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100th IEEE Vehicular technology Conference, VTC 2024-Fall

作者： Wen, Yuxuan Yang, Liu Bai, Chaoyuan Liu, Heng Chengdu611756 China Southwest Jiaotong University Key Lab of Information Coding & Transmission Institude of Mobile Communication Chengdu611756 China National Engineering Laboratory of Integrated Transportation Big Data Application Technology Chengdu611756 China

ISBN: (纸本)9798331517786

With the continuous increase of IoT devices, multiple devices desire to use network resources simultaneously during peak hours and overload conditions, leading to collisions and a reduction in the network's effective throughput. The Access Class Barring (ACB) method has been proposed as the optimal potential solution in LTE communication networks to overcome this problem. However, existing ACB schemes do not fully utilize preamble resources, and most schemes do not consider the situation where PUSCH resources are limited. Therefore, this paper proposes a two-stage ACB algorithm that considers the situation of limited PUSCH resources. This algorithm recycles part of the preamble resources and sets the ACB factor based on the number of PUSCH resources. Simulation results show that our proposed algorithm significantly outperforms traditional schemes in terms of total service time, delay, throughput, and PUSCH resource efficiency. © 2024 IEEE.

关键词： Internet of things

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Travel Characteristics and Combination Choice Behavior Modeling of Passengers under the Influence of Epidemic Prevention Policies 24

Travel Characteristics and Combination Choice Behavior Model...

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24th COTA International Conference of transportation Professionals: Resilient, Intelligent, Connected, and Lowcarbon Multimodal transportation, CICTP 2024

作者： Zhang, Yue Dong, Chunjiao Li, Penghui Dong, Qianru Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport School of Traffic and Transportation Beijing Jiaotong Univ. Beijing China State Key Laboratory of Intelligent Vehicle Safety Technology China Automotive Engineering Research Institute Co. Ltd. Chongqing China

ISBN: (数字)9780784485484

ISBN: (纸本)9780784485484

The intermodal travel characteristics and combination selection behaviors of passengers are key issues to providing reasonable, efficient, and safe solutions, ensuring the traffic order, and improving quality. With the Beijing Winter Olympics as a background, by combining the Stated Preference and Revealed Preference surveys, the research develops a decision-making behavior model based on nested logit to investigate the passenger travel choices. The impacts of individual attributes, epidemic prevention policies, and preferential measures on the choice of intermodal travel, as well as the combination of departure time and travel mode, are studied. The results show that cultural and creative products have a significant impact on the combined travel choices. The cultural and creative products and consumer vouchers have a significant impact on the choice of intermodal travel. The research results can provide insights into traffic organization and management policies during large-scale events. © ASCE.

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Flood Resilience Assessment of Riverside Urban Communities - Taking Ciqikou Street as an example 9

Flood Resilience Assessment of Riverside Urban Communities -...

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9th Academic Conference of Geology Resource Management and Sustainable Development

作者： Xu, Hui Zhang, Shuang School of Economics and Management Chongqing University of Posts and Telecommunications Chongqing400707 China Chongqing Innovation Center of Industrial Big-Data Co. Ltd. National Engineering Laboratory for Industrial Big-data Application Technology Chongqing400707 China

ISBN: (纸本)9781921712784

Riverside urban communities are the most vulnerable urban unit to flood disasters due to their characteristics of severe disaster exposure, weak resistance to risks and high requirements for emergency management. This article uses "community flood resilience" to describe its stability, recovery and adaptability in the face of flood disasters. A flood resilience indicator system of riverside communities using 18 indicators separated into 5 domains is constructed through field research and literature review. Combining expert opinions and using network analysis, the weight of each indicator is determined. Indicator data is obtained by processing remote sensing image, geographic information data and other means. The results show that disaster relief, public health management, medical facilities, etc. contribute more to flood resilience in study area;ability to reducing runoff velocity and storing water, road profiles and transportation methods are the key points to improve the resilience of the study area. The article recommends measures such as strengthening technological early warning and command, building rainwater mitigation facilities, and enhancing residents' ability and awareness of flood avoidance to minimize the loss of future flood disasters in this street. © 2022 by Aussino Academic Publishing House.

关键词： Floods

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Research on Cyberattack Detection of Connected Automated Vehicles Based on Support Vector Machine

Research on Cyberattack Detection of Connected Automated Veh...

