Search

Paper (Maniar and Bhattacharyay, 2021) introduces a discrete random-walk (RW) model with a site dependent waiting time and an external force i.e. a site dependent drift. The RW is compared with a Smoluchowski equation in continuous space and time with space dependent diffusivity and space dependent damping. Using numerical simulations in Maniar and Bhattacharyay (2021) it is shown that the equilibrium distribution satisfies locally the Stokes–Einstein relation i.e. there is a constant temperature in the whole system. Here we show that the result can be recovered analytically with a continuous limit in the RW master equation. Moreover, we evidence that the RW model should be carefully defined in order to satisfy locally Stokes–Einstein relation, indeed a different definition of the discrete RW process describes a system that satisfies the Smoluchowski equation with constant damping, where the temperature is not uniform. [ABSTRACT FROM AUTHOR]

Dedicated Bus Lane (DBL) is a typical strategy to ensure priority for public transportation. However, when the frequency of bus departures is low, the DBL often remains vacant, reducing the efficiency of traffic utilization. Variable bus lane (VBL) strategy allows for the provision of service to social vehicles in specific scenarios, aiming to alleviate traffic congestion and improve emission efficiency at intersections. To analyze the impact of this strategy on dynamic queuing behavior and traffic efficiency at an isolated intersection, this paper proposes a multidimensional stochastic queuing model. The model incorporates various factors such as traffic demand, signal timing, bus arrival time, and the length of the variable area at intersections. By examining the steady-state distribution of queue length and calculating performance indicators, the effectiveness of VBL in improving intersection performance is evaluated. Numerical simulations have demonstrated that the proposed model accurately describes the vehicle queuing process at intersections under different conditions. Theoretical analysis confirms that the implementation of VBL strategy can effectively improve traffic efficiency at intersections and minimize the queue length of vehicles. [ABSTRACT FROM AUTHOR]

This paper focuses on platoon control of autonomous vehicles (AVs) equipped with V2X technology and the phenomenon that the large platoons are split into multiple sub-platoons due to the communication restrictions. At the same time, with the popularity of AVs and connected human-driven vehicles (CVs), this paper also carries out the research of mixed traffic flow mixed with AV platoons, CVs and regular human-driving vehicles (RVs). According to the characteristics of the different types of vehicles, this paper extends the corresponding car-following models based on intelligent driver model (IDM), and considers the functional degradation of AVs under different car-following modes. In this paper, the AVs are classified into the second-level degenerated AV (D2AV), the first-level degenerated AV (D1AV) and the normal functioning AV (NAV) based on the differences in car-following modes. The degradation of AVs is represented via the change of communication topologies and models. Linear stability analysis is conducted. Numerical simulation shows that the higher level of AV degradation, the worse the stability of traffic flow. Under the same conditions, the more sub-platoons and the larger maximum size of sub-platoons, the better the stability of the traffic flow. The increase in communication strength of AVs is also beneficial to stability of traffic flow. In order to compensate for degradation, an adaptive gain feedback control strategy is proposed. Simulation shows that the adaptive gain feedback strategy can effectively improve the ability of the traffic flow to resist disturbances, reduce the fluctuations of velocity and acceleration, and contribute to the stability of platoon system and traffic flow. • A general car-following models are established, including eight types of vehicles. • Considering graded degradation, linear stability analysis is conducted. • Exploring the effect of the various factors of sub-platoon on traffic stability. • Proposing an adaptive gain feedback control strategy and proving its effectiveness. [ABSTRACT FROM AUTHOR]

The continuity of acceleration changes is often overlooked by existing car-following models, leading to a limitation in capturing realistic driving dynamics for emission estimation, which are essential for the application in microscopic traffic evaluations. This paper investigated and modeled the jerk-constrained acceleration stochastic process using the Markov model. A new car-following model considering the acceleration stochastic process was proposed, which incorporated two modes of unconscious following and active acceleration approaching. Additionally, a bi-objective model calibration framework was introduced to balance the trade-off between traffic-related performance and emission estimation performance. Numerical simulation was conducted to compare the performance of the new model with the conventional Wiedemann model. Results demonstrated that the proposed model provides more realistic vehicle dynamics and accurate emission estimations. Specifically, compared to the Wiedemann model, the new model reduced the root-mean-square error (RMSE) of spacing headway by 0.73 m and the RMSE of vehicle-specific power (VSP) distribution by 11.57%. • Jerk-constrained stochastic acceleration process was modeled with the Markov model. • Proposing a new car-following model considering the stochastic acceleration process. • The new model provides realistic vehicle dynamics and accurate emission estimations. • A bi-objective model calibration framework was introduced for emission estimation. [ABSTRACT FROM AUTHOR]

