Smart Cars on Smart Roads: An IEEE Intelligent Transportation Systems Society Update

To promote tighter collaboration between the IEEE Intelligent Transportation Systems Society and the pervasive computing research community, the authors introduce the ITS Society and present several pervasive computing-related research topics that ITS Society researchers are working on. This department is part of a special issue on Intelligent Transportation.     

IEEE Intelligent Systems 2007 Annual Index, Volume 22

The IEEE Intelligent Systems 2007 annual index includes a complete author index and a list of all articles and departments published this year. The PDF file is free, and all titles link to their Computer Society Digital Library abstracts. IEEE Intelligent Systems subscribers can also access the HTML file, which includes internal links for coauthors.     

面向智能交通系统的图像处理

图像处理在智能交通系统（ＩＴＳ）中扮演着极其重要的角色。文章综述了目前ＩＴＳ领域中所广泛采用的图像采集设备、图像处理硬件和图像处理软件,并给出了大量的应用实例。最后,结合目前的研究成果对其今后的发展进行了展望。     

Erratum

IEEE International Conference on Robotics and Automation (ICRA). IEEE/RSJ International Conference on Intelligent Robots and Systems. The American Control Conference. IFAC World Congress. IEEE Conference on Control Technology and Applications. IEEE Conference on Decision and Control. International Conference on Unmanned Aircraft Systems. IEEE International Conference on Systems, Man and Cybernetics. IEEE International Conference on Communications.     

CALL FOR PAPERSEI北大核心CSCD

2012 IEEE Multi-conference on Systems and Control(IEEE MSC 2012) October 3-5,2012 Dubrovnik Palace Hotel,Dubrovnik,CROATIA The 2012 IEEE Multi-Conference on Systems and Control(MSC 2012) will take place in Dubrovnik Palace Hotel,Dubrovnik,Croatia,on October 3 5,2012.MSC 2012 includes two international conferences sponsored and promoted by the IEEE Control Systems Society: The IEEE Conference on Control Applications(CCA) The IEEE International Symposium on Intelligent Control(ISIC)     

A Report on CNSM 2010

The 6th International Conference on Network and Service Management (CNSM 2010) was held on October 25–29, 2010 in Niagara Falls, Canada. CNSM is a premier annual conference, sponsored by IEEE Communications Society and IFIP Working Group on Network and Distributed Systems Management, in the general area of network, systems, and service management. Built upon the success starting in 2005 to collocate six management workshops within the same week (MANWEEK), this year we debuted the single track conference CNSM ().     

时间依赖网络中国邮路问题

中国邮路问题是图论中的经典问题,得到了深入的研究和广泛应用。近年来,由于计算机网络与通信、智能交通系统等复杂应用领域的需求,时间依赖网络问题的研究具有更为重要的现实应用意义。本文首次提出了时间依赖网络中的中国邮路问题,建立了该问题的整数线性规划模型,并对该模型的上界进行了分析,最后给出了网络应用实例。     

Spatial-temporal graph neural network for traffic forecasting: An overview and open research issues

Applied Intelligence - Traffic forecasting plays an important role of modern Intelligent Transportation Systems (ITS). With the recent rapid advancement in deep learning, graph neural networks...     

End-to-end quantum-inspired method for vehicle classification based on video stream

Neural Computing and Applications - Intelligent Transportation Systems (ITS) are the most widely used systems for road traffic management. The vehicle type classification (VTC) is a crucial ITS...     

A Postcard from the Editor

The editor in chief of IEEE Intelligent Systems drops a brief note about his activities during the last couple of months.     

2006 Reviewers

Lists, in alphabetical order, the reviewers who contributed to IEEE Intelligent Systems during 2006.     

The Most Cited Intelligent Systems Articles

In a study of its most cited articles, IEEE Intelligent Systems achieved an H-Index rating of 30 using citation information from ISI's Web of Knowledge and Google Scholar. The author also found that computer science departments' H-Index is strongly related to their ranking in Newsweek's computer science department ranking.     

