Local Planning Research Articles

Local Path Planning of Unmanned Surface Vehicles’ Formation Based on Vector Field and Flow Field Traction

Local Path Planning of Unmanned Surface Vehicles’ Formation Based on Vector Field and Flow Field Traction

A real time data-driven dynamic glasius bionic neural network path planning algorithm for polar under-ice feature scanning by “Xinghai 1000” AUV

Using Autonomous Underwater Vehicle (AUV) to survey polar under-ice feature is crucial for studying polar marine environment and global climate change. Compared with seafloor terrain scanning, it faces several challenges, such as uncertain under-ice environment, lack of reliable positioning methods, and stringent constraints on recovery location. Thus, taking “Xinghai 1000” as analysis object, this paper proposes a real time data-driven dynamic glasius bionic neural network path planning algorithm (RDGPP), which consists of an online bi-level path planning module. In global planning module, dynamically hierarchical strategy is used to realize task area layering. On this basis, global coverage path is planned by combining neuron activity value updated which utilize real-time environmental information obtained by FLS sonar with multivariant strategy. Moreover, due to AUV recovery mode limitation, return strategy has been devised in multivariant strategy to ensure AUV automatic return to launch point, thereby reducing energy usage. In local planning module, Flagged bit and GBNN-driven A-star algorithm (FGA) is introduced to minimize deadlock escape time for AUV. Simulation experiments verify RDGPP algorithm advancement in key indicators such as turning times, running time, etc., and effectiveness is verified by “Xinghai 1000” under-ice experiment.

Optimal Trajectory Planning for Wheeled Robots (OTPWR): A Globally and Dynamically Optimal Trajectory Planning Method for Wheeled Mobile Robots

In recent years, with the widespread application of indoor inspection robots, efficient motion planning has become crucial. Addressing the issue of discontinuous and suboptimal robot trajectories resulting from the independent nature of global and local planning, we propose a novel optimal path-planning method for wheeled mobile robots. This method leverages differential flatness to reduce dimensionality and decouple the problem, achieving globally optimal, collision-free paths in a two-dimensional flat output space through diagonal search and polynomial trajectory optimization. Comparative experiments in a simulated environment demonstrate that the proposed improved path search algorithm reduces search time by 46.6% and decreases the number of visited nodes by 43.1% compared to the original algorithm. This method not only ensures the optimal path and efficient planning but also ensures that the robot’s motion trajectory satisfies the dynamic constraints, verifying the effectiveness of the proposed optimal path planning algorithm for wheeled mobile robots.

Exploring attitudes and perceptions regarding a self-driving demonstration

Purpose Public opinion regarding autonomous vehicles (AV) heavily influences how quickly the technology will be implemented and adopted in the future. However, there is a dearth of empirical evaluations in the literature about riders' perceptions toward service characteristics of shared autonomous vehicles (SAVs) and their attitudes toward developing AVs. Therefore, the aim of this study is to identify attitudes, views and concerns regarding a self-driving demonstration called RAPID (Rideshare, Automation and Payment Integration Demonstration) incorporated with an already-existing on-demand ridesharing service in Arlington, Texas. Design/methodology/approach This study developed a ridership survey to collect data from those who had experience using the service at least once during the service deployment. As the RAPID service operations were restricted to the areas near the University of Texas at Arlington (UTA) campus, sample population of this study is highly skewed with all participants being affiliated with UTA. Findings Findings indicated that survey respondents positively perceived the service features, including comfort, boarding the vehicles, ride safety, booking and scheduling, vehicle speed, climate control and service cost. To complement the survey results, the authors conducted interviews and a focus group study and used conventional content analysis to gain more in-depth insights about RAPID service operations from the perspectives of users and non-users in the post-implementation period. The results indicated that geographic accessibility, service availability and trip cost were the primary concerns of the focus group participants. Originality/value This study offers critical insights into individual attitudes and perceptions toward shared AVs (SAVs) that will assist local, state and federal transit authorities and planners in formulating policies and transportation strategies to target SAV ridership when the service is more widespread.