Time series could be mapped into complex networks through the visibility or horizontal visibility algorithms, and the properties of the constructed network reflect the nonlinear dynamics of the time series. When horizontal visibility algorithm is directly applied to climate anomaly time series, in which both local maximum and local minimum are equally important, local minimum might be "overlooked". In this paper, we propose a new method that maps climate anomaly time series into signed networks. Positive and negative data values of climate anomaly time series are classified into two types and mapped as nodes of signed networks. Links connecting nodes of the same type are assigned positive signs, while links connecting neighboring nodes of different types are assigned negative signs. This method is also applicable to time series those are assumed to be "stationary" or with no significant trends. Four kinds of degree as well as the degree distributions of the signed networks have been defined. Specifically, the degree and degree distribution could be partly derived analytically for periodic and uncorrelated random time series. The theoretical predictions for periodic and uncorrelated random time series have also been verified by extensive numerical simulations. Based on the entropy of the distribution of net degree, we propose a new complexity measure for chaotic time series. Compared to some previous complexity measures, the new complexity measure is an objective measure without transforming continuous values into discrete probability distributions but still has higher accuracy and sensitivity. Moreover, correlation information of stochastic time series can also be extracted via a topological parameter, the mean of ratio degree, of the signed networks. The extraction of serial correlation has been illustrated through numerical simulations and verified through an empirical climate time series. • A new method mapping time series into signed networks has been proposed. • Degree distributions have been derived for periodic and random time series. • A complexity measure based on signed networks has been proposed. • Correlation information of time series can be extracted from signed networks. [ABSTRACT FROM AUTHOR]

Distributed statistical inference has received enormous attracted attention in recent years. In this paper, a novel communication efficient one-step estimator on a distributed system is presented, which only needs one round of communication, effectively lowers the communication cost and sufficiently reduces the local computation complexity compared with the existing one-step method. The resulting estimator is statistically efficient as that the entire dataset is analyzed on one machine. Under mild conditions, a risk upper bound is established and the consistency together with asymptotic normality is demonstrated for the proposed estimator. Finally, numerical simulations are carried out to conform the theoretical result. [ABSTRACT FROM AUTHOR]

In the real word, the periodic disturbance in traffic flow caused by disrupting maneuvers has a huge impact on the car-following stability. As analyzed in this paper, the asymptotic stability of a car-following model, quantified by the coefficient of dynamic responses, is relatively low at low disturbing frequencies, and gradually increases as the disturbing frequency increases. Fortunately, the development of connected and automated vehicle (CAV) technology and the existing researching works on CAV platoon control have shown great prospect of CAV platooning in the improvement of car-following stability. In order to develop a method to manage the CAV platooning with the explicit purpose of optimizing the car-following stability under periodic disturbance, this study presents an autonomous platoon formation strategy (APFS) for CAV platoon. At certain disturbing frequency, APFS can automatically split a large CAV car-following group into a leading CAV and a number of small CAV platoons, and all CAVs in each platoon follow either the last CAV in the previous platoon or the leading CAV, abiding by the newly designed platoon-based IDM (P-IDM) car-following strategy, so that the overall car-following stability of the CAV group can be optimized. Results of numerical simulations demonstrate that, compared with several existing platoon control strategies, the proposed APFS is capable of significantly enhancing the stability of CAV car-following group, as well as passenger comfort and fuel economy of CAVs, under various types of periodic disturbance. In general, APFS works most effectively when the disturbing frequency is around 0.4 ∼ 0.6 rad/s. Therefore, the proposed APFS shows good potentials in mitigating the oscillation in traffic flow due to periodic perturbations and improving the asymptotic stability of CAV car-following groups. • The asymptotic stability of car-following model under periodic disturbance is analyzed. • A coefficient of dynamic response is defined to quantify the car-following stability under periodic disturbance. • A platoon-based IDM (P-IDM) strategy is designed to elevate the car-following stability of CAV platoon. • An autonomous platoon formation strategy (APFS) is proposed to optimize the car-following stability of CAV platoon. [ABSTRACT FROM AUTHOR]

