Three-dimensional Urban Environment Research Articles

Rapid data collection and processing in dense urban edge computing networks with drone assistance

In the edge computing network systems for the Internet of Things (IoT), there is growing attention to utilizing drones for collecting data and maintaining the freshness of data processing. This study focuses on analyzing the problems related to trajectory planning and task scheduling in a single drone-assisted edge computing network within a dense, three-dimensional urban environment. We first design an edge computing network architecture and establish an air-to-ground channel model between the drone and ground mobile devices to address the blockage caused by buildings in urban environments. Subsequently, to provide effective edge computing services, we structure the problem as a Partially Observable Markov Decision Process (POMDP) and introduce an optimization framework based on reinforcement learning. This improves data timeliness and reduces energy consumption.

Non-metric distance judgements are influenced by image projection geometry and field of view.

Despite its mathematical simplicity and ubiquity in imaging technology, there has long been doubt about the ability of linear perspective to best represent human visual space, especially at wide-angle fields of view under natural viewing conditions. We investigated whether changes to image geometry had an impact on participants' performance, specifically in terms of non-metric distance estimates. Our multidisciplinary research team developed a new open-source image database to study distance perception in images by systematically manipulating target distance, field of view, and image projection using non-linear natural perspective projections. The database consists of 12 outdoor scenes of a virtual three-dimensional urban environment in which a target ball is presented at increasing distance, visualised using both linear perspective and natural perspective images, rendered, respectively, with three different fields of view: 100°, 120°, and 140° horizontally. In the first experiment (N = 52), we tested the effects of linear versus natural perspective on non-metric distance judgements. In the second experiment (N = 195), we investigated the influence of contextual and previous familiarity with linear perspective, and individual differences in spatial skills on distance estimations. The results of both experiments showed that distance estimation accuracy improved in natural compared with linear perspective images, particularly at wide-angle fields of view. Moreover, undertaking a training session with only natural perspective images led to more accurate distance judgements overall. We argue that the efficacy of natural perspective may stem from its resemblance to the way objects appear under natural viewing conditions, and that this can provide insights into the phenomenological structure of visual space.

Limited Effect of Ground Floor Fogging on Mosquito Distribution in High-Rise Condominia

Fogging with insecticides is one of the main control measures for adult mosquito populations employed in countries that are affected by dengue. In many such countries, urban communities are increasingly characterised by high-density residence in high-rise condominia. Although fogging is typically applied at the ground level, its efficacy in three-dimensional urban environments is poorly understood. Here, we investigated the effect of fogging on vector mosquito distribution and abundance in high-rise condominia by conducting a before-after fogging survey. We showed that although mosquitoes were significantly concentrated at the lower levels in high-rise condominia, they were found throughout the three-dimensional environments. Fogging did not significantly alter this distribution or abundance pattern across any floor level. Thus, any fogging effect was short-lived as mosquito populations recovered within a few days before the subsequent scheduled treatment. In addition, increasing fogging frequency within practicable limits did not prolong the intended control effect. As urban mosquitoes are increasingly insusceptible to fogging due to insecticide resistance and vertical avoidance, this study demonstrates the need to implement other mosquito control strategies for high-rise condominia to manage mosquito populations.

Impact of Different Combinations of Green Infrastructure Elements on Traffic-Related Pollutant Concentrations in Urban Areas

Urban air quality is a major problem for human health and green infrastructure (GI) is one of the potential mitigation measures used. However, the optimum GI design is still unclear. The purpose of this study is to provide some recommendation that could help in the design of the GI (mainly, the selection of locations and characteristics of trees and hedgerows). Aerodynamic and deposition effects of each vegetation element of different GI scenarios are investigated. Computational fluid dynamics (CFD) simulations of a wide set of GI scenarios in an idealized three-dimensional urban environment are performed. In conclusion, it was found that trees in the middle of the avenue (median strip) reduce street ventilation, and traffic-related pollutant concentrations increase, in particular for streets parallel to the wind. Trees in the sidewalks act as a barrier for pollutants emitted outside, specifically for a 45° wind direction. Regarding hedgerows, the most important effect on air quality is deposition and the effects of green walls and green roofs are limited to their proximity to the building surfaces.

