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Neural network based online traffic signal controller design with reinforcement training

Neural network based online traffic signal controller design...

引用

International Conference on Intelligent Transportation

作者： Yujie Dai Jinzong Hu Dongbin Zhao Fenghua Zhu State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation Chinese Academy of Sciences (CAS) Beijing China Changchun Institute of Optics Fine Mechanics and Physics Chinese Academy of Sciences (CAS) China

Traffic congestion leads to problems like delays, decreasing flow rate, and higher fuel consumption. Consequently, keeping traffic moving as efficiently as possible is not only important to economy but also important to environment. Traffic system is a large complex nonlinear stochastic system. Traditional mathematical methods have some limitations when they are applied in traffic control. Thus, computational intelligence (CI) technologies gain more and more attentions. Neural Networks (NNs) is a well developed CI technology with lots of promising applications in traffic signal control (TSC). In this paper, a neural network (NN) based signal controller is designed to control the traffic lights in an urban traffic road network. Scenarios of simulation are conducted under a microscopic traffic simulation software. Several criterions are collected. Results demonstrate that through online reinforcement training the controllers obtain better control effects than the widely used pre-time and actuated methods under various traffic conditions.

关键词： Artificial neural networks Training Vehicles Roads Software Real time systems Learning systems

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Modeling and analyzing transportation systems based on ACP approach

Modeling and analyzing transportation systems based on ACP a...

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International Conference on Intelligent Transportation

作者： Fenghua Zhu Fei-Yue Wang Runmei Li Yisheng Lv Songhang Chen State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation Chinese Academy of Sciences (CAS) Beijing China School of Electronics and Information Engineering Beijing Jiaotong University BJTU Beijing China

The ACP (Artificial societies, Computational experiments and Parallel execution) approach has provided us an opportunity to look into new methods in addressing transportation problems from new perspectives. In this paper, we present our works and results of applying ACP approach in modeling and analyzing transportation system, especially carrying out computational experiments based on artificial transportation systems. Two aspects in the modeling process are analyzed. The first is growing artificial transportation system from bottom up using agent-based technologies. The second is modeling environment impacts in simple-is-consistent principle. Finally, two computational experiments are carried out on one specific ATS, Jinan ATS, and numerical results are presented to illustrate the applications of our method.

关键词： Analytical models Rain Computational modeling Vehicles Object oriented modeling

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An optimized modeling method based on BPEL4WS

An optimized modeling method based on BPEL4WS

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IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI

作者： Sheng Liu Gang Xiong Dong Fan Jianshi Yao State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation Chinese Academy of Science Beijing 100190 China Unit 61541 The Chinese People's Liberation Army Beijing 100094 China

As an efficient business process execution language which supports web services, BPEL4WS is widely supported by the academic and the industrial circles. According to the shortcomings such as number of computer terms, abstract model definition and the complex description of people activity, this paper presents easy-to-use BPEL4WS modeling method and tool which encapsulates computer terms and convert business models to BPEL4WS models directly. In comparison to the other modeling methods, our method cut down the number of modeling elements by more than 85 percent and save the modeling time by 80 percent and accelerate model running by more than 40 percent. Thus it is more appropriate for popularization.

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Video vehicle detection through multiple background-based features and statistical learning

Video vehicle detection through multiple background-based fe...

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International Conference on Intelligent Transportation

作者： Mingxia Sun Kunfeng Wang Ming Tang Fei-Yue Wang Jinfeng Yang Tianjin Key Laboratory of Advanced Signal Processing Civil Aviation University of China Tianjin China State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation Chinese Academy of Sciences (CAS) Beijing China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences (CAS) Beijing China

This paper presents a generic video vehicle detection approach through multiple background-based features and statistical learning. The main idea is to configure several virtual loops (as detection zones) on the image, assuming moving vehicles may cause pixel intensities and local texture to change, and then by identifying such pixel changes to detect vehicles. In this research, multiple pattern classifiers including LDA + Adaboost, SVM, and Random Forests are used to detect vehicles that are passing through virtual loops. We extract fourteen pattern features (related to foreground area, texture change, and luminance and contrast in the local virtual loop zone and the global image) to train pattern classifiers and then detect vehicles. As experimental results illustrate, the proposed approach is quite robust to detect vehicles under complex dynamic environments, and thus is able to improve the accuracy of traffic data collection in all weather for long term.

关键词： Vehicles Feature extraction Training Image edge detection Vehicle detection Meteorology Radio frequency

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The strategies of avoiding energy holes in wireless sensor networks

The strategies of avoiding energy holes in wireless sensor n...

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2011 4th International Congress on Image and Signal Processing(第四届图像与信号处理国际学术会议 CISP 2011)

作者： Xu QIAN Zhengjie WANG Xiaoguang ZHAO School of Mechanical Electronic & Info. Engineering China University of Mining & Technology (Beijing State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automati

Wireless sensor networks are characterized by multihop network. Some nodes in network are required to forward a disproportionately high amount of traffic and die early, leaving the unmonitored areas in network and leading to the problem of energy hole. This paper investigates a variety of strategies to avoid the energy hole, such as communication power control, data aggregation, nonuniform energy distribution, mobile node auxiliary and clustering. The analysis and comparison of different strategies are given and the advantages and disadvantage of them are discussed in this paper.

关键词： wireless sensor networks energy balance energy hole network lifetime

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A Energy Balanced Deployment for Linear Wireless Sensor Networks

A Energy Balanced Deployment for Linear Wireless Sensor Netw...

