Effect of looking at the car that follows in an optimal velocity model of traffic flow

Stability and energy consumption analysis of arctic fleet: modeling and simulation based on future motion of multi-ship

Ensuring the safety of Arctic shipping and preserving the Arctic ecological environment are emerging as key challenges in the shipping sector. Ship collisions and getting trapped in ice are frequently occurring under dynamic ice conditions due to the Arctic environment, making research on ship navigation in Arctic routes significant. Leveraging ship networking technology, we developed an intelligent microscopic model which considered factors such as the future motion trends of multi-ships in front and the influence of pack ice, and carried out a stability analysis of the model utilizing linear and nonlinear methods. Additionally, the accuracy of the theoretical results was further validated through simulation experiments with diverse scenarios. The conclusions manifest that the model can magnify the anti-disturbance ability of traffic flow. Additionally, the problem of energy consumption due to ship speed is explored, and it is determined that the model has a positive intention in reducing speed fluctuations and ship energy consumption. This paper highlights the potential of intelligent microscopic models in studying the safety and sustainability of Arctic shipping routes, providing targeted initiatives to improve safety, efficiency, and sustainability in Arctic shipping.

Exploring Safety-Stability Tradeoffs in Cooperative CAV Platoon Controls with Bidirectional Impacts

Advanced sensing technologies and communication capabilities of Connected and Autonomous Vehicles (CAVs) empower them to capture the dynamics of surrounding vehicles, including speeds and positions of those behind, enabling judicious responsive maneuvers. The acquired dynamics information of vehicles spurred the development of various cooperative platoon controls, particularly designed to enhance platoon stability with reduced spacing for reliable roadway capacity increase. These controls leverage abundant information transmitted through various communication topologies. Despite these advancements, the impact of different vehicle dynamics information on platoon safety remains underexplored, as current research predominantly focuses on stability analysis. This knowledge gap highlights the critical need for further investigation into how diverse vehicle dynamics information influences platoon safety. To address this gap, this research introduces a novel framework based on the concept of phase shift, aiming to scrutinize the tradeoffs between the safety and stability of CAV platoons formed upon bidirectional information flow topology. Our investigation focuses on platoon controls built upon bidirectional information flow topologies using diverse dynamics information of vehicles. Our research findings emphasize that the integration of various types of information into CAV platoon controls does not universally yield benefits. Specifically, incorporating spacing information can enhance both platoon safety and string stability. In contrast, velocity difference information can improve either safety or string stability, but not both simultaneously. These findings offer valuable insights into the formulation of CAV platoon control principles built upon diverse communication topologies. This research contributes a nuanced understanding of the intricate interplay between safety and stability in CAV platoons, emphasizing the importance of information dynamics in shaping effective control strategies.

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.

The Car-Following Model and Its Applications in the V2X Environment: A Historical Review

The application of vehicle-to-everything (V2X) technology has resulted in the traffic environment being different from how it was in the past. In the V2X environment, the information perception ability of the driver–vehicle unit is greatly enhanced. With V2X technology, the driver–vehicle unit can obtain a massive amount of traffic information and is able to form a connection and interaction relationship between multiple vehicles and themselves. In the traditional car-following models, only the dual-vehicle interaction relationship between the object vehicle and its preceding vehicle was considered, making these models unable to be employed to describe the car-following behavior in the V2X environment. As one of the core components of traffic flow theory, research on car-following behavior needs to be further developed. First, the development process of the traditional car-following models is briefly reviewed. Second, previous research on the impacts of V2X technology, car-following models in the V2X environment, and the applications of these models, such as the calibration of the model parameters, the analysis of traffic flow characteristics, and the methods that are used to estimate a vehicle’s energy consumption and emissions, are comprehensively reviewed. Finally, the achievements and shortcomings of these studies along with trends that require further exploration are discussed. The results that were determined here can provide a reference for the further development of traffic flow theory, personalized advanced driving assistance systems, and anthropopathic autonomous-driving vehicles.

Controlling the Connected Vehicle with Bi-Directional Information: Improved Car-Following Models and Stability Analysis

Connected vehicle (CV) technologies are changing the form of traditional traffic models. In the CV driving environment, abundant and accurate information is available to vehicles, promoting the development of control strategies and models. Under these circumstances, this paper proposes a bidirectional vehicles information structure (BDVIS) by making use of the acceleration information of one preceding vehicle and one following vehicle to improve the car-following models. Then, we deduced the derived multiple vehicles information structure (DMVIS), including historical movement information of multiple vehicles, without the acceleration information. Next, the paper embeds the four kinds of basic car-following models into the framework to investigate the stability condition of two structures under the small perturbation of traffic flow and explored traffic response properties with different proportions of forward-looking or backward-looking terms. Under the open boundary condition, simulations on a single lane are conducted to validate the theoretical analysis. The results indicated that BDVIS and the DMVIS perform better than the original car-following model in improving the traffic flow stability, but that they have their own advantages for differently positioned vehicles in the platoon. Moreover, increasing the proportions of the preceding and following vehicles presents a benefit to stability, but if traffic is stable, an increase in any of the parameters would extend the influence time, which reveals that neither β₁ or β₂ is the biggest the best for the traffic.

