Delay Characteristics Research Articles

Analysis of the retraction papers in oncology field from Chinese scholars from 2013 to 2022.

To analyze the characteristics of retracted oncology papers from Chinese scholars and the reasons for retraction. Data on retracted oncology papers from Chinese scholars published from 2013 to 2022 were retrieved from the Retraction Watch database. The retraction number and annual distribution, article types, reasons for retraction, retraction time delay, publishers, and journal characteristics of the retracted papers were analyzed. A total of 2695 oncology papers from Chinese scholars published from 2013 to 2022 had been retracted. The majority of these papers were published from 2017 to 2020. In terms of article type, 2538 of the retracted papers were research articles, accounting for 94.17% of the total number of retracted papers. The main reasons for retraction were data, result, and image problems, duplicate publication, paper mills, author- and third-party-related reasons, plagiarism, false reviews, and method errors. The retraction time delay for the retracted papers ranged from 0 to 3582 days (median, 826 days). The retractions mainly occurred within the first 4 years after publication. A total of 77 publishers were involved in the retracted papers. In terms of journal distribution, 394 journals were involved in the retracted papers, of which 368 (93.40%) were included in the SCI database. There were 243 journals with an impact factor of <5 (66.03%). In the field of oncology, the annual distribution of retracted papers from Chinese scholars exhibited first an increasing and subsequently a decreasing trend, reaching a peak in 2019, indicating an improvement in the status of retraction after 2021. The main type of the retracted papers was research article, and the main reason for retraction was academic misconduct. The retractions were mainly concentrated in several major publishers and periodicals in Europe and the United States. Most of the journals had low-impact factors.

MixMatch: Flow Matching for Mixnet Traffic

Mixnets provide communication anonymity against network adversaries by routing packets independently via multiple hops, delaying them artificially at each hop, and introducing cover traffic. We show that these features (particularly the use of cover traffic) significantly diminish the effectiveness of state-of-the-art flow correlation techniques developed to link the two ends of a Tor connection. In this work, we propose novel methods to determine whether a set of endpoints exchanges packets via a mixnet and demonstrate their effectiveness by applying them to the Nym mixnet. We consider Nym in both an idealized lab setup and the official live network, and propose and compare three classifiers to conduct flow matching on it. Our statistical classifier tests whether egress packet timestamps are consistent with ingress timestamps and the (known) routing delay characteristic of the mixnet. In contrast, our two deep learning (DL) classifiers learn to distinguish matched from unmatched flow pairs from collected datasets directly, rather than relying on priors that describe the delay distribution. All three classifiers use our flow merging technique, which enables testing a match for sets of communicating endpoints of any cardinality. Considering a use case where two observed endpoints communicate exclusively to exchange a file through Nym, we find that flow matching is fast and accurate in the idealized lab setup. If flow pairs are aligned using all network observations in a download, we achieve a TPR of circa 0.6 (DL) and 0.47 (statistical) at an FPR of 10^-2 after only processing 100 observations. We evaluate classifier performance under key variations of this setup: the absence of loop cover traffic, an increased or decreased average per-mix delay, larger communicating sets (three endpoints) with faster responders, and the presence of realistic network effects (live network). The classifiers' matching performance diminishes on the live network where packet losses and variable propagation delays exist, reducing DL TPR to circa 0.26 and statistical TPR to circa 0.28 at an FPR of 10^-2. Informed by the insights of our analyses, we outline countermeasures that can be deployed in mixnets such as Nym to mitigate flow matching threats.

Wheel slip ratio control considering time delay characteristic for electro-mechanical braking system

Electro-mechanical braking (EMB) system is a novel brake-by-wire (BBW) system which is the development direction of the electrification and intelligent vehicle braking system. However, as the EMB contains a mechanical transmission mechanism, there is an inevitable time delay in the braking process, which will cause problems of the wheel slip ratio control. To address this issue, this paper proposes a novel wheel slip ratio control system based on a hierarchical control framework, comprising a slip ratio control layer and a clamping force control layer. Firstly, an EMB actuator model considering the stiffness and damping characteristics of the ball screw is constructed and the correspondence between the model and the EMB object is verified. Subsequently, a model-based compensate active disturbance rejection control (MCADRC) algorithm based on the EMB actuator model is designed to compensate the uncertainty of the EMB and improve the tracking accuracy of the clamping force. Furthermore, the influence of time delay on slip ratio control is analyzed and a slip ratio controller considering time delay characteristic is developed to improve the slip ratio control quality. Finally, the HiL test results show that the proposed controller can effectively reduce the jitter of slip ratio by 1.2% and improve the response speed of slip ratio control 7.8%, which prove the real-time and effectiveness of the controller.