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IEEE International Conference on Intelligent transportation engineering (ICITE)

作者： Runzhe Liu Xin Peng Zhanbo Sun Zhihang Huang Haitao Hu National Engineering Laboratory of Integrated Transportation Big Data Application Technology Southwest Jiaotong University Chengdu China

Connected automated vehicles (CAVs) are facing the threat of cyberattacks while exchanging state information. Most of the existing research focuses on the communication technologies and the network security technologies, with the purpose of providing corresponding preventive solutions for the specific technical means of attack behavior, which are highly targeted but weak in universality of application. In this paper, a type of adversary model based on attack effects, namely, disturbance attack, was established. A numerical simulation platform for CAVs cyberattack experiment was built to quantitatively analyze the impacts of CAVs cyberattacks on traffic. 9 measurement indicators were constructed based on traffic safety indicators and traffic flow parameters for the characteristic impacts of various attacks. Using the cyberattack experiment simulation platform to generate attack feature datasets, A cyberattack detection model of CAVs on the basis of nonlinear Support Vector Machine was established. The model showed a sound classification performance, with a detection rate of more than 95% within 3s of the attack. The research method in this paper has a universal reference value for cyberattacks detection of CAVs. The results help better understand the effects of CAV-related cyberattacks and shed light on proactive defense against such attacks.

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Blind Information Extraction of Machine Faults Based on Separating Matrix

Blind Information Extraction of Machine Faults Based on Sepa...

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IEEE International Conference on Intelligent transportation engineering (ICITE)

作者： Hao Li Yifan Tan Yun Pu Officers College of PAP Chengdu China National Engineering Laboratory of Integrated Transportation Big Data Application Technology

ISBN: (数字)9781728194097

ISBN: (纸本)9781728194103

Blind signal processing is an effective feature extraction method for mechanical vibration signals. However due to noise corruption, independent source signals can't always be accurately recovered or separated from the acquired sensor observations. Then feature information extracted from source signals can't naturally represent machine states of the detected mechanical equipment. Generally in blind signal processing, the separating matrix may contain as much information contents as the separated source signals. The separating matrix can directly be processed to extract its singular values as useful feature information by the singular value decomposition (SVD) method. Thus a blind information extraction method was proposed to extract singular values of separating matrix as the desired feature information of the detected machine. The experimental results of gear pump indicate that this method can be applied to feature extraction of mechanical equipment.

关键词： Feature extraction Gears Vibrations Signal processing data mining Pumps Time-domain analysis

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Stability Analysis of Connected Automated Vehicle Platoon Controller Under Unreliable Communication Conditions

Stability Analysis of Connected Automated Vehicle Platoon Co...

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International Conference on Intelligent transportation

作者： Lei Yang Yafei Liu Zhanbo Sun Qiruo Yan Ziye Qin Xuting Wang National Engineering Laboratory of Integrated Transportation Big Data Application Technology School of Transportation and Logistics Southwest Jiaotong University Chengdu China

The paper investigates the longitudinal control problem of a connected automated vehicle (CAV) platoon operating under the multiple-predecessor following (MPF) topology, while considering unreliable communication circumstances characterized by random packet loss and heterogeneous time-varying delay. To model random packet loss, a Bernoulli probabilistic distribution is employed, where the packet loss rate is influenced by the communication distance. A linear feedback controller is then developed to handle such packet loss and delay. The sufficient conditions for the asymptotic stability of the platoon controller are derived using linear matrix inequalities and a Lyapunov-based approach. The delay margin condition is obtained, which is associated with the packet loss rate and the number of consecutive packet losses. The string stability of the platoon with delay and packet loss is also analyzed by the transfer function. Simulation experiments demonstrate that the proposed method approach effectively maintains the stability of the platoon in the presence of delay and packet loss.

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Time-aware bike flow prediction framework with dynamic edge fusion and memory integration

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Knowledge-Based Systems 2025年

作者： Taha M.Rajeh Tianrui Li Zhpeng Luo Muhammad Hafeez Javed Fares Alhaek School of Computing and Artificial Intelligence Southwest Jiaotong University Chengdu 611756 PR China Engineering Research Center of Sustainable Urban Intelligent Transportation Ministry of Education Chengdu 611756 PR China National Engineering Laboratory of Integrated Transportation Big Data Application Technology Southwest Jiaotong University Chengdu 611756 PR China Stirling College Chengdu University Chengdu 610106 PR China Computing Science Faculty of Natural Sciences University of Stirling FK9 4LA Stirling UK Manufacturing Industry Chains Collaboration and Information Support Technology Key Laboratory of Sichuan Province Southwest Jiaotong University Chengdu 611756 PR China

Bike-Sharing Systems (BSSs) have become a popular solution to urban sustainability concerns, providing affordable and environmentally friendly transportation. However, modeling and predicting shared-bike flow patterns are essential for developing intelligent transportation systems and facilitating city management. Despite the existence of several inflow and outflow prediction models, certain unresolved issues remain, including the inability to differentiate and capture heterogeneous dynamic relationships within daily flows, and the suboptimal utilization of historical flow data for forecasting. To address these limitations, we propose MVRC (Multi-View Relational Framework based on Clustering), a novel deep-learning framework for precise inflow and outflow prediction. The MVRC framework models three types of heterogeneous dynamic flow relationships during different periods of the day. Initially, we introduce a novel clustering method to group nearby stations exhibiting similar patterns, followed by creating a dynamic memory module to store and update edge attributes based on the time of day. Furthermore, the dynamic edge fusion mechanism effectively integrates heterogeneous, time-evolving flow features, capturing their varying impacts. To further enhance the model’s capabilities, an offline component that leverages historical data is incorporated, improving performance during testing. Extensive experiments conducted on real datasets from New York City and Washington, D.C., demonstrate the superior prediction efficiency and framework effectiveness of the MVRC framework compared to existing state-of-the-art techniques. These results highlight the practicality and efficacy of MVRC in terms of prediction accuracy and stability.

