Hasil untuk "City planning"

E. Gómez‐Baggethun, D. Barton

K. An

Abstract The electrification of city bus systems is an increasing trend, with many cities replacing their diesel buses with battery electric buses (BEBs). Due to limited battery capacities, and to random battery discharge rates—which are affected by weather, road and traffic conditions—BEBs often need daytime charging to support their operation for a whole day. The deployment of charging infrastructures, as well as the number of stand-by buses available, has a significant effect on the operational efficiency of electric bus systems. In this work, a stochastic integer program has been developed to jointly optimise charging station locations and bus fleet size under random bus charging demand, considering time-of-use electricity tariffs. The stochastic program is first approximated by its sample average and is solved by a customised Lagrangian relaxation approach. The applicability of the model and solution algorithm is demonstrated by applications to a series of hypothetical grid networks and to a real-world Melbourne City bus network. Managerial insights are also presented.

Eduardo Miranda

This paper explains the Visual Milestone Planning (VMP) method using an agile vocabulary to facilitate its adoption by agile practitioners as a front end for a hybrid development process. VMP is a visual and collaborative planning approach which promotes a shared understanding of the work approach and commitment through the direct manipulation by team members of the reified planning constructs involved in the development of the plan. Once the product backlog has been established and relevant milestones identified, a novel construct called the milestone planning matrix is used to document the allocation of product backlog items to milestones. The milestones due dates are later determined by grouping sticky notes representing the work to be performed into time-boxes called work packages and accommodating them on a resource and time scaled scheduling canvas very much as it would be done in a Tetris game.

Felicia H. M. Liu, Karen P. Y. Lai, Bertrand Seah et al.

Abstract This paper critically assesses the complex interplay between urban transitions of digitisation and sustainability. Building on a mixed-method research design, we unpack the challenges of decarbonising digital infrastructure while attending to urban sustainability goals in a land- and water-scarce country facing significant physical climate risks. We identify transferrable lessons on the economic, technological, and environmental synergies and trade-offs behind data centre development and argue that stewarding the global data centre sector towards sustainability requires an ecosystem-wide approach. We identify implementation gaps across five key dimensions: technological innovation, policy and regulation, finance, infrastructure, and people. We find that the progress and uptake of sustainability initiatives are often impeded by risk-averse DC operators, who are most concerned with real and perceived risks of downtime. We conclude with recommendations for data centre stakeholders to align the low-carbon transition of the data centre sector with broader objectives of climate resilience, smart city development, and sustainable finance.

Jing Wu, Yawei Wang, Gaizhong Chen et al.

As a famous coastal tourist city in China, Sanya is facing the dual challenges of solid waste management and resource utilization while tourism is booming. To realize efficient solid waste management and innovative circular economy models, Sanya actively explores and practices the construction path of a “zero-waste city”. In this study, Pearson correlation analysis and material flow analysis were used to analyze the factors influencing the amount of municipal solid waste (MSW) generated in Sanya and the changes in the effectiveness of MSW treatment in Sanya before the construction of the “zero-waste city” (2018) and five years later (2023). The results of the study show that the construction of a “zero-waste city” in Sanya, through the implementation of a series of policy measures, including the strengthening of strategic planning and leadership, the upgrading of capacity building, and the promotion of nationwide action participation, has effectively promoted the efficient synergistic treatment of MSW, thereby realizing both environmental benefits and economic benefits.

Jie Deng, Wenhao Chai, Junsheng Huang et al.

City scene generation has gained significant attention in autonomous driving, smart city development, and traffic simulation. It helps enhance infrastructure planning and monitoring solutions. Existing methods have employed a two-stage process involving city layout generation, typically using Variational Autoencoders (VAEs), Generative Adversarial Networks (GANs), or Transformers, followed by neural rendering. These techniques often exhibit limited diversity and noticeable artifacts in the rendered city scenes. The rendered scenes lack variety, resembling the training images, resulting in monotonous styles. Additionally, these methods lack planning capabilities, leading to less realistic generated scenes. In this paper, we introduce CityCraft, an innovative framework designed to enhance both the diversity and quality of urban scene generation. Our approach integrates three key stages: initially, a diffusion transformer (DiT) model is deployed to generate diverse and controllable 2D city layouts. Subsequently, a Large Language Model(LLM) is utilized to strategically make land-use plans within these layouts based on user prompts and language guidelines. Based on the generated layout and city plan, we utilize the asset retrieval module and Blender for precise asset placement and scene construction. Furthermore, we contribute two new datasets to the field: 1)CityCraft-OSM dataset including 2D semantic layouts of urban areas, corresponding satellite images, and detailed annotations. 2) CityCraft-Buildings dataset, featuring thousands of diverse, high-quality 3D building assets. CityCraft achieves state-of-the-art performance in generating realistic 3D cities.