Local Climate Change Adaptation under the Lenses of Public Health: A Case Study from Porto, Portugal

Introduction: Climate change is a pressing public health issue. Urban populations, especially in coastal areas, are highly vulnerable. As climate change progresses, local adaptation becomes increasingly important. We present a case study about the inclusion of public health concerns in local climate change adaptation in Porto (Portugal). Methods: We analysed two local adaptation plans using qualitative content analysis and conducted semi-structured interviews with a purposeful sample of 6 key stakeholders with different profiles. We did a qualitative content analysis of the respective transcripts. Results: Porto is undergoing health-relevant consequences of climate change, which are expected to worsen further in the future. Porto’s geographical and demographic characteristics and urban environment make its population highly vulnerable to climate change-related health risks. Public health is recognized as a central element in local adaptation efforts. Drivers for integrating health concerns include growing climate change awareness, a sense of urgency, social capital, institutional networks, access to resources, and political commitment. Nevertheless, challenges like data limitations, resource constraints, climate knowledge gaps, communication issues, and political cycles hinder both local adaptation and the integration of health considerations. Discussion/Conclusion: In Porto, health seems both a powerful mobilizing issue and a central topic concerning local adaptation. However, the complex and long-term nature of climate change and the associated uncertainty hinder adaptation efforts. High-quality data about both the local climate and population health are thus essential. The transversal nature of risk is recognized and multi-sectorial approaches, public participation, mainstreaming, and policy integration are necessary to prevent imbalances. Local adaptation efforts, including health-related efforts, are shaped by the international (belonging to the European Union), national, and local contexts. Successful local adaptation and inclusion of health aspects require mainstreaming and policy integration across different areas and involvement of multiple stakeholders, including the population, in order to maximize resources and avoid undesired trade-offs.

Mapping and Localization of Autonomous Mobile Robots in Simulated Indoor Environments

Autonomously making a map, localizing within it, and planning with it are fundamental problems in mobile robotics. Every autonomous mobile robot system must include a solution to all three problems. These three problems are interconnected, with simultaneous localization and mapping (SLAM) being a well-known issue. However, there is indeed a growing and developing realization in the research field that path planning how a robot goes about mapping and finding an environment (and then operating in the environment such as starting to the destination point) can avoid degenerate conditions and greatly reduce SLAM complexity. In this paper, the implementation of an autonomous mobile robot system for indoor environments using open-source ROS packages and a combination of cartography algorithm and adaptive Monte Carlo localization (AMCL) algorithms has been implemented. The system addresses the challenge of developing three components such as mapping, localization, and path planning systems for indoor autonomous mobile robots. The mapping module creates a global map using the cartography ROS package and SLAM algorithm. The localization module estimates the robot's pose using the AMCL approach. The planning module generates collision-free trajectories and control commands using the moving base ROS package. The experimental results demonstrate the effectiveness of this approach and its valuable contribution to the robotics field. The cartography algorithm mapping algorithm generates accurate and reliable maps, while the localization algorithm successfully determines the robot's position with good performance. Additionally, the path planning algorithm effectively avoids both static and dynamic obstacles, ensuring smooth navigation in the environment.

Evaluating local climate policy: Municipal action plans through the lens of resilience and environmental justice

In the US, local governments are increasingly crucial in driving climate action. Drawing upon previous scholarly work, this study assesses nine local climate action plans in the state of Michigan. It introduces a comprehensive framework integrating climate resilience and environmental justice (EJ) indicators to evaluate plan content. Despite recognizing global climate concerns, qualitative content analysis shows that plans lack localized analyses and actions, hampering planning efforts as a result of insufficient data, minimal coordination, limited funds, and finite policy options. Key aspects like equitable resource distribution, environmental burdens, and community engagement are often overlooked. Without addressing these limitations, local governments lack the tools to effectively implement justice-oriented climate policies.