关键词： Flow prediction data fusion Attention Bike flow Clustering Graph convolutional networks Urban computing

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Path Tracking Control for Connected Automated Vehicle Using Lateral Stability Envelope at Handling Limits

Path Tracking Control for Connected Automated Vehicle Using ...

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International Conference on Intelligent transportation

作者： Linbin Chen Yafei Liu Zhanbo Sun Lei Yang National Engineering Laboratory of Integrated Transportation Big Data Application Technology School of Transportation and Logistics Southwest Jiaotong University Chengdu China

To improve the lateral stability and accuracy of path tracking control for connected automated vehicle (CAV) at handling limit conditions, the paper develops a model predictive control (MPC) method ultizing a lateral stability envelope. Specifically, the lateral stability envelope for vehicle state variables (i.e., sideslip angle and yaw rate) is derived by analyzing dynamic changes in the limit slip angle of the front wheel. This envelope varies with the steering angle and is incorporated into the proposed MPC controller as a constraint, which can guarantee lateral stability at handling limits. To further enhance the tracking accuracy, a reference for the yaw rate is derived by backstepping control considering the lateral displacement error. This reference is formulated as the objective for the MPC controller to regulate tracking errors. Simulation experiments demonstrate that the proposed controller can decrease the yaw rate and steering angle fluctuations in path tracking with low road adhesion compared with the nominal controller.

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Revisit the scheduling problem in Hurdle, V.F., 1973: A novel mathematical solution approach and two extensions

arXiv

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arXiv 2020年

作者： Fan, Wenbo School of Transportation and Logistics National Engineering Laboratory of Integrated Transportation Big Data Application Technology Southwest Jiaotong University Chengdu China

The scheduling problem in Hurdle (1973) was formulated in a general form that simultaneously concerned the vehicle dispatching, circulating, fleet sizing, and patron queueing. As a constrained variational problem, it remains not fully solved for decades. With technical prowess in graphic analysis, the author unveiled the closed-form solution for the optimal dispatch rates (with key variables undetermined though), but only suggested the lower and upper bounds of the optimal fleet size. Additionally, such a graphic analysis method lacks high efficiency in computing specific scheduling problems, which are often of a large scale (e.g., hundreds of bus lines). In light of this, the paper proposes a novel mathematical solution approach that first relaxes the original problem to an unconstrained one, and then attacks it using calculus of variations. The corresponding Euler-Lagrange equation yields the closed-form solution of the optimal dispatching rates, to which Hurdle's results are a special case. Thanks to the proposed approach, the optimal fleet size can also be solved. This paper completes the work of Hurdle (1973) by formalizing a solution method and generalizing the results. Based on that, we further make two extensions to the scheduling problem of general bus lines with multiple origins and destinations and that of mixed-size or modular buses. Closed-form results are also obtained with new insights. Among others, we find that the solutions for shuttle/feeder lines are a special case to our results of general bus lines. Numerical examples are also provided to demonstrate the effectiveness and efficiency of the proposed approach. Copyright © 2020, The Authors. All rights reserved.

关键词： Scheduling

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Coordinated Congestion Pricing for Bi-Modal Multi-Region Urban Networks

Coordinated Congestion Pricing for Bi-Modal Multi-Region Urb...

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International Conference on Intelligent transportation

作者： Xiangyu He Yu Zhao Yafei Liu Zhanbo Sun National Engineering Laboratory of Integrated Transportation Big Data Application Technology School of Transportation and Logistics Southwest Jiaotong University Chengdu China

ISBN: (数字)9798331505929

ISBN: (纸本)9798331505936

Extensive studies have explored designing pricing schemes for single-mode or homogeneous networks. The development of bi-modal Macroscopic Fundamental Diagrams (3D-MFD) facilitates real-time coordinated control strategies for bi-modal multi-regional urban networks. This research explores the traffic dynamics of mixed networks with urban networks and expressways, proposing two 3D-MFD-based coordinated pricing schemes for bi-modal multi-region urban networks. The first scheme utilizes a Model Predictive Control (MPC) approach to integrating toll rates into the 3D-MFD-based optimization problem. The second scheme applies feedback control theory to simultaneously determine the dynamic price and estimate the value of Time (VOT) and trip length distribution of commuters. The proposed coordinated pricing schemes are further compared with uncoordinated pricing schemes. Numerical examples indicate that coordinated pricing by comprehensively considering the traffic flow and demand across different regions of the urban network achieves more effective congestion alleviation.

关键词： Sensitivity Pricing Real-time systems Feedback control Optimization Intelligent transportation systems Predictive control

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