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Traffic signal controller based on mobile agent

Traffic signal controller based on mobile agent

引用

2012 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2012

作者： Chen, Cheng Li, Zhenjiang State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Dongguan Research Institute of CASIA Cloud Computing Center Chinese Academy of Sciences Songshan Lake Dongguan China

ISBN: (纸本)9781467324007

With mobile agent technology, multi-agent traffic management system is one effective approach to realize the demand-based control. Traffic signal controller is the base of traffic management system. Hence, the realization of traffic signal controller based on mobile agent is indispensable. In this paper, we detailed the traffic signal controller based on Mobile agent in CASIA. Meanwhile, test data about its performance is given. © 2012 IEEE.

关键词： controllers

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A target-reaching controller for mobile robots using spiking neural networks

A target-reaching controller for mobile robots using spiking...

引用

19th International Conference on Neural Information Processing, ICONIP 2012

作者： Wang, Xiuqing Hou, Zeng-Guang Lv, Feng Tan, Min Wang, Yongji Vocational and Technical Institute Hebei Normal University Shijiazhuang Hebei 050031 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100090 China State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9783642344770

Autonomous navigation plays important role in mobile robots. In this paper, a navigation controller based on spiking neural networks (SNNs) for mobile robots is presented. The proposed target-reaching navigation controller, in which the reactive architecture is used, is composed of three sub-controllers: the obstacle-avoidance controller and the wall-following controller using spiking neural networks (SNNs), and the goal-reaching controller. The experimental results show that the navigation controller can control the mobile robot to reach the target successfully while avoiding the obstacle and following the wall to get rid of the deadlock caused by local minimum. The proposed navigation controller does not require accurate mathematical models of the environment, and is suitable to unknown and unstructured environment. © 2012 Springer-Verlag.

关键词： Mobile robots

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A weighted pattern recognition algorithm for short-term traffic flow forecasting

A weighted pattern recognition algorithm for short-term traf...

引用

IEEE International Conference on Networking, Sensing and control

作者： Shuangshuang Li Zhen Shen Fei-Yue Wang State Key Laboratory of Management and Control for Complex Systems Beijing Engineering Research Center for Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China

The k-nearest neighbor (k-NN) nonparametric regression is a classic model for single point short-term traffic flow forecasting. The traffic flows of the same clock time of the days are viewed as neighbors to each other, and the neighbors with the most similar values are regarded as nearest neighbors and are used for the prediction. In this method, only the information of the neighbors is considered. However, it is observed that the “trends” in the traffic flows are useful for the prediction. Taking a sequence of consecutive time periods and viewing the a sequence of “increasing”, “equal” or “decreasing” of the traffic flows of two consecutive periods as a pattern, it is observed that the patterns can be used for prediction, despite the patterns are not from the same clock time period of the days. Based on this observation, a pattern recognition algorithm is proposed. Moreover, empirically, we find that the patterns from different clock time of the days can have different contributions to the prediction. For example, if both to predict the traffic flow in the morning, the pattern from the morning can lead to better prediction than same patterns from afternoon or evening. In one sentence, we argue that both the pattern and the clock time of the pattern contain useful information for the prediction and we propose the weighted pattern recognition algorithm (WPRA). We give different weights to the same patterns of different clock time for the prediction. In this way, we take both virtues of the k-NN method and the PRA method. We use the root mean square error (RMSE) between the actual traffic flows and the predicted traffic flows as the measurement. By applying the results to actual data and the simulated data, about 20% improvement compare with the PRA is obtained.

关键词： Clocks Data models Pattern recognition Prediction algorithms Mathematical model Meteorology Vectors

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A novel parking control algorithm for a car-like mobile robot

A novel parking control algorithm for a car-like mobile robo...

引用

IEEE International Conference on Networking, Sensing and control

作者： Yaru Zhang Shuming Tang Zhilin Zhang State Key Laboratory of Management and Control for Complex Systems Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China

This paper proposes a novel algorithm for parking motion of a Car-like mobile robot. The algorithm presented here addresses calculating equations for planning a parking path in real time. Moreover, by incorporating the constraints of the mechanical and kinematical characteristics of the car and the geometry of the parking lot in the path planning, we can turn a parking problem into solving algebraic equations. By tracking a planned path, the Car-like mobile robot can drive into the parking area without hitting any boundaries. The efficiency of the proposed algorithm is demonstrated by simulation.

关键词： Vehicles Mobile robots Algorithm design and analysis Mathematical model Turning Equations Signal processing algorithms

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A review on vision-based pedestrian detection in intelligent transportation systems

A review on vision-based pedestrian detection in intelligent...

引用

IEEE International Conference on Networking, Sensing and control

作者： Bo Li Qingming Yao Kunfeng Wang State Key Laboratory of Management and Control for Complex Systems Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China

Pedestrians are key participants in transportation systems, so pedestrian detection in video surveillance systems is of great significance to the research and application of intelligent Transportation systems (ITS). We review some methods and models for vision-based pedestrian detection in recent years. In this paper, the pedestrian detection techniques are divided into macroscopic and microscopic according to different application in transportation systems. Macroscopic pedestrian detection aims to estimate crowd density without distinguishing each pedestrian, and microscopic pedestrian detection focuses on detection and recognition of individual pedestrians. The latter detection style is deeply studied, so it is presented in detail in this paper, especially for the feature-classifier-based detection method. Finally, the pedestrian detection algorithms are discussed and concluded from the viewpoint of video surveillance and ITS. Existing problems and future trends are presented in that section.

关键词： Feature extraction Shape Training Transportation Traffic control Video surveillance

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A vehicle license plate recognition system based on analysis of maximally stable extremal regions

A vehicle license plate recognition system based on analysis...