Enhanced Potential Field-Based Collision Avoidance in Cluttered Three-Dimensional Urban Environments

With the various applications of unmanned aerial vehicles (UAVs), the number of UAVs will increase in limited airspace, leading to an increased risk collision. To reduce such potential risk, this work proposes a collision avoidance strategy for UAVs using an enhanced potential field (EPF) approach in cluttered three-dimensional urban environments. Using the EPF formulated in a two-dimensional environment, the avoidance maneuvers for both horizontal and vertical planes are generated by introducing rotation matrices, and these maneuvers are combined by applying a weighting factor. The numerical simulations with various meaningful scenarios are conducted to validate the performance of the proposed approach. To mimic practical situations, UAV dynamics and sensor limitations were considered. The simulation results show that the proposed approach provides an efficient, reliable, and collision-free path without local minima and unreachable goal issues.

Trajectory planning for unmanned aerial vehicles in complicated urban environments: A control network approach

Trajectory planning is crucial for Unmanned Aerial Vehicles (UAVs) applications. It is still a challenge to plan UAV trajectories in large-scale complicated three-dimensional urban environments, mainly due to the complexities associated with handling a tremendous number of obstacles. To relieve this difficulty, this study proposes a two-stage control network approach. The first stage is an offline planning stage, aiming at constructing a discrete control network in the working environment achieving collision avoidance and meanwhile considering UAV kinetic properties. The second stage is an online planning stage, where a feasible corridor is generated based on the shortest path in the control network, and the obtained route is smoothed by a three-dimensional Dubins curve algorithm; then, a time-optimal trajectory generation algorithm is applied to trace the designed spatial path. Numerical studies based on a virtual city as well as a large-scale real-world urban area are conducted. The results show that the proposed approach is able to identify reasonable UAV trajectories within negligible computational time.

LSwarm: Efficient Collision Avoidance for Large Swarms With Coverage Constraints in Complex Urban Scenes

In this letter, we address the problem of collision avoidance for a swarm of UAVs used for continuous surveillance of an urban environment. Our method, LSwarm, efficiently avoids collisions with static obstacles, dynamic obstacles and other agents in three-dimensional urban environments while considering coverage constraints. LSwarm calculates collision avoiding velocities that maximize the conformity of an agent to an optimal path given by a global coverage strategy and ensure sufficient resolution of the coverage data collected by each agent. Our algorithm is formulated based on optimal reciprocal collision avoidance and is scalable with respect to the size of the swarm. We evaluate the coverage performance of LSwarm in realistic simulations of a swarm of quadrotors in complex urban models. In practice, our approach can compute collision avoiding velocities for a swarm composed of tens to hundreds of agents in a few milliseconds on dense urban scenes consisting of tens of buildings.

An urban scale inverse modelling for retrieving unknown elevated emissions with building-resolving simulations

This study illustrates an atmospheric source reconstruction methodology for identification of an unknown continuous point release in the geometrically complex urban environments. The methodology is based on the renormalization inversion theory coupled with a building resolving Computational Fluid Dynamics (CFD) modelling approach which estimates the release height along with the projected location on the ground surface and the intensity of an unknown continuous point source in an urban area. An estimation of the release height in a three-dimensional urban environment is relatively more difficult from both technical and computational point of view. Thus, a salient feature of the methodology is to address the problem of vertical structure (i.e. height of a source) in atmospheric source reconstruction in three-dimensional space of an urban region. The inversion methodology presents a way to utilize a CFD model fluidyn-PANACHE in source reconstruction in the urban regions. The described methodology is evaluated with 20 trials of the Mock Urban Field Setting Test (MUST) field experiment in various atmospheric stability conditions varying from neutral to stable and very stable conditions. The retrieved source parameters in all the 20 trials are estimated close to their true source. The source height is retrieved within a factor of two and four in 55% and 75% of the MUST trials, respectively. The averaged location error for all 20 trials is obtained 14.54 m with a minimum of 3.58 m and maximum of 34.55 m. The averaged estimated release rate for all trials is overpredicted within a factor of 1.48 of the true source intensity and in 85% of the trials, it is retrieved within in factor of two. In source reconstruction with non-zero measurements, it was observed that the use of all concentration measurements instead of only non-zero essentially makes only the small differences in quality of the source reconstruction and gives a little additional information for better constraining the source parameters. A posteriori uncertainty analysis in the retrieved source parameters is also performed by adding a controlled noise in the concentration measurements and the source reconstruction results were also compared with an earlier study based on the stochastic Bayesian approach for identical 14 MUST trials. The study is useful for emergency regulators to detect an unknown accidental or deliberated continuous point releases in urban regions.

