物联网智能交通拥堵判别算法的研究与实现

针对城市道路交叉口的常发性交通拥堵现象,依据RFID检测系统的特点,提出了一种基于物联网前端信息采集技术的交通流检测方法。并且对城市道路交叉口采集到的交通流量相对增量、车辆的时间占有率相对增量以及地点平均车速等信息进行了对比性分析和统计推导,从理论上论证了交通拥挤产生时的交通流特点,然后以此为基础给出了交通拥挤事件出现时的判别准则,构造出相应的拥挤检测指标及判别算法。最后利用Matlab编程再结合实际交通测量数据验证了算法的正确性。     

智能停车场在城市拥堵缓解中的研究与应用

文章就“停车问题”对城市拥堵的影响展开研究, 通过分析路边停车对道路通行的干扰和停车场对周边交通疏导的影响, 提出取缔路边停车管理模式和增加智能诱导停车系统, 并通过对比仿真结果来证明目前城市路边停车对交通路网畅通的影响, 为未来城市拥堵缓解工作提供了一种思路。     

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.     

一种城市交通路网实时动态多路口路径导航量子搜索方法

城市交通拥堵日益严重,高效的路径导航方法一直是当前研究的热点和缓解拥堵的主要途径.现有的研究成果主要集中在对单个车辆行驶时间的路径寻优和小规模路网的多车辆均衡化的路径导航,没有实现大规模多车辆多路径的实时动态路径导航.当前研究主要存在以下局限：（1）导航方案评价指标单一,不能充分表示导航方案的优劣;（2）无法实现大规模路网的实时导航.针对这些问题,本文提出一种城市交通路网实时动态多路口路径导航量子搜索方法（A Route Guidance Method based on Quantum Searching for Real-time Dynamic Multi-intersections in Urban Traffic Networks,RGQS）,该方法充分考虑各种因素,实时提供大规模路网的路径导航.本文的实验分别在人工路网和真实路网中验证了RGQS方法相比于对比算法可以使行驶时间减少达到20%.     

Freeway traffic surveillance and control

In the past decade, automatic freeway surveillance and control systems have been introduced in several cities in the United States. Effective use of the hardware that has been implemented requires a sound mathematical basis for evaluation and optimization studies. In this paper, the nature of freeway congestion and the structure of systems which have been implemented to relieve this congestion are discussed. Mathematical models of freeway traffic which allow consideration of on-ramp metering control are developed. Finally, several freeway traffic-control problems are discussed, current approaches are described, and formulations of improved (optimal) approaches are developed.     

Intelligent beaconless geographical forwarding for urban vehicular environments

A Vehicular Ad hoc Network is a type of wireless ad hoc network that facilitates ubiquitous connectivity between vehicles in the absence of fixed infrastructure. Source based geographical routing has been proven to perform well in unstable vehicular networks. However, these routing protocols leverage beacon messages to update the positional information of all direct neighbour nodes. As a result, high channel congestion or problems with outdated neighbour lists may occur. To this end, we propose a street-aware, Intelligent Beaconless (IB) geographical forwarding protocol based on modified 802.11 Request To Send (RTS)/ Clear To Send frames, for urban vehicular networks. That is, at the intersection, each candidate junction node leverage digital road maps as well as distance to destination, power signal strength of the RTS frame and direction routing metrics to determine if it should elect itself as a next relay node. For packet forwarding between Intersections, on the other hand, the candidate node considers the relative direction to the packet carrier node and power signal strength of the RTS frame as routing metrics to elect itself based on intelligently combined metrics. After designing the IB protocol, we implemented it and compared it with standard protocols. The simulation results show that the proposed protocol can improve average delay and successful packet delivery ratio in realistic wireless channel conditions and urban vehicular scenarios.     

PLC在交通信号控制系统中的应用

随着我国城市化和现代化建设的迅速发展,交通问题成为社会经济发展的一个大问题。原有的信号灯定时控制方法已经无法满足越来越拥堵道路的需求。城市道路交通信号PLC智能控制系统运行可靠、操作简便、应用范围广,能够有效降低车辆延误及停车的次数,缓解道路交通拥堵情况。本文基于S7-200系列PLC控制系统,根据时间指令将24小时分为:白天控制与夜间控制两个时间段,并运用了实时检测、判断延时,实现交通灯信号的智能控制,有效缓解交通高峰期的压力和主干道路口的拥挤现状,推动我国城市道路交通信号灯控制系统的科学化、智能化发展。     

Research of traffic flow multi-objectives intelligent control method for junction network

Junction network is a special type of roadwork pattern that scatters and distributes around the specific zone of metropolitan and in that contains different grade and functional roads of arterial road, urban freeway and expressway. Intelligent control is new development where the control problem is to find the combination of control measures that result for the best road performance and control effectiveness. The problems of multi-objective coordinated metering and evaluation for local ramp is considered. This paper discusses the optimal coordination of mainline and ramp, a modified ramp latency model is posed using the method of queuing theory, and a ramp control with better mechanism compare to artificial neural network using radical based function-support vector machine algorithm is designed. With in-situ traffic flow data of Beijing ring and radial freeway during high-density period, three known and the designed novel methodologies are compared, the intensive simulations show the effectiveness of the proposed approach, particularly at the aspect of minimize reduplicated waiting time for junction network. using these methodologies demonstrates the comparative control efficiency and accuracy.     