In this paper, we study the horizontal visibility graphs mapped from multifractal trinomial measures, which are determined by three parameters, p 1 , p 2 , and p 3 , where 0 < p 1 < p 2 < p 3 < 1 , p 1 + p 2 + p 3 = 1. First, we regard multifractal trinomial measures as time series and map them into horizontal visibility graphs. Then, we study the degree distributions in the three cases of p 1 p 3 = p 2 2 , p 1 p 3 > p 2 2 , and p 1 p 3 < p 2 2 . Due to the self-similarity of the induced graphs, the degree distributions of the series are derived using an iterative method. And the numerical simulations coincide excellently with the theoretical degree distributions. • HVGs mapped from multifractal trinomial measures are studied. • Degree distributions of HVGs are derived in an iterative method. • The numerical results obtained support the theoretical analysis. [ABSTRACT FROM AUTHOR]

This paper proposes a novel cascading failure dynamics model for duplex weighted network with unequal flow distribution between layers and taking into account the collapse probability of overloaded nodes. Firstly, the parameter of failure elasticity is introduced to the redundancy capacity of the nodes to carry the load, and the expressions for the tolerance threshold of the entire network in different cases are derived. In addition, the cascading failure processes caused by different deliberate attack strategies are simulated on idealized networks and the IEEE39 network, respectively. Inflection points for the effectiveness of the two attack strategies are obtained, and tolerance thresholds of the theoretical calculations are compared and analyzed with the results of the numerical simulations. Meanwhile, our results indicate that the collapse probability and the redistribution rule are vital in the vulnerability of the network, and the protection mechanism is more effective against attacks on the node of lowest load. Finally, the duplex network becomes more robust as the parameter of failure elasticity increases. Furthermore, the tolerance threshold of the networks presents an ascending trend after dropping initially as the inter-layer distribution proportion increases, and the trend of the numerical simulation is consistent with the theoretical analysis. • A novel cascading failure model of two-layer weighted networks is presented. • We derive the expression of the tolerance threshold for overall duplex network. • Inflection points for the effectiveness of the two attack strategies are obtained. • Duplex networks become more robust as the parameter of failure elasticity increases. [ABSTRACT FROM AUTHOR]

This paper proposes a novel quantum image encryption algorithm based on a local substitution and global permutation scheme. First, a plaintext-related secret key is generated by using a hyperchaotic system; second, the plain image is scrambled employing a block-based general Arnold transform and permutation-based special linear transform; third, S-box substitution and special linear transform are iterated multiple times until certain conditions are achieved. A novel controlled alternated quantum walks scheme is also proposed to generate substitution boxes. Numerical simulation shows that the proposed encryption scheme can effectively a encrypt plain image to an incomprehensible noise image, and is capable of resisting a variety of attacks. • The quantum circuit of Arnold transform with keys is designed to improve hardware application. • This paper proposes a new two-particles quantum walks scheme. • The quantum implementation of S-box substitution is given to improve the encryption efficiency. [ABSTRACT FROM AUTHOR]

From the perspective of driver's visual characteristics, based on the influence of the two-point preview steering decision and stopping sight distance on the car-following behavior in small-radius curves, the new car-following model considering driver's desired visual angle on curved roads is proposed in this paper. The dynamic performance and safety of the new model are explored subsequently. First, the neutral stability condition of the new model is derived by linear stability analysis. Then, the evolution process of small disturbance of traffic flow is analyzed by numerical simulation, and the same conclusion of linear stability is obtained. That is, introducing the effect of the driver's desired visual, designing a reasonable curve radius, and the large vehicle becoming the leading vehicle is conducive to improving the stability of the traffic flow and effectively alleviating traffic congestion. Finally, the safety of the new model is analyzed by using the stopping sight distance, which shows that the newly introduced factor can also effectively improve the safety of car-following behavior on curved roads. • The desired visual angle following model for small radius curves is proposed. • Two-point preview steering decision is considered in the new car-following model. • The safety of the car-following model was evaluated using the stopping sight distance on the curved road. • The stability condition of the new model is deduced. [ABSTRACT FROM AUTHOR]

