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埋入式传感、图像处理技术和机器学习方法在路面监测与分析中应用的最新研究进展

Engineering 2021年第6期 309-334页

作者：侯越李秋晗张晨陆国阳叶周景陈逸涵汪林兵曹丹丹 Beijing Key Laboratory of Traffic Engineering Beijing University of Technology National Center for Materials Service Safety University of Science and Technology Beijing School of Transportation Southeast University Department of Civil and Environmental Engineering The Hong Kong Polytechnic University Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport Beijing Jiaotong University Department of Civil and Environmental Engineering Virginia Tech

在现代交通系统中,道路作为车辆和行人使用频率最高的民用基础设施之一,其服役状况和使用寿命直接影响通行体验和效率。因此,在路面发生不可逆损伤之前进行路面健康监测和及时养护,对于保障公共交通服务质量以及通行安全至关重要。通过... 详细信息

在现代交通系统中,道路作为车辆和行人使用频率最高的民用基础设施之一,其服役状况和使用寿命直接影响通行体验和效率。因此,在路面发生不可逆损伤之前进行路面健康监测和及时养护,对于保障公共交通服务质量以及通行安全至关重要。通过路面结构动力响应监测和路面状况评估可有效表征路面损伤状况。埋入式传感器、图像处理和机器学习是目前常用的三种路面结构动力响应监测技术和分析方法。本文综述了近年来上述三种技术在路面工程中的应用现状,并阐述了这些技术在未来路面工程监测与分析中的发展方向。

关键词：路面监测与分析最新的研究进展埋入式传感器图像处理技术机器学习方法

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Overview of AI and Communication for 6G Network: Fundamentals, Challenges, and Future Research Opportunities

arXiv

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arXiv 2024年

作者： Cui, Qimei You, Xiaohu Ni, Wei Nan, Guoshun Zhang, Xuefei Zhang, Jianhua Lyu, Xinchen Ai, Ming Tao, Xiaofeng Feng, Zhiyong Zhang, Ping Wu, Qingqing Tao, Meixia Huang, Yongming Huang, Chongwen Liu, Guangyi Peng, Chenghui Pan, Zhiwen Sun, Tao Niyato, Dusit Chen, Tao Khan, Muhammad Khurram Jamalipour, Abbas Guizani, Mohsen Yuen, Chau National Engineering Research Center of Mobile Network Technologies Beijing University of Posts and Telecommunications Beijing100876 China Department of Broadband Communication Peng Cheng Laboratory Shenzhen518055 China National Mobile Communications Research Laboratory Southeast University Nanjing210096 China Fudan University Shanghai200433 China School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China CICT Mobile Communication Technology Co. Ltd. Beijing100020 China Department of Electronic Engineering Shanghai Jiao Tong University Shanghai200240 China Shanghai Jiao Tong University Shanghai200240 China College of Information Science and Electronic Engineering Zhejiang University Hangzhou310058 China China Mobile Research Institute Beijing100053 China Huawei Technologies Shanghai201206 China College of Computing and Data Science Nanyang Technological University Singapore117583 Singapore VTT Technical Research Centre of Finland Ltd. EspooFI-02044 VTT Finland Center of Excellence in Information Assurance King Saud University Riyadh11362 Saudi Arabia School of Electrical and Information Engineering University of Sydney NSW2006 Australia Abu Dhabi United Arab Emirates School of Electrical and Electronics Engineering Nanyang Technological University Singapore639798 Singapore

With the growing demand for seamless connectivity and intelligent communication, the integration of artificial intelligence (AI) and sixth-generation (6G) communication networks has emerged as a transformative paradigm. By embedding AI capabilities across various network layers, this integration enables optimized resource allocation, improved efficiency, and enhanced system robust performance, particularly in intricate and dynamic environments. This paper presents a comprehensive overview of AI and communication for 6G networks, with a focus on emphasizing their foundational principles, inherent challenges, and future research opportunities. We first review the integration of AI and communications in the context of 6G, exploring the driving factors behind incorporating AI into wireless communications, as well as the vision for the convergence of AI and 6G. The discourse then transitions to a detailed exposition of the envisioned integration of AI within 6G networks, delineated across three progressive developmental stages. The first stage, AI for Network, focuses on employing AI to augment network performance, optimize efficiency, and enhance user service experiences. The second stage, Network for AI, highlights the role of the network in facilitating and buttressing AI operations and presents key enabling technologies, such as digital twins for AI and semantic communication. The final stage, AI as a Service, it is anticipated that future 6G networks will innately provide AI functions as services, supporting application scenarios like immersive communication and intelligent industrial robots. Specifically, we have defined the quality of AI service, which refers to a framework for measuring AI services within the network. We further summarize the standardization process of AI for wireless networks, highlighting key milestones and ongoing efforts. In addition, we conduct an in-depth analysis of the critical challenges faced by the integration of AI and communications