Mingbao Chen, Zhibin Xu

Cities are the frontiers of the Sustainable Development Goals (SDGs) adopted in the United Nations 2030 Agenda. Although quantitative methods have been applied to assess cities’ sustainability progress, knowledge gaps exist in the differences between inland and coastal cities’ performance and their internal variations against common standards. Using the Voronoi-based kaleidoscope diagram embedded in two circular plots, the article visualises the overall sustainability progress of China’s inland and coastal cities in economy, society, biosphere and partnership. By measuring overall progress with circular length and individual scores with kaleidoscope area size, triple inland-coastal gaps and trifold intracoastal inequalities were highlighted, as well as city types characterised by economy-society balance and land–sea relation. References for implementing sustainable development transformations for coastal cities were derived, along with the circular-kaleidoscope diagram’s potential for checking the pulse of cities’ performances in further uses and finishing the circle.

Maria S. Frolova

In 2021-2023 In Yekaterinburg, 3 volumes of author's essays were published on the development of the cultural sphere of the capital of the Urals. The release of review texts was initiated by the Department of Culture of the Yekaterinburg Administration. On 864 pages, using archival materials, unique historical and contemporary photographs, the “spirit of the development of the arts” is presented - music, theater and cinema in Volume 1, sculpture, painting and architecture in Volume 2, literature, art education and the educational system in Volume 3. The chosen genre - essays - is original and productive. Texts are a form of summing up, recording successes in the development of the Yekaterinburg/Sverdlovsk sphere of culture. The tercentenary anniversary of Yekaterinburg (the city can be scientifically categorized as a regional or peripheral capital), which took place in 2023, is an occasion for reflection and further planning. Richly illustrated, gift-type books are deep and original from the point of view of analytics of the development of the cultural sphere. The authors were leading academic researchers and employees of the largest cultural institutions of Yekaterinburg - the Sverdlovsk Regional Museum of Local Lore, UrFU named after the first President of Russia B. N. Yeltsin, the Museum of the History of Yekaterinburg, the Sverdlovsk Music School named after P. I. Tchaikovsky. Using the general scientific critical method, methods of synthesis and analysis, the text of the review provides a brief overview of all three volumes of essays, characterizes the merits of the publication, and provides criticism.

Maroš Krivý

Constantinos Chamzas, Caelan Garrett, Balakumar Sundaralingam et al.

Recent work has shown that complex manipulation skills, such as pushing or pouring, can be learned through state-of-the-art learning based techniques, such as Reinforcement Learning (RL). However, these methods often have high sample-complexity, are susceptible to domain changes, and produce unsafe motions that a robot should not perform. On the other hand, purely geometric model-based planning can produce complex behaviors that satisfy all the geometric constraints of the robot but might not be dynamically feasible for a given environment. In this work, we leverage a geometric model-based planner to build a mixture of path-policies on which a task-specific meta-policy can be learned to complete the task. In our results, we demonstrate that a successful meta-policy can be learned to push a door, while requiring little data and being robust to model uncertainty of the environment. We tested our method on a 7-DOF Franka-Emika Robot pushing a cabinet door in simulation.

Douglas Beck, Joseph Carlson, Zohreh Davoudi et al.

In preparation for the 2023 NSAC Long Range Plan (LRP), members of the Nuclear Science community gathered to discuss the current state of, and plans for further leveraging opportunities in, QIST in NP research at the Quantum Information Science for U.S. Nuclear Physics Long Range Planning workshop, held in Santa Fe, New Mexico on January 31 - February 1, 2023. The workshop included 45 in-person participants and 53 remote attendees. The outcome of the workshop identified strategic plans and requirements for the next 5-10 years to advance quantum sensing and quantum simulations within NP, and to develop a diverse quantum-ready workforce. The plans include resolutions endorsed by the participants to address the compelling scientific opportunities at the intersections of NP and QIST. These endorsements are aligned with similar affirmations by the LRP Computational Nuclear Physics and AI/ML Workshop, the Nuclear Structure, Reactions, and Astrophysics LRP Town Hall, and the Fundamental Symmetries, Neutrons, and Neutrinos LRP Town Hall communities.

Wenyu Han, Congcong Wen, Lazarus Chok et al.

