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Zhang J.,CAS Institute of Automation | Zhang J.,Qingdao Academy of Intelligent Industries | Wen D.,National University of Defense Technology | Zeng S.,CAS Institute of Automation | Zeng S.,Qingdao Academy of Intelligent Industries
IEEE Transactions on Intelligent Transportation Systems | Year: 2016

Dynamic ridesharing arranges shared rides for passengers and drivers in real time. Since, in many dynamic ridesharing services, drivers are crowdsourced, the price mechanism design for such services is a fundamental problem. In this paper, a discounted trade reduction mechanism is designed for dynamic ridesharing pricing. Properties of the proposed mechanism are investigated. We also conduct experiments to evaluate the price mechanism. Experimental results show that our mechanism outperforms three double auction baseline mechanisms and illustrate the effect of adjusting the parameter values of our mechanism. © 2015 IEEE.


Zeng M.,CAS Institute of Automation | Zhang X.,Chinese Academy of Sciences | Li J.,Qingdao Academy of Intelligent Industries | Meng Q.,Intelligent Systems Technology, Inc.
Proceedings of the World Congress on Intelligent Control and Automation (WCICA) | Year: 2016

Characterizing the fluctuations properties in wind speed signals is a significant problem in the field of nonlinear dynamics and aerodynamics. In this paper, firstly, to fully capture the details of the wind field fluctuation, a 3D ultrasonic anemometer is selected to measure the wind speed data in a short-term wind field experiment. Then, we employ the multifractal detrended fluctuation analysis (MF-DFA) to reveal the fluctuations characteristics of the short-term wind speed time series. We find that short-term wind speed data exhibit obvious multifractal dynamic behaviors, mainly due to the different long-range correlations. In particular, this multifractality is related to the nonlinear features of the wind speed time series. Furthermore, the effects of sampling frequency on multifractal features of wind speed time series are investigated. The results suggest that when the sampling frequency is higher or lower than 5Hz, there exist different power law relations between the sampling frequency and the singularity value at the peak of multifractal spectrums. © 2016 IEEE.


Dong X.,CAS Institute of Automation | Dong X.,Qingdao Academy of Intelligent Industries
Proceedings - 2016 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2016 | Year: 2016

Virtual Reality (VR) is a three-dimensional computer-generated virtual world. It is essential to introduced VR technology to education area to develop new teaching mode to improve the efficiency and quality of teaching and learning. Among them, VR classroom has quickly become most dazzling star with its subversive advantage. This paper proposes an overall integration solution of VR classroom, including its composition, its scene design of various disciplines and its main advantage. Finally, a case study of a geography lesson is provided to show its advantages and strong potentiality. © 2016 IEEE.


Gong X.,CAS Institute of Automation | Gong X.,Qingdao Academy of Intelligent Industries
Proceedings - 2016 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2016 | Year: 2016

In this article, I would like to share my daughter's experience on self-STEAM education. In our daily life, she can always find problems and then dream them with her imagination, finally narrows down her solutions to solve problems in her own way. During these problem-solving processes, I noticed that she went through sciences, technology, engineering, arts and mathematics in a very natural way. So I would like to say, STEAM is the way we learn and grow ever since we were born. But later at school, we are trained in a way that subjects are completely disconnected. It might take time to change this situation at school, but at home, as parents, we need to realize that children can discover new things by themselves even from young ages, and provide rich learning environment for them and let them 'STEAM' themselves in their own way. © 2016 IEEE.


Yuan Y.,CAS Institute of Automation | Yuan Y.,Qingdao Academy of Intelligent Industries | Wang F.-Y.,CAS Institute of Automation | Wang F.-Y.,National University of Defense Technology | Zeng D.,CAS Institute of Automation
Information Sciences | Year: 2016

Sponsored search advertising (SSA) markets have witnessed soaring bid prices from advertisers, which have been considered to be a potential challenge to the long-term stability, profitability and effectiveness of the SSA ecosystem. One approach to addressing this challenge is identifying cooperative and stable bidding strategies for competing advertisers with the objective of reaching socially optimal outcomes in repeated SSA auctions. Although useful in analyzing advertisers’ bidding behavior in single auction sessions, static game-theoretic analysis and simulation studies in the extant SSA literature offer only limited insights for characterizing the long-term evolutionary dynamics and stability of advertisers’ bidding behavior. In this paper, we address this problem by applying evolutionary game theory and coevolutionary simulation. Our key finding is that a group of “nice” and retaliatory (NR) strategies can promote stable cooperation among competing advertisers. Advertisers using NR strategies will never deviate from cooperation first (nice) and always punish their rivals’ deviations using competitive bids (retaliatory). The NR strategies are shown to be able to encourage advertisers to decrease their bids to obtain revenue that is equal to that awarded under the Vickrey-Clarke-Groves (VCG) auction mechanism and are further shown to alleviate bid inflation effectively at the system level. © 2016 Elsevier Inc.


