A control method applied to mixed traffic flow for the coupled-map car-following model

In light of previous work [Phys. Rev. E 60 4000 （1999）], a modified coupled-map car-following model is proposed by considering the headways of two successive vehicles in front of a considered vehicle described by the optimal velocity function. The non-jam conditions are given on the basis of control theory. Through simulation, we find that our model can exhibit a better effect as p = 0.65, which is a parameter in the optimal velocity function. The control scheme, which was proposed by Zhao and Gao, is introduced into the modified model and the feedback gain range is determined. In addition, a modified control method is applied to a mixed traffic system that consists of two types of vehicle. The range of gains is also obtained by theoretical analysis. Comparisons between our method and that of Zhao and Gao are carried out, and the corresponding numerical simulation results demonstrate that the temporal behavior of traffic flow obtained using our method is better than that proposed by Zhao and Gao in mixed traffic systems.

Continuum modeling for two-lane traffic flow

In this paper, we study the continuum modeling of traffic dynamics for two-lane freeways. A new dynamics model is proposed, which contains the speed gradient-based momentum equations derived from a car-following theory suited to two-lane traffic flow. The conditions for securing the linear stability of the new model are presented. Numerical tests are can＇ied out and some nonequilibrium phenomena are observed, such as small disturbance instability, stop-and-go waves, local clusters and phase transition.

Lane changing analysis for two-lane traffic flow

In this paper, the two-lane traffic are studied by using the lane-changing rules in the car-following models. The simulation show that the frequent lane changing occurs when the lateral distance in car following activities is considered and it gives rise to oscillating waves. In contrast, if the lateral distance is not considered （or considered occasionally）, the lane changing appears infrequently and soliton waves occurs. This implies that the stabilization mechanism no longer functions when the lane changing is permitted. Since the oscillating and soliton waves correspond to the unstable and metastable flow regimes, respectively, our study verifies that a phase transition may occur as a result of the lane changing.

A control method for congested traffic in the coupled map car-following model

Based on the pioneer work of Konishi et al, a new control method is presented to suppress the traffic congestion in the coupled map （CM） car-following model under an open boundary. A control signal concluding the velocity differences of the two vehicles in front is put forward. The condition under which the traffic jam can be contained is analyzed. The results axe compared with that presented by Konishi et al [Phys. Rev. 1999 E 60 4000-4007]. The simulation results show that the temporal behavior obtained by our method is better than that by the Konishi＇s et al. method, although both the methods could suppress the traffic jam. The simulation results are consistent with the theoretical analysis.

Dynamics of Motorized Vehicle Flow under Mixed Traffic Circumstance

为了学习混合交通的动力学，流动由组成机械化并且非机械化的车辆，一个汽车追随者模型基于免费、小心的碰撞的原则，开车被建议。侧面的磨擦并且重叠开车被介绍描述在机械化车辆和非机械化的车辆之间的相互作用。由数字模拟，流动密度关系，时间空间的动力学，和速度进化详细被调查。结果显示非机械化的车辆在机械化车辆流动上有重要影响并且引起最大的流动在大约 13% 衰退。非机械化的车辆能减少机械化车辆速度和原因速度摆动当机械化车辆密度是低的时。而且，非机械化的车辆在震荡的速度上看重要抑制效果密度是否是中等的，高度，和如此的效果是机械化了车辆密度增加变弱。结果也强调为分开的必要性从非机械化的车辆机械化了车辆。

The Effect of Self-Driving Car on Urban Traffic

Based on the idea of infinitesimal analysis, we establish the basic model of relation between speed and flow. Since putting a certain amount of self-driving car will affect the average speed of mixed traffic flow, we choose the proportion of self-driving car to be a variable, denoted by k. Based on the least square method, we find two critical values of k that are 38.63% and 68.26%. When k 38.63%, the self-driving cars have a negative influence to the traffic. When 38.63% < k < 68.26%, they have a positive influence to the traffic. When k > 68.26%, they have significant improvement to the traffic capacity of the road.

