基于模糊控制的入口匝道智能控制方法

在建立高速路交通流模型的基础上,结合模糊控制理论设计出了基于模糊逻辑的入口匝道控制器,该控制器根据期望密度和实际车流密度的误差和误差变化量,决定入口匝道的调节率。仿真结果表明,该控制器具有较好的稳态和动态性能,能避免交通拥挤,从而提高主线的通行能力。     

Review of road traffic control strategies

Traffic congestion in urban road and freeway networks leads to a strong degradation of the network infrastructure and accordingly reduced throughput, which can be countered via suitable control measures and strategies. After illustrating the main reasons for infrastructure deterioration due to traffic congestion, a comprehensive overview of proposed and implemented control strategies is provided for three areas: urban road networks, freeway networks, and route guidance. Selected application results, obtained from either simulation studies or field implementations, are briefly outlined to illustrate the impact of various control actions and strategies. The paper concludes with a brief discussion of future needs in this important technical area.     

Freeway Traffic Control Using Iterative Learning Control-Based Ramp Metering and Speed Signaling

In this paper, an iterative learning approach for the freeway density control under ramp metering and speed regulation is developed in a macroscopic level traffic environment. Rigorous analyses show that the proposed learning control schemes guarantee the asymptotic convergence of the traffic density to the desired one. The two major features of the learning-based density control are: 1) less prior modeling knowledge required in the control system design and 2) the ability to reject exogenous traffic perturbations. The control schemes are applied to a freeway model, and simulation results confirm the efficacy of the proposed approach     

Dependable Traffic Control Strategies for Urban and Freeway Networks

Traffic congestion is a growing problem in many countries around the world. It has been recognized that instead of constructing more roads and freeways to counter this problem it is prudent to improve the utilization of existing road network through a judicious combination of advances in control engineering, communication and information technology. The traffic control architecture proposed in this paper is a combination of communicating Urban Traffic Control Architecture (UTCA) and Freeway Traffic Control Architecture (FTCA). The UTCA combines context-awareness, Cyber-Physical Systems (CPS) principles, and Autonomic Computing System (ACS) principles to optimize traffic congestion and enforce safety in urban traffic network. The UTCA includes a network of adaptive intersection traffic controllers and their immediate supervisory systems, who are also networked. The central piece of each traffic controller is an arbiter, which is a mini CPS. It is aware of the traffic dynamics at the intersection managed by it, by virtue of continuous input from monitoring sensors. Due to this context-awareness ability and its communication ability to exchange traffic information with its neighbors, it can execute policy-based reactions in order to enable safe and efficient traffic throughput at its intersection. Each urban traffic supervisory system is designed with ACS principles in order to minimize downtime caused by environmental emergencies and maximize security of the subsystem under it. A supervisory subsystem will also collect global traffic flow information and contextual constraints from its neighbors. Based on this input it will modify policies and communicate them to its traffic controller for timely adaptation. The urban traffic flowing into freeway traffic will be mediated by Intelligent Ramp Meters (IRM). An IRM interacts with the urban traffic control system and its nearest Intelligent Roadside Unit (IRSU) to regulate the flow of traffic from urban to freeway network. The FTCA consists of a network of mutually interacting IRSUs which monitor traffic flow, communicate with IRMs for providing traffic guidance for freeway drivers. An IRSU will communicate with the vehicles in the zone managed by it in order to provide information on rerouting when road and weather conditions warrant it. It also facilitates exchange of information between vehicles, guide them in lane changes and maintaining safe distance in order to avoid collision.     

Tenth International Conference on Road Transport Information andControl (IEE Conf. Publ. No.472)

The following topics were dealt with: route guidance; driver information systems; traffic information systems; network management; incident management; access ramp control; road user charging; urban traffic management; road traffic control; public transport information; and public transport priority     

基于XDR大数据分析的高架用户识别技术

城市高架路场景下,用户行驶速度相对较快、人流密集,客户对通信体验要求更高。首先,介绍了网络质量管控大数据平台体系架构;其次,设计了基于XDR大数据分析的高架用户识别的算法;最后,通过XDR大数据分析处理,与高架路段指纹库匹配,输出高架用户运动轨迹,提升了高架用户识别准确性,为高架路无线网络质量监控提供辅助支撑。     

电子监控技术在高速公路中的应用

电子监控技术是保障高速公路实现"安全、快速、舒适、方便"管理目标的重要手段.分析了高速公路电子监控技术的层次,分别介绍了高速公路电子监控系统3个层次的具体内容,简要阐述了高速公路系统中电子监控技术的发展趋势.     