关键词： Resource allocation

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Adaptive Handover Decision Inspired By Biological Mechanism in Vehicle Ad-hoc Networks

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Computers, Materials & Continua 2019年第9期61卷 1117-1128页

作者： Xuting Duan Jingyi Wei Daxin Tian Jianshan Zhou Haiying Xia Xin Li Kunxian Zheng Beijing Advanced Innovation Center for Big Data and Brain Computing Beijing100191China Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems&SafetyControl Beijing100191China School of Transportation Science and Engineering Beihang UniversityBeijing100191China Department of Engineering and Design University of SussexBrightonBN19RHUK Research Institute of Highway Ministry Transport Beijing100088China Department of Computer Science and Technology Tsinghua UniversityHaidian DistrictBeijing100088China

In vehicle ad-hoc networks(VANETs),the proliferation of wireless communication will give rise to the heterogeneous access environment where network selection becomes *** by the self-adaptive paradigm of cellular attractors,this paper regards an individual communication as a cell,so that we can apply the revised attractor selection model to induce each connected *** at improving the Quality of Service(QoS),we presented the bio-inspired handover decision-making *** addition,we employ the Technique for Order Preference by Similarity to an Ideal Solution(TOPSIS)for any vehicle to choose an access *** paper proposes a novel framework where the bio-inspired mechanism is combined with *** a dynamic and random mobility environment,our method achieves the coordination of performance of heterogeneous networks by guaranteeing the efficient utilization and fair distribution of network resources in a global *** experimental results confirm that the proposed method performs better when compared with conventional schemes.

关键词： Revised attraction selection model TOPSIS VANETs QoS

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Max-min energy balance in wireless-powered hierarchical fog-cloud computing networks

Max-min energy balance in wireless-powered hierarchical fog-...

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作者： Liu, Jingxian Xiong, Ke Ng, Derrick Wing Kwan Fan, Pingyi Zhong, Zhangdui Letaief, Khaled Ben School of Computer and Information Technology Beijing Jiaotong University Beijing100044 China Beijing Key Laboratory of Traffic Data Analysis and Mining Beijing Jiaotong University Beijing100044 China School of Electrical Engineering and Telecommunications UNSW Sydney SydneyNSW2052 Australia Department of Electronic Engineering Tsinghua University Beijing100084 China Beijing National Research Center for Information Science and Technology Tsinghua University Beijing100084 China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China Beijing Engineering Research Center of High-Speed Railway Broadband Mobile Communications Beijing Jiaotong University Beijing100044 China Hong Kong Peng Cheng Laboratory Shenzhen518055 China

This paper investigates the wireless-powered hierarchical fog-cloud computing networks, where multiple energy-constrained users harvest energy from a hybrid access point (HAP) firstly and then use their harvested energy to offload their computation tasks to fog/cloud servers via the HAP or compute their tasks locally. To pursue multi-user fairness, an optimization problem is formulated to maximize the minimal energy balance among all users by jointly optimizing time assignments, computation central processing unit (CPU) frequencies, and the computing mode selection. Since the problem is mixed-integer combinatorial non-convex, which is intractable, a generalized Benders decomposition (GBD)-based method is proposed, which guarantees the globally optimal solution. To release the high computational complexity of the proposed GBD-based method, a penalized successive convex approximation (P-SCA)-based algorithm is designed as an alternative to obtain a suboptimal solution with low computational complexity. Numerical results show that among different optimizable factors in the system, computing mode selection is the dominant one on affecting the system performance. Moreover, for each user, local computing is a better choice, if it is with relatively poor channel gain and small local computing delay. Otherwise, fog/cloud computing may be a better choice. Additionally, for the users with relatively high channel gains, if their local computing delays are less than those selecting fog computing, cloud computing should be a better choice. © 2002-2012 IEEE.

