Hasil untuk "City planning"

M. Batty

I define big data with respect to its size but pay particular attention to the fact that the data I am referring to is urban data, that is, data for cities that are invariably tagged to space and time. I argue that this sort of data are largely being streamed from sensors, and this represents a sea change in the kinds of data that we have about what happens where and when in cities. I describe how the growth of big data is shifting the emphasis from longer term strategic planning to short-term thinking about how cities function and can be managed, although with the possibility that over much longer periods of time, this kind of big data will become a source for information about every time horizon. By way of conclusion, I illustrate the need for new theory and analysis with respect to 6 months of smart travel card data of individual trips on Greater London’s public transport systems.

Adeb Ali Ebrahim

The primary drivers of agricultural land depletion in Taiz be diagnosed quantitatively in this study, proposing for the first time a replicable conflict-sensitive urban management model. The overarching objective is to bridge the critical gap between sustainable urban expansion and the preservation of agro-ecological systems in fragile, data-scarce contexts. A combination of unplanned sprawl, crisis, and ineffective governance, Taiz City's rapid urbanization between 2000 and 2024 resulted in a 35% loss of agricultural land. This study proposes that governance reduces the primary causes of conflict escalation and the severity of sprawl. This study combines GIS spatial analysis (Landsat 8/9 and support vector machine classification), regression modeling, and global case comparisons (Medellín and Mumbai) to assess land-use trends. The findings indicate that governance diminishes the effects (β = −0.50, p < 0.01), sprawl (β = 0.85, p < 0.01), and conflict (β = 0.002, p < 0.05) explain 85% of the variance in losses. By 2024, 3.2 million residents' food security was at risk because of the urbanization of 60% of peri-urban fertile lands. Vertical expansion, tenure regularization and GIS planning will reclaim 20% of land by 2030.

Zheng Tang, Shuo Wang, David C. Anastasiu et al.

The ninth AI City Challenge continues to advance real-world applications of computer vision and AI in transportation, industrial automation, and public safety. The 2025 edition featured four tracks and saw a 17% increase in participation, with 245 teams from 15 countries registered on the evaluation server. Public release of challenge datasets led to over 30,000 downloads to date. Track 1 focused on multi-class 3D multi-camera tracking, involving people, humanoids, autonomous mobile robots, and forklifts, using detailed calibration and 3D bounding box annotations. Track 2 tackled video question answering in traffic safety, with multi-camera incident understanding enriched by 3D gaze labels. Track 3 addressed fine-grained spatial reasoning in dynamic warehouse environments, requiring AI systems to interpret RGB-D inputs and answer spatial questions that combine perception, geometry, and language. Both Track 1 and Track 3 datasets were generated in NVIDIA Omniverse. Track 4 emphasized efficient road object detection from fisheye cameras, supporting lightweight, real-time deployment on edge devices. The evaluation framework enforced submission limits and used a partially held-out test set to ensure fair benchmarking. Final rankings were revealed after the competition concluded, fostering reproducibility and mitigating overfitting. Several teams achieved top-tier results, setting new benchmarks in multiple tasks.

Simon Dold, Malte Helmert, Jakob Nordström et al.

We introduce lower-bound certificates for classical planning tasks, which can be used to prove the unsolvability of a task or the optimality of a plan in a way that can be verified by an independent third party. We describe a general framework for generating lower-bound certificates based on pseudo-Boolean constraints, which is agnostic to the planning algorithm used. As a case study, we show how to modify the $A^{*}$ algorithm to produce proofs of optimality with modest overhead, using pattern database heuristics and $h^\textit{max}$ as concrete examples. The same proof logging approach works for any heuristic whose inferences can be efficiently expressed as reasoning over pseudo-Boolean constraints.

Israel Puerta-Merino, Carlos Núñez-Molina, Pablo Mesejo et al.

