Offset control of traffic signal using cellular automaton traffic model

This paper deals with an offset control of traffic signals using a cellular automaton traffic model. A stochastic optimal control method for distributed traffic signals is modified to achieve coordinated traffic signal control with the proposed offset control method. In the proposed coordinated traffic signal control method, splits of each cycle and common cycle length are calculated using a modified stochastic optimal control method, and then the offset is calculated using an estimation method based on a modified CA traffic model at intervals. Also, simulations are carried out at multiple intersections using a micro traffic simulator. The effectiveness of the proposed coordinated control method is proved by comparing with other traffic signal control methods such as pre-timed signal control, two types of the traditional coordinated control and distributed control.     

基于混沌导频信号同步控制的混沌保密通信

分析了现有混沌掩盖保密通信存在的问题,给出了混沌同步控制信号与混沌调制信号相分离的混沌保密通信新方法.新方法采用混沌导频信号独立完成通信收发两端的混沌系统同步控制,较好地解决了原有混沌通信系统中已调信号既实现同步控制又承载信息信号所引起的信息信号须远小于混沌调制信号和抗噪声性能差的问题.构建了采用Sprott系统I为混沌模型的混沌通信新方案仿真电路.仿真实验表明:通信收发两端混沌同步控制实现方式更灵活、混沌同步更精确、信息信号大小不再受混沌信号影响、抗噪声性能更强.同时,混沌调制信号和混沌同步控制信号分开也有助于这两方面技术独立地研究与发展,有利于构建性能更好的混沌保密通信系统.     

CATS: An adaptive traffic signal system based on car-to-car communication

Traffic signal controls play an important role in regulating vehicular flow at road intersections. Traditional systems are not capable of adjusting the timing pattern in accordance with vehicular demand. This results in excessive delays for road users. Hence it is necessary to develop dynamic systems that can adjust the timing patterns according to traffic demand. In this paper, the design and implementation of an adaptive traffic signal control system based on car-to-car communication is presented. Also, a clustering algorithm is defined which will assist in estimating the density of vehicles approaching an intersection. The cycle time, which is calculated using the estimated density of vehicular traffic, helps in reducing both the waiting time for vehicles at intersections and queue length. It is also shown that the proposed solution is collision free at intersections. The proposed system is compared with a classic pre-timed system and an adaptive fuzzy logic system. The simulations also show that the data convergence time and the communication delay between vehicles and traffic signals do not compromise the efficiency of the system.     

Automatic tuning of communication protocols for vehicular ad hoc networks using metaheuristics

The emerging field of vehicular ad hoc networks (VANETs) deals with a set of communicating vehicles which are able to spontaneously interconnect without any pre-existing infrastructure. In such kind of networks, it is crucial to make an optimal configuration of the communication protocols previously to the final network deployment. This way, a human designer can obtain an optimal QoS of the network beforehand. The problem we consider in this work lies in configuring the File Transfer protocol Configuration (FTC) with the aim of optimizing the transmission time, the number of lost packets, and the amount of data transferred in realistic VANET scenarios. We face the FTC with five representative state-of-the-art optimization techniques and compare their performance. These algorithms are: Particle Swarm Optimization (PSO), Differential Evolution (DE), Genetic Algorithm (GA), Evolutionary Strategy (ES), and Simulated Annealing (SA). For our tests, two typical environment instances of VANETs for Urban and Highway scenarios have been defined. The experiments using ns- 2 (a well-known realistic VANET simulator) reveal that PSO outperforms all the compared algorithms for both studied VANET instances.     

Cognitive vertical handover engine for vehicular communication

Always best connected (ABC) communication is an essential requirement for intelligent transportation system. In this paper, we propose a cognitive vertical handover (CVHO) engine to ensure seamless connectivity on the move. Analytic hierarchy process and artificial neural network are used for the development of the algorithm and MATLAB is used as simulation platform. The CVHO engine, which is knowledge based context aware system, takes into account multiple relevant criteria and previous experiences. This system is capable of performing both voluntary and reflex actions. A detailed literature review is presented to compare this work with the conventional methods of vertical handover. A case study, considering the network selection in a typical highway traffic scenario, which consists of both peer-to-peer (P2P) and mobile networks, is presented for the validation of the design. Three radio access technologies, WLAN (P2P), UMTS and WiMAX (mobile networks), are considered for simulation. The results show that the presented model not only realistically optimizes the best available network on the move but also avoids unnecessary handovers. This algorithm is specific to vehicular communication system and hence variation in network selection with vehicle speed is shown.     

NCTUns tool for wireless vehicular communication network researches

Several goals such as improving road safety and increasing transport efficiency are being pursued in intelligent transportation systems (ITS). Wireless vehicular communication is one technology to achieve these goals. Conducting vehicular experiments on the roads is an approach to studying the effectiveness of wireless vehicular communication. However, such an approach is costly, hard-to-control (repeat), dangerous, and infeasible when many vehicles and people are involved in the field trial. In contrast, the simulation approach does not have these problems. It is a very useful approach and complements the field trial approach. This paper presents NCTUns, an open source integrated simulation platform, for wireless vehicular communication network researches. This tool tightly integrates network and traffic simulations and provides a fast feedback loop between them. Therefore, a simulated vehicle can quickly change its driving behavior such as moving speed and direction when it receives a message from the wireless vehicular communication network. This capability is required by several novel ITS applications such as active collision avoidance systems. In this paper, we present the design, implementation, validation, and performance of this tool.     