关键词： Energy transfer

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Using Downward-Looking Lidar to Detect and Track Traffic

Using Downward-Looking Lidar to Detect and Track Traffic

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Annual Conference of Industrial Electronics Society

作者： Haiyang Qiu Sicong Zhu Hangbin Wu Hui Wang Ru Zhang School of Electronics and Information Jiangsu University of Science and Technology Zhenjiang China Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport UCL center for transport study Ministry of Transport visiting scholar UCL Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport UCL center for transport study Beijing Jiaotong University Beijing Jiaotong University Beijing China College of Surverying and Geoinfomatics Tongji University Shanghai China Deep Blue Honors School Jiangsu University of Science and Technology Zhenjiang China

This paper presents a solution to detect pedestrian and vehicle using a 16-line LIDAR. Unlike prior researches, the downward-looking LIDAR is mounted on a bridge over road lanes instead of mounting on a moving vehicle. The sensor detects motorized and non-motorized traffic and classifies the traffic into different modes. The detected object is tracked with the Kalman filter method. Compared with the high-end sensor of high resolution, the 16-line LIDAR is affordable and cost-effective, and the experiment demonstrates its acceptable detection rate and trajectory estimation precision. Beside detection range, the application of downward-looking LIDAR has a satisfied result.

关键词： Laser radar Three-dimensional displays Radar tracking Trajectory Mathematical model Classification algorithms Kalman filters

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Future-proofing cities against negative city mobility and public health impacts of impending natural hazards: a system dynamics modelling study

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The Lancet Planetary Health 2025年第3期9卷 e207-e218页

作者： Garcia, Leandro Hafezi, Mehdi Lima, Larissa Millett, Christopher Thompson, Jason Wang, Ruoyu Akaraci, Selin Goel, Rahul Reis, Rodrigo Nice, Kerry A Zapata-Diomedi, Belen Hallal, Pedro C Moro, Esteban Amoako, Clifford Hunter, Ruth F Centre for Public Health Queen's University Belfast Belfast United Kingdom Physical Activity Epidemiology Group University of São Paulo São Paulo Brazil Complex Systems Governance Group Faculty of Engineering and Applied Sciences Cranfield University Cranfield United Kingdom Public Health Policy Evaluation Unit School of Public Health Imperial College London London United Kingdom NOVA National School of Public Health Public Health Research Centre Comprehensive Health Research Center NOVA University Lisbon Lisbon Portugal Instituto de Estudos para Políticas de Saúde São Paulo Brazil Transport Health and Urban Systems Research Lab Faculty of Architecture Building and Planning University of Melbourne Melbourne VIC Australia Institute of Public Health and Wellbeing University of Essex Essex United Kingdom Transportation Research and Injury Prevention Centre Indian Institute of Technology Delhi New Delhi India People Health & Place Research Unit Prevention Research Center School of Public Health Washington University in St. Louis St Louis MO United States Healthy Liveable Cities Lab Centre for Urban Research RMIT University Melbourne VIC Australia Department of Health and Kinesiology University of Illinois Urbana–Champaign IL United States Connection Science Institute for Data Science and Society MIT Cambridge MA United States Department of Mathematics and GISC Universidad Carlos III de Madrid Leganes Spain Department of Planning College of Art and Built Environment Kwame Nkrumah University of Science and Technology Kumasi Ghana

Background: The world faces increasing risk from more frequent and larger scale natural hazards, including infectious disease outbreaks (IDOs) and climate change-related extreme weather events (EWEs). These natural hazards are expected to have adverse mobility and public health impacts, with people living in cities especially vulnerable. Little is known about how transport systems can be optimally designed to make cities more resilient to these hazards. Our aim was to investigate how cities’ transport systems, and their resulting mobility patterns, affect their capabilities to mitigate mobility and health impacts of future large-scale IDOs and EWEs. Methods: System dynamics modelling was used to investigate how different city mobility scenarios can affect the health and mobility impacts of four plausible future IDO and EWE (flooding) shocks in three cities: Belfast, UK;Belo Horizonte, Brazil;and Delhi, India. Three city mobility scenarios with incremental degrees of modal shift towards active travel (private motor vehicle volume reduced to 50% and 20% of total road trip volume in vision 1 and 2, and motor vehicle volume [including buses] reduced to 20% of total road trip volume in vision 3) were tested. For each city and each IDO and EWE shock, we estimated the percentage of deaths prevented in visions 1, 2, and 3, relative to the reference scenario, as well as changes in mode share over time. Findings: In all scenarios, all cities showed reduced susceptibility to flooding, with 4–50% of deaths potentially prevented, depending on case city, city mobility, and EWE scenario. The more ambitious the transition towards healthier city mobility patterns, the greater the resilience against flooding. Only vision 3 (the most ambitious transition) showed reduced vulnerability to IDOs, with 6–19% of deaths potentially prevented. Evolution of mode shares varied greatly across cities and mobility scenarios under the IDO shocks. Interpretation: Our results emphasise the importance