Twin-field quantum key distribution (TF-QKD) can overcome the fundamental rate-loss limit in the point-to-point QKD without a quantum repeater, so as to realize key distribution over long distance. In general, weak coherent pulse (WCP) emitted from the attenuated laser is often used as the photon source for TF-QKD and its variants, however, the key generation rate and transmission distance may be restricted for TF-QKD protocols using this type of photon source as it contains a large proportion of vacuum part. Another candidate of photon source within reach of current technology is the heralded single-photon source (HSPS). In this paper, we propose two TF-QKD variants with HSPS and provide the analytical derivation of upper bounds of yields separately with active and passive decoy-state methods. Numerical simulations show that the active decoy-state TF-QKD with HSPS (referred to as Protocol (1) achieves higher secret key rate and tolerates more large transmission loss than the original TF-QKD with WCP source. However, since the active modulation of decoy intensities may leak additional information to the eavesdropper Eve, thus we extend the result of Protocol 1 and further propose a passive decoy-state TF-QKD with HSPS (referred to as Protocol (2). The simulation results demonstrate that the performance of Protocol 2 is close to the original active TF-QKD protocol, and its security and flexibility are further improved. • An efficient passive twin-field quantum key distribution with heralded single-photon source is proposed. • Deriving the tighter upper bounds on yields separately with active and passive decoy-state methods. • Performance advantage of heralded single-photon source in quantum key distribution is demonstrated. • Passive twin-field quantum key distribution provides a comparable performance to current protocols. [ABSTRACT FROM AUTHOR]

The coordination and the energy consumption are very important for the platooning of connected and automated vehicles (CAVs). A novel cooperative optimal control for CAVs platoon on basic freeway sections is proposed in this paper. A cost function is designed to address the cooperation of followers, the motion synchronization with the leading vehicle and appropriate energy consumptions. A third-order consensus strategy is suggested to design the control input. A more effective and flexible spacing strategy is introduced. The asymptotically stability and string stability conditions of the system are established. By constructing and solving the LMI optimization problem, the optimal control gains are derived and the global cost function is minimized to a specific upper bound. Numerical simulations are performed on several specific traffic scenarios. The results demonstrate the effectiveness of the presented modeling method. • A novel cooperative optimal control method for CAVs platoon is developed. • A cost function is designed to achieve the cooperative performance and appropriate energy consumption. • A third-order consensus strategy is proposed to design the control input. • The stability conditions and optimal control gains are derived. [ABSTRACT FROM AUTHOR]

This paper studies the collective dynamic behaviors of a general adjacent coupled chain under a periodic driving force and dichotomous noise in both unconfined and confined spaces. The precise conditions for the stability, synchronization, and stochastic resonance (SR) of the system in an unconfined space were analytically derived and verified by numerical algorithms. The stability and synchronization of the adjacent coupled chain in the unconfined space were found to be related to the system and noise parameters. The collective dynamic behaviors of the adjacent coupled chain in the confined space were also analyzed through numerical simulations, and it was found that due to boundary constraints, the adjacent coupled chain consistently achieves stability and synchronization in the confined space. Moreover, when compared with the unconfined system, the output amplitude of the confined system exhibits more complex SR phenomena, such as double-peak SR, multi-peak SR, superharmonic SR and so on. [ABSTRACT FROM AUTHOR]

The propagation and evolution of risks in the system adversely affects the safety of automated terminal handlings. Therefore, it is necessary to explore the formation and development process of handling risks, predict the path and pattern of risk propagation and summarize the evolution features to improve the efficiency of multi-level handlings at automated terminals (ATMH). This paper proposes a double-layer dynamics risk propagation and evolution model. First, a complex network of risk relationships is established, and the Gillespie algorithm is employed to simulate the risk propagation dynamics based on the metric of state transition value and the dynamic mean-field theory. Next, an evolution hypernetwork is constructed and the average smooth hyperdegree distribution is derived using Poisson process and continuity methods. The simulation results show that the risk propagation link group obtained by the empirical testing is credible. The theoretical predictions of risk evolution agree well with the numerical simulations. The greater the probability of risk propagation, the more active the evolution. The model provides a certain theoretical reference for the risk management of automated terminals. • A risk propagation and evolution model based on complex network and hypernetwork. • State transition combined with mean-field theory to calculate infection probability. • Quantify risk propagation probabilities and simulate dynamic processes. • The constructed risk evolution hypernetwork has good scale-free characteristics. • The greater the probability of risk propagation, the more active of risk evolution. [ABSTRACT FROM AUTHOR]