Machine learning in vehicular networking: An overview

As vehicle complexity and road congestion increase, combined with the emergence of electric vehicles, the need for intelligent transportation systems to improve on-road safety and transportation efficiency using vehicular networks has become essential. The evolution of high mobility wireless networks will provide improved support for connected vehicles through highly dynamic heterogeneous networks. Particularly, 5G deployment introduces new features and technologies that enable operators to capitalize on emerging infrastructure capabilities. Machine Learning (ML), a powerful methodology for adaptive and predictive system development, has emerged in both vehicular and conventional wireless networks. Adopting data-centric methods enables ML to address highly dynamic vehicular network issues faced by conventional solutions, such as traditional control loop design and optimization techniques. This article provides a short survey of ML applications in vehicular networks from the networking aspect. Research topics covered in this article include network control containing handover management and routing decision making, resource management, and energy efficiency in vehicular networks. The findings of this paper suggest more attention should be paid to network forming/deforming decision making. ML applications in vehicular networks should focus on researching multi-agent cooperated oriented methods and overall complexity reduction while utilizing enabling technologies, such as mobile edge computing for real-world deployment. Research datasets, simulation environment standardization, and method interpretability also require more research attention.     

基于模糊C均值聚类和随机森林的短时交通状态预测方法

交通拥堵长期以来是城市面临的主要问题之一,解决交通拥堵瓶颈刻不容缓。准确的短时交通状态预测有利于市民预知交通出行信息,及时采取措施避免陷入拥堵困境。该文提出一种基于模糊C均值聚类(FCM)和随机森林的短时交通状态预测方法。首先,利用一种新颖的融合时空信息的自适应多核支持向量机(AMSVM)来预测短时交通流参数,包括流量、速度和占有率。其次,基于FCM算法分析历史交通流,获取历史交通状态信息。最后,利用随机森林算法分析所预测的短时交通流参数,得到最终预测的短时交通状态。该方法在融合时空信息的同时采用随机森林算法应用于短时交通状态预测这一全新的研究领域。实验结果表明,FCM对历史交通状态的评估方式适用于不同的高速路和城市道路场景。其次,随机森林比其它常见的机器学习方法具有更高的预测精度,从而提供实时可靠的短时交通出行信息。     

A taxonomy for congestion control algorithms in packet switchingnetworks

The authors propose a new taxonomy for congestion control algorithms in packet switching computer networks based on control theory. They view a network as a large, distributed control system, in which a congestion control scheme is a (distributed) control policy executable at each node (host or switches) of the network in order to a certain level of stable conditions. This taxonomy provides a coherent framework for the comparative study of existing algorithms and offers clues toward the development of new congestion control strategies     

Simulation study on the interactivity of failure detection and signaling congestion control in intelligent optical networks

The Intelligent Optical Network (ION) has emerged as a promising technology in the development of optical networks. ION has a separate control plane, where real-time processing is a most substantial feature. However, the complicated control and management infrastructure requires multiple protocols to cooperate in the same signaling network, and jitter may impair real-time processing, like fast failure detection. In this article, the interactivity of failure detection and network congestion control will be analyzed and proposed solutions will be evaluated by simulations. The failure detection protocol in the control plane is inherited from IP networks. However, there is a scalability problem in the ION when requiring fast detection time. Congestion in the signaling network may be caused by various events. It could be fatal when interacting with fast failure detection would trigger a positive feedback. Several solutions will be presented and analyzed with respect to fast and scalable failure detection and congestion control. We performed a series of intensive simulations to study the interactivity of failure detection and congestion control on the 32-node USNET. The simulation results show that the proposed Enhanced Hello protocol performs well in both fast detection mode and congestion state, especially with far less false failure alarms. The Retransmission Reduction mechanism, which is designed to alleviate congestion, can avoid message loss in some degree, but gives little improvement in other aspects.     

基于模糊控制理论的交通信号控制算法研究

造成交通拥挤往往突出表现在道路的交叉口处,在综合了模糊控制技术和城市信号交叉口交通信号控制技术基础上,针对多路口交通控制的特征及实际交通状况,对已有模糊控制算法进行了改进,在单路口模糊控制研究的基础上,研究了基于相序优化模糊控制的城市区域交通信号控制系统。此方法不需要建立复杂的交通流模型,对城市交通控制系统实施模糊控制,可以有效地解决交通信号控制过程中复杂性和随机性难题,从而对绿灯信号的调整做出更合理的匹配,提高交叉路口的通行率近20%。     

An analysis of vehicle-to-infrastructure communications for non-signalised intersection control under mixed driving behaviour