Environmental Literacy among Primary Level Students in Bangladesh: A Comparative Study between Urban and Rural Areas

Environmental literacy (EL) is considered a key skill for primary students who will be responsible for solving the environmental problems that affect Bangladesh and other countries. This study explored the EL of primary students in urban and rural areas of Bangladesh, using the five EL components: knowledge, skill, awareness, attitude, ability to evaluate, and participation, declared in 1977 Tbilisi conference on environment education. A qualitative approach was used, and data were collected through surveys, focus group discussions, and student interviews. Thematic and descriptive analysis was performed on the findings. The results indicated that urban students had higher EL scores than rural students in all components. The study also suggested the implications of the findings for curriculum developers, policymakers, environmental NGOs, local project planners, and future research. Teacher’s World: Journal of Education and Res arch, 50(1): 21-42

Smallholder Farmers' Perception of Climate Change and Multiple Adoption of Adaptation Strategies in Côte d'Ivoire

Climate change is a global concern today due to its impacts on all aspects of life. This study analyzes the perceptions of smallholder cocoa farmers on climate change and their subsequent adaptation strategies in the Zanzan district of northeastern Côte d’Ivoire. Data collected from 322 randomly selected smallholder farmers were analyzed using a multivariate Probit. The results indicate that farmers perceive climate change through changes in climatic parameters such as rainfall, temperature and winds. To adapt to these changes, farmers adopt several strategies that are either complementary or substitutable from their point of view. The most widespread adaptation strategies in the study area are fallow, staking, shifting the sowing period and crop rotation. This multiple adoption is linked to several factors including the gender of the producer, his level of education, the possession of cereal crops, the presence of soil restoration programs in the locality. The study recommends strengthening meteorological and climate information systems and disseminating knowledge in order to increase awareness of climate change and integrate adaptation strategies into local management plans.

Flood risk awareness and transportation mode choice in communities with varying flooding frequencies: The cases of Bozkurt, Kastamonu, Turkey and Malanday, Marikina, Philippines

This study investigates the post-flood transportation mode choices (TMC) of communities exposed to floods of varying frequencies, focusing on Bozkurt, Turkey, recently afflicted by a major flood, and Malanday, Philippines, which endures an average of 10 floods annually. The study considers 17 factors affecting TMC, including age, occupation, income, housing type, flood experience, education level, changes in travel time, primary transportation mode, duration of residence, gender, marital status, relocation status, personal losses, disruption of daily activities, time to return to routine, satisfaction with road maintenance, and satisfaction with flood measures. Data were collected through surveys and analysed using regression analysis.The findings indicate that personal and cultural characteristics, and flood frequency, have limited effects on TMC. The most impactful factors on post-flood TMC are changes in travel time (42.11 %), personal losses (23.75 %), and satisfaction with road maintenance (11.30 %). The study demonstrates that flood risk awareness is directly related to education level and flood experience. In Malanday, where 84 % of the population are university or high school graduates, floods are regarded as routine events. In contrast, in Bozkurt, where only 37 % have similar education levels, the community experienced panic under flood conditions, adversely affecting decision-making processes.The research provides insights into how communities exposed to floods adjust their TMC, offering essential information for mitigating flood risks and increasing flood awareness. Moreover, the findings deliver suggestive information for local governments and planners in developing more effective flood management and transportation planning strategies.

Multi-level surfel map construction for accurate localization in intelligent vehicles

Abstract The role of mapping in achieving accurate localization in intelligent vehicles is crucial. Accurate maps enable intelligent vehicles to attain accuracy in localization and path planning, ultimately enhancing the safety and overall driving experience. However, the interference of dynamic objects poses a challenge to map updates and subsequent localization. To address this issue, this study proposes a novel algorithm for constructing multi-level semantic surfel maps, along with a corresponding hierarchical localization method. The proposed method divides the map into three levels: semantic level, surfel level, and trajectory level. During the map construction phase, we utilize semantic segmentation technology to accurately distinguish between static and dynamic environments, filter out dynamic point clouds, and focus solely on modeling static scenes. This effectively eliminates the interference of dynamic objects on map updates, ensuring the construction of a precise and reliable static environment model. In the subsequent hierarchical localization phase, a node-level localization method is introduced, which achieves coarse localization by matching perception information with the map.The results of experiments conducted in various scenarios indicate an average absolute trajectory error of 4cm between the transformation matrices of each node in the map. Our algorithm achieves a 92% success rate in node-level localization and an average pose-level localization error of 8.2cm, demonstrating the feasibility and robustness of the proposed algorithm.

