Sustainability

Research

23 pages, 3508 KiB

Open AccessArticle

Multi-Objective Design of UAS Air Route Network Based on a Hierarchical Location–Allocation Model

by Zhaoxuan Liu, Lei Nie, Guoqiang Xu, Yanhua Li and Xiangmin Guan

Sustainability 2023, 15(23), 16521; https://doi.org/10.3390/su152316521 - 3 Dec 2023

Viewed by 738

This research concentrates on the Unmanned Aircraft System (UAS) demand sites’ hierarchical location–allocation problem in air route network design. With demand sites (locations where UAS operations are requested) organized and allocated according to the spatial hierarchy of UAS traffic flows, the hierarchical structure [...] Read more.

This research concentrates on the Unmanned Aircraft System (UAS) demand sites’ hierarchical location–allocation problem in air route network design. With demand sites (locations where UAS operations are requested) organized and allocated according to the spatial hierarchy of UAS traffic flows, the hierarchical structure guarantees resource conservation and economies of scale through traffic consolidation. Therefore, in this paper, the UAS route network with a three-level hierarchy is developed under a multi-objective decision-making framework, where concerns about UAS transportation efficiency from the user side and construction efficiency from the supplier side are both simultaneously considered. Specifically, a bi-level Hybrid Simulated Annealing Genetic Algorithm (HSAGA) with global and local search combined is proposed to determine the optimal number, location, and allocation of hierarchical sites. Moreover, using the information of site closeness and UAS demand distribution, two problem-specific local search operators are designed to explore elite neighborhood regions instead of all the search space. A case study based on the simulated UAS travel demand data of the Beijing area in China was conducted to demonstrate the effectiveness of the proposed method, and the impact of critical parameter settings on the network layout was explored as well. Findings from this study will offer new insights for UAS traffic management in the future. Full article

(This article belongs to the Special Issue Sustainable Development of Airspace Systems)

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19 pages, 7929 KiB

Open AccessArticle

Air Traffic Sector Network: Motif Identification and Resilience Evaluation Based on Subgraphs

by Zongbei Shi, Honghai Zhang, Yike Li and Jinlun Zhou

Sustainability 2023, 15(18), 13423; https://doi.org/10.3390/su151813423 - 7 Sep 2023

Viewed by 689

Abstract

Air traffic control systems play a critical role in ensuring the sustainable and resilient flow of air traffic. The air traffic sector serves as a fundamental topological unit and is responsible for overseeing and maintaining the system’s sustainable operation. Examining the structural characteristics [...] Read more.

Air traffic control systems play a critical role in ensuring the sustainable and resilient flow of air traffic. The air traffic sector serves as a fundamental topological unit and is responsible for overseeing and maintaining the system’s sustainable operation. Examining the structural characteristics of the air traffic sector network is a useful approach to gaining an intuitive understanding of the system’s sustainability and resilience. In this paper, an air traffic sector network (ATSN) was established in mainland China using the complex network theory, and its motif characteristics were analyzed from a microscopic perspective. Additionally, subgraph resilience was defined in order to describe the network topology by analyzing changes in subgraph motif concentration and subgraph residual concentration. Our empirical findings indicated that motifs exhibit high connectivity, while anti-motifs are found in subgraph structures with low connectivity. The motif concentration of subgraphs can efficiently reflect the distribution of heterogeneous subgraph structures within a network. During the process of resilience evaluation, the subgraph motif concentration remains relatively stable but is sensitive to the transition state of the network from disturbance to recovery. The resilience of the system at the macroscopic scale is aligned with the resilience of each heterogeneous subgraph structure to some extent. Topological indicators have a more significant impact on the resilience of the ATSN than air traffic flow characteristics. This study has the outcome of uncovering the preference for connection among nodes and the rationality of sector structure delineation in ATSNs. Additionally, this research addresses the fundamental mechanism behind the network disturbance recovery process, and identifies the connection between network macro- and microstructure in the resilience process. Full article