Mitigation of tropospheric delay induced errors in TS-InSAR ground deformation monitoring

ABSTRACT Interferometric Synthetic Aperture Radar (InSAR) is capable of detecting crust deformation. However, the accuracy is limited by spatiotemporal changes in the lower troposphere. In this paper, we constructed a periodic zenith total delay negative exponential function (PZTD-NEF) model of atmospheric spatiotemporal variation characteristics based on ERA-5 data to alleviate the temporal oscillation bias introduced by tropospheric delay and improve the accuracy of time series InSAR (TS-InSAR) inversion of surface deformation. We evaluated the model’s performance using the phase standard deviation (STD), atmospheric delay correlation coefficient with topography and the spatial structure function. The results were compared with a linear topography-dependent empirical model, generic atmospheric correction online service (GACOS) and ERA-5 methods. Our method reduces the STD of the phase of 83% of the interferograms by 12.8%. For vertical stratification delay correction, the correlation between the proposed method and the Linear, GACOS, and ERA-5 reached 0.734, 0.708, and 0.729, respectively. We found that accounting for spatiotemporal variation characteristics of tropospheric delay can alleviate the seasonal oscillations of vertical stratification delay and improve the accuracy of the deformation time series solution by 40.04%. We also used the Kunming continuous operation reference station system (KMCORS) to verify the displacement results of our method.

Improved stability and stabilization criteria for multi-rate sampled-data control systems via novel delay-dependent states

This paper aims to obtain less conservative stability and stabilization conditions for sampled-data linear systems with multiple sampling rates. To this end, three novel delay-dependent states resulting from sampling are introduced in the augmented state, enabling the exploitation of the sawtooth-type characteristics of the sampling-induced delay in both stability and stabilization processes. Additionally, a novel discontinuous function is included in Lyapunov–Krasovskii-based functional to enhance the capacity to extract more information from specific sampling pattern for each state. Especially, to strengthen the interdependence among the components of the augmented state, supplementary zero equalities are incorporated into the stability analysis conditions. Furthermore, by including a novel weighted state derivative in the augmented state, this paper proposes an effective method that can transform the parameter-dependent stability conditions into stabilization conditions formulated in terms of linear matrix inequalities. Finally, the validity and practicality of the proposed method are demonstrated through two illustrative examples.

Analysis of Phase-Locked Loop Filter Delay on Transient Stability of Grid-Following Converters

To ensure precise phase estimation within the q-axis of the phase-locked loop (PLL), integrating a filter into the q-axis loop is essential to mitigate grid-voltage harmonics. Nevertheless, the intrinsic delay characteristics of this filter impede PLL synchronization during significant grid disturbances. This study begins by developing mathematical models for three types of filters—moving-average filter (MAF) for eliminating odd harmonic components, dq-frame cascaded delayed signal cancellation (dqCDSC) filter, and notch filter (NF). Following the reduction in filter orders, a third-order nonlinear large-signal model of the PLL, incorporating an additional q-axis internal filter, is formulated. Using phase plane analysis, this study investigates the transient synchronism of the grid-following converter (GFL) and explores the influence of delay time constants from the three PLL filters on its behavior while delineating the boundaries of their basins of attraction. Theoretical findings indicate that, relative to the traditional SRF-PLL, incorporating an internal filter into the PLL compromises the transient synchronous stability of GFL. Specifically, greater filter delay time constants exacerbate the GFL’s vulnerability to transient instability amid substantial grid disturbances. Hence, careful consideration is essential when using MAF-PLL and NF-PLL in situations demanding high synchronization stability. The theoretical analyses are validated using Matlab/Simulink to verify their accuracy.

What are the key stability challenges in high-bandwidth, non-minimum phase systems with time-varying, and non-smooth delays?

