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检索条件"机构=Key Laboratory of Urban ITS Technology Optimization and Integration"

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A method of visual management platform for connected vehicles data

A method of visual management platform for connected vehicle...

引用

International Conference on Connected Vehicles and Expo (ICCVE)

作者： Yunpeng Wang Yuzhou Li Daxin Tian Jian Wang Jiajie Wang School of Information Engineering Academy of Armored Forces Engineering Beijing China Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems & Safety Control Beihang University Beijing China Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies Nanjing China Key Lab. of Urban ITS Technology Optimization and Integration Ministry of Public Security of China Hefei China

At present, the collection of connected vehicles data is not a problem any more but the platform and visualization are the most needed for traffic data. Management of the collected data, platform operation, and visualization technology are the topics of this paper. Through using the new ECharts data visualization tool, we could achieve large data in real-time display with an ordinary WEB browser.

关键词： Data visualization Big data Vehicles Databases Connected vehicles Market research

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A method for dividing roadside unit alliances with cooperative vehicle infrastructure system 3

A method for dividing roadside unit alliances with cooperati...

引用

3rd International Conference on Electronics technology and Artificial Intelligence, ETAI 2024

作者： Chen, Siqi Hao, Ying Wei, Jing Xing, Jiandong Wang, Jixiang Beihang University 37 Xueyuan Road Haidian District Beijing100191 China Hefei Innovation Research Institute Beihang University West of the intersection between Wenzhong Road and Weiwu Road Xinzhan District Hefei230013 China Anhui Keli Information Industry Co. Ltd. 628 Huangshan Road Shushan District Hefei230000 China Key Laboratory of Urban ITS Technology Optimization and Integration Ministry of Public Security 628 Huangshan Road Shushan District Hefei230000 China North China University of Technology 5 Jinyuanzhuang Road Shijingshan District Beijing100144 China

ISBN: (纸本)9781510683143

With cooperative vehicle infrastructure system, information exchange can occur between vehicles and road side units(RSU), and there is potential for the improvement of communication benefits brought about by vehicle road collaboration to be explored. This article reduces the cost of roadside unit information dissemination through vehicle to vehicle(V2V) communication. The roadside units participating in the cooperation each distribute a portion of the message, while the vehicles exchange information during aggregation, thereby achieving information sharing. However, cooperation between roadside units can also lead to increased costs. To address this issue, this article establishes a collaborative vehicle road communication scenario and proposes a core network side alliance partitioning method based on message passing neural network (MPNN). The effectiveness of the algorithm is verified through simulation. © 2024 SPIE.

关键词： Deep reinforcement learning

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An Evaluation Model for Epidemic Routing in VANETs

An Evaluation Model for Epidemic Routing in VANETs

引用

Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing, UIC-ATC

作者： Daxin Tian Yue Yang Haiying Xia Guohui Zhang Ministry of Public Security of China Key Lab of Urban ITS Technology Optimization and Integration Hefei China Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control Beihang University Beijing China Research Institute of Highway Ministry Transport Beijing China School of Information Engineering Academy of Armored Forces Engineering Beijing China

ISBN: (纸本)9781467372121

Epidemic routing has emerged as a promising candidate for providing message dissemination method in vehicular ad hoc networks. In this paper, we present a novel model to evaluate the capacity of epidemic routing in vehicular networks with considering the traffic signal control as a significant factor in urban area. Our study reveal that epidemic routing can behave differently in various traffic signal control situations where messages can be forwarded by vehicles passing through the intersections from other directions. The simulation results prove the accuracy of the model.

关键词： Roads Vehicles Delays Routing Turning Simulation Dynamic programming

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Tunnel moving target detection based on local structure of image and gray scale information

Tunnel moving target detection based on local structure of i...

引用

IEEE International Conference on Intelligent Transportation Engineering (ICITE)

作者： Haiyang Yu Yawen Hu Hongyu Guo Lin Fang People's Republic of China Key Laboratory of Urban ITS Technology Optimization and Integration Ministry of Public Security Hefei China School of Transportation Science and Engineering Beihang University Beijing China Infrastructure Systems and Safety Control Beihang University Beijing China Information Industry Co. Ltd. Beijing China

ISBN: (纸本)9781467390491

Tunnel moving target detection is subject to the influence of light condition and motion blur, the traditional motion detection method based on pixel points can not be very good at segmenting moving target. To solve this problem, frame difference detection method based on local structure of image and gray level information is proposed. The local mean difference information of the image is calculated by the improved algorithm, and then the similarity measure function and the gray scale measure function are constructed. The similarity measure function effectively describes the structural features of moving objects, and reduces the influence of image background information. The gray scale function is better to highlight the contrast of the target brightness, to increase the division of the target area and the background parts, and to realize the moving target detection correctly. The experimental results show that the detection method of the fusion structure and the gray level information can effectively segment the moving object.