Small watersheds are the best control and management unit for improving soil conservation services in karst areas

Climate factors and changes in landscape patterns are often recognized as the primary drivers of soil conservation services. The influence mechanism of climate factors and landscape patterns on soil conservation service is scale-dependent and spatial heterogeneous. However, it is not clear whether small watershed scale is more conducive to soil erosion control than large scale such as county scale and township scale. For the purpose of creating land use development plans that take local conditions into account, it is crucial to clarify the effects of climate and landscape pattern factors on soil conservation change. Wujiang River basin (WRB), a typical karst basin located in the catchment of the largest first-level tributary on the upper Yangtze River in China, was used as the study area in this research. Soil conservation services provided by water erosion control (SPC) in WRB from 2005 to 2020 were evaluated using the RUSLE model based on the modified rock exposure rate. By using stepwise regression model and multi-scale geographically weighted regression model (MGWR), the spatial heterogeneity of the influence of different driving factors on soil conservation service was comprehensively studied at the scale of district, township and small watershed. The results show that the SPC fluctuates obviously, but the trend is not significant. Climate factor is the dominant factor affecting SPC. With the change of scale from large to small, the adjusted R2 of the regression model gradually increases, especially the factors related to landscape pattern, and more driving factors can be revealed more comprehensively and effectively. Therefore, the small watershed scale is the best control unit to improve the SPC when formulating the regional management landscape plan. The findings of this research also have benchmark significance for other ecological fragile areas, and can provide more comprehensive suggestions for local ecosystem management and landscape planning.

A local collision-free motion planning strategy for hyper-redundant manipulators based on dynamic safety envelopes

A local collision-free motion planning strategy for hyper-redundant manipulators based on dynamic safety envelopes

Comparative study of CTA/CTV and MRTA for preoperative simulation of microvascular decompression in neurovascular compression syndromes.

Neurovascular compression syndrome (NVCS), characterized by cranial nerve compression due to adjacent blood vessels at the root entry zone, frequently presents as trigeminal neuralgia (TN), hemifacial spasm (HFS), or glossopharyngeal neuralgia (GN). Despite its prevalence in NVCS assessment, Magnetic Resonance Tomographic Angiography (MRTA)'s limited sensitivity to small vessels and veins poses challenges. This study aims to refine vessel localization and surgical planning for NVCS patients using a novel 3D multimodal fusion imaging (MFI) technique incorporating computed tomography angiography and venography (CTA/CTV). A retrospective analysis was conducted on 76 patients who underwent MVD surgery and were diagnosed with single-site primary TN, HFS, or GN. Imaging was obtained from MRTA and CTA/CTV sequences, followed by image processing and 3D-MFI using FastSurfer and 3DSlicer. The CTA/CTV-3D-MFI showed higher sensitivity than MRTA-3D-MFI in predicting responsible vessels (98.6% vs. 94.6%) and NVC severity (98.6% vs. 90.8%). Kappa coefficients revealed strong agreement with MRTA-3D-MFI (0.855 for vessels, 0.835 for NVC severity) and excellent agreement with CTA/CTV-3D-MFI (0.951 for vessels, 0.952 for NVC). Resident neurosurgeons significantly preferred CTA/CTV-3D-MFI due to its better correlation with surgical reality, clearer depiction of surgical anatomy, and optimized visualization of approaches (p < 0.001). Implementing CTA/CTV-3D-MFI significantly enhanced diagnostic accuracy and surgical planning for NVCS, outperforming MRTA-3D-MFI in identifying responsible vessels and assessing NVC severity. This innovative imaging modality can potentially improve outcomes by guiding safer and more targeted surgeries, particularly in cases where MRTA may not adequately visualize crucial neurovascular structures.