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Spatial data science Languages: commonalities and needs

arXiv

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arXiv 2025年

作者： Pebesma, Edzer Fleischmann, Martin Parry, Josiah Nowosad, Jakub Graser, Anita Dunnington, Dewey Pronk, Maarten Schouten, Rafael Lovelace, Robin Appel, Marius Abad, Lorena Institute for Geoinformatics University of Münster Germany Department of Social Geography and Regional Development Charles University Czech Republic United States Institute of Landscape Ecology University of Münster Germany Center for Digital Safety and Security AIT Austrian Institute of Technology Vienna Austria Wherobots Inc. United States Hydrology Software Deltares Netherlands Oslo Norway Institute for Transport Studies University of Leeds United Kingdom Department of Geodesy Bochum University of Applied Sciences Germany Department of Geoinformatics - Z GIS University of Salzburg Austria Urban Data Science Delft University of Technology Netherlands Institute of Geoecology and Geoinformation Adam Mickiewicz University Poznan Poland

Recent workshops brought together several developers, educators and users of software packages extending popular languages for spatial data handling, with a primary focus on R, Python and Julia. Common challenges discussed included handling of spatial or spatio-temporal support, geodetic coordinates, in-memory vector data formats, data cubes, inter-package dependencies, packaging upstream libraries, differences in habits or conventions between the GIS and physical modelling communities, and statistical models. The following set of insights have been formulated: (i) considering software problems across data science language silos helps to understand and standardise analysis approaches, also outside the domain of formal standardisation bodies;(ii) whether attribute variables have block or point support, and whether they are spatially intensive or extensive has consequences for permitted operations, and hence for software implementing those;(iii) handling geometries on the sphere rather than on the flat plane requires modifications to the logic of simple features, (iv) managing communities and fostering diversity is a necessary, on-going effort, and (v) tools for cross-language development need more attention and support. © 2025, CC BY-SA.

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Identifying Highly Influential Travellers for Spreading Disease on a Public transport System

Identifying Highly Influential Travellers for Spreading Dise...

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IEEE International Symposium on World of Wireless Mobile and Multimedia Networks (WoWMoM)

作者： Ahmad El Shoghri Jessica Liebig Raja Jurdak Lauren Gardner Salil S. Kanhere University of New South Wales Sydney NSW Australia Data61 Commonwealth Scientific and Industrial Research Organization Brisbane QLD AUSTRALIA School of Computer Science Queensland University of Technology Brisbane QLD AUSTRALIA Department of Civil and Systems Engineering Johns Hopkins University Baltimore MD USA Research Center for Integrated Transport Innovation (rCITI) UNSW Sydney Sydney NSW AUSTRALIA School of Computer Science and Engineering University of New South Wales Sydney NSW AUSTRALIA

ISBN: (数字)9781728173740

ISBN: (纸本)9781728173757

The recent outbreak of a novel coronavirus and its rapid spread underlines the importance of understanding human mobility. Enclosed spaces, such as public transport vehicles (e.g. buses and trains), offer a suitable environment for infections to spread widely and quickly. Investigating the movement patterns and the physical encounters of individuals on public transit systems is thus critical to understand the drivers of infectious disease outbreaks. For instance, previous work has explored the impact of recurring patterns inherent in human mobility on disease spread, but has not considered other dimensions such as the distance travelled or the number of encounters. Here, we consider multiple mobility dimensions simultaneously to uncover critical information for the design of effective intervention strategies. We use one month of citywide smart card travel data collected in Sydney, Australia to classify bus passengers along three dimensions, namely the degree of exploration, the distance travelled and the number of encounters. Additionally, wes imulate disease spread on the transport network and trace the infection paths. We investigate in detail the transmissions between the classified groups while varying the infection probability and the suspension time of pathogens. Our results show that characterizing individuals along multiple dimensions simultaneously uncovers a complex infection interplay between the different groups of passengers, that would remain hidden when considering only a single dimension. We also identify groups that are more influential than others given specific disease characteristics, which can guide containment and vaccination efforts.