Recent advances in Large Language Models (LLMs) are fostering their integration into several reasoning-related fields, including Automated Planning (AP). However, their integration into Hierarchical Planning (HP), a subfield of AP that leverages hierarchical knowledge to enhance planning performance, remains largely unexplored. In this preliminary work, we propose a roadmap to address this gap and harness the potential of LLMs for HP. To this end, we present a taxonomy of integration methods, exploring how LLMs can be utilized within the HP life cycle. Additionally, we provide a benchmark with a standardized dataset for evaluating the performance of future LLM-based HP approaches, and present initial results for a state-of-the-art HP planner and LLM planner. As expected, the latter exhibits limited performance (3\% correct plans, and none with a correct hierarchical decomposition) but serves as a valuable baseline for future approaches.

S. Meerow

Abstract Cities are expanding green infrastructure and presenting it as a panacea for social and environmental challenges, but the reality is more complex and inherently political. We need to advance our understanding of these politics, which I divide into the politics of green infrastructure performance and planning. I use New York City as a case study to begin unpacking these politics of planning. New York City's green infrastructure program focuses on water quality, but aims to provide other sustainability benefits. How are potential benefits prioritized, factored into planning, and what are the implications of these decisions? I examine these questions by combining spatial analyses, survey, and interview data. I survey local stakeholders about the relative importance of six benefits of green infrastructure (managing stormwater, reducing social vulnerability, increasing access to green space, improving air quality, mitigating the urban heat island effect, and increasing landscape connectivity). Second, I use spatial multi-criteria analysis to identify priority neighborhoods for green infrastructure based on those criteria. I examine tradeoffs and synergies between criteria and compare modeled priorities with existing green infrastructure locations. Interviews with key decision-makers provide a deeper understanding of planning processes. Results illustrate why spatial planning represents a critical challenge for green infrastructure planning.

Denise Capasso da Silva, David A. King, Shea V. Lemar

Cities can enhance their sustainability planning by prioritizing accessibility as a performance metric for transportation planning. In this context, accessibility measures the ease of reaching opportunities and captures more characteristics of sustainable cities than the more conventionally used mobility metrics, focusing on the overall ability to move and generally recommending faster speeds to overcome distance. However, how cities can prioritize accessibility in planning is understudied. This research presents a case of Tempe, Arizona, putting accessibility into practice through a 20-min lens. Using a 20-min threshold for all modes, the city aims to promote travel for daily activities that is less reliant on private autos. The analysis presented here documents the challenges that planners face when planning for accessibility. The challenges range from technical points to decisions that need to be made about the quality of the built environment. The analysis also shows that Tempe, which is a classically suburban city of wide roads and single-family homes that was built around the automobile, is highly accessible by a 20-min metric by bicycling, walking and transit. These results suggest that planners focus on street network improvements that prioritize accessibility as part of a sustainability strategy.

Hang Ni, Yuzhi Wang, Hao Liu

Urban regeneration presents significant challenges within the context of urbanization, requiring adaptive approaches to tackle evolving needs. Leveraging advancements in large language models (LLMs), we propose Cyclical Urban Planning (CUP), a new paradigm that continuously generates, evaluates, and refines urban plans in a closed-loop. Specifically, our multi-agent LLM-based framework consists of three key components: (1) Planning, where LLM agents generate and refine urban plans based on contextual data; (2) Living, where agents simulate the behaviors and interactions of residents, modeling life in the urban environment; and (3) Judging, which involves evaluating plan effectiveness and providing iterative feedback for improvement. The cyclical process enables a dynamic and responsive planning approach. Experiments on the real-world dataset demonstrate the effectiveness of our framework as a continuous and adaptive planning process.

Elliot Gestrin, Marco Kuhlmann, Jendrik Seipp

Classical planners are powerful systems, but modeling tasks in input formats such as PDDL is tedious and error-prone. In contrast, planning with Large Language Models (LLMs) allows for almost any input text, but offers no guarantees on plan quality or even soundness. In an attempt to merge the best of these two approaches, some work has begun to use LLMs to automate parts of the PDDL creation process. However, these methods still require various degrees of expert input or domain-specific adaptations. We present NL2Plan, the first fully automatic system for generating complete PDDL tasks from minimal natural language descriptions. NL2Plan uses an LLM to incrementally extract the necessary information from the short text input before creating a complete PDDL description of both the domain and the problem which is finally solved by a classical planner. We evaluate NL2Plan on seven planning domains, five of which are novel and thus not in the LLM training data, and find that NL2Plan outperforms directly generating the files with an LLM+validator combination. As such, NL2Plan is a powerful tool for assistive PDDL modeling and a step towards solving natural language planning task with interpretability and guarantees.

