Simulating train movement in railway traffic using a car-following model

Based on a car-following model, in this paper, we propose a new traffic model for simulating train movement in railway traffic. In the proposed model, some realistic characteristics of train movement are considered, such as the distance headway and the safety stopping distance. Using the proposed traffic model, we analyse the space-time diagram of traffic flow, the trajectory of train movement, etc. Simulation results demonstrate that the proposed model can be successfully used for simulating the train movement. Some complex phenomena can be reproduced, such as the complex acceleration and deceleration of trains and the propagation of train delay.     

An Improved Walk Model for Train Movement on Railway Network

In this paper, we propose an improved walk model for simulating the train movement on railway network. In the proposed method, walkers represent trains. The improved walk model is a kind of the network-based simulation analysis model. Using some management rules for walker movement, walker can dynamically determine its departure and arrival times at stations. In order to test the proposed method, we simulate the train movement on a part of railway network. The numerical simulation and analytical results demonstrate that the improved model is an effective tool for simulating the train movement on railway network. Moreover, it can well capture the characteristic behaviors of train scheduling in railway traffic.     

Simulation optimization for train movement on a single-track railway

Optimizing train movement has a great significance for railway traffic. In this paper, based on the optimal velocity car-following model, we propose a new simulation model for optimizing train movement in railway traffic. Here a kind of single-track railway is considered. Our aim is to reduce the energy consumption of train movement and ensure the train being on time by controlling the velocity curve of train movement. The simulation results indicate that the proposed model is effective for optimizing train movement. In addition, some major characteristics of train movement can be well captured. This method provides a new way to optimize train movement in railway traffic.     

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 traffic congestion in the coupled map （CM） car-following model under open boundary condition. The influence of the following car 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 temporal behavior obtained by ours is better than that proposed by the Konishi＇s et al. The simulation results are consistent with the theoretical analysis.     

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 traffic congestion in the coupled map (CM) car-following model under open boundary condition. The influence of the following car 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 thetemporal behavior obtained by ours is better than that proposed by the Konishi's et al. The simulation results are consistent with the theoretical analysis.     

An Improved Car-Following Model for Multiphase Vehicular Traffic Flow and Numerical Tests

This paper attempts to introduce an improved difference model that modifies a car-following model, which takes the next-nearest-neighbor interaction into account. The hnprovement of this model over the previous one lies in that it performs more realistically in the dynamical motion for small delay time. The traffic behavior of the improved model is investigated with analytic and numerical methods with the finding that the new consideration could further stabilize traffic flow. And some simulation tests verify that the proposed model can demonstrate some complex physical features observed recently in real traffic such as the existence of three phases： free flow, coexisting flow, and jam flow; spontaneous formation of density waves; sudden flow drop in flow-density plane; traffic hysteresis in transition between the free and the coexisting flow. Furthermore, th.e improved model also predicts that the stable state to relative density in the coexisting flow is insusceptible to noise.     

Traffic Modelling for Moving-Block Train Control System

This paper presents a new cellular automaton （CA） model for train control system simulation. In the proposed CA model, the driver reactions to train movements are captured by some updated rules. The space-time diagram of traffic flow and the trajectory of train movement is used to obtain insight into the characteristic behavior of railway traffic flow. A number of simulation results demonstrate that the proposed CA model can be successfully used for the simulations of railway traffic. Not only the characteristic behavior of railway traffic flow can be reproduced, but also the simulation values of the minimum time headway are close to the theoretical values.     

An Improved Discrete-Time Model for Heterogeneous High-Speed Train Traffic Flow

This paper aims to present a simulation model for heterogeneous high-speed train traffic Row based on an improved discrete-time model(IDTM).In the proposed simulation model,four train control strategies,including departing strategy,traveling strategy,braking strategy,overtaking strategy,are well defined to optimize train movements.Based on the proposed simulation model,some characteristics of train traffic Bow are investigated.Numerical results indicate that the departure time intervals,the station dwell time,the section length,and the ratio of fast trains have different influence on traffic capacity and train average velocity.The results can provide some theoretical support for the strategy making of railway departments.     

Stability Analysis for Car Following Model Based on Control Theory

Stability analysis is one of the key issues in car-following theory. The stability analysis with Lyapunov function for the two velocity difference car-following model （for short, TVDM） is conducted and the control method to suppress traffic congestion is introduced. Numerical simulations are given and results are consistent with the theoretical analysis.     

Discrete event model-based simulation for train movement on a single-line railway

The aim of this paper is to present a discrete event model-based approach to simulate train movement with the considered energy-saving factor. We conduct extensive case studies to show the dynamic characteristics of the traffic flow and demonstrate the effectiveness of the proposed approach. The simulation results indicate that the proposed discrete event model-based simulation approach is suitable for characterizing the movements of a group of trains on a single railway line with less iterations and CPU time. Additionally, some other qualitative and quantitative characteristics are investigated. In particular, because of the cumulative influence from the previous trains, the following trains should be accelerated or braked frequently to control the headway distance, leading to more energy consumption.     

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 are 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.     