基于单周期控制的功率因数校正研究

利用单周期控制（One-Cycle Control,OCC）的功率因数校正器,无需传统功率因数校正电路所需的模拟乘法器、输入电压采样、固定斜波发生器。因此,大大简化了功率因数校正（Power Factor Correction,PFC）电路的设计,缩小了装置体积。文章对OCC PFC原理进行了详细的分析,并研制了一台基于ICE2PCS02的500W PFC校正器,验证了其有效性。     

Linear quadratic state feedback and robust neural network estimatorfor field-oriented-controlled induction motors

A field-oriented control scheme for an induction motor with a linear quadratic optimal regulator and a robust neural network estimator is proposed. The state feedback is designed by using the synchronous frame motor model. The number of the states is increased in order to take into account the presence of two integrators on the flux and torque errors. The resulting model is suitably simplified and the corresponding approximations are discussed. The procedure proposed is shown to be suitable also for the design of the state feedback via the pole placement technique. A comparison with standard proportional integral regulators is provided. The rotor flux is estimated by using a robust neural network observer. The network training set is suitably designed in order to preserve the drive effectiveness also in the presence of large parameter uncertainties. The robust neural observer is compared with an extended Kalman filter and a standard neural network observer. Using a 250 kW induction motor as a case study, the simulation results show the effectiveness of the proposed solution, both during transient and steady-state operating conditions     

Nonlinear control for linear induction motor servo drive

This paper describes a newly designed nonlinear control strategy to control a linear induction motor servo drive for periodic motion. Based on the concept of the nonlinear state feedback theory and optimal technique, a nonlinear control strategy, which is composed of an adaptive optimal control system and a sliding-mode flux observation system, is developed to improve the drawbacks in previous works concerned with complicated intelligent control. The control and estimation methodologies are derived in the sense of Lyapunov theorem so that the stability of the control system can be guaranteed. The sliding-mode flux observation system is implemented using a digital signal processor with a high sampling rate to make it possible to achieve good dynamics. Computer simulations and experimental results have been conducted to validate the effectiveness of the proposed control scheme under the occurrence of possible uncertainties and different reference trajectories. The merits of the proposed control system are indicated in comparison with a traditional optimal control system.     

Network architecture and communication modules for guaranteeing acceptable control and communication performance for networked multi-agent systems

When sensory and actuation devices in a control system are exchanging data through one common communication medium, the sharing of communication bandwidth will induce unavoidable data latency and might degrade the control performance. Hence, the utilization of communication resource and the requirement of control specification should be analyzed and properly designed when implementing a control system over a network architecture. In this paper, we analyze the performance of information sharing of multiple cooperative agents over one communication network, and propose design methodologies of guaranteeing acceptable control and communication performance in a networked control system. In particular, we study the relationship between the sampling rates of a control system,and the transmission rates of a communication network, and then utilize an integrated networked control design chart to help select design parameters and visualize overall system performance at different sampling and transmission rates. Based on the design parameters selected, the communication modules by utilizing deadband control and state estimation are presented for guaranteeing both control and communication performance. Simulation studies are conducted in a network-and-control simulation tool that is developed on the Matlab/Simulink platform and is used to demonstrate the proposed design methodologies. Both the analysis and simulation results illustrate the characteristics of designing mechanisms between control and communication performance and show the improvement of implementing the proposed communication modules.     