City modeling and generation have attracted an increased interest in various applications, including gaming, urban planning, and autonomous driving. Unlike previous works focused on the generation of single objects or indoor scenes, the huge volumes of spatial data in cities pose a challenge to the generative models. Furthermore, few publicly available 3D real-world city datasets also hinder the development of methods for city generation. In this paper, we first collect over 3,000,000 geo-referenced objects for the city of New York, Zurich, Tokyo, Berlin, Boston and several other large cities. Based on this dataset, we propose AETree, a tree-structured auto-encoder neural network, for city generation. Specifically, we first propose a novel Spatial-Geometric Distance (SGD) metric to measure the similarity between building layouts and then construct a binary tree over the raw geometric data of building based on the SGD metric. Next, we present a tree-structured network whose encoder learns to extract and merge spatial information from bottom-up iteratively. The resulting global representation is reversely decoded for reconstruction or generation. To address the issue of long-dependency as the level of the tree increases, a Long Short-Term Memory (LSTM) Cell is employed as a basic network element of the proposed AETree. Moreover, we introduce a novel metric, Overlapping Area Ratio (OAR), to quantitatively evaluate the generation results. Experiments on the collected dataset demonstrate the effectiveness of the proposed model on 2D and 3D city generation. Furthermore, the latent features learned by AETree can serve downstream urban planning applications.

Mohammadreza Hasanpour

The present study was conducted to identify the future dimensions of smart city planning research. Participants in this study were municipal managers and urban planners with at least 15 years of experience and a master's degree or higher. Individuals were selected by purposive sampling. Sampling was performed with the participation of 10 experts. Data collection tools fell into two groups: 1- review and upstream documents, urban planning documents in the library section, 2- semi-structured interview in the field section where the semi-structured interview with the participants continued until the theoretical saturation stage. Content analysis method was used to analyze the qualitative data. In order to ensure the validity, the interview questions were approved by 3 experienced urban  planning experts and managers, 1 of whom had a master's degree and 2 of whom had a doctorate. In order to measure the reliability, the krippendorf coefficient was used, the overall coefficient of which was 84%. ATLASTI software has been used in the content analysis section. In order to identify future smart city planning research scenarios, SCENARIOWIZARD software has been used.  The results of factor analysis show that out of 176 available indicators (items), 33 basic themes can be identified and 9 categories of constructive themes have been obtained. Finally, 9 scenarios were identified based on the importance of all 9 factors. The results indicate that the main output of the realization of smart cities and e-municipality is to set conditions for providing services in the healthiest way to citizens, eliminating corruption, creating new job opportunities, and service and transformation in the economic and commercial sectors, increasing the effective presence of the private sector and improving the business environment, reducing damage to the environment, smart governance and increasing satisfaction

Anqi Zhou, Anqi Zhou, Younghwan Pan

Introduction: This study investigated the influence of indoor lighting environments on paper reading efficiency and brain fatigue to explore lighting parameters that benefit users during various reading durations.Methods: The study was conducted in the Smart Lighting Lab, where 12 participants were tested under different illuminance levels and correlated color temperatures (CCT) for three distinct reading durations. Reading efficiency during the task tests and objective measures of brain activity by monitoring participants’ electroencephalograms (EEGs) were used as key factors to assess participants’ fatigue levels.Results: By analyzing the subjective and objective results, we found that paper reading efficiency was significantly affected by changes in the lighting environment. Also, based on the results of this study, we propose lighting recommendations for paper reading tasks of different durations. For a 15 min reading task, the lighting condition of 500 lux-6,500 K were the most efficient for reading; for a 30 min reading task, 500 lux-4,000 K lighting environments were found to be the most effective; and 750 lux-6,500 K was the best lighting environment for a 60 min reading duration.Discussion: These suggestions can serve as a reference for designing indoor lighting environment. In addition, they provide guidance to researchers and reviewers conducting similar studies.

Administrative boundaries are ubiquitous. A vital technology of power within the modern nation-state’s mode of bureaucratic governance, they carve up and abstract land and water alike into conceptual totalities that, in their simplification, render them legible to centralised administrative bodies. This is a foundational tool of state planning, the impact of which permeates all aspects of socio-economic life. These boundaries are not passive; they do not simply define a geographical area. Rather, they are selective in what they encompass and, as a result, what they include and exclude and what is rendered visible and, hence, valuable. This article describes an example of the real-world impact of this selectivity through discussion of the experiences of a community-led charity (Ardagh Community Trust) and the community group that founded it (Friends of Horfield Common). In their work to demonstrate that an administrative-boundary-spanning public green space (Horfield Common) and leisure facility (the Ardagh) was a vital community resource and hub, this article focuses on the work of Friends of Horfield Common/Ardagh Community Trust to ensure that their local community, one dissected by multiple administrative boundaries, was recognised and acknowledged when, in 2008, Bristol City Council in the UK proposed the sale of multiple publicly owned green spaces through their Parks and Green Space Strategy. Administrative boundaries played a key role in defining and determining which sites in the city were proposed for sale and in structuring the accompanying public consultation process, thereby determining which communities were recognised as communities in relation to this policy and, hence, which communities’ opinions were actively sought and heard. This article concludes by highlighting some of the potential political and economic costs attendant on reifying administrative boundaries rather than lived communities in both planning and consultation processes.

Thomas Chabal, Robin Strudel, Etienne Arlaud et al.

