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Advances in Urban Planning and the Digitalization of City Management

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A special issue of Urban Science (ISSN 2413-8851). This special issue belongs to the section "Intelligent Cities and Technology".

Deadline for manuscript submissions: 31 March 2027 | Viewed by 17154

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Special Issue Editors

Prof. Dr. Cezar Scarlat

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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

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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: land cover and use; land cover and use changes; urban ecology; landscape ecology; sustainable spatial development; environmental planning; systems ecology; spatial ecology; environmetrics; geostatistics; research ethics; predatory publishing
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 250 words) can be sent to the Editorial Office for assessment.

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 1800 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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Published Papers (9 papers)

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Research

19 pages, 2057 KB

Open AccessArticle

Digitalization of Urban Biowaste Deposition and Collection Systems for Data-Driven Municipal Decision-Making

by Susana Maia, Vitória Souza and Carlos Afonso Teixeira

Urban Sci. 2026, 10(5), 278; https://doi.org/10.3390/urbansci10050278 - 15 May 2026

Viewed by 382

Abstract

This study proposes and tests an analytical framework for interpreting digitally monitored municipal biowaste collection services through comparable diagnostics of operational performance, additional effort, and emissions intensity. The framework was applied to 572 collection services recorded between July and December 2025 in the Municipality of Barreiro, Portugal, covering seven circuits operating under different urban morphologies and collection configurations. Service-level operational records were transformed into physically interpretable performance indicators and an additional operational effort index was derived from robust normalization of serviced container density and service time per kilometer. The results showed marked heterogeneity across service regimes, with the highest effort observed in residential circuits characterized by greater spatial and temporal demand, while the non-domestic and communal circuits remained at or below municipal reference conditions. At the municipal scale, operational effort was moderately associated with mass collected per kilometer (ρ = 0.490, n = 572), weakly and non-significantly associated with mass per hour (ρ = 0.075, p = 0.074), and negatively associated with mass per container (ρ = −0.325). For services operating above municipal reference conditions (Eesf > 0, n = 286), emissions intensity was negatively associated with both effort components and with the aggregate effort index, with the strongest association observed for Eesf (ρ = −0.554). The results indicate that higher operational effort tends to coincide with greater spatial mass recovery, but not with higher container-level yield or proportionate improvements in emissions performance. More broadly, the study shows that the analytical value of digital monitoring depends not only on data availability, but also on the ability to convert routine service records into interpretable diagnostics for municipal decision-making. Full article

(This article belongs to the Special Issue Advances in Urban Planning and the Digitalization of City Management)

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18 pages, 639 KB

Open AccessArticle

Digitalization of Last-Mile Delivery: Comparative Assessment of Mobile Applications for Urban Parcel Locker Networks

by Maria Cieśla and Artur Budzyński

Urban Sci. 2026, 10(5), 247; https://doi.org/10.3390/urbansci10050247 - 4 May 2026

Viewed by 595

Abstract

The rapid growth of e-commerce has significantly increased direct-to-consumer deliveries, putting competitive and environmental pressure on urban last-mile logistics. Out-of-home (OOH) delivery options, particularly parcel lockers, are increasingly integrated into city mobility strategies to reduce congestion and emissions. However, the role of mobile applications front-ending these networks remains under-researched. This study aims to evaluate the user experience (UX) and functional adequacy across three major parcel-locker apps in Poland: InPost Mobile, DPD Mobile, and ORLEN Paczka. A cross-sectional, mixed-methods approach combining in situ corridor testing and structured post-task questionnaires was employed with 30 users at real locker locations in Katowice. The results indicate that interface simplicity, predictable information flow, and technical stability are the dimensions most consistently associated with higher user ratings. InPost Mobile consistently achieved the highest ratings due to its focus on core workflows, whereas applications emphasizing broader functional coverage (ORLEN Paczka) exhibited usability trade-offs, and DPD Mobile underperformed in speed and stability. Because the study relied on a small convenience sample (n = 30) in a single city and was skewed toward younger adults (18–24), the findings should be interpreted as exploratory and primarily reflective of a digitally proficient demographic rather than the broader user population. Full article

(This article belongs to the Special Issue Advances in Urban Planning and the Digitalization of City Management)

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35 pages, 859 KB

Open AccessArticle

Digitalizing Urban Planning Governance: Empirical Evidence from Yerevan and a Multi-Layer Framework for Data-Driven City Management

by Khoren Mkhitaryan, Anna Sanamyan, Hasmik Hambardzumyan, Armenuhi Ordyan and Gor Harutyunyan

Urban Sci. 2026, 10(4), 183; https://doi.org/10.3390/urbansci10040183 - 29 Mar 2026

Viewed by 626

Abstract

The rapid digitalization of cities is reshaping urban planning practices; however, significant gaps persist between technological investments and institutional governance capacity, particularly in transition economies. This study investigates how digital tools can be systematically embedded within planning processes to improve decision-making quality, coordination, and administrative efficiency. Drawing on urban governance theory and an empirical implementation study conducted in Yerevan, Armenia (population 1.1 million) between 2019 and 2023, the paper develops and operationalizes a multi-layer governance framework that aligns digital instruments—including geospatial information systems, performance dashboards, and decision-support platforms—with strategic, tactical, and operational levels of city management. The framework is evaluated through institutional analysis of municipal policy documents, planning databases, and semi-structured interviews with planning officials. The results reveal substantial governance barriers, including data fragmentation, organizational silos, and limited digital capacity. Framework-based implementation produced measurable improvements: planning decision cycles shortened by 43%, GIS utilization increased from 18% to 68% of eligible projects, inter-agency data sharing rose sixfold, and annual cost savings of approximately $1.2 million were achieved through reduced duplication and faster approvals. By combining conceptual design with empirical validation, the study advances digital urban governance research and offers a transferable, evidence-based model for implementing resilient and efficient data-driven planning systems in resource-constrained contexts. Full article