(This article belongs to the Special Issue Sustainable Development of Airspace Systems)

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22 pages, 6766 KiB

Open AccessArticle

Capacity Assessment and Analysis of Vertiports Based on Simulation

by Honghai Zhang, Jingyu Li, Yuhan Fei, Cheng Deng and Jia Yi

Sustainability 2023, 15(18), 13377; https://doi.org/10.3390/su151813377 - 6 Sep 2023

Viewed by 950

Abstract

City air traffic as a new transportation mode has gradually attracted attention in recent years which will bring endless vitality to future urban development. An objective and accurate assessment of the vertiport capacity for UAVs (Unmanned Aerial Vehicles) is the basis for implementing [...] Read more.

City air traffic as a new transportation mode has gradually attracted attention in recent years which will bring endless vitality to future urban development. An objective and accurate assessment of the vertiport capacity for UAVs (Unmanned Aerial Vehicles) is the basis for implementing air traffic flow management for UAVs, which is also a prerequisite for improving the efficiency of urban airspace resources used. Firstly, new topology designs are proposed and named as connected and compact topology designs based on the existing central airport topology design. Subsequently, three modes of operation are summarized for vertiports with multiple TLOF pads: independent operation, dependent operation, and segregated operation. In the next place, the overall traffic flow of the vertiport model is established based on AnyLogic while analyzing the logic of UAV operation in three modes as mentioned above. Eventually, according to the simulation results, the vertiport operation capacity, the UAVs delay, and surface area utilization under different operation modes and topology designs are analyzed. The simulation result shows that the overall average delay time of UAVs for independent operation mode is about 100 s less than that of segregated operation and it also shows that the utilization rate of independent operation mode under central design is as high as 54.42% while the utilization rate of TLOF pads of other design is less than 50%, and its vertiport capacity is the largest, so the independent operational mode under central configuration is the optimal combination. Full article

(This article belongs to the Special Issue Sustainable Development of Airspace Systems)

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20 pages, 2898 KiB

Open AccessArticle

Research on Logistics Path Optimization for a Two-Stage Collaborative Delivery System Using Vehicles and UAVs

by Qiqian Zhang, Xiao Huang, Honghai Zhang and Chunyun He

Sustainability 2023, 15(17), 13235; https://doi.org/10.3390/su151713235 - 4 Sep 2023

Viewed by 852

Abstract

A two-stage planning model for the carrier–vehicle problem with drone (CVP-D) is established in this paper, with the objective of minimizing the delivery time of the drone and the distance traveled by the truck while considering the impact of payload on the drone [...] Read more.

A two-stage planning model for the carrier–vehicle problem with drone (CVP-D) is established in this paper, with the objective of minimizing the delivery time of the drone and the distance traveled by the truck while considering the impact of payload on the drone flight distance. Firstly, based on the customer coordinates, an improved K-Means ++ clustering algorithm is designed to plan the vehicle stopping points, and the vehicle departs from the warehouse to traverse all stopping points in order. Based on the vehicle stopping points, a multi-chromosome genetic algorithm is designed to optimize the vehicle driving path. Then, the drone route is optimized without considering the no-fly zone. Finally, the real data of Jiangsu Province are introduced as a case study to calculate the cost and total time required before and after improvement. The results showed an approximate savings of 16% in time and 19% in cost. Full article

(This article belongs to the Special Issue Sustainable Development of Airspace Systems)

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20 pages, 10160 KiB

Open AccessArticle

Data-Driven Insights into Population Exposure Risks: Towards Sustainable and Safe Urban Airspace Utilization by Unmanned Aerial Systems

by Hongbo He, Xiaohan Liao, Huping Ye, Chenchen Xu and Huanyin Yue

Sustainability 2023, 15(16), 12247; https://doi.org/10.3390/su151612247 - 10 Aug 2023

Viewed by 1082

Abstract

With the rapid increase in unmanned aerial vehicles (UAVs), ensuring the safety of airspace operations and promoting sustainable development of airspace systems have become paramount concerns. However, research dedicated to investigating the population exposure risks of UAV operations in urban areas and their [...] Read more.