The analysis and control of stability in high-bandwidth systems characterized by non-minimum phase delays represent a formidable challenge within the realm of control theory and engineering. This research aims to address the pivotal question of whether it is feasible to enhance the stability of such intricate systems. These systems inherently possess uncertain and swiftly changing delay characteristics, rendering them exceptionally demanding to control effectively. In the course of this investigation, we embark on a comprehensive exploration of the theoretical underpinnings of the stability of high-bandwidth, non-minimum phase delay systems. This encompassing inquiry encompasses a meticulous consideration of both derivative-delay and piecewise continuous delay components. To underpin our analysis, we judiciously incorporate feedback mechanisms, drawing upon mathematical tools such as the Jensen inequality and Lyapunov-based methodologies to rigorously establish stability conditions. Furthermore, our exploration extends to encompass the concept of input-output stability and complements it with the notion of asymptotic stability, thereby ensuring that the systems in question exhibit uniform stability across diverse temporal domains. The outcomes of our investigation furnish compelling evidence that by harnessing the power of discrete-time Lyapunov-Krasovskii functionals, it becomes conceivable to circumscribe the maximum delay within predefined thresholds. This achievement holds the promise of enhancing stability in non-minimum phase delay systems characterized by high bandwidth. These findings have far-reaching implications, profoundly influencing the design and control paradigms across a spectrum of engineering applications. Notably, this impact extends to areas such as communication networks, real-time control systems, and robotics, where the mitigation of instability due to non-minimum phase delays has been an enduring challenge.

A comprehensive packaging solution from DC to 113 GHz for InGaAs amplifiers

AbstractThis letter presents the design, fabrication and measurement of a 72 kHz to 113 GHz ultra‐broadband amplifier that includes a direct current (DC)‐blocking functionality. This amplifier module stands out with a high average gain of 12.5 dB in the frequency range from almost DC to 110 GHz. This work not only combines electrical interconnections but also mechanical design considerations, thermal requirements and practical application specific aspects. To ensure a low thermal resistance, the InGaAs amplifier IC is directly mounted on an aluminium submount, applying an advanced gluing concept, and interconnected to an input and output 50 grounded coplanar waveguide by wire bonds with a length of only 135 . To enable convenient usage of the package, 1 mm connectors are utilized. This amplifier module exhibits excellent thermal behaviour and group delay characteristics, making it an ideal choice for use in optical data transmission experiments.

Coordinated scheduling of integrated electricity, heat, and hydrogen systems considering energy storage in heat and hydrogen pipelines

The increasing interdependency of electricity, heat, and hydrogen sectors in recent years provides a growing incentive to make use of the possible synergies obtained when coordinating these energy sectors from the perspective of an integrated energy system (IES). However, coordinated scheduling frameworks remain poorly developed for integrated electricity, heat, and hydrogen systems, and the energy storage potentials in heat and hydrogen pipelines have not been quantitatively analyzed. The present work addresses these issues by separately analyzing the energy storage value provided by district heat systems (DHSs) and hydrogen transmission systems (HTSs). These storage potentials are applied to develop an operation model that considers the delay characteristics of heat pipelines and hydrogen pipeline storage. Then, we develop a coordinated scheduling model for a power–heat–hydrogen IES. The analysis is facilitated by quantifying the value of energy storage in heat pipelines and hydrogen pipelines in terms of operation costs. Finally, a case study is conducted to verify the necessity of accounting for the dynamic energy storage potentials of the DHS and HTS during IES optimization. Numerical results verify the economic value of comprehensive consideration of heat and hydrogen pipeline storage, which results in higher operational flexibility of IES with lower operating cost and reduced wind power curtailment.

Quasi-dynamic modeling and simulation of district heating systems: A laplace transform-based approach

The technological development direction for China's green and low-carbon energy transformation is constructing a multi-energy collaborative smart integrated energy system. As an essential subsystem of energy systems in northern China, district heating system (DHS) plays a crucial role in ensuring people's livelihood. The energy system transformation and the development of the new generation of heating systems impose increasing demands on the simulation computations of regional heating systems. This paper establishes a quasi-dynamic model for heating systems based on the Laplace transform as the foundation. It transforms the continuous thermal dynamics in the time domain into the Laplace domain for quantitatively analyzing the heat transfer loss characteristics and transmission delay characteristics in the heat transport process. Furthermore, it converts the internal complex transmission processes of the system into equivalent source-load boundary conditions to obtain a thermal state analysis model with clear physical significance. This approach significantly reduces the computational complexity of network analysis while ensuring computational accuracy. The established quasi-dynamic model is applied to cases of different scales. The computational results are compared and validated against the commercial simulation software Apros and actual operational data. The urban DHS case study calculation results show a mass flow mean relative error of 3.02% and a supply/return water temperature mean relative error of 2.46%, supporting more refined dynamic scheduling.