Response and flux of information in extended nonequilibrium dynamics

It is well known that entropy production is a proxy to the detection of nonequilibrium, i.e., of the absence of detailed balance; however, due to the global character of this quantity, its knowledge does not allow to identify spatial currents or fluxes of information among specific elements of the system under study. In this respect, much more insight can be gained by studying transfer entropy and response, which allow quantifying the relative influence of parts of the system and the asymmetry of the fluxes. In order to understand the relation between the above-mentioned quantities, we investigate spatially asymmetric extended systems. First, we consider a simplified linear stochastic model, which can be studied analytically; then, we include nonlinear terms in the dynamics. Extensive numerical investigation shows the relation between entropy production and the above-introduced degrees of asymmetry. Finally, we apply our approach to the highly nontrivial dynamics generated by the Lorenz 96 model for Earth oceanic circulation.

Correlations and responses for a system of n coupled linear oscillators with asymmetric interactions

We focus on the asymmetry of the interaction in the optimal velocity (OV) model, which is a model of self-driven particles, and analytically investigate the effects of the asymmetry on the fluctuation-response relation, which is one of the remarkable relationships in statistical physics. By linearizing a modified OV model, i.e., the backward-looking optimal velocity model, which can easily control the magnitude of asymmetry in the interaction, we derive n coupled linear oscillators with asymmetric interactions. We analytically solve the equations of the n coupled linear oscillators and calculate the response and correlation functions. We find that the fluctuation response relation does not hold in the n coupled linear oscillators with asymmetric interactions. Moreover, as the magnitude of the asymmetry increases, the difference between the response and correlation functions increases .

Cluster statistics and quasisoliton dynamics in microscopic optimal-velocity models

Using the non-linear optimal velocity models as an example, we show that there exists an emergent intrinsic scale that characterizes the interaction strength between multiple clusters appearing in the solutions of such models. The interaction characterizes the dynamics of the localized quasisoliton structures given by the time derivative of the headways, and the intrinsic scale is analogous to the "charge" of the quasisolitons, leading to non-trivial cluster statistics from the random perturbations to the initial steady states of uniform headways. The cluster statistics depend both on the quasisoliton charge and the density of the traffic. The intrinsic scale is also related to an emergent quantity that gives the extremum headways in the cluster formation, as well as the coexistence curve separating the absolute stable phase from the metastable phase. The relationship is qualitatively universal for general optimal velocity models.

Platoon Interactions and Real-World Traffic Simulation and Validation Based on the LWR-IM

Platoon based traffic flow models form the underlying theoretical framework in traffic simulation tools. They are essentially important in facilitating efficient performance calculation and evaluation in urban traffic networks. For this purpose, a new platoon-based macroscopic model called the LWR-IM has been developed in [1]. Preliminary analytical validation conducted previously has proven the feasibility of the model. In this paper, the LWR-IM is further enhanced with algorithms that describe platoon interactions in urban arterials. The LWR-IM and the proposed platoon interaction algorithms are implemented in the real-world class I and class II urban arterials. Another purpose of the work is to perform quantitative validation to investigate the validity and ability of the LWR-IM and its underlying algorithms to describe platoon interactions and simulate performance indices that closely resemble the real traffic situations. The quantitative validation of the LWR-IM is achieved by performing a two-sampled t-test on queues simulated by the LWR-IM and real queues observed at these real-world locations. The results reveal insignificant differences of simulated queues with real queues where the p-values produced concluded that the null hypothesis cannot be rejected. Thus, the quantitative validation further proved the validity of the LWR-IM and the embedded platoon interactions algorithm for the intended purpose.

Kinetic Monte Carlo simulations of one-dimensional and two-dimensional traffic flows: comparison of two look-ahead rules

We employ an efficient list-based kinetic Monte Carlo (KMC) method to study traffic flow models on one-dimensional (1D) and two-dimensional (2D) lattices based on the exclusion principle and Arrhenius microscopic dynamics. This model implements stochastic rules for cars' movements based on the configuration of the traffic ahead of each car. In particular, we compare two different look-ahead rules: one is based on the distance from the car under consideration to the car in front of it, and the other one is based on the density of cars ahead. The 1D numerical results of these two rules suggest different coarse-grained macroscopic limits in the form of integro-differential Burgers equations. The 2D results of both rules exhibit a sharp phase transition from freely flowing to fully jammed, as a function of the initial density of cars. However, the look-ahead rule based on the density of the traffic produces more realistic results. The KMC simulations reported in this paper are compared with those from other well-known traffic flow models and the corresponding empirical results from real traffic.

Dissipative system with asymmetric interaction and Hopf bifurcation

A dissipative system with asymmetric interaction, as well as the optimal velocity model, generally shows a Hopf bifurcation concerned with the transition from homogeneous motion to the formation of nontrivial patterns. We reveal that the origin of Hopf bifurcation in macroscopic phenomena is strongly related to asymmetric interaction in a microscopic many-body system, using the continuum system derived from the original discrete system.

Instability of pedestrian flow and phase structure in a two-dimensional optimal velocity model

A two-dimensional optimal velocity model was proposed for the study of pedestrian and granular flow. We investigate the stability of homogeneous flow in the linear approximation and show the phase diagram of the model. We also investigate the property of the model by numerical simulation in the cases of unidirectional and counter flow. From these results, we present a unified understanding of the behavior of pedestrians and other related systems.

Equivalence of linear response among extended optimal velocity models

We investigate the property of extended optimal velocity (OV) models of traffic flow, in which a driver looks at arbitrary number of vehicles that precede. We prove an equivalence of linear response among extended models. This equivalence provides a natural understanding of the improvement of the stability of traffic flow.

Dynamical model of a cooperative driving system for freeway traffic

We propose an extended optimal velocity model applicable to cooperative driving control system, which will be realized in the near future. In the model, a vehicle is controlled by the system using the information of arbitrary number of vehicles that precede or follow. We investigate the stability of uniform flow and the response to a disturbance in the linear approximation.