Intersection control has an important role in the management of urban traffic to ensure safety, high traffic flow and to prevent congestion. Recently, a growing body of literature has been reported on the theme of non-signalised intersection control in which traffic lights are replaced with intelligent road side units. Data from several studies suggest that non-signalised control could reduce vehicle delays and fuel consumption significantly whilst ensuring safety. However, there is little published data on the impact of the mixed driving behaviour with human-driven vehicles and autonomous vehicles. This paper investigates the emerging role of connectivity and vehicle autonomy in the context of traffic control under the mixed driving behaviour scenario. The concepts of vehicle-to-infrastructure (V2I) communications and multi-agent systems are central to achieving a robust and reliable traffic-light-free intersection control. Comprehensive computer simulation results on a four-way intersection indicate over 96% reduced average vehicle delay and 37% less fuel consumption with the non-signalised control solution compared to the traffic light control. The outcome of this study offers some important insights into enabling cooperation between vehicles and traffic infrastructure via V2I communications, in order to make more efficient real-time decisions about traffic conditions, whilst ensuring a higher degree of safety.     

大数据背景下智慧城管数据采集策略分析

随着我国城市的快速发展,城市管理问题也日益凸显,如夜市摊贩问题、交通拥堵问题、道路破损问题、施工工地问题、交通路灯故障问题、车辆随意停放问题、城市清洁问题等,这些问题会影响到城市的正常运转,给市民生活造成不良体验,从而受到社会的广泛关注。基于此,文中首先简要介绍了智慧城管的相关概念,然后详细讨论了传统数据采集和大数据下的智慧城管相关策略,阐述了智慧城管的相关应用。     

Road State Novel Detection Approach in VANET Networks Based on Hadoop Ecosystem

Wireless Personal Communications - The problem of road congestion is becoming more and more serious in urban areas, which calls for solutions. This makes life in cities uncomfortable and costs a...     

Joint rate and power control algorithms for wireless networks

There is a fundamental tradeoff between power consumption, data transmission rates, and congestion levels in a wireless network. These three elements influence the performance of rate and power control strategies, and they need to be coordinated judiciously. This paper proposes dynamic rate and power control algorithms for distributed wireless networks that also account for the congestion levels in a network. The design is pursued by formulating state-space models with and without uncertain dynamics and by determining control signals that help meet certain performance criteria (such as robustness and desired levels of signal-to-interference ratio). Simulation results illustrate the performance of the proposed control schemes.     

Infrastructure‐based vehicular congestion detection scheme for V2I

With the increasing number of vehicles, traffic jam becomes one of the major problems of the fast‐growing world. Intelligent transportation system (ITS) communicates perilous warnings and information on forthcoming traffic jams to all vehicles within its coverage region. Real‐time traffic information is the prerequisite for ITS applications development. In this paper, on the basis of the vehicle‐to‐infrastructure (V2I) communication, a novel infrastructure‐based vehicular congestion detection (IVCD) scheme is proposed to support vehicular congestion detection and speed estimation. The proposed IVCD derives the safety time (time headway) between vehicles by using iterative content‐oriented communication (COC) contents. Meanwhile, the roadside sensor (RSS) provides an infrastructure framework to integrate macroscopic traffic properties into the estimation of both the traffic congestion and vehicle safety speed. The main responsibilities of RSS in IVCD are to preserve privacy, aggregate data, store information, broadcast routing table, estimate safety speed, detect traffic jam, and generate session ID (S‐ID) for vehicles. Monte Carlo simulations in four typical Chinese highway settings are presented to show the advantage of the proposed IVCD scheme over the existing Greenshield's and Greenberg's macroscopic congestion detection schemes in terms of the realized congestion detection performance. Real road traces generated by Simulation of Urban Mobility (SUMO) over NS‐3.29 are utilized to demonstrate that the proposed IVCD scheme is capable of effectively controlling congestion in both single and multilane roads in terms of density and speed health with previous schemes in this field.     

Unified control infrastructure for carrier network evolution

Migration strategies for the network control infrastructure are discussed, to evolve carrier networks toward an optical transport backbone optimized for IP traffic. The strategies presented aim to protect carriers' investments in their current multiservice and IP-routed networks, while expediting the backbone migration toward a unified packet-over-optical core for IP and multiservice transport. This unified core network simplifies the network layers and control systems, and consolidates data and multiservice traffic to reduce network cost with improved bandwidth efficiency. The network control system, including signaling, addressing, and routing, is analyzed in detail to demonstrate the feasibility of the proposed infrastructure. Built on multiprotocol label switching (MPLS) technology, the presented solutions take phased evolution steps to reduce network cost, improve bandwidth efficiency, and offer practical options for internetworking during the migration. These solutions provide carriers with competitive advantages to consolidate multiple services onto an IP-centric optical transport network. The unified control infrastructure not only offers flexible options for network upgrade with reduced network management overhead, but also supports enhanced networking and traffic engineering capabilities to ensure no compromise in the service level agreement committed to end customers.