Thermal performance of cavity masonry wall structures in the solar rich areas of Western China

Air cavities can effectively improve the thermal performance of building envelope. A cavity masonry wall (CMW) is a common and suitable envelope in the solar rich areas of Western China for integrating thermal insulation and heat storage. However, suitable structures for CMWs have not been obtained for different indoor and outdoor climates, which hinders the realization of near-zero energy buildings. In the present study, thermal performance was analyzed for different CMW structures to obtain the design method of the CMW structure. A mathematical model of CMWs was established and validated based on experiments. This model was used to analyze the effects of different structures for CMWs, and suitable structures were determined. Climate adaptability characteristics were analyzed for the suitable structures. Finally, the energy performance of buildings with CMWs was analyzed. A climate index for CMW structure design comprising the ratio of cooling relative to heating (RCH) was proposed to divide the outdoor climate, with winter heating when RCH ≤0.17, and winter heating and summer cooling when RCH >0.17. The suitable structures were obtained in different indoor and outdoor climates, where the closed air cavity was preferably placed on the low temperature side of the construction. The suitable structures exhibited better heat transfer attenuation delay characteristics to adapt to indoor and outdoor climates. It had a significant impact on the heating load compared with buildings with masonry walls, and a saving of above 10%. The design method of CMW structure proposed in this study can provide guidance for the application.

An Integrated Model Based Prediction of Machining Accuracy for Milling Machine

The accuracy of machining can be predicted during the design process of CNC machine tools, while the prediction accuracy depends on the prediction model. However, when establishing the prediction model, the coupling effect among the machine tool’s different components is always ignored for modeling efficiency, so this will lead to its reliability cannot be guaranteed. To address this problem, the model reduction theory and the lumped parameter method are used in this study to set the state-space equations of the essential structural parts. Moreover, the electro-mechanical coupling parameter equation of the servo system is transformed into a state-space equation. Then the state-space equations of the components and the servo system are coupled to establish the machine tool dynamic model. Furthermore, a theoretical model of instantaneous undeformed chip thickness is found, and according to the linear relationship between the micro-cutting force and the instantaneous undeformed chip thickness, the instantaneous cutting force model of the cylindrical milling cutter is established. Based on these, the integrated model, which considers the mechanical structure, control system and cutting force, is obtained and further used in Simulink to build the machining accuracy prediction platform, as well as the accuracy of the integrated prediction model is verified. Moreover, the prediction model established by the integrated modeling method can effectively simulate the actual machining conditions of the machine tool, and the superiority of prediction is confirmed by comparing the simulated and measured results in peripheral milling applications. The results show the error in the system response efficiency is 14.8%, while the error in position accuracy and delay characteristics is less than 10%, the error between the predicted size of the prediction model and the actual size is within 28 μm, a minimum prediction error is 7 μm.

Assessing heterogeneity of patient and health system delay among TB in a population with internal migrants in China.

The diagnostic delay of tuberculosis (TB) contributes to further transmission and impedes the implementation of the End TB Strategy. Therefore, we aimed to describe the characteristics of patient delay, health system delay, and total delay among TB patients in Shanghai, identify areas at high risk for delay, and explore the potential factors of long delay at individual and spatial levels. The study included TB patients among migrants and residents in Shanghai between January 2010 and December 2018. Patient and health system delays exceeding 14 days and total delays exceeding 28 days were defined as long delays. Time trends of long delays were evaluated by Joinpoint regression. Multivariable logistic regression analysis was employed to analyze influencing factors of long delays. Spatial analysis of delays was conducted using ArcGIS, and the hierarchical Bayesian spatial model was utilized to explore associated spatial factors. Overall, 61,050 TB patients were notified during the study period. Median patient, health system, and total delays were 12 days (IQR: 3-26), 9 days (IQR: 4-18), and 27 days (IQR: 15-43), respectively. Migrants, females, older adults, symptomatic visits to TB-designated facilities, and pathogen-positive were associated with longer patient delays, while pathogen-negative, active case findings and symptomatic visits to non-TB-designated facilities were associated with long health system delays (LHD). Spatial analysis revealed Chongming Island was a hotspot for patient delay, while western areas of Shanghai, with a high proportion of internal migrants and industrial parks, were at high risk for LHD. The application of rapid molecular diagnostic methods was associated with reduced health system delays. Despite a relatively shorter diagnostic delay of TB than in the other regions in China, there was vital social-demographic and spatial heterogeneity in the occurrence of long delays in Shanghai. While the active case finding and rapid molecular diagnosis reduced the delay, novel targeted interventions are still required to address the challenges of TB diagnosis among both migrants and residents in this urban setting.