考虑通行能力和交通流稳定性的雾天高速公路限速研究

从通行能力和交通流稳定性两个层面对雾天高速公路限速值进行研究。选取经驾驶模拟器数据标定的雾天跟驰模型来描述车辆跟驰行为,并计算雾天高速公路通行能力和交通流稳定性。分别提出优先考虑通行能力和优先考虑交通流稳定性的雾天高速公路限速方案。研究结果表明:轻雾场景和浓雾场景分别在限速100 km/h和80 km/h时的通行能力最大,均在限速40 km/h时的通行能力最小;轻雾场景和浓雾场景均在限速40 km/h时的交通流稳定性最优,分别在限速60 km/h和100 km/h时的交通流稳定性最差;采用优先考虑通行能力的限速方案时,雾天高速公路通行能力最大,较最小通行能力可提升28.68%~44.66%,稳定性则较最优值下降18.81%~82.92%;采用优先考虑交通流稳定性的限速方案时,交通流稳定性最优,较最差值可增加1.97倍~106.33倍,通行能力则较最大值减小22.29%~30.87%。

降雨天气下人机混驾交通流跟驰特性研究

为揭示降雨天气下人机混驾交通流跟驰规律,从分析降雨对行车的影响入手,引入路面附着系数、驾驶能见度等参数,改进Gipps安全距离和行车加速度限制,针对不同跟驰模式建立元胞自动机模型,探寻降雨强度、渗透率双重影响的人机混驾交通流跟驰特性。数值仿真结果表明:雨天渗透率与通行能力呈正相关,但当渗透率低于0.25时,智能网联车对混合交通流平均速度、临界密度及通行能力的影响有限;当降雨强度高于0.3 mm/min时,随雨强度增大会加剧智能网联车跟驰退化,显著降低混合交通流的自由速度、临界速度及通行能力;小雨情况下,约0.1的渗透率可弥补降雨造成的通行能力损失;在中雨至大雨的降雨强度区间内,降雨强度每增加0.1 mm/min,相应提高渗透率0.1,路段通行能力可恢复到与晴天纯人工驾驶交通流相当的水平。

A New Car Following Model:Comprehensive Optimal Velocity Model

在这份报纸，我们在场一个新汽车追随者模型，即全面最佳的速度模型(COVM ) ，谁的最佳的速度功能不仅取决于前面的车辆的下列距离，而且与领先取决于速度差别车辆。模拟结果证明 COVM 理论上是超过以前的改进。然后，模型的稳定性条件被线性稳定性分析获得，它证明了模型能在阶段图比以前的模型获得一个更大的稳定的区域。通过非线性的分析，汉堡包， Korteweg-de Vries (KdV ) 和修改 KdV (mKdV ) 方程为三角形的冲击波， soliton 波浪，和 kink-antikink soliton 波浪被导出。同时，数字模拟也被执行证明模型能模仿这些密度波浪。

A new car-following model considering velocity anticipation

The full velocity difference model proposed by Jiang et al. [2001 Phys. Rev. E 64 017101] has been improved by introducing velocity anticipation. Velocity anticipation means the follower estimates the future velocity of the leader. The stability condition of the new model is obtained by using the linear stability theory. Theoretical results show that the stability region increases when we increase the anticipation time interval. The mKdV equation is derived to describe the kink-antikink soliton wave and obtain the coexisting stability line. The delay time of car motion and kinematic wave speed at jam density are obtained in this modeh Numerical simulations exhibit that when we increase the anticipation time interval enough, the new model could avoid accidents under urgent braking cases. Also, the traffic jam could be suppressed by considering the anticipation velocity. All results demonstrate that this model is an improvement on the full velocity difference model.

A new car-following model yielding log-normal type headways distributions

Modeling time headways between vehicles has attracted increasing interest in the traffic flow research field recently, because the corresponding statistics help to reveal the intrinsic interactions governing the vehicle dynamics. However, most previous micro-simulation models cannot yield the observed log-normal distributed headways. This paper designs a new car-following model inspired by the Galton board to reproduce the observed time-headway distributions as well as the complex traffic phenomena. The consistency between the empirical data and the simulation results indicates that this new car-following model provides a reasonable description of the car-following behaviours.

A new coupled-map car-following model based on a transportation supernetwork framework

A new car-following model is proposed by considering information from a number of preceding vehicles with intervehicle communication. A supernetwork architecture is first described, which has two layers： a traffic network and a communication network. The two networks interact with and depend on each other. The error dynamic system around the steady state of the model is theoretically analyzed and some nonjam criteria are derived. A simple control signal is added to the model to analyze the criteria of suppressing traffic jams. The corresponding numerical simulations confirm the correctness of the theoretical analysis. Compared with previous studies concerning coupled map models, the controlled model proposed in this paper is more reasonable and also more effective in the sense that it takes into account the formation of traffic congestion.