The waiting processes of both passengers and taxis at taxi stand of transport hubs are a complicated random queueing problem because of some typical random characteristics, including the random number of passengers carried by per taxi, random arrival behaviors of passengers, and taxis, random length of boarding time for a batch of passengers, etc. In particular, the arriving process of passengers at transport hubs often has multiple uncertain peak hours within a day, which makes the waiting times of both the passengers and the taxis highly variable and unpredictable at a certain time. Hence, it is necessary to explore and understand the dynamic queues of the passengers and taxis through fully studying the random nature of this system. In this paper, a matching model with two random inputs is developed to simulate the dynamic queueing behaviors of passengers and taxis by considering the random features of the matching number of passengers, matching time, and time-dependent arrival processes, etc. We obtain some important quantities of queues along the time. A series of numerical simulations is conducted to find how the queues of passengers and taxis are affected by the most possible factors. The proposed model in this paper can provide a methodological possibility of clarifying the dynamic queues of passengers and taxis for not only the computer simulation but also the statistical inference, and will further help to improve the service of the passenger–taxi system. • A matching queueing model is proposed to depict the queues of passenger and taxi. • Typical random characteristics of passengers and taxis are considered. • Quantitative measures related the passengers' and taxis' queues are obtained. • Factors that can affect queue behaviors are clarified. [ABSTRACT FROM AUTHOR]

This paper discusses the theoretical analysis and microcontroller implementation of resistive–capacitive shunted Josephson junction (JJ) with unharmonic current-phase relation. The rate equations describing the system under study exhibit no, two, or four equilibrium points and their stability are investigated.The presence of Pitchfork bifurcation depends on the unharmonic parameter and the external direct current (DC) source. The hysteresis of current–voltage characteristics in resistive–capacitive shunted JJ with unharmonic current-phase relation is sensitive to the unharmonic parameter. The system under study exhibits periodic oscillations, continuous spiking oscillations, periodic bursting oscillations, and chaotic attractors with varying shapes which are sensitive to the modulation and unharmonic parameters. Finally, the microcontroller implementation of resistive–capacitive shunted JJ with unharmonic current-phase relation is realized and the microcontroller results are qualitatively the same as those obtained during the numerical simulations. • Resistive–capacitive shunted JJ with a high temperature. • Complex dynamical properties investigated. • Microcontroller implementation with validated the obtained results. [ABSTRACT FROM AUTHOR]

In this paper, the bifurcation control for a fractional-order delayed prey-predator system with disease and cannibalism is investigated. Firstly, the existence, uniqueness and non-negativity of the solutions are studies, and the stability of equilibrium points are discussed. Next, taking time delay as the bifurcation parameter, the conditions of creation for Hopf bifurcation are confirmed. Then, two feedback controllers are introduced, which successfully control the Hopf bifurcation, and bifurcation control of the two controllers are simply compared theoretically. Finally, numerical simulations show that cannibalism has an significant influence in controlling the stability of the model, and when the parameters are appropriate, the disease can be removed. Meanwhile, the feedback controllers can control the bifurcation well. In general, the control effect of time-delay feedback controller should be better than that of traditional feedback controller. However, we found that the control effect of the traditional feedback controller is better than the time-delay feedback controller, the control effect completely depends on the selection of parameters. [ABSTRACT FROM AUTHOR]

The global μ -synchronization problem of nonlinear drive–response complex networks with uncertainties is investigated in this paper. Unbounded multiple time delays, such as internal delays, coupling delays, and sampling delays in impulse instants are considered in our complex network model. The difficulties caused by these multiple time delays are overcome by introducing a generalized impulsive delayed comparison principle. A delayed impulsive controller is designed, and some novel synchronization criteria are derived in order to make drive–response complex networks achieve μ -synchronization. Compared with the existing related works, there is no restriction about impulse intervals and delays, as well as, the external coupling matrix is no longer needed to satisfy the dissipative coupling condition. Finally, two numerical simulations are shown to present the correctness of our theoretical results. [ABSTRACT FROM AUTHOR]

