Spreading Patterns of Malicious Information on Single‐Lane Platooned Traffic in a Connected Environment

Wang, Pengcheng; Yu, Guizhen; Wu, Xinkai; Wang, Yunpeng; He, Xiaozheng

doi:10.1111/mice.12416

Cited by 19 publications

(4 citation statements)

References 94 publications

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“…Concretely, trains measure their dynamic states (i.e., position, velocity, and acceleration) and then transmit them to other trains via train‐to‐train communication. There is an update delay when trains receive the state information from others (Parise et al., 2019; Wang et al., 2019). Ideally, the average update delay for one‐way train‐to‐train transmission is usually between 26–50ms in the simulation tests for train control systems (Liu & Yuan, 2018).…”

Section: Introductionmentioning

confidence: 99%

Control strategy for stable formation of high‐speed virtually coupled trains with disturbances and delays

Liu

Zhou

et al. 2022

Computer aided Civil Eng

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Virtual coupling (VC) brings unprecedented opportunities for the train operation system by controlling multiple trains as a virtually coupled train set (VCTS) via train automation and communication. To deal with communication delays and small disturbances in a VCTS, this paper developed a tube‐based control approach for the VCTS, focusing on optimizing the control performances and meanwhile guaranteeing the individual and string stability. Specifically, a tube model predictive control (MPC) framework is constructed to handle safety constraints and regulate bounded small disturbances. Then, the individual stability and string stability are ensured by designing the constraint sets for inputs and proper coefficient tuning within the stable region. Finally, simulation‐based experiments verify that the proposed approach shows better robustness and higher efficiency, which can regulate train states within a tube, and the VCTS can be asymptotically stable and string stable facing disturbances and delays.

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Section: Introductionmentioning

confidence: 99%

Control strategy for stable formation of high‐speed virtually coupled trains with disturbances and delays

Liu

Zhou

et al. 2022

Computer aided Civil Eng

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“…It concluded that enhanced performance and safety are attainable through V2V communication and collaboration. Wang et al [27] evaluated the impact of cyberattacks on a single platoon moving in a single lane, treating cyberattacks as similar to the dissemination of malicious information. The observation revealed that these cyberattacks notably disrupted the flow of traffic.…”

Section: Literature Reviewmentioning

confidence: 99%

Anomaly Detection in Connected and Autonomous Vehicle Trajectories Using LSTM Autoencoder and Gaussian Mixture Model

Wang,

Li,

Khattak

2024

Electronics

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Connected and Autonomous Vehicles (CAVs) technology has the potential to transform the transportation system. Although these new technologies have many advantages, the implementation raises significant concerns regarding safety, security, and privacy. Anomalies in sensor data caused by errors or cyberattacks can cause severe accidents. To address the issue, this study proposed an innovative anomaly detection algorithm, namely the LSTM Autoencoder with Gaussian Mixture Model (LAGMM). This model supports anomalous CAV trajectory detection in the real-time leveraging communication capabilities of CAV sensors. The LSTM Autoencoder is applied to generate low-rank representations and reconstruct errors for each input data point, while the Gaussian Mixture Model (GMM) is employed for its strength in density estimation. The proposed model was jointly optimized for the LSTM Autoencoder and GMM simultaneously. The study utilizes realistic CAV data from a platooning experiment conducted for Cooperative Automated Research Mobility Applications (CARMAs). The experiment findings indicate that the proposed LAGMM approach enhances detection accuracy by 3% and precision by 6.4% compared to the existing state-of-the-art methods, suggesting a significant improvement in the field.

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“…Recently, the IDM has been widely used for traffic flow (28). In this study, the IDM is selected to simulate HVs for the following reasons: (1) the IDM shows clearly the intuitive physical meaning and provides collision-free behaviors and smooth traffic flow; (2) it is of great realism compared with other controllers when capturing the dynamics of different congestion levels; and (3) it is a sophisticated model that has been used to model the longitudinal dynamics of HVs in many existing studies (29)(30)(31)(32).…”

Section: Modeling Of Heterogeneous Trafficmentioning

confidence: 99%

Impact of Platoon Management on Heterogeneous Traffic under V2X Communication Limitation

Dai

Yang

Zhong

2023

Transportation Research Record: Journal of the Transportation R

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The advent of vehicle-to-everything (V2X) communication technology, as well as driving automation that is happening at a rapid pace, enables the potential for transforming the transportation system. The near future will, therefore, bring the coexistence of human-driven vehicles (HVs), connected vehicles (CVs), and connected and automated vehicles (CAVs). Correspondingly, platoon management based on V2X communication is expected to improve traffic capacity and fuel efficiency. However, there is a lack of analysis of the impact of platoon management on heterogeneous traffic combined with CVs. Moreover, V2X communication limitation is usually dismissed in existing studies. To address these limitations, this paper explores the impact of platoon management on the capacity of heterogeneous-traffic environments under different CV and CAV market penetration rates (MPRs) with the fundamental diagram considering V2X communication limitations, and further studies the changes in capacity and fuel efficiency of traffic combined with different platoon sizes. Firstly, in light of platoon management, we propose the heterogeneous traffic configurations through distribution characteristics of nine types with simulated models. Secondly, the fundamental diagram considering platoon management with V2X communication limitation is proposed under different CV and CAV MPRs. Thirdly, numerical simulations are conducted to demonstrate the impact of platoon size on the changes in capacity and fuel efficiency of traffic. Conclusions are drawn from the results of the simulations: with the cooperation of CVs and CAVs, the traffic capacity and the fuel efficiency will be promoted, particularly under high CV MPR or high CAV MPR environments.

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Spreading Patterns of Malicious Information on Single‐Lane Platooned Traffic in a Connected Environment

Cited by 19 publications

References 94 publications

Control strategy for stable formation of high‐speed virtually coupled trains with disturbances and delays

Control strategy for stable formation of high‐speed virtually coupled trains with disturbances and delays

Anomaly Detection in Connected and Autonomous Vehicle Trajectories Using LSTM Autoencoder and Gaussian Mixture Model

Impact of Platoon Management on Heterogeneous Traffic under V2X Communication Limitation

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