引用

IEEE International Conference on Networking, Sensing and control

作者： Bo Li Bin Tian Qingming Yao Kunfeng Wang State Key Laboratory of Management and Control for Complex Systems Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China

Vehicle License Plate Recognition (VLPR) system is a core module in intelligent Transportation systems (ITS). In this paper, a VLPR system is proposed. Considering that license plate localization is the most important and difficult part in VLPR system, we present an effective license plate localization method based on analysis of Maximally Stable Extremal Region (MSER) features. Firstly, MSER detector is utilized to extract candidate character regions. Secondly, the exact locations of license plates are inferred according to the arrangement of characters in standard license plates. The advantage of this license plate localization method is that less assumption of environmental illumination, weather and other conditions is made. After license plate localization, we continue to recognize the license plate characters and color to complete the whole VLPR system. Finally, the proposed VLPR system is tested on our own collected dataset. The experimental results show the availability and effectiveness of our VLPR system in locating and recognizing all the explicit license plates in an image.

关键词： Licenses Image color analysis Character recognition Lighting Histograms Feature extraction Image segmentation

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Rear lamp based vehicle detection and tracking for complex traffic conditions

Rear lamp based vehicle detection and tracking for complex t...

引用

IEEE International Conference on Networking, Sensing and control

作者： Ye Li Qingming Yao State Key Laboratory of Management and Control for Complex Systems Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China

In video surveillance system, detection and tracking of vehicles are two foundational and significant tasks. In this paper, a vehicle detection and tracking method based on rear lamp pairs is proposed. The proposed method combines color with motion information to perform vehicle detection. In order to adapt to different weather conditions like night, the rear lamps are divided into two categories: unlit lamps and lighted lamps. First, threshold segmentation are used to extract both the unlit and lighted lamp candidates in hue-saturation-value (HSV) color space and the thresholds are selected automatically by maximally stable extremal region (MSER) method. Then, all lamp candidates are tracked by using Kalman filter and lamp candidates with short-lived trajectories are removed to avoid disturbances. Next, two adjacent lamp candidates with similar speed are bound together as a region of interest (ROI), which represents a potential pair of lamps. Image cross-correlation symmetry analysis based on Gabor filter is utilized to find the ROIs with symmetrical texture and these symmetric ROIs can be regarded as pairs of lamps. The experimental results show that the proposed method can effectively deal with various illumination conditions and improve the accuracy and robustness of vehicle detection. In addition, this method can perform vehicle detection and tracking under complex traffic conditions and the Gabor filter based symmetry analysis can successfully suppress subtle difference between the left and right parts of a vehicle as well as environment noises.

关键词： Vehicles Image color analysis Vehicle detection Gabor filters Correlation Tracking Kalman filters

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Learning weighted features for human action recognition

Learning weighted features for human action recognition

引用

International Conference on Pattern Recognition

作者： Wen Zhou Chunheng Wang Baihua Xiao Zhong Zhang Long Ma State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences China

ISBN: (纸本)9781467322164

In traditional bag-of-words method, each local feature is treated evenly for representation. One disadvantage of this method is that it is not robust to noise, which makes the performance impaired. In this paper, a novel human action recognition approach which learns weights for features is proposed, where each feature is assigned a weight for human action representation. These weights are learned jointly with discriminative model. There are two advantages of our model. First, small weights are assigned to noise, which can help to reduce the effect of noise on representation of human action. Second, discriminative features, which are critical for human action recognition, are assigned large weights. Experimental results demonstrate the advantages of the proposed method.

关键词： Humans Noise Support vector machines Accuracy Kernel Feature extraction Noise measurement

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Polarization trend in sponsored search auctions

Polarization trend in sponsored search auctions

引用

22nd Workshop on Information Technologies and systems, WITS 2012

作者： Yuan, Yong Zeng, Daniel Zhao, Huimin Cheng, Jiesi State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Department of Management Information Systems University of Arizona Tucson AZ United States Sheldon B. Lubar School of Business University of Wisconsin-Milwaukee Milwaukee WI United States

Quality score (QS) plays a critical role in sponsored search auctions and in practice is closely related to the historical click-through rate (CTR) of an advertisement. Existing research, however, has not explicitly considered this correlation between QS and historical CTR. In this paper, we strive to bridge this gap. Based on a discrete time-dependent optimal control model, which explicitly captures the CTR-QS correlation, we analyze the optimal positioning strategy and the widely-observed greedy positioning strategy for advertisers. We find that both strategies lead advertisers to monotonically increase or decrease their ranks over time, and thus may result in a polarization trend in sponsored search markets. Our findings can help characterize advertisers' behavior dynamics and also offer valuable insights and suggestions to search engines.

关键词： Polarization

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A dynamic user adaptive combination strategy for hybrid movie recommendation

A dynamic user adaptive combination strategy for hybrid movi...

引用

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

作者： Cai Chen Daniel Zeng State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences China

Movie recommendation is a very popular service in internet based movie related websites such as NetFlix, MovieLens. The performance of the recommendation plays the key role in the user experience. Existing works have shown that combining content based and collaborative filtering based algorithms is the best way for movie recommendation. Nevertheless, the performance of this hybrid algorithm is strongly depended on the strategy how to combine the basic pure algorithms. Existing works usually use a static combination strategy which may generate even worse performance for some users. To solve this problems, in this paper we propose a new item based hybrid algorithm that uses a dynamic user adaptive combination strategy. Besides, we also exploit the external open resources IMDB as the movie content data. Experiments on real datasets show that the dynamic user adaptive combination strategy can significantly enhance the performance of the recommendation and the external open resource IMDB is a very good information resource for recommendation.

关键词： Measurement History Algorithm design and analysis DH-HEMTs Filtering algorithms

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