In most signalized intersections, in order to solve the problem of insufficient road space, left-turn bays are commonly set up at intersections with a shared through and left-turn lane. However, this design tends to result in the potential queue overflow and blockage problems, which further make the discharge process of either left-turn vehicles or through vehicles at the intersections to be interrupted unexpectedly during their respective green phase. As a result, the queueing processes of vehicles present high nonlinearity and uncertainty during a signal cycle. In this paper, a stochastic queueing model is proposed to characterize the dynamics and uncertainty of queues at signalized intersections with a left-turn bay. The proposed model takes full account of the random interaction between the through movement and the left-turn movement under the influence of overflow and blockage of queues. We obtain some average performance indicators as well as the signal-state-dependent dynamic performance measure of queues and its variance at any given time point within a signal cycle. The proposed analytical model is validated against the VISSIM simulation model under different scenarios; the results show a good degree of agreement. In addition, in order to systematically determine the queue dynamics and uncertainty, we also conduct a series of numerical simulations to quantitatively capture the queue characteristics of vehicles at signalized intersections with left-turn bay by considering possible factors. • Develop a stochastic model to describe the queues at signals with left-turn bay. • Random interactions between the different movements are focused. • Signal-state-dependent dynamic performance measures of queues are obtained. • Factors that can affect the queue dynamics are examined. [ABSTRACT FROM AUTHOR]

The research of chiral particles is of great significance to understanding the collective behavior of biomolecules. In this paper, we research the collective motion of chiral particles based on the Vicsek model using computer numerical simulations. When there is no noise, it is found that there is a critical coupling density ρ c. When the coupling density of the particle is smaller than the critical coupling density, the order parameter of the particle will decrease with the increase of the chirality. When the coupling density is greater than the critical coupling density, the order parameter does not change with the chirality. In addition, the critical coupling density decreases as the particle number N and decoupled parameter L / r increase, but first decreases and then increases as the decoupled parameter v / r increases. Further, when there is noise, the order parameter of the particle with small coupling density or small noise amplitude will decrease with the increase of chirality, whereas the order parameter with large coupling density or large noise amplitude will not change. Our results improve the collective motion properties of chiral self-propelled particles. Besides, our work may inspire new strategies for manipulating self-propelled particles with different chirality to maintain a highly ordered state. • There exists a critical coupling density ρ c. • Order parameter decreases with the increase of the chirality when ρ < ρ c . • Order parameter does not change with the chirality when ρ > ρ c . • Order parameter with small coupling density or small noise amplitude will decrease with the increase of chirality. • Order parameter with large coupling density or large noise amplitude will not change casually. [ABSTRACT FROM AUTHOR]

A supply chain system can be considered as an interdependent supply chain network (ISCN) which consists of an undirected cyber-network and a directed physical-network. To survive against disruptions, an ISCN needs to maintain operations and connectedness, referred to as robustness. Studies on the robustness of ISCNs when considering both functional and structural cascading failures are still scarce. In this paper, we first propose a cascading failure model which considers these two cascading failures simultaneously. We also present a model to generate ISCNs with different network types and interconnecting patterns. Using the transition threshold based on the proposed all-type connected sub-network, we can evaluate the robustness of ISCNs more properly. We then conduct numerical simulations to investigate how some parameters (e.g., network type, interconnecting pattern, the distribution of different types of nodes, etc.) affect the robustness of ISCNs under random and targeted disruptions. The results mainly show that the robustness of ISCNs can be affected seriously by different network types, interconnecting patterns, and disruption types; and the distribution of different types of nodes is more uniform, the corresponding ISCN is more robust, no matter what the disruption type is. Our results may provide help for building robust ISCNs. • We proposed a model to generate ISCNs with different network types and interconnecting patterns. • We proposed a concept of sub-network called all-type connected sub-network. • We construct a cascading failure model considering both functional and structural cascading failures. • The distribution of different types of nodes is more uniform, the corresponding ISCN is more robust. [ABSTRACT FROM AUTHOR]