Fast Marching Square Method for UAVs Mission Planning with consideration of Dubins Model Constraints

In this work we present an approach for mission planning carried out by Unmanned Aerial Vehicles (UAVs) in a three-dimensional urban environment. The approach is based on the Fast Marching Square (FM2) algorithm. The FM2 algorithm is used as the planner, which generates the optimal-time path from an initial point to a final point, avoiding static obstacles in a three-dimensional building environment. The Dubins airplane model is used to check if the path resulting from the FM2 is feasible, considering constraints in flight such as turning rate, climb rate and velocity. All these constraints are considered for a fixed-wing aircraft. Thanks to this approach, the trajectory generated by the FM2 will be perfectly feasible for an UAV, always considering its constraints and the static obstacles of the environment. Two examples of application will be shown to demonstrate the good performance of the approach, introducing different altitude constraints.

An [formula omitted] loopshaping approach for bio-inspired reflexive visual navigation in three-dimensional urban environments

Safe autonomous navigation of aerial microsystems in unknown, cluttered environments is contingent on developing accurate localization estimates within the power and bandwidth constraints imposed by the microsystem. The insect visuomotor system combines a lightweight, spatially distributed sensor array (compound eyes) with high bandwidth-capable processing algorithms for efficient information extraction that enables autonomous navigation in complex, obstacle laden environments. In this paper, a novel control theoretic framework is introduced that combines the H∞ loop shaping controller synthesis approach with spatial decompositions of instantaneous patterns of optic flow modeled using analogs of wide field motion sensitive interneurons of the insect visuomotor system. Local proximity and velocity estimates are obtained by the decomposition of spherical optic flow patterns that are based on parameterization of typical three-dimensional urban environments. The motion-state estimates are combined with an H∞ controller to synthesize closed loop systems that provide theoretically justified robustness guarantees in the presence of large uncertainties in the local environment structure while mitigating measurement noise and gusts. The insect-inspired visual navigation technique is used to demonstrate safe obstacle avoidance and terrain following behavior in simulation on an autonomous rotary wing microsystem in an urban-like environment subjected to gusts. The current study presents a strong theoretical contribution that demonstrates the suitability of coupling insect-like vision sensing and processing mechanism with the H∞ loop shaping controller, which precludes explicit extraction of the detailed environment depth map, in achieving safe reflexive navigation in unstructured three-dimensional environments. The computational efficiency and simplicity of the current approach offer a promising alternative to satisfying the payload, power and bandwidth constraints imposed by aerial microsystems.

Autonomous Navigation in Three-Dimensional Urban Environments Using Wide-Field Integration of Optic Flow

In this paper, a control theoretic framework is introduced to analyze an information extraction approach from patterns of optic flow based on analogs to wide-field motion-sensitive interneurons in the insect visuomotor system. An algebraic model of optic flow is developed, based on a parameterization of three-dimensional urban environments. It is shown that estimates of proximity and speed, relative to these environments, can be extracted using weighted summations of the instantaneous patterns of optic flow. Small perturbation techniques are then applied to link weighting patterns to outputs, which are applied as feedback to facilitate stability augmentation and perform local obstacle avoidance and terrain following. Additive noise and environment uncertainties are incorporated into an offline procedure for determination of optimal weighting functions. Stability is proven via local asymptotic analysis and the resulting approach demonstrated in simulation using a micro helicopter in a three-dimensional urbanlike environment.