With the rapid increase in unmanned aerial vehicles (UAVs), ensuring the safety of airspace operations and promoting sustainable development of airspace systems have become paramount concerns. However, research dedicated to investigating the population exposure risks of UAV operations in urban areas and their spatial pattern is still missing. To address this gap, this study evenly divides the urban space into uniform grids and calculates critical areas for two UAV types within each grid. By integrating geospatial data, including buildings, land use, and population, data-driven risk maps are constructed to assess the spatial distribution patterns and potential population exposure risks of two UAV types and compare them with commonly used census units. The results indicate that the mean time between failures (MTBF) for the selected generic and rotary-type UAVs can be up to 9.04 × 10⁸ h and 1.22 × 10⁸ h, respectively, at acceptable risk levels, considering uncertainties. The spatial pattern of population exposure risk exhibits spatial heterogeneity and multi-scale effects in urban areas, aligning with population distribution. High-risk areas concentrate in regions characterized by high population mobility, such as transport hubs, commercial service areas, residential zones, and business districts. Additionally, the comparation emphasizes the potential bias introduced by using census units in risk assessment, especially in regions with significant urban build-up. This framework enables the evaluation of safety and acceptability across diverse urban land use areas and offers guidance for airspace management in megacities, ensuring the safe integration of UAVs in urban environments. Full article

(This article belongs to the Special Issue Sustainable Development of Airspace Systems)

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17 pages, 10328 KiB

Open AccessArticle

Risk Topics Discovery and Trend Analysis in Air Traffic Control Operations—Air Traffic Control Incident Reports from 2000 to 2022

by Wenquan Liu, Honghai Zhang, Zongbei Shi, Yufei Wang, Jing Chang and Jinpeng Zhang

Sustainability 2023, 15(15), 12065; https://doi.org/10.3390/su151512065 - 7 Aug 2023

Cited by 1 | Viewed by 1285

Abstract

The safety of air traffic control (ATC) operations is an important cornerstone for the sustainable development of the civil aviation industry. In order to clarify the risk factors in the control operation process and to achieve digital representation of the safety risks of [...] Read more.

The safety of air traffic control (ATC) operations is an important cornerstone for the sustainable development of the civil aviation industry. In order to clarify the risk factors in the control operation process and to achieve digital representation of the safety risks of civil aviation control operations, starting from the ATC incident reports, we fully mine the safety risk information and unspoken rules of ATC operations. A risk perception model for air traffic control operations safety based on the Latent Dirichlet Allocation (LDA) topic model and the Semantic Network Based on BERT (BSN) model is suggested. First, 17 risk topics and keywords were found in the incident reports collected using the LDA topic model. These topics included those pertaining to the stage of aircraft operation, human factors in control operation, and the sector or airspace operation status and structure. The findings indicate that while most risk subjects have not changed significantly, they do show an upward tendency. Human factors and operational rules and procedures account for the highest share of all key causes, and they also have a significant impact on how risk topics evolve over time. Finally, the BSN model in the air traffic control field was built based on the keywords of each risk issue in order to highlight any potential correlations between distinct risk topics. The results show that some risk topics have interrelated risk characteristics, and there are regularities of mutual evolution between these risk topics. The relevant research results can better mine air traffic control unsafe information and lay a foundation for accurately perceiving air traffic control operations risks. Full article

(This article belongs to the Special Issue Sustainable Development of Airspace Systems)

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17 pages, 4166 KiB

Open AccessArticle

Research on Public Air Route Network Planning of Urban Low-Altitude Logistics Unmanned Aerial Vehicles

by Honghai Zhang, Tian Tian, Ouge Feng, Shixin Wu and Gang Zhong

Sustainability 2023, 15(15), 12021; https://doi.org/10.3390/su151512021 - 5 Aug 2023

Viewed by 1327

Abstract

As urban populations continue to grow and road traffic congestion worsens, traditional ground logistics has become less efficient. This has led to longer logistics times and increased costs. Therefore, unmanned aerial vehicle (UAV) logistics has become increasingly popular. However, free-planned routes cannot meet [...] Read more.