This paper addresses the problem of copying an unknown assembly of primitives with known shape and appearance using information extracted from a single photograph by an off-the-shelf procedure for object detection and pose estimation. The proposed algorithm uses a simple combination of physical stability constraints, convex optimization and Monte Carlo tree search to plan assemblies as sequences of pick-and-place operations represented by STRIPS operators. It is efficient and, most importantly, robust to the errors in object detection and pose estimation unavoidable in any real robotic system. The proposed approach is demonstrated with thorough experiments on a UR5 manipulator.

Dominik Drexler, Jendrik Seipp, Hector Geffner

Recently, sketches have been introduced as a general language for representing the subgoal structure of instances drawn from the same domain. Sketches are collections of rules of the form C -> E over a given set of features where C expresses Boolean conditions and E expresses qualitative changes. Each sketch rule defines a subproblem: going from a state that satisfies C to a state that achieves the change expressed by E or a goal state. Sketches can encode simple goal serializations, general policies, or decompositions of bounded width that can be solved greedily, in polynomial time, by the SIW_R variant of the SIW algorithm. Previous work has shown the computational value of sketches over benchmark domains that, while tractable, are challenging for domain-independent planners. In this work, we address the problem of learning sketches automatically given a planning domain, some instances of the target class of problems, and the desired bound on the sketch width. We present a logical formulation of the problem, an implementation using the ASP solver Clingo, and experimental results. The sketch learner and the SIW_R planner yield a domain-independent planner that learns and exploits domain structure in a crisp and explicit form.

Justin Kottinger, Shaull Almagor, Morteza Lahijanian

In the Multi-Agent Path Finding (MAPF) problem, the goal is to find non-colliding paths for agents in an environment, such that each agent reaches its goal from its initial location. In safety-critical applications, a human supervisor may want to verify that the plan is indeed collision-free. To this end, a recent work introduces a notion of explainability for MAPF based on a visualization of the plan as a short sequence of images representing time segments, where in each time segment the trajectories of the agents are disjoint. Then, the explainable MAPF problem asks for a set of non-colliding paths that admits a short-enough explanation. Explainable MAPF adds a new difficulty to MAPF, in that it is NP-hard with respect to the size of the environment, and not just the number of agents. Thus, traditional MAPF algorithms are not equipped to directly handle explainable-MAPF. In this work, we adapt Conflict Based Search (CBS), a well-studied algorithm for MAPF, to handle explainable MAPF. We show how to add explainability constraints on top of the standard CBS tree and its underlying A* search. We examine the usefulness of this approach and, in particular, the tradeoff between planning time and explainability.

Ali Yousefi, Saeedeh Ketabi, Iraj Abedi

There is a huge problem and time-consuming computation to optimize the IMRT treatment plan. Extracting the optimized plan from the predicted 3D3 so-called optimizing the KBP is also involved in this challenge. Some algorithms and methods have been presented for clustering and down-sampling the voxels to make the problem smaller, in recent years. In the current research, a novel down-sampling method is presented for optimizing the knowledge-based planning more efficiently. The concept of SVSIDB and corresponding down-sampling algorithm are proposed under title of SMP-2. The algorithm has been run on the data of 30 patients from the Open-KBP dataset. For each patient, there are 19 sets of dose prediction data in this dataset. Therefore, a total of 570 KBP-optimizing problems have been solved by applying the QuadLin model in the CVX framework. Resulted plans are evaluated and compared regarding two main fields which are the quality of the treatment plan as well as the computation efficiency. Solve time is the evaluation criteria for the latter field i.e. computation efficiency. The results of the current study indicated a remarkable improvement in the computation efficiency. Accordingly, the proposed method, SMP-2, reduced the average solving time by 46% in comparison to the full-data QuadLin model. The results also show an up to 53% reduction in solve time along with up to 22% improvement in clinical criteria compared to the previous research. Evaluation of the research results indicated that the SVSIDB has not only reduced the solve time but also improved the quality of the treatment plans. This is a remarkable achievement of the proposed model compared to the previous research and confirmed the significant effectiveness of the SVSIDB method which has the potential of even more improvement of the computation efficiency.

Ruizhi Liao, Liping Chen

In response to challenges posed by urbanization, David Bollier from the University of Southern California raised a new idea for city planning: a comprehensive network and applications of information technologies. IBM later echoed the idea and initiated its Smart Planet vision in 2008. After that, the smart city concept was quickly adopted by major cities throughout the world, and it has gradually evolved into a strategic choice by ambitious cities. This paper looks into the smart city trend by reviewing how the concept of smart city was proposed and what the essence of a smart city is. More specifically, the driving forces of the smart city development in China are investigated, and the key differences of smart cities between China and other countries are summarized. Finally, four big challenges to build future smart cities are discussed.