Kevin Wang, Junbo Li, Neel P. Bhatt et al.

Recent advancements in Large Language Models (LLMs) have showcased their ability to perform complex reasoning tasks, but their effectiveness in planning remains underexplored. In this study, we evaluate the planning capabilities of OpenAI's o1 models across a variety of benchmark tasks, focusing on three key aspects: feasibility, optimality, and generalizability. Through empirical evaluations on constraint-heavy tasks (e.g., $\textit{Barman}$, $\textit{Tyreworld}$) and spatially complex environments (e.g., $\textit{Termes}$, $\textit{Floortile}$), we highlight o1-preview's strengths in self-evaluation and constraint-following, while also identifying bottlenecks in decision-making and memory management, particularly in tasks requiring robust spatial reasoning. Our results reveal that o1-preview outperforms GPT-4 in adhering to task constraints and managing state transitions in structured environments. However, the model often generates suboptimal solutions with redundant actions and struggles to generalize effectively in spatially complex tasks. This pilot study provides foundational insights into the planning limitations of LLMs, offering key directions for future research on improving memory management, decision-making, and generalization in LLM-based planning. Code available at https://github.com/VITA-Group/o1-planning.

Yu. P. Voronov

The article explores the process of creating a large cooperative housing complex in a district of New York. It highlights the unique circumstances that made the cooperative City project possible in the United States. The article also examines the efforts of European countries to foster urban residents’ involvement in urban development. It provides examples of innovative solutions implemented by the population of various European cities. The article delves into the Russian experience of utilizing public initiatives to enhance urban development and improve the quality of life. It emphasizes that the promotion of cooperation in urban life is supported by both governmental authorities and individual citizens and local communities. The article highlights a new phase in this process — changes in urban planning, with the transition from general to master plans becoming part of federal policy.

علی اکبر سالاری پور, آرمان حمیدی, عالیه فریدی فشتمی et al.

امروزه بخش بزرگی از رفتارهای محیط زیستی شهروندان تحت تأثیر ارتباط و میزان دلبستگی آن‍ها با شهر است. به‌طوری‌که دلبستگی به مکان و شهر مؤلفه‌ای حیاتی در پرورش شهروندان حامی محیط‌زیست محسوب می‍گردد. پژوهش حاضر از نوع توصیفی- کمی می‍باشد. جهت جمع‍آوری اطلاعات باهدف سنجش تأثیر میزان دلبستگی به شهر و همچنین خصوصیات فردی شهروندان، بر بروز رفتارهای حامی محیط زیستی در میان شهروندان، تعداد 402 پرسشنامه از طریق ساکنین شهر رشت تکمیل شده است. داده‍های به‌دست‌آمده از پرسشنامه‍ها به‌صورت کمی وارد نرم‌افزار SPSS شده و سپس با استفاده از نرم‌افزار Smart PLS3 به مدل‌سازی و تجزیه‌وتحلیل یافته‍ها پرداخته شده است. نتایج پژوهش نشان داد که برخلاف انتظار رابطه تأثیرگذاری میان شاخص‍های دلبستگی فردی به مکان، محل تولد، مدت سکونت و میزان تحصیلات بر رفتارهای حامی محیط زیستی شهروندان، وجود ندارد؛ اما از سوی دیگر نتایج مدل‌سازی نمایانگر این موضوع بود که در گام نخست رفتارهای حامی محیط زیستی شهروندان بیش‍ترین ارتباط و اثرپذیری را از دلبستگی اجتماعی شهروندان با مکان یا شهر دارند. سپس در گام بعدی تعدادی از ویژگی‌های فردی شهروندان ازجمله سن و وضعیت تأهل نیز بر رفتارهای حامی محیط زیستی شهروندان تأثیرگذار می‌باشد و رابطه مستقیمی میان آن‌ها برقرار است.