关键词： Pathogens Australia Suspensions Global Positioning System Infectious diseases Sociology

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Online transmission policy in wireless powered networks with urgency-aware age of information 15

Online transmission policy in wireless powered networks with...

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15th IEEE International Wireless Communications and Mobile Computing Conference, IWCMC 2019

作者： Lu, Yang Xiong, Ke Fan, Pingyi Zhong, Zhangdui Letaief, Khaled Ben School of Computer and Information Technology Beijing Jiaotong University Beijing100044 China Beijing Key Laboratory of Traffic Data Analysis and Mining Beijing Jiaotong University Beijing100044 China Department of Electronic Engineering Tsinghua University Beijing100084 China State Key Lab of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China Beijing Engineering Research Center of High-speed Railway Broadband Mobile Communications Beijing Jiaotong University Beijing100044 China Hong Kong University of Science and Technology Hong Kong Hong Kong

ISBN: (纸本)9781538677476

This paper investigates the age of information (AoI) for a radio frequency (RF) energy harvesting (EH) enabled network, where a sensor first scavenges energy from a wireless power station and then transmits the collected status update to a sink node. To capture the thirst for the fresh update becoming more and more urgent as time elapsing, urgency-aware AoI (U-AoI) is defined, which increases exponentially with the increment of time between two received updates. Due to EH, a waiting time is required at the sensor before transmitting the status update. An optimization problem is formulated to minimize the long-term average U-AoI under constraint of energy causality. A two-layer algorithm is presented to solve it, where the outer loop is designed based on Dinklebach's method, and the inner loop presents a semi-closed-form expression of the optimal waiting time policy based on Karush-Kuhn-Tucker (KKT) optimality conditions. Numerical results show that our proposed optimal transmission policy outperforms the zero time waiting policy and equal time waiting policy in terms of long-term average U-AoI, especially when the networks are in slight load. It also shows that the system U-AoI first decreases and then keeps unchanged with the increments of EH circuit's saturation level. © 2019 IEEE.

关键词： Energy harvesting

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Optimal Design of SWIPT-Aware Fog Computing Networks

Optimal Design of SWIPT-Aware Fog Computing Networks

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IEEE Conference on Computer Communications Workshops, INFOCOM Wksps

作者： Jingxian Liu Ke Xiong Pingyi Fan Zhangdui Zhong Khaled Ben Letaief Beijing Key Laboratory of Traffic Data Analysis and Mining Beijing Jiaotong University Beijing China Department of Electronic Engineering Tsinghua University Beijing China Beijing Engineering Research Center of High-speed Railway Broadband Mobile Communications Beijing Jiaotong University Beijing China The Hong Kong University of Science and Technology Hong Kong

This paper studies a simultaneous wireless information and power transfer (SWIPT)-aware fog computing network, where a multiple antenna fog function integrated hybrid access point (F-HAP) transfers information and energy to multiple heterogeneous single-antenna sensors and also helps some of them fulfill computing tasks. By jointly optimizing energy and information beamforming designs at the F-HAP, the bandwidth allocation and the computation offloading distribution, an optimization problem is formulated to minimize the required energy under communication and computation requirements, as well as energy harvesting constraints. Two optimal designs, i.e., fixed offloading time (FOT) and optimized offloading time (OOT) designs, are proposed. As both designs get involved in solving non-convex problems, there are no known solutions to them. Therefore, for the FOT design, the semidefinite relaxation (SDR) is adopted to solve it. It is theoretically proved that the rank-one constraints are always satisfied, so the global optimal solution is guaranteed. For the OOT design, since its non-convexity is hard to deal with, a penalty dual decomposition (PDD)-based algorithm is proposed, which is able to achieve a suboptimal solution. The computational complexity for two designs are analyzed. Numerical results show that the partial offloading mode is superior to binary benchmark modes. It is also shown that if the system is with strong enough computing capability, the OOT design is suggested to achieve lower required energy; Otherwise, the FOT design is preferred to achieve a relatively low computation complexity.

关键词： Edge computing Task analysis Array signal processing Wireless communication Channel allocation Computational complexity Economics

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