智能交通系统中2.5G和3G移动通信系统的应用

介绍了ITS的通信业务以及目前为了提供ITS业务所使用的通信系统，讨论了2．5G和3G在ITS中的应用。     

IEEE Intelligent Systems Honors Volunteer Reviewers

This article thanks all of the volunteer reviewers from 2008 who contributed their time to IEEE Intelligent Systems to ensure that the magazine contains the very best content in research and development in artificial intelligence. The excellence of the peer-reviewed articles that appear in IS stems from the tireless efforts of the magazine's volunteer reviewers.     

Multi-modal Information Integration for Interactive Multi-agent Systems

This paper proposes a multi-agent system that carries out cooperative work. To achieve this, we use Fuzzy Associative Memory Organizing Unit Systems (FAMOUS) and Conceptual Fuzzy Sets (CFS). By using these proposed methods, each agent robot can decide its own behaviour to suit the situation in its environment. We apply this system to an Intelligent Transportation System (ITS) and do simulations.     

地图匹配技术及其在智能交通系统中的应用

地图匹配(Map Matching)技术利用电子地图和定位信息来确定车辆在道路上的准确位置,是一种软件纠错技术。该文在引入地图匹配问题的基础上,分析讨论了目前主要的地图匹配算法,并结合智能交通系统(ITS)的需求,探讨了车辆所在道路上具体位置的识别方法,最后对地图匹配技术在ITS中的应用进行了回顾和展望。     

Conference Reports: 2005 International Test Conference

The 36th annual IEEE International Test Conference convened from 8 to 10 November 2005 in Austin, Texas. The location was a significant move for ITC: It was the first time the conference had met west of the Mississippi, as ITC's general chair Rob Aitken pointed out during his introduction at the plenary session. The conference theme, "Test: Survival of the Fittest," called to mind the test industry's rapidly evolving and increasingly competitive nature, especially of recent years.     

基于LS-SVM的交通流时序数据补齐方法

实时、准确的交通流数据是实现智能运输系统（Intelligent Transportation Systems,简称ITS）的关键,对交通流的控制和诱导有直接影响。由于种种原因,通过交通检测器获得的数据往往是不完整的,存在丢失现象,影响了后续模型的实际应用效果。针对这一问题,提出一种基于最小二乘支持向量机 （Least Squares Support Vector Machines,简称LS-SVM） 的交通流时间序列数据补齐模型,利用交通流历史数据对丢失值进行诊断和修补。利用实例仿真验证表明,LS-SVM具有较好的泛化能力和很强的鲁棒性,采用基于LS-SVM的交通流时间序列模型补齐丢失数据能够取得很好的效果。     

A learning-based comprehensive evaluation model for traffic data quality in intelligent transportation systems

Human motion modelling has attracted more and more attentions in various industrial fields with the event of information technology. Previous studies focus on capturing, animating, understanding and modelling human gestures or physical activities. However, in many applications such as Intelligent Transportation Systems (ITS), the traffic data quality (TDQ) is becoming a critical issue which can has great influence on the efficiency of the modelling. In this paper, we focus on evaluating the traffic data quality (TDQ) from the large amount of detectors and traffic flow data in the modelling of Intelligent Transportation Systems (ITS). We first introduce four error indices of an occupancy speed model and an occupancy flow model as model evaluation indices, and two indices from experts as non-model evaluation indices. Then, we propose a comprehensive evaluation model (CEM) for TDQ. Furthermore, we develop two algorithms for training the parameters in CEM based on the least square method (LSM) and the adaptive network based fuzzy inference system (ANFIS). We compare the proposed algorithms with the real-world traffic flow data which has been collected on Beijing ring-roads and connected lines. The experimental results show that the ANFIS-based learning method outperforms in most scenarios and ensures the evaluation error less than 10 %, which can significantly improve the efficiency of identifying traffic flow detectors with low data quality.     

浅谈车牌定位前的车辆图像预处理

随着我国国民经济的高速发展,国内高速公路、城市道路、停车场的建设越来越多,车牌识别系统(LPR)作为智能交通系统(ITS)的一部分起着举足轻重的作用,它的广泛应用必将有助于我国交通管理自动化的进程。一般来说,整个车牌识别系统分为图像采集、车牌定位、字符分割、字符识别四大部分。该文在现有研究算法的理论基础上,详细阐明了车牌定位前的预处理工作,即车辆图像灰度化、二值化、边缘检测以及中值滤波等。