The heterogeneity in edge weights plays a crucial role in the spread of a rumor on networks. To investigate the effects of weight distribution on a rumor spreading, we employ an ISR pairwise model on weighted regular random networks in this paper. The basic reproductive ratio of this model is derived, and it indicates that the heterogeneity in transmission rate leads to a fall in the basic reproductive ratio when the average transmission rate is fixed. Besides, by assuming that the transmission rate is a linear function of the edge weight, numerical simulation results of the model on networks with a bimodal weight distribution show that weight heterogeneity has a complex impact on the dynamics of a rumor. When we fix the proportions of two weights but vary their values to keep a constant average weight, increasing the heterogeneity in weight distribution slows down the initial growth rate, the final size and the maximum influence of a rumor, but increases the duration for rumor spreading. However, if we change both the values and proportions of two weights, only the mean and variance of the weight distribution are not able to provide sufficient information to predict the dynamics of a rumor. Moreover, we get similar simulation results in the case of nonlinear transmission rate. [ABSTRACT FROM AUTHOR]

In the connected vehicle environment, a vehicle can obtain the information of multiple front and rear vehicles. This driving strategy of bi-directional visual field and multiple anticipation can be implemented to traffic flow modeling. In this paper, an extended car-following model with consideration of bi-directional visual field and multiple anticipation is proposed. A novel macroscopic traffic flow model is developed based on the relationship between the microscopic and macroscopic variables, and the validity of the model is confirmed through the theoretical and numerical studies. The stability analysis shows that the multiple anticipation can improve the stability of traffic flow, and the results of numerical simulation illustrates that the new model can reproduce the local clustering phenomenon of traffic flow. • An extended car following model in the connected vehicle environment is proposed. • A multi-anticipative bi-directional visual field macroscopic model is developed. • The stability of the model is analyzed. [ABSTRACT FROM AUTHOR]

Understanding the robustness of real-world complex systems is a key step to design reliable systems and maintain their stability and normal functions. In this paper, we propose a flow redistribution model in two-layer multiplex network and study its cascading dynamics, where an initial edge failure may cause large cascading failure through the network. In our model, initially an edge on layer A fails and a proportion a of flow on the edge is redistributed to the overlap link in layer B if there exists one, while the remaining (1 − a) proportion of flow is redistributed under a local weighted flow redistribution rule. Similarly a proportion b of flow of a failed edge in layer B is redistributed to the overlap link in layer A. The cascading failure continues until a steady state is reached. We analytically calculate the resilience threshold of the network and validate it by numerical simulations. We firstly find that there is an optimal weighting of edge flow at which the robustness of the system is the highest. Then we find that for the two coupled layers of networks with obviously different resilience, the layer with smaller resilience benefits from the coupled system while the robustness of the layer with larger resilience is damaged due to inter-layer cascading process. The coupled system is the most robust when the inter-layer degree correlation is maximally positive. • There is an optimal weighting of edge flow at which the robustness is the highest. • The layer with smaller resilience benefits more from the coupled system. • The network is the most robust when the degree correlation is maximally positive. [ABSTRACT FROM AUTHOR]

In this paper, we propose a class of growth models, named Fibonacci trees F (t) , with respect to the nature of Fibonacci sequence { F t }. First, we show that models F (t) have power-law degree distribution with exponent greater than 3. Then, we analytically study two significant topological indices, i.e., optimal mean first-passage time (O M F P T) and mean first-passage time (M F P T), for random walks on Fibonacci trees F (t) , and obtain the analytical expressions using some combinatorial approaches. The methods used are widely applied for other network models with self-similar feature to derive analytical solution to O M F P T or M F P T , and we select a candidate model to validate this viewpoint. In addition, we observe from theoretical analysis and numerical simulation that the scaling of M F P T is linearly correlated with vertex number of models F (t) , and show that Fibonacci trees F (t) possess more optimal topological structure than the classic scale-free tree networks. [ABSTRACT FROM AUTHOR]