Optimal scheduling of electric-gas-heat system considering dual virtual energy storage of gas network management and heat network storage

Aiming at the problem of wind curtailment caused by the lack of system flexibility, an optimal scheduling strategy for improving the flexibility of the electricity-gas-heat interconnection system by the coordinated operation of the gas network management and storage characteristics and the heat storage characteristics of the heat network is proposed. Firstly, the influence of gas network storage and heat network storage on improving flexibility is analyzed respectively. Then, an electricity-gas-heat interconnected system scheduling model considering the dynamic characteristics of gas network management and t the delay characteristics of heat storage in heat network, which greatly improves the imbalance between supply and demand of flexibility in space and time brought by the anti-peak regulation characteristics of wind power to the system. Finally, the IEEE-24 nodes power system, Belgium’s 20-node natural gas network and 6-node thermal network are used, for example, analysis. The results show that the proposed scheduling scheme improves the flexibility of the system while its operating cost and wind curtailment cost are the lowest, which promotes the consumption of wind power.

A Novel Bilevel Electromechanical Compound Braking Coordinated Control Strategy for Electric Vehicles

Due to the difference of response time and braking type between the motor and the pneumatic braking system, it is still difficult to coordinate the motor braking and the pneumatic braking to ensure the vehicle stability and maximal energy regeneration. To address this challenge, a bilevel electromechanical compound braking coordinated control strategy for electric vehicles is proposed considering general and emergency braking state. First, in general braking state, considering the delay characteristics of the pneumatic braking system, a Lagrange quadratic interpolation prediction algorithm is designed to start the pneumatic braking system in advance. Second, in emergency braking state, a model predictive control method is proposed to optimize the braking torque distribution while controlling the wheel slip ratio in a stable range. In order to obtain the optimal control effect, a modified adaptive cuckoo search algorithm is put forward, in which three adaptive impact factors are added. Finally, the proposed control strategy is verified under three road conditions and compared with the conventional control strategy. The results demonstrate significant improvements under gravel road condition, including a 7% increase in energy recovery efficiency, a 92.1% enhancement in the following effect of pneumatic braking torque, and a 43.5% reduction in wheel fluctuation.

An $ L_{\infty} $ performance control for time-delay systems with time-varying delays: delay-independent approach via ellipsoidal $ \mathcal{D} $-invariance

&lt;p&gt;This paper is concerned with a delay-independent output-feedback controller synthesis suppressing the $ L_{\infty} $-gain of linear time-delay systems with time-varying delays. We first proposed a continuous-time version of the existing discrete-time ellipsoidal $ {{\mathcal D}} $-invariant set and established its existence condition in terms of some linear matrix inequalities (LMIs). This existence condition was further extended to characterizing the $ L_{\infty} $-gain of linear time-delay systems with time-varying delays. Because of the delay-independent property of the proposed $ {{\mathcal D}} $-invariant set, the $ L_{\infty} $-gain analysis does not depend on the choice of delays including their magnitudes and time derivatives. Based on this analysis method, we also constructed an output-feedback controller synthesis for ensuring the $ L_{\infty} $-gain of time-delay systems bounded by a performance level $ \rho $. In an equivalent fashion to the $ L_\infty $-gain analysis method, this controller synthesis is independent of the delays in the sense that the obtained controller coefficients do not depend on the delay characteristics. Finally, numerical results were given to demonstrate the effectiveness and validity of the proposed results.&lt;/p&gt;

Stability Analysis of Sampled-Data Systems Based on Sawtooth-Characteristic-Based Hierarchical Integral Inequality.

The aim of this article is to investigate the stability of sampled-data systems (SDSs) by introducing a sawtooth-characteristic-based hierarchical integral inequality (SCBHII) and to obtain the maximum allowable sampling period that maintains the stability of the system. First, by associating the sawtooth characteristics of the input delay in SDSs with free matrices, an SCBHII is proposed; its accuracy improves as the hierarchy increases. Subsequently, a high-order two-sided looped-functional, which considers both the sampling multi-integral states and the sawtooth pattern, is introduced to cater to the aforementioned inequality. In addition, the system variables are augmented by sawtooth pattern-related terms, which eliminates the need for additional secondary processing when determining the negative-definiteness of derivatives with high-order terms. By combining the high-order two-sided looped-functional with the proposed SCBHII, a stability criterion for SDSs with reduced conservatism is achieved, presented in the form of linear matrix inequalities. The proposed inequality technique and the stability criterion are shown to be effective and superior through three numerical examples and a real-world simplified power market model.