A velocity-difference-separation model for car-following theory

We introduce a velocity-difference-separation model that modifies the previous models in the literature. The improvement of this new model over the previous ones lies in that it not only theoretically retains many strong points of the previous ones, but also performs more realistically than others in the dynamical evolution of congestion. Furthermore, the proposed model is investigated with analytic and numerical methods, with the finding that it can demonstrate some complex physical features observed in real traffic such as the existence of three phases： free flow, synchronized flow, and wide moving jam; sudden flow drop in flow-density plane; and traffic hysteresis in transition between the free and the synchronized flow.

A new coupled map car-following model considering drivers' steady desired speed

Based on the pioneering work of Konishi et al., in consideration of the influence of drivers＇ steady desired speed ef/ect on the traffic flow, we develop a new coupled map car-following model in the real world. By use of the control theory, the stability condition of our model is derived. The validity of the present theoretical scheme is verified via numerical simulation, confirming the correctness of our theoretical analysis.

A Model of Car-Following with Adaptive Headway

The performances of a well-known GHR car-following model was investigated by using numerical simulations in describing the acceleration and deceleration process induced by the motion of a leading car. It is shown that in GHR model vehicle is allowed to run arbitrarily close together if their speed are identical,and it waves aside even though the separation is larger than its desired distance. Based on these investigations, a modified GHR model which features a new nonlinear term which attempts to adjust the inter-vehicle spacing to a certain desired value was proposed accordingly to overcome these deficiencies. In addition, the analysis of the additive nonlinear term and steady-state flow of the new model were studied to prove its rationality.

Considering Backward Effect in Coupled Map Car-Following Model

Based on the pioneer work of Konishi et al,a new control method is proposed to suppress the trafficcongestion in the coupled map (CM) car-following model under open boundary condition.The influence of the followingcar to the system has been considered.Our method and that presented by Konishi et al.[Phys.Rev.E 60 (1999) 4000]are compared.Although both the methods could suppress the traffic jam,the simulation results show that the temporalbehavior obtained by ours is better than that proposed by the Konishi's et al.The simulation results are consistent withthe theoretical analysis.

A Data-Driven Car-Following Model Based on the Random Forest

The car-following models are the research basis of traffic flow theory and microscopic traffic simulation. Among the previous work, the theory-driven models are dominant, while the data-driven ones are relatively rare. In recent years, the related technologies of Intelligent Transportation System (ITS) re- presented by the Vehicles to Everything (V2X) technology have been developing rapidly. Utilizing the related technologies of ITS, the large-scale vehicle microscopic trajectory data with high quality can be acquired, which provides the research foundation for modeling the car-following behavior based on the data-driven methods. According to this point, a data-driven car-following model based on the Random Forest (RF) method was constructed in this work, and the Next Generation Simulation (NGSIM) dataset was used to calibrate and train the constructed model. The Artificial Neural Network (ANN) model, GM model, and Full Velocity Difference (FVD) model are em- ployed to comparatively verify the proposed model. The research results suggest that the model proposed in this work can accurately describe the car- following behavior with better performance under multiple performance indicators.

Application of singular perturbation method in analyzing traffic density waves

Car following model is one of microscopic models for describing traffic flow. Through linear stability analysis, the neutral stability lines and the critical points are obtained for the different types of car following models and two modified models. The singular perturbation method has been used to derive various nonlinear wave equations, such as the Kortewegde-Vries （KdV） equation and the modified Korteweg-de-Vries （mKdV） equation, which could describe different density waves occurring in traffic flows under certain conditions. These density waves are mainly employed to depict the formation of traffic jams in the congested traffic flow. The general soliton solutions are given for the different types of car following models, and the results have been used to the modified models efficiently.

Traffic dynamical characteristics and nonlinear density waves with consideration of navigation

In this dissertation, based on the existing macroscopic and microscopic models for traffic flow, several improved mathematical models in accordance with the rapid development of intelligent transportation system （ITS） are proposed, and the corresponding theoretical analysis and numerical simulation are performed. In addition, the relationships between macroscopic and microscopic traffic models are examined, in which emphasis is particularly laid on the investigation of the various nonlinear density waves in traffic flows. The contents of the dissertation are as follows.