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2011 International Conference on Computer Science and Network Technology(2011计算机科学与网络技术国际会议 ICCSNT 2011)

作者： Zhengjie Wang Xiaoguang Zhao Xu Qian College of Information and Electrical Engineering Shandong University of Science and Technology Qi State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese School of Mechanical Electronic & Info. Engineering China University of Mining & Technology (Beijin

ISBN: (纸本)9781457715860

Linear wireless sensor networks are characterized by a linear topology and multihop forwarding patterns. Sensors closer to the base station are usually required to forward a large amount of traffic for sensors farther from the base station, leading to the environment cannot be effectively monitored. The energy consumption balance is achieved in the paper by adjusting the distance between nodes. The distance of nodes near the base station become short because they have to forward the more traffic. The node deployment is converted to optimization problems of distance distribution between nodes. The network lifetime under different number of forwarding region is discussed. Simulation results show that this deployment strategy obtains the energy consumption balance.

关键词： wireless sensor networks optimal communication distance energy consumption balance distance optimal

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Agent-based traffic simulation and traffic signal timing optimization with GPU

Agent-based traffic simulation and traffic signal timing opt...

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International Conference on Intelligent Transportation

作者： Zhen Shen Kai Wang Fenghua Zhu State Key Laboratory of Intelligent Control and Management of Complex Systems Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences (CAS) Beijing China Center of Military Computational Experiments and Parallel Systems Technology and College of Mechatronics Engineering and Automation National University of Defense Technology Changsha Hunan China

With the advantage of simulating the details of a transportation system, the “microsimulation” of a traffic system has long been a hot topic in the Intelligent Transportation systems (ITS) research. The Cellular Automata (CA) and the Multi-Agent System (MAS) modeling are two typical methods for the traffic microsimulation. However, the computing burden for the microsimulation and the optimization based on it is usually very heavy. In recent years the Graphics Processing Units (GPUs) have been applied successfully in many areas for parallel computing. Compared with the traditional CPU cluster, GPU has an obvious advantage of low cost of hardware and electricity consumption. In this paper we build an MAS model for a road network of four signalized intersections and we use a Genetic Algorithm (GA) to optimize the traffic signal timing with the objective of maximizing the number of the vehicles leaving the network in a given period of time. Both the simulation and the optimization are accelerated by GPU and a speedup by a factor of 195 is obtained. In the future we will extend the work to large scale road networks.

关键词： Graphics processing unit Vehicles Roads Optimization Computational modeling Genetic algorithms Timing

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Dynamic identifying and tracking framework for cutters using RFID technology in digital workshop

Dynamic identifying and tracking framework for cutters using...

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2011 International Conference on Electronic and Mechanical Engineering and Information Technology, EMEIT 2011

作者： Zhou, Guanghui Xiao, Zhongdong Wang, Ben Jiang, Pingyu State Key Laboratory for Manufacturing Systems Engineering Xi'an China School of Mechanical Engineering Xi'an Jiaotong University Xi'an China School of Management Xi'an Jiaotong University Key Lab. of the Ministry of Education for Process Control and Efficiency Engineering Xi'an China High-Performance Materials Institute Florida State University Tallahassee FL United States

ISBN: (纸本)9781612840857

For effectively solving the problem of accurate tracking and control of cutters in digital workshop, this paper presents a novel RFID-based dynamic identifying and tracking framework for cutters in digital workshop (RFID-DITF-CDW). An overall architecture for RFID-DITF-CDW is established and its key enabling technologies including RFID-based realtime information collecting, dynamic misuse detecting of cutter change on CNC machines, real-time position identifying, status tracking, and service life forecasting for cutters are discussed. Finally, a prototype system of RFID-DITF-CDW is developed and applied in a real typical CNC machining workshop to demonstrate the validity of presented framework and enabling technologies. © 2011 IEEE.

关键词： Radio frequency identification (RFID)

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Algorithm design of traffic incident automatic detection based on mobile detection

Algorithm design of traffic incident automatic detection bas...

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IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI

作者： Zi Zhang Xiaoli Lin Bin Hu Communications Commission of Guangzhou Municipality Guangzhou Communication Information Construction Investment and Operation Company Limited Guangzhou China Transportation Management General Station of Guangzhou Haizhu Guangzhou China State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation Chinese Academy and Sciences Beijing China

Most researches of traffic incident auto-detection are based on the data from fixed detectors, which are limited by costs and position. In order to resolve this problem, existing algorithms of traffic incident automatic detection are analyzed and compared, and an algorithm of traffic incident auto-detection are provided based on mobile-detection technology. The traffic data are grouped in 5-min intervals, analyzed by a three-layer BP neural network, and utilized for traffic incident detection. 16 traffic incidents of different locations and different levels are modeled in the simulation experiment based on VISSIM, and detection rate, false alarm rate and average detection time are adopted as indicators to evaluate the algorithm. Finally, the algorithm is proved to be effective and applicable in practice.

关键词： Three dimensional displays Bayesian methods Detectors

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Forecasting group behavior via multiple plan recognition

Forecasting group behavior via multiple plan recognition

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IEEE International Conference on Intelligence and Security Informatics, ISI

作者： Xiaochen Li Wenji Mao Daniel Zeng Huachi Zhu Key Laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy and Sciences Beijing China Department of Management Information Systems University of Arizona Tucson Tucson AZ USA Beijing Police Department China

Forecasting group behavior is critical to national and international security. Various forecasting methods have been developed previously. However, the majority of them are data-driven methods and rely heavily on the structured data which are often hard to obtain. To overcome the limitation of previous methods, we propose a novel plan recognition method for detecting multiple group behavior based on graph search. We further conduct human experiments in security informatics domain to empirically evaluate our proposed method. The experimental results show the effectiveness of our method.

关键词： Security Forecasting Libraries Informatics Bayesian methods Approximation methods

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