Halil Burak Akdeniz, Sinan Levend, Şaban İnam

Global climate change, one of the most important problems of today, and human activities have negative effects on the sustainability of natural resources. It has become necessary to establish planning and management mechanisms for the sustainable use of drinking water basins within the protection-use balance. Beyşehir Basin, Türkiye was chosen as the study area. The aim of this study is to present a new model approach for the use of Analytical Hierarchy Process and Geographic Information Systems, based on the unique topographic, hydrological, and environmental characteristics of the basin, in the determination of the drinking water basin protection zones. Thirteen criteria, which affect the reaching of the pollutants to the water surface and reflect the topographic, hydrological, and environmental characteristics of the basin, were used in the determination of the protection zones. As a result of the study, it was determined that 2.83% of the basin is in the absolute protection zone, 44.97% in the short-range protection zone, 35.93% in the medium-range protection zone and 16.26% in the long-range protection zone. In the last stage, the conservation areas determined by the current legal regulations for the basin and the protection zones determined by the model approach were spatially and areally compared. According to the results of the comparison, it was determined with the proposed protection model that the absolute protection, the short-range protection, and the medium-range protection zones increased areally, and the spatial distributions of these protection zones were shaped according to the structure of the basin.

M. Nieuwenhuijsen

A. Bonakdar, I. Audirac

Through a critical reading of city branding theories and practices, this article identifies a nexus between city branding and urban planning related to master planning and placemaking. It brings attention to the challenges facing city branding including asymmetrical political processes, social inequity, tokenism, and gentrification. While city branding’s recent turn to participatory approaches unveils a rampant adoption of planning processes repackaged as master planning the place brand strategy, this stream of research and practice remains isolated and disconnected from urban planning theory and ethics. Recognizing this link, the article suggests, could help city branding address its challenges and develop its theoretical basis with more socially responsible and normative underpinnings.

C. Nilon, Myla F. J. Aronson, S. Cilliers et al.

Raj Korpan

This paper presents VBMO, the Voting-Based Multi-Objective path planning algorithm, that generates optimal single-objective plans, evaluates each of them with respect to the other objectives, and selects one with a voting mechanism. VBMO does not use hand-tuned weights, consider the multiple objectives at every step of search, or use an evolutionary algorithm. Instead, it considers how a plan that is optimal in one objective may perform well with respect to others. VBMO incorporates three voting mechanisms: range, Borda, and combined approval. Extensive evaluation in diverse and complex environments demonstrates the algorithm's ability to efficiently produce plans that satisfy multiple objectives.

Nguyen Hong Thuy

In preschool activities, children's need for cooperation is extremely strong. In today's era, the knowledge economy along with the scientific and technological revolution and international integration are developing rapidly. That requires children to know how to cooperate, share, listen, resolve conflicts and coordinate with each other. Therefore, cooperation skills are an indispensable factor to help children succeed. The article studies the reality of cooperative skills education management in Thai Nguyen city preschools in terms of planning, organizing and directing implementation, thereby proposing solutions such as: Organize training for teachers on cooperative skills education methods for 5-6 year old children in preschool; Mobilize forces inside and outside the school to participate in educating cooperation skills for 5-6 year old children in preschool; Mobilizing forces inside and outside of the school; Development of facilities to serve cooperative skills education activities for 5-6 year old children in preschool.

Lestari Juniawati Ani, Edi Nugroho Lukito, Insap Santosa Paulus

The implementation of the smart city concept in Indonesia has become a necessity and is no longer an option, but a necessity. Indeed, the complexity of the problems facing the government is very high and requires smart solutions. As a form of supporting local governments in Indonesia in developing smart city master plans, the Ministry of Communication and Informatics of the Republic of Indonesia in 2017 launched the "Movement Towards 100 Smart Cities" program. During the implementation of the program, the Ministry of Communication and Informatics has compiled a guidebook that was used by local governments. However, the guidebook is considered unable to accommodate all the needs of local governments to develop smart city master plans. This research aims to identify the synchronization between RPJMD and smart city master plans in Indonesia by using literature analysis and document analysis methods that aim to facilitate local governments in preparing smart city master plans. The analysis results show a link between the RPJMD document and the smart city master plan based on the mapping carried out on the RPJMD document which has previously been prepared as a regional development planning document.

Chao Chen, Daqing Zhang, Xiaojuan Ma et al.