Adaptive collaborative optimization of traffic network signal timing based on immune-fireworks algorithm and hierarchical strategy

Applied Intelligence - In contemporary urban areas, the construction speed of urban roads lags far behind the growth rate of the number of vehicles. The traffic delay caused by excessive vehicles...     

一种分簇车联网通信方法

针对分簇后的车联网大数据量下网关节点的传输瓶颈问题,结合DMAC分簇算法,提出了通过使用方向性天线在簇与簇之间使相距两跳远的簇头直接建立虚拟通信路径的方法。仿真结果表明：与全向通信方式相比,方法使得簇间通信的端到端延迟减少了110ms,网络的吞吐量增加了将近3Mbps。     

基于单片机无线通信技术的盲人交通提示系统设计

为解决盲人交通问题,研究开发了一种新型交通语音提示系统。采用AT89S51单片机结合无线射频芯片NRF401的方法,为盲人设计一套便携式的信号发送/接收终端,以半双工通信的方式和ISD1420语音录放模块来共同实现交通灯信号的无线语音提示功能,性能比现有语音提示系统有了较大提高。     

Adaptive routing for road traffic

The article reports on an integrated system which uses road congestion information to guide routing, both in advance and while in transit. It offers two novel features: historic information about congestion is collected and retained for use when planning routes; and GPS tracks vehicles while they undertake journeys, and the Global System for Mobile Communications (GSM) Short Message Service (SMS) maintains communications between a moving vehicle and a central planning service to suggest revised routes avoiding congestion     

交通信号机多路信号转接器设计

介绍了一种在交通控制实验室中实现多台信号机共享一个倒计时牌的信号转接器的设计,该转接器能够按照用户要求从多台交通信号机的倒计时信号中选择需要的信号送至倒计时牌显示。转接器遵循设备的RS-485传输协议,利用MAX309逻辑器件实现信号切换,结构简单,成本低,使用可靠,可用于多种串行数据传输设备的信号切换,具有一定的实用价值。     

Adaptive active queue management controller for TCP communication networks using PSO-RBF models

Addressing performance degradations in end-to-end congestion control has been one of the most active research areas in the last decade. Active queue management (AQM) is a promising technique to congestion control for reducing packet loss and improving network utilization in transmission control protocol (TCP)/Internet protocol (IP) networks. AQM policies are those policies of router queue management that allow for the detection of network congestion, the notification of such occurrences to the hosts, and the adoption of a suitable control policy. Radial bias function (RBF)-based AQM controller is proposed in this paper. RBF as a nonlinear controller is suitable as an AQM scheme to control congestion in TCP communication networks since it has nonlinear behavior. Particle swarm optimization (PSO) algorithm is also employed to derive RBF output weights such that the integrated-absolute error is minimized. Furthermore, in order to improve the robustness of RBF controller, an error-integral term is added to RBF equation. The output weights and the coefficient of the integral error term in the latter controller are also optimized by PSO algorithm. It should be noted that in both proposed controllers the parameters of radial basis functions are selected to symmetrically partition the input space. The results of the comparison with adaptive random early detection (ARED), random exponential marking (REM), and proportional-integral (PI) controllers are presented. Integral-RBF has better performance not only in comparison with RBF but also with ARED, REM and PI controllers in the case of link utilization while packet loss rate is small.     

基于监督机器学习的车载协作通信中继选择

为提高车载协作通信链路的可靠性与连通性,提出了一种在下行非正交多址接入(NOMA)的中继网络中基于监督机器学习算法的中继选择方案,通过构建反向传播(BP)神经网络预测模型,对候选中继集的中断概率进行预测,以此来进行基于最小中断概率的中继选择,提高了下行链路的连通性.在Matlab中,利用样本数据进行网络训练后,得出的预...     

Distributed and adaptive traffic signal control within a realistic traffic simulation

As traffic congestion rises within urban centers around the world, the intelligent control of traffic signals within cities is becoming increasingly important. Previous research within the area of intelligent traffic signal control has several shortcomings, including a reliance on historical data, the use of centralized systems which cannot handle city-sized problem instances and solutions which are not capable of addressing real-world traffic scenarios (e.g., constantly varying volumes and complex network structures). The research reported here proposes algorithms capable of controlling traffic signals that rely on traffic observations made by available sensor devices and local communication between traffic lights. This solution allows signals to be updated frequently to match current traffic demand, while also allowing for significantly large problem sizes to be addressed. To evaluate the developed system, a realistic traffic model was developed using information supplied by the City of Ottawa, Canada. It was found, through simulation within the SUMO traffic simulation environment, that the proposed adaptive system resulted in higher overall network performance when compared to the current fixed signal plan controllers, which were recreated using information from the City of Ottawa. This work also includes examples of why fixed signal controllers are inferior to an adaptive control system.     

Performance analysis of hybrid WiMAX/DSRC scenarios for vehicular communication environment

Microsystem Technologies - Internet becomes a vital and important service being integrated in the current scenarios of competing technologies, therefore there is a need for higher speed broadband...     

Adaptive modeling for hydroacoustic signal processing

Adaptive modeling is a well-known technique used in controlling automatic systems. This paper discusses the possibility of using the adaptive model of the surrounding water environment and receiving antenna array for the purpose of locating hydroacoustic sources. The proposed method of hydroacoustic signal primary treatment is described. The experimental results are shown. The potential of the new method to improve passive target detection is also considered. The article was translated by the authors.