Enabling Space-Air integration: A Satellite-UAV networking authentication scheme

One of the goals of sixth-generation mobile networks (6G) is to achieve a larger network coverage area. Satellite networks enable global coverage and aerial nodes such as Unmanned Aerial Vehicle (UAV) can serve as a supplement to ground networks in remote environments. Therefore, 6G networks are gradually evolving towards Space-Air-Ground integrated networks. The combination of UAV networks and satellite networks is a research hotspot in the field of Space-Air integrated networks. However, the combination of UAV networks and satellite networks currently faces many challenges in terms of security. The characteristics of large propagation delay and unstable communication links in satellite networks make them vulnerable to various attacks, including eavesdropping, tampering, and impersonation. Meanwhile, existing research on UAV networks mainly focuses on UAV-Ground networking authentication mechanisms, which are not suitable for resource-constrained nodes in the Space-Air integration scenario. Therefore, based on elliptic curve public key cryptography and Chebyshev polynomial, we propose a secure networking authentication scheme for satellite nodes and UAV nodes in the Space-Air integration scenario. The security analysis indicates that our scheme possesses security attributes such as mutual authentication, key agreement, identity anonymity, unlinkability, perfect forward-backward security, and resistance against various protocol attacks, among other security properties. Performance analysis also indicates certain advantages of our scheme over existing schemes in terms of signaling, bandwidth, and computational overhead.

Chaotic time delay feature cancellation and bandwidth enhancement in cascaded-coupled nanolasers

As an important part of optical sources, nanolasers have a prominent influence in photonic circuit integration, and their nonlinear dynamics has become one of the research hotspots in recent years. In this work, we investigate the time-delay signature and bandwidth characteristics in a cascade-coupled nanolaser system, in which the master nanolaser is connected to an external feedback cavity and injected into the intermediate nanolaser and the slave nanolaser sequentially. The 0-1 chaos test is introduced to quantify the dynamics of the nanolaser, which can accurately distinguish whether the laser is in a chaotic state, and the autocorrelation function is used to analyze the time-delay characteristics in the laser output signal. This type of calculation has the advantages of fast operation speed, high accuracy and anti-noise robustness. The lower the autocorrelation value, the more difficult it is to extract useful information from the chaotic random sequence. The bandwidth is defined as a value where the range between DC and frequency contains 80% of the spectral power, a value that is only applicable to chaotic states. In the simulation, we compare and analyze the two cases of whether the intermediate nanolaser has a peak with obvious time-delay signature. The research results show that by selecting appropriate system parameters, the slave nanolaser can always output a broadband chaotic signal without obvious time-delay signature. Under the condition of a certain injection intensity, by changing the frequency detuning parameter, the intermediate nanolaser has an obvious time-delay signature, and then the slave nano-laser can output chaotic signals which can suppress time-delay signature and enhance bandwidth in a small parameter interval. When the time-delay signal of the intermediate nanolaser is completely hidden, the slave nanolaser can achieve the suppression of the time-delay signature in a larger parameter plane, meanwhile the bandwidth is significantly enhanced. In addition, by plotting the two-dimensional spatial distribution diagram and bandwidth line diagram of the output from the nanolaser under frequency detuning and injection intensity, it is determined that the nanolaser can simultaneously suppress the delay characteristics and enhance the bandwidth under chaotic signals. This provides an important theoretical basis for realizing the practical applications in secrecy-enhanced chaotic optical communication.

Vehicle-to-vehicle cooperative driving model considering end-to-end delay of communication network

To explore the mechanism of the end-to-end transmission delay of the communication network on the collaborative driving process for traffic flow in the vehicle-to-vehicle communication environment, based on the idea of the car-following model, this paper introduces characteristic parameters characterizing the end-to-end transmission delay of the network into Newell's following model and proposes a CD and OV model by considering the time delay characteristics of the collaborative driving process from information transmission to control decision and then to physical execution. To determine the cooperative driving system's stability criterion, the stability analysis of the new model is examined. By using the reductive perturbation approach, the spatiotemporal evolution mechanism of the traffic flow around the critical stability point under the influence of various transmission delays is analyzed. The resulting modified Korteweg-de Vries (mKdV) equations and density wave solutions are derived. The results show that the end-to-end transmission delay of the network has a significant shock effect on the stability of the vehicle-vehicle cooperative driving system, and the stability of the traffic flow and the ability to suppress traffic congestion becomes worse with the increase in the end-to-end transmission delay.