As urban populations continue to grow and road traffic congestion worsens, traditional ground logistics has become less efficient. This has led to longer logistics times and increased costs. Therefore, unmanned aerial vehicle (UAV) logistics has become increasingly popular. However, free-planned routes cannot meet the safety and efficiency requirements of urban airspace mobility. To address this issue, a public air route network for low-altitude logistics UAVs needs to be established in urban areas. This paper proposes a public route network planning method based on the obstacle-based Voronoi diagram and A* algorithm, as follows: Firstly, construct a city airspace grid model in which the characteristics of the airspace are mapped onto the grid map. Introduce an obstacle clustering algorithm based on DBSCAN to generate representative obstacle points as the Voronoi seed nodes. Utilize the Voronoi diagram to establish the initial route network. Then, conduct an improved path planning by employing the A* algorithm for obstacle avoidance in route edges that pass through obstacles. To ensure the safe operation of drones, set constraints on the route safety interval. This process will generate a low-altitude public air route network for urban areas. After considering the flight costs of logistics UAVs at different altitudes, the height for the route network layout is determined. Finally, the route network evaluation indicators are established. The simulation results demonstrate that compared with the city road network planning method and the central radial network planning method, the total route length is shortened by 7.1% and 9%, respectively, the airspace coverage is increased by 9.8% and 35%, respectively, the average network degree is reduced by 52.6% and 212%, respectively, and the average flight time is reduced by 19.4s and 3.7s, respectively. In addition, by solving the network model using the Dijkstra algorithm, when the energy cost and risk cost weights are 0.6 and 0.4, respectively, and the safety interval is taken as 15 m, the total path cost value of the planned trajectory is minimized. Full article

(This article belongs to the Special Issue Sustainable Development of Airspace Systems)

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16 pages, 2793 KiB

Open AccessArticle

Research on Rapid Congestion Identification Method Based on TSNE-FCM and LightGBM

by Cheng Deng, Qiqian Zhang, Honghai Zhang, Jingyu Li and Changyuan Ning

Sustainability 2023, 15(14), 11322; https://doi.org/10.3390/su151411322 - 20 Jul 2023

Viewed by 668

Abstract

The terminal area is a convergence point for inbound and outbound traffic, and it is characterized by a complex airspace structure and high traffic density. It is an area that frequently experiences flight congestion and ground delays. A system capable of the intelligent, [...] Read more.

The terminal area is a convergence point for inbound and outbound traffic, and it is characterized by a complex airspace structure and high traffic density. It is an area that frequently experiences flight congestion and ground delays. A system capable of the intelligent, reliable, timely, and accurate identification of air traffic congestion for air–ground coupled flight flow constitutes a key technology with respect to unlocking the potential capacity of the terminal area, mitigating traffic congestion, and assisting air-traffic-control-related decision making. Therefore, this article aims to extract and analyze the multi-scale and multi-dimensional evaluation indicators of air–ground coupled flight flow congestion, use the TSNE-FCM algorithm to classify congestion levels, and, based on this work, construct a real-time and fast congestion identification model using the LightGBM algorithm. The case study analyzed China Baiyun Airport (CAN), and the experimental results indicate the following: (1) The congestion level classification achieved using the TSNE-FCM algorithm is superior to that achieved using the FCM algorithm. Furthermore, flight delays predominantly occur in slightly congested and congested states. (2) The congestion identification model based on LightGBM outperforms the XGBoost, RandomForest, and ExtraTree models. The macro-average and micro-average AUC curve areas for the LightGBM model were 0.96 and 0.96, respectively. The LightGBM model demonstrates excellent performance and is suitable for identifying congestion levels in practical engineering applications. Full article

(This article belongs to the Special Issue Sustainable Development of Airspace Systems)

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