Lin S.,University of Chinese Academy of Sciences | Kong Q.-J.,Qingdao Academy of Intelligent Industries | Kong Q.-J.,CAS Institute of Automation
2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014 | Year: 2014

Traffic control is an effective and efficient method for the problem of traffic congestion. For complex urban traffic networks, it is necessary to design a high-level controller to regulate the traffic demands. Under the parallel control framework for complex traffic networks, we design a demand-balance MPC controller based on the MFD-based multi-subnetwork model, which can optimize the network traffic mobility and the network traffic throughput by regulating the input traffic flows of the subnetworks. The transferring traffic flows among subnetworks are indirectly controlled by the demand-balance MPC controller, and a global optimality can be achieved for the entire traffic network. The simulation results show the effectiveness of the proposed controller in improving the network traffic throughput. © 2014 IEEE.


Liu Y.,Qingdao Academy of Intelligent Industries | Wang K.,Intelligent Systems Technology, Inc.
Proceedings of 2014 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2014 | Year: 2014

Vehicle classification system is an important part of intelligent transportation system (ITS), which can provide us the necessary information for autonomous navigation, toll systems, surveillance and security systems, and transport planning. In this paper, we introduce a vehicle classification system based on dynamic Bayesian network (DBN). Three main types of features are employed in our system: the geometrical characteristic of the vehicle, the location and shape of license plate, and the vehicle pose. Firstly, vehicle detection and tracking method are used to locate the vehicle. Then, we extract the features from video sequences. Gaussian Mixture Model (GMM) is used to construct the probability distribution of the feature. Finally, we classify a vehicle into one of four classes: sedan, bus, microbus, and unknown. The experiment shows the proposed method can achieve classification exactly and credibly. © 2014 IEEE.


Wang F.-Y.,Chinese Academy of Sciences | Wang F.-Y.,National University of Defense Technology | Wang F.-Y.,Qingdao Academy of Intelligent Industries
IEEE Transactions on Intelligent Transportation Systems | Year: 2015

Provides an overview of the technical articles and features presented in this issue. © 2000-2011 IEEE.


Wang F.-Y.,Chinese Academy of Sciences | Wang F.-Y.,National University of Defense Technology | Wang F.-Y.,Qingdao Academy of Intelligent Industries
IEEE Transactions on Intelligent Transportation Systems | Year: 2015

The first issue of IEEE Intelligent Transportation Systems Society (ITSS) starts with survey papers on technology and security for intelligent vehicles. The first paper titled 'Intra-Vehicle Networks: A Review' by S. Tuohy, M. Glavin, C. Hughes, E. Jones, M. Trivedi, and L. Kilmartin presents a comprehensive overview of current research on advanced intra-vehicle networks and identifies outstanding research questions for the future. J. Petit and S. E. Shladover's paper, 'Potential Cyberattacks on Automated Vehicles' analyzes the threats on autonomous automated vehicle and cooperative automated vehicle. 'A Video-Analysis-Based Railway-Road System for Detecting Hazard Situations at Level Crossings' by H. Salmane, L. Khoudour, and Y. Ruichek explores the possibility of implementing a smart video surveillance security system that is tuned toward detecting and evaluating abnormal situations induced by users in level crossing. 'Traffic Flow Prediction for Road Transportation Networks with Limited Traffic Data' by A. Abadi, T. Rajabioun, and P. A. Ioannou, uses a dynamic traffic simulator to generate flows in all links using available traffic information, estimated demand, and historical traffic data available from links equipped with sensors. The paper titled 'GNSS Multipath and Jamming Mitigation Using High-Mask-Angle Antennas and Multiple Constellations' studies the optimal antenna mask angle that maximizes the suppression of interference but still maintains the performance of a single constellation with a low-mask-angle antenna.


Zhao Y.-F.,Qingdao Academy of Intelligent Industries | Kong Q.-J.,Qingdao Academy of Intelligent Industries | Gao H.,Qingdao Academy of Intelligent Industries | Zhu F.-H.,Qingdao Academy of Intelligent Industries | Wang F.-Y.,Qingdao Academy of Intelligent Industries
2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014 | Year: 2014

With the rapid growth of the number of urban vehicles, it will be not advisable to alleviate traffic congestion by changing the traffic facilities only. And the traditional control strategies for single intersection or regional multiple intersections have been confirmed to have some effect in the past few decades, but still need to be improved. Based on ACP (Artificial societies, Computational experiments, Parallel execution) idea, we firstly proposed the concept of 'event agent' in this paper, which refers to the ratings that traffic states give corresponding timing plans. Based on event agent, we used computational methods to establish a Parallel transportation Management Systems (PtMS), which was a self-completing system. In the system plenty of artificial events were generated, and some of them can not only simulate the actual traffic events, but also be substitutes for the actual events. Then through the parallel execution between actual and artificial events, the system recommends the most suitable timing plans to the current traffic state. Different from traditional control strategies, event agent based PtMS takes results as an orientation according to the idea of data-driven, which is more adaptive to the characteristics of transportation systems. For ensuring the validity and accuracy of experiments, our related data are all based on the famous traffic micro-simulation software Paramics. Furthermore, we compared our method with the classic Webster method, and experiments achieved good results. © 2014 IEEE.

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