urban Mobility Solutions: Shaping Bucharest as a Smart City
by Nistor Andrei and Cezar Scarlat
Urban Sci. 2025, 9(9), 335; https://doi.org/10.3390/urbansci9090335 - 27 Aug 2025
Cited by 1 | Viewed by 1033
Abstract
The metropolitan agglomeration in and around Bucharest, Romania’s capital and largest city, has experienced significant growth in recent decades, both economically and demographically. With over two million residents in its metropolitan area, Bucharest faces urban mobility challenges characterized by congested roads, overcrowded public [...] Read more.
The metropolitan agglomeration in and around Bucharest, Romania’s capital and largest city, has experienced significant growth in recent decades, both economically and demographically. With over two million residents in its metropolitan area, Bucharest faces urban mobility challenges characterized by congested roads, overcrowded public transport routes, limited parking, and air pollution. This study evaluates the potential of AI-driven adaptive traffic signal control to address these challenges using an agent-based simulation approach. The authors focus on Bucharest’s north-western part, a critical congestion area. A detailed road network was derived from OpenStreetMap and calibrated with empirical traffic data from TomTom Junction Analytics and Route Monitoring (corridor-level speeds and junction-level turn ratios). Using the MATSim framework, the authors implemented and compared fixed-time and adaptive signal control scenarios. The adaptive approach uses a decentralized, demand-responsive algorithm to minimize delays and queue spillback in real time. Simulation results indicate that adaptive signal control significantly improves network-wide average speeds, reduces congestion peaks, and flattens the number of en-route agents throughout the day, compared to fixed-time plans. While simplifications remain in the model, such as generalized signal timings and the exclusion of pedestrian movements, these findings suggest that deploying adaptive traffic management systems could deliver substantial operational benefits in Bucharest’s urban context. This work demonstrates a scalable methodology combining open geospatial data, commercial traffic analytics, and agent-based simulation to rigorously evaluate AI-based traffic management strategies, offering evidence-based guidance for urban mobility planning and policy decisions. Full article
(This article belongs to the Special Issue Advances in Urban Planning and the Digitalization of City Management)
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