可远程升级的GPS／GPRS车载终端设计

针对道路运输行业对车辆管理信息化的要求,设计了基于GPS／GPRS技术的车辆定位控制跟踪终端。利用GPRS网络上报车辆的方位到监控中心,根据监控中心的指令,执行信息采样速率控制等各项操作．并提出基于一种GPRS网络的嵌入式软件远程在线升级方案。     

一种道路场景切换链优化方法研究与实践

道路场景是网络质量的重要形象窗口。由于终端移动速度快，为保障业务质量与用户感知，切换性能优化至关重要。现网中，由于道路场景LTE网络建设情况复杂，大量存在反向切换、越区覆盖、冗余邻区等导致网络切换性能下降的因素。为改善LTE网络切换性能，本文提出了一种针对道路场景的切换链优化方法，并通过实践证明了所提方法的有效性。     

Decoupled stator-flux-oriented induction motor drive with fuzzyneural network uncertainty observer

A stator-flux-oriented induction motor drive using online rotor time-constant estimation with a robust speed controller is introduced in this paper. The estimation of the rotor time constant is made on the basis of the model reference adaptive system using an energy function. The estimated rotor time-constant is used in the current-decoupled controller, which is designed to decouple the torque and flux in the stator-flux-field-oriented control. Moreover, a robust speed controller, which is comprised of an integral-proportional speed controller and a fuzzy neural network uncertainty observer, is designed to increase the robustness of the speed control loop. The effectiveness of the proposed control scheme is demonstrated by simulation and experimental results     

认知无线网状网中基于差分演化的功率控制与信道分配

信道分配对于提高认知无线网状网性能具有重要作用.考虑到节点功率对网络干扰的影响,定义了网络干扰边及潜在干扰边,通过量化通信功率控制等级,给出了联合功率控制与信道分配的网络模型.提出一种基于差分演化的功率控制与信道分配算法,设计了实数编码规则及相应的约束控制机制以保证个体的有效性,确保算法的快速收敛.一系列仿真实验表明本文算法的有效性.     

Study on Road Network Traffic Coordination Control Technique With Bus Priority

On the basis of distributed traffic control framework, fuzzy theory, and artificial neural networks technique, the road network traffic intelligent coordination control technique with bus priority was proposed. The whole road network was regarded as a large-scale system, and the subsystems were the intersections. Multiphase intelligent signal controller that controlled its own traffic and cooperated with its neighbors was installed at each intersection. By exchanging information collected from its social vehicle detectors and the bus detection and location devices, and cooperating with adjacent signal controllers, social vehicle coordination and bus priority in the whole road network were realized. Bus priority module, green observation module, and phase switch module comprised the hard core of the controller. In each module, the fuzzy rule base system was designed in detail. To improve the control system's robusticity, the fuzzy relations of the three modules were implemented by one neural network. The target of this proposed method was to maximize the possibility for vehicles to depart from the upstream intersection, and the traveling bus nearby the local intersection to pass the local intersection without stoppage while the utility efficiency of the green signal time was at a relatively high level. The actual application shows that the proposed method can decrease the average vehicle delay and average travel time effectively.     

Efficiency measure of routing protocols in vehicular ad hoc network using freeway mobility model

To move packets among the vehicles mobility pattern of vehicles in a vehicular network performs an imperative factor for creating competent routing protocol. To reproduce the movement features of vehicles in VANET is the main purpose of the mobility model. Manhattan mobility model is conversed by a lot of researchers. Merely very limited research study is prepared on highway and freeway mobility models. In this document Cluster scheme, different routing protocols are used to the freeway mobility based vehicular architecture. The Ns2.34 simulation effect illustrates the effort of cluster scheme over different protocols and standard 802.11p. The competence of the routing protocols in the vehicular communication by means of freeway movement pattern is estimated by different network parameters.     

The areawide real-time traffic control (ARTC) system: a new trafficcontrol concept

A traffic control system, called areawide real-time traffic control (ARTC), that addresses frequent occurrences of congestion and provides areawide traffic progression is presented. The signal controllers in ARTC are interconnected through a computer network. By exchanging traffic flow information among the signal controllers, ARTC provides a new concept in areawide traffic control. With a global view of the traffic in the area, ARTC anticipates congestion. Simulation results of the ARTC prototype control algorithm over a linear road topology are also presented, and the results show significant improvement over an optimized fixed time control. The signal controllers and the computer network are designed to support the real-time communication requirements and a sufficient level of fault tolerance