This paper proposes a continuum model based on a three-dimensional flow-concentration surface for multi-class traffic. The model assumes that the flow of any vehicle class is a function of the class density as well as the fraction of road area occupied by other vehicle classes. By considering occupancy of road area instead of lane occupancy, the model effectively describes traffic flow that does not follow lane discipline. The propagation speed of small disturbance (PSSD), conventionally defined from the two-dimensional flow–density relationship, is reformulated for each class using a three-dimensional flow–concentration surface. Using the proposed PSSD and a speed–area occupancy (speed- A O) relationship, a second-order continuum model for multi-class traffic is formulated. The speed– A O relationship captures class-specific congestion and replicates the gap-filling behaviour commonly observed in lane-indisciplined traffic. Properties of the proposed model are validated theoretically where possible, and through numerical simulation when theoretical derivations are cumbersome. Numerical simulation of the proposed multi-class traffic model replicates field-observed phenomena such as shockwaves and rarefaction waves, local cluster effect, and gap-filling behaviour. Finally, the model is calibrated using field traffic data collected on a road section with bottleneck, and is found to replicate class-wise vehicle flows and speeds, and stop-and-go phenomena. • Use of a three-dimensional flow–concentration surface for multi-class traffic. • Analytical formulation of class-wise propagation speeds of small disturbances (PSSD) for multi-class traffic. • A novel higher-order model that does not restrict the number of vehicle classes. • Analytical proofs and numerical checks of fundamental traffic flow properties. • Calibration of the model with real-world multi-class traffic flow data. [ABSTRACT FROM AUTHOR]

Different from the existing lattice model that considers the impact of a single ramp on the traffic flow in a closed single-lane traffic flow this paper considers a traffic flow model with dual ramps, including one on-ramp and one off-ramp, and further studies the influence of the position relationship between consecutive ramps. Based on previous studies which show that historical speed and historical headway information have a positive effect on traffic in a closed single-lane environment, the historical flow information is introduced to study the ability of historical flow information to correct road instability caused by ramp crossings. Through linear analysis theory, we obtain the neutral stability curve and the stability critical condition of the model. Then we verify the results of the previous theoretical analysis through numerical simulations. [ABSTRACT FROM AUTHOR]

In this paper, combining with the empirical particulate emission model, we studied Particulate Matter (PM) emission of two typical cellular automata traffic models (VDR and TT models) with slow-to-start rules under periodic boundary condition and open boundary condition. Numerical simulations show the two slow-to-start models have different emissions under the same initial and boundary conditions. Under periodic boundary condition, the metastable traffic flow emits the most particulate matter for VDR model, and the traffic flow in decelerated state emits the most. For TT model, the vehicles with the most emissions are those in the state of traffic congestion and deceleration. Moreover, the emission characteristics of particulate matter in the two models are analyzed and compared. Under open boundary condition, the resulting phase diagram and flux diagram to reflect traffic congestion are obtained. Research shows that the injection probability and removal probability have a great impact on PM emissions. Numerical simulation displays that the trend of particulate emission varies with the different state of vehicle movements in spite of the same removal probability. For different removal probabilities, different maximum particle concentrations are emitted from traffic flows in the same movement state. Moreover, the emission of VDR model is significantly different from that of TT model in vehicle deceleration state. • Particulate Matter (PM) emission of two typical cellular automata traffic models with slow-to-start rules under periodic boundary condition and open boundary condition was studied. • Under periodic boundary condition, numerical simulations display the metastable traffic flow emits the most particulate matter for VDR model. For TT model, the vehicles with the most emissions are those in the state of traffic congestion and deceleration. • Under open boundary condition, numerical simulations show that the injection probability and removal probability have a great impact on PM emissions. [ABSTRACT FROM AUTHOR]

In this paper, we investigate an SIR epidemic model with varying population sizes and regime switching in a two patch setting. Sufficient conditions for extinction and persistence in the mean of the diseases are obtained. In addition, we establish sufficient conditions for the existence of positive recurrence of the solutions to the model in the case of persistence by constructing a suitable stochastic Lyapunov function with regime switching. Finally, numerical simulations are performed to test our theory conclusion. • An SIR epidemic model with regime switching in a two patch setting is proposed. • The dynamic behaviors of the system are studied. • We establish sufficient conditions for extinction and persistence of the diseases. • The existence of positive recurrence of the solutions to the model is obtained. • Numerical simulations are performed to test our theory conclusion. [ABSTRACT FROM AUTHOR]