考虑自适应巡航车辆影响的上匝道系统混合交通流模型

在考虑自适应巡航(adaptive cruise control, ACC)车辆的交通流模型的基础上, 建立了考虑ACC车辆影响的上匝道系统混合交通流模型, 研究ACC车辆引入对上匝道交通系统交通流的影响. 为了描述ACC车辆和手动驾驶车辆在交通流运行中的差异, 分别构建了基于常车头时距原则的ACC 车辆跟驰子模型和手动驾驶车辆MCD元胞自动机子模型; 基于上匝道车辆合流驶入主线的需求, 建立了换道子模型, 引入了表征驾驶员换道心理的参数λ. 通过对混合交通流模型进行数值模拟发现, ACC车辆的混入可以有效改善上匝道系统交通流的运行, 降低合流等事件对于交通流运行的影响, 抑制交通拥堵的时空范围及拥堵强度, 提高交通流的平均速度和流量. 此外在混合交通流模型中, ACC车辆期望车头时距H_d的减小与换道心理参数λ 的增大均可以提高混合交通流运行的速度和流量, 而合流区长度l_w对混合交通流影响则因上匝道车辆驶入概率的不同而存在差异.     

考虑双速度差效应的耦合映射跟驰模型

基于Konishi等的研究工作,提出了涉及前方两辆车车头间距的优化速度函数的耦合映射跟驰模型. 采用反馈控制方法,研究了耦合映射跟驰模型中的交通拥堵控制. 利用反馈控制理论,给出了头车速度发生变化时交通流保持稳定的条件,并与Konishi等得到的结果进行了比较. 数值模拟结果表明,所提出的模型在经典的反馈控制方法下描述的交通拥堵现象得到了有效抑制. 关键词： 交通流 耦合映射跟驰模型 优化速度函数 反馈控制     

Analysis of the stability and density waves for traffic flow

In this paper, the optimal velocity model of traffic is extended to take into account the relative velocity. The stability and density waves for traffic flow are investigated analytically with the perturbation method. The stability criterion is derived by the linear stability analysis. It is shown that the triangular shock wave, soliton wave and kink wave appear respectively in our model for density waves in the three regions: stable, metastable and unstable regions. These correspond to the solutions of the Burgers equation, Korteweg－de Vries equation and modified Korteweg－de Vries equation. The analytical results are confirmed to be in good agreement with those of numerical simulation. All the results indicate that the interaction of a car with relative velocity can affect the stability of the traffic flow and raise critical density.     

基于智能交通系统的耦合映射跟驰模型和交通拥堵控制

基于智能交通诱导信息，提出一种改进的耦合映射跟驰模型，用于描述单车道的交通流动力学特性及其拥堵控制.利用反馈控制理论，给出了在头车速度发生变化时交通流保持稳定的条件.分析结果表明，考虑前方更多车辆的信息对交通流有致稳作用，亦即稳定性条件明显减弱.数值模拟证实了理论分析的正确性，通过与他人相关工作的比较得知，考虑智能交通诱导信息能够更有效地抑制交通拥堵. 关键词： 交通流 智能交通系统 耦合映射跟驰模型 交通拥堵控制     

Efficiency promotion for an on-ramp system based on intelligent transportation system information

<正>The effect of cars with intelligent transportation systems(ITSs) on traffic flow near an on-ramp is investigated by car-following simulations.By numerical simulations,the dependences of flux on the inflow rate are investigated for various proportions of cars with ITSs.The phase diagrams as well as the spatiotemporal diagrams are presented to show different traffic flow states on the main road and the on-ramp.The results show that the saturated flux on the main road increases and the free flow region is enlarged with the increase of the proportion of cars with ITS.Interestingly,the congested regions of the main road disappear completely when the proportion is larger than a critical value.Further investigation shows that the capacity of the on-ramp system can be promoted by 13%by using the ITS information, and the saturated flux on the on-ramp can be kept at an appropriate value by adjusting the proportion of cars with ITS.     

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.     

考虑最邻近前车综合信息的反馈控制跟驰模型

拥堵控制中, 通过车辆运行状态感知与控制的交互融合, 实现对车辆有效控制的过程, 具有信息物理融合系统的典型特征. 本文基于Konishi等的研究工作, 从交通信息系统与交通物理系统融合的角度, 进一步考虑优化速度差和安全间距对车流的影响, 在耦合映射跟驰模型中, 提出了一种考虑最邻近前车综合信息的交通拥堵反馈控制方案. 运用反馈控制理论, 给出了头车速度发生变化时交通流保持稳定的条件, 并与前人工作进行了比较. 理论分析与数值模拟结果一致表明, 耦合映射跟驰模型在本文提出的控制方案下能更有效地抑制交通拥堵. 关键词： 交通流 交通拥堵控制 耦合映射跟驰模型 信息物理融合系统     

Feedback control scheme of traffic jams based on the coupled map car-following model

Based on the pioneering work of Konishi et al. [Phys. Rev. E （1999） 60 4000], a new feedback control scheme is presented to suppress traffic jams based on the coupled map car-following model under the open boundary condition. The effect of the safe headway on the traffic system is considered. According to the control theory, the condition under which traffic jams can be suppressed is analyzed. The results are compared with the previous results concerning congestion control. The simulations show that the suppression performance of our scheme on traffic jams is better than those of the previous schemes, although all the schemes can suppress traffic jams. The simulation results are consistent with theoretical analyses.     

Modified coupled map car-following model and its delayed feedback control scheme

A modified coupled map car-following model is proposed, in which two successive vehicle headways in front of the considering vehicle is incorporated into the optimal velocity function. The steady state under certain conditions is obtained. An error system around the steady state is studied further. Moreover, the condition for the state having no traffic jam is derived. A new control scheme is presented to suppress the traffic jam in the modified coupled map car-following model under the open boundary. A control signal including the velocity differences between the following and the considering vehicles, and between the preceding and the considering vehicles is used. The condition under which the traffic jam can be well suppressed is analysed. The results are compared with that presented by Konishi et al. (the KKH model). The simulation results show that the temporal behaviour obtained in our model is better than that in the KKH model. The simulation results are in good agreement with the theoretical analysis.