关键词： Image segmentation Object detection Brightness Electronic mail Motion segmentation Lighting Transportation

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A Vehicular Positioning Enhancement with Connected Vehicle Assistance Using Extended Kalman Filtering 1st

A Vehicular Positioning Enhancement with Connected Vehicle A...

引用

1st International Conference on 5G for Future Wireless Networks, 5GWN 2017

作者： Tian, Daxin Liu, Wenhao Duan, Xuting Rong, Hui Guo, Peng Wang, Wenyang Zhang, Haijun Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University XueYuan Road No. 37 Beijing100191 China China Automotive Technology and Research Center Automotive Engineering Research Institute East Xianfeng Road No. 68 Tianjin300300 China School of Computer and Communication Engineering University of Science and Technology Beijing XueYuan Road No. 30 Beijing100083 China Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control School of Transportation Science and Engineering Beihang University XueYuan Road No. 37 Beijing100191 China Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies Si Pai Lou. 2 Nanjing210096 China Key Lab of Urban ITS Technology Optimization and Integration The Ministry of Public Security of China Hefei230088 China

ISBN: (纸本)9783319728223

In this paper, we consider the problem of vehicular positioning enhancement with emerging connected vehicles (CV) technologies. In order to actually describe the scenario, the Interacting Multiple Model (IMM) filter is used for depicting varies of observation models. A CV-enhanced IMM filtering approach is proposed to locate a vehicle by data fusion from both coarse GPS data and the Doppler frequency shifts (DFS) measured from dedicated short-range communications (DSRC) radio signals. Simulation results state the effectiveness of the proposed approach called CV-IMM-EKF. © 2018, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Global positioning system

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REFF: REliable and Fast Forwarding in Vehicular Ad-hoc Network 1st

REFF: REliable and Fast Forwarding in Vehicular Ad-hoc Netwo...

引用

1st International Conference on 5G for Future Wireless Networks, 5GWN 2017

作者： Tian, Daxin Dai, Ziyi Zheng, Kunxian Zhou, Jianshan Duan, Xuting Guo, Peng Rong, Hui Wang, Wenyang Zhang, Haijun Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University XueYuan Road No. 37 Beijing100191 China China Automotive Technology and Research Center Automotive Engineering Research Institute East Xianfeng Road No. 68 Tianjin300300 China School of Computer and Communication Engineering University of Science and Technology Beijing XueYuan Road No. 30 Beijing100083 China Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control School of Transportation Science and Engineering Beihang University XueYuan Road No. 37 Beijing100191 China Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies Si Pai Lou. 2 Nanjing210096 China Key Lab of Urban ITS Technology Optimization and Integration The Ministry of Public Security of China Hefei230088 China

ISBN: (纸本)9783319728223

Vehicular Ad-Hoc Network (VANET) has emerged as an increasingly dominant technology for future connected vehicle and vehicular networks, where the focus of the development of VANET lies in the standardization of message transmission and dissemination via multi-hop broadcasting. However, the current communication protocols concerning VANET face many challenges, including data flooding and collision, transmission delay and other problems. Most of the challenges are closely related to next-hop selection. Therefore, this paper proposes a new routing protocol named REliable and Fast Forwarding (REFF) to optimize the selection of nodes in VANET. In this protocol, node filtering and node evaluation are two main steps. Distance between previous node and candidate node, relative velocity between previous node and candidate nodes, included angle between direction of target node’s velocity and candidate node’s velocity and transmission power of candidate node are adopted as indexes to help select a specific node as the next hop using Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). By using this technique, the number of candidates as next-hop is largely reduced, avoiding the data flooding and resulting transmission relay. In addition, simulations based on experiments are done to verify the feasibility. The results show that message achieves a faster and more reliable transmission using REFF. © 2018, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Vehicular ad hoc networks

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Modeling and Simulation on Cooperative Movement of Vehicle Group Based on the Behavior of Fish 1st

Modeling and Simulation on Cooperative Movement of Vehicle G...

引用

1st International Conference on 5G for Future Wireless Networks, 5GWN 2017

作者： Tian, Daxin Kang, Lu Zheng, Kunxian Duan, Xuting Rong, Hui Guo, Peng Wang, Wenyang Zhang, Haijun Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University XueYuan Road No.37 Beijing100191 China China Automotive Technology and Research Center Automotive Engineering Research Institute East Xianfeng Road No.68 Tianjin300300 China School of Computer and Communication Engineering University of Science and Technology Beijing XueYuan Road No.30 Beijing100083 China Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control School of Transportation Science and Engineering Beihang University XueYuan Road No.37 Beijing100191 China Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies Si Pai Lou. 2 Nanjing210096 China Key Lab of Urban ITS Technology Optimization and Integration The Ministry of Public Security of China Hefei230088 China

ISBN: (纸本)9783319728223

Fatigue driving might affect the traffic safety when the vehicles are on the cruising state in highway. Trying to solve this problem, this paper uses the movement pattern of the fish