(This article belongs to the Special Issue Advances in Urban Planning and the Digitalization of City Management)

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27 pages, 15826 KB

Open AccessArticle

Enabling Citizen Engagement via Geolocated AR Interaction with a Digital Twin City

by Xin Zhang, André Brown and Antony Pelosi

Urban Sci. 2026, 10(4), 176; https://doi.org/10.3390/urbansci10040176 - 24 Mar 2026

Viewed by 424

Abstract

This study reports on the devising and testing of the implementation and effectiveness of geolocated augmented reality (AR) as a potential means to convey urban information and elicit citizen interaction with the ability to interface with a digital twin city (DTC) environment. We have taken an open platform approach. The prospective approach is specifically chosen to test a set of technologies that could inform and actively engage citizens in matters of urban design and development. Critically, in line with the strategy of openness, the approach employs mobile technologies freely available to both citizens and city authorities. We first examine the recent DTC frameworks and the AR technologies capable of delivering the desired on-site interaction. Subsequently, we describe the structured development and testing of a prototype geolocated AR open technology implementation that could effectively integrate mutual communication with a DTC representation. In the case study, we examine the information flow paradigm between the physical and the virtual, then report on the technology’s usability. The study reveals promising performance and potential for the mobile AR system that has been developed, meeting the target expectations for the desired forms of public engagement that could be integrated with a DTC environment. If implemented, this approach has the potential to foster site-specific engagement, both digitally and physically, to enable citizens to interact with city authorities and, more broadly, to promote spatial smartness and urban intelligence. Full article

(This article belongs to the Special Issue Advances in Urban Planning and the Digitalization of City Management)

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18 pages, 1238 KB

Open AccessArticle

Digital Twin in Territorial Planning: Comparative Analysis for the Development of Adaptive Cities

by Valeria Mammone, Maria Silvia Binetti and Carmine Massarelli

Urban Sci. 2026, 10(2), 80; https://doi.org/10.3390/urbansci10020080 - 2 Feb 2026

Viewed by 1263

Abstract

Increasing urbanisation and the intensification of environmental and climate challenges require a review of governance models and tools supporting urban and territorial planning. The Twin Transition concept (green and digital) requires the integration of advanced monitoring and simulation systems. In this context, Digital Twins (DTs) have evolved from static virtual replicas to dynamic urban intelligence systems. Thanks to the integration of IoT sensors and artificial intelligence algorithms, DT enables the transition from a descriptive to a prescriptive approach, supporting climate uncertainty management and real-time territorial governance. The ability to integrate multi-source data and provide high-resolution site-specific representations makes these tools strategic for planning, resource management, and the assessment of urban and peri-urban resilience. The contribution comparatively analyses different digital twin frameworks, with particular attention to their applicability in highly complex environmental contexts, such as the city of Taranto. As a Site of National Interest, Taranto requires models capable of integrating industrial pollutant monitoring with urban regeneration and biodiversity protection strategies. The study assesses the potential of DT as predictive models to support governance for more sustainable, adaptive, and resilient cities. 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, 1098 KB

Open AccessArticle

Simulation-Based Evaluation of AI-Orchestrated Port–City Logistics

by Nistor Andrei

Urban Sci. 2026, 10(1), 58; https://doi.org/10.3390/urbansci10010058 - 17 Jan 2026

Viewed by 1535

Abstract

AI technologies are increasingly applied to optimize operations in both port and urban logistics systems, yet integration across the full maritime city chain remains limited. The objective of this study is to assess, using a simulation-based experiment, the impact of an AI-orchestrated control policy on the performance of port–city logistics relative to a baseline scheduler. The study proposes an AI-orchestrated approach that connects autonomous ships, smart ports, central warehouses, and multimodal urban networks via a shared cloud control layer. This approach is designed to enable real-time, cross-domain coordination using federated sensing and adaptive control policies. To evaluate its impact, a simulation-based experiment was conducted comparing a traditional scheduler with an AI-orchestrated policy across 20 paired runs under identical conditions. The orchestrator dynamically coordinated container dispatching, vehicle assignment, and gate operations based on capacity-aware logic. Results show that the AI policy substantially reduced the total completion time, lowered truck idle time and estimated emissions, and improved system throughput and predictability without modifying physical resources. These findings support the expectation that integrated, data-driven decision-making can significantly enhance logistics performance and sustainability in port–city contexts. The study provides a replicable pathway from conceptual architecture to quantifiable evidence and lays the groundwork for future extensions involving learning controllers, richer environmental modeling, and real-world deployment in digitally connected logistics corridors. Full article

(This article belongs to the Special Issue Advances in Urban Planning and the Digitalization of City Management)

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17 pages, 3487 KB

Open AccessArticle

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

Cited by 1 | Viewed by 1101

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 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

Open AccessArticle

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 4 | Viewed by 7147

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 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

Open AccessArticle

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 5 | Viewed by 2558

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 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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