The Networked Data Lab: lessons from four years of analytical collaboration on common problems in health on social care

ObjectiveThe Networked Data Lab (NDL) is a UK-wide network of analytical teams embedded in the health and care system. Each year, we support five local partners to acquire and link new health and social care datasets on a different topic. The NDL provides insights from this linked data to help UK policymakers improve health and care, leveraging public, patient, and stakeholder engagement to prioritise topics of shared local interest. Approach Now in its fourth year, the NDL has commissioned a Learning Study (LS) to evaluate progress towards its aims. This employs a theory-based approach to test and assess key assumptions about programme impact through a Theory of Change. For the study, semi-structured interviews with analysts and stakeholders at the five NDL sites were conducted to identify factors influencing the programme’s impact. ResultsDrawing on interim LS findings, we will describe the types of impact the programme has achieved, and some of the key barriers and enablers to analytical collaboration across geographic and organisational boundaries. Themes include senior sponsorship; stakeholder input into problem definition; information governance and tools and skills. Themes will be illustrated with case studies drawn from the different NDL topic areas, including children and young people’s mental health and unpaid carers. Conclusions and ImplicationsThe Networked Data Lab shows that data linkages can provide unique insights that local service planners can act on, but highlights a complex set of conditions that need to be met to enable impactful analytics using real-world health and care data.

Local preferences for the adoption and modification of climate policy instruments under a radical left government: unveiling the impact and legacy of Barcelona in Common

ABSTRACT This study aims to uncover how shifting towards a radical left ideology affects a city’s climate policy. Using semi-structured interviews with stakeholders and an analysis of local action plans and laws enacted in Barcelona between 1984 and May 2023, we find that the period of local government led by the radical left, embodied by Barcelona in Common, saw a significant increase in the adoption of climate-related policy instruments, with a preference for ‘soft’ over ‘hard’ measures. Likewise, this administration more actively raised the ambition of pre-existing policy instruments, though evidence suggests that this trend is driven by other, non-ideological factors. The results further show that ‘hard’ policy instruments especially were more prone to changes, both in terms of raising or reducing policy ambition. Overall, these findings enhance our understanding of local climate policymaking and how it is affected by partisan politics.

ENCODING RESTRICTIONS AS AN OBJECT OF CADASTRAL SYSTEMS IN UKRAINE

Transparency and uniformity of registration of land use restrictions are interdependent and complementary aspects critical for ensuring effective management of land resources. The interaction of transparency and uniformity creates conditions for accessibility, comprehensibility, and better perception of data. The study analyses land use restrictions identification during their registration in the State Land and Urban Planning Cadastres to determine the uniformity of the registration. The analysis mainly focuses on the main attributes of the land use restrictions, such as code and name. Based on the research results, we established that the classification of land use restrictions for registration in various state cadastral systems, particularly State Land and Urban Planning Cadastres, is mostly not identical and requires coordination. There is an unjustified duplication of some land use restrictions and ambiguity in assigning them to specific categories. A particular problem is coding land use restrictions as registration objects without considering the hierarchical spatial organisation of restriction zones and the principle of logical construction. There is also an inexplicable duplication of some categories of land use restrictions, as in: the protected archaeological territory (codes 06.06.3 and 16.04), the historic and cultural protected territory (codes 06.06.5 and 16.03), the historical and cultural reserve (codes 06.06.4 and 16.02), the historical area of ​​the inhabited place (codes 06.06.2 and 16.07). In addition, there are minor differences in the names. It is worth noting that correctly identifying land use restrictions is essential for developing local urban planning documents due to the requirements of integrating information from various sources and updating them regularly. Transparency and uniformity of registration of land use restrictions in the State Land Cadastre and Urban Planning Cadastre are the main factors contributing to the effective management of land resources, ensuring legal certainty, attracting investments, and protecting the rights of land owners. They also contribute to reducing corruption, increasing trust in public authorities, and protecting the environment. Keywords: restrictions, code, state land cadastre, urban planning cadastre.

Climate change adaptation mainstreaming through strategic environmental assessments. An in-depth analysis of environmental indicators from spatial plans in Friuli Venezia Giulia Region (Italy)

Climate change adaptation, CCA henceforth, is nowadays a shared concern, deeply investigated and advocated by international research and political organisations. However, both CCA implementation and its monitoring and evaluation (M&E) are challenges yet to be properly addressed. From a spatial planning perspective, local plans are the land-use-oriented tools with the highest potential to enhance CCA operativity. Strategic Environmental Assessment (SEA) is also acknowledged to be a key instrument to integrate climate change concerns and hence, to monitor and evaluate climate change (CC) risks and CCA efforts. This study addresses two hypotheses, i.e., i) indicators included in SEAs' spatial plans may be used at the service of CCA M&E, ii) the full extent of indicators can be captured by multi-level planning analyses. To this aim, this study provides an in-depth analysis, through a multi-step systematic categorization, of the indicators used within the SEA of regional and municipal plans in the Friuli Venezia Giulia Region (Italy). This study brings novelty in the SEA research field by bridging the climate risk theoretical principles to the methodological approach for analysing SEAs' indicators, which are classified within the risk function frame. Key insights come from the metrics, the indicators' explicitness for CCA, and the indicators' extent into the climate risk function. Finally, the paper paves the way for further research of CC- and CCA-related indicators in both spatial planning and other public sectors to support CCA mainstreaming through SEAs.

SEEG4D: a tool for 4D visualization of stereoelectroencephalography data.

Epilepsy is a prevalent and serious neurological condition which impacts millions of people worldwide. Stereoelectroencephalography (sEEG) is used in cases of drug resistant epilepsy to aid in surgical resection planning due to its high spatial resolution and ability to visualize seizure onset zones. For accurate localization of the seizure focus, sEEG studies combine pre-implantation magnetic resonance imaging, post-implant computed tomography to visualize electrodes, and temporally recorded sEEG electrophysiological data. Many tools exist to assist in merging multimodal spatial information; however, few allow for an integrated spatiotemporal view of the electrical activity. In the current work, we present SEEG4D, an automated tool to merge spatial and temporal data into a complete, four-dimensional virtual reality (VR) object with temporal electrophysiology that enables the simultaneous viewing of anatomy and seizure activity for seizure localization and presurgical planning. We developed an automated, containerized pipeline to segment tissues and electrode contacts. Contacts are aligned with electrical activity and then animated based on relative power. SEEG4D generates models which can be loaded into VR platforms for viewing and planning with the surgical team. Automated contact segmentation locations are within 1 mm of trained raters and models generated show signal propagation along electrodes. Critically, spatial-temporal information communicated through our models in a VR space have potential to enhance sEEG pre-surgical planning.

Improving the Quality of Climate Change Adaptation Planning Through State Mandate: The Case of California

Problem, research strategy, and findings As communities everywhere experience accelerating climate change impacts, local governments must proactively plan and implement adaptation or resilience strategies. A significant challenge is effectively scaling up these efforts in diverse communities. In 2015, the State of California passed Senate Bill 379 (SB379), requiring climate change adaptation and resilience strategies in local plans, making it the first U.S. state to broadly mandate such requirements locally. Our study measured the effects of SB379 on the quality of local plans that address climate change adaptation or resilience and assessed which types of plans jurisdictions selected to meet the requirements. Using a longitudinal study, we analyzed plan quality before and after SB379 took effect using criteria developed for earlier studies of voluntary climate adaptation plans. We found that California plans have significantly improved when assessed against theoretical criteria, and most jurisdictions have chosen their local hazard mitigation plans to meet the requirements. The flexible and cooperative design of the mandate and its loose enforcement suggest local jurisdictions are willing to address climate change, even when challenged with more stringent requirements if incentives align. As a natural policy experiment, California’s experience offers a unique opportunity to examine the effects of a state planning mandate and the choices local jurisdictions make to comply. Takeaway for practice Cooperative mandates that require local governments to address climate change adaptation and resilience in their plans but offer flexibility in how they do so may improve the quality of plans. Practitioners should seek to leverage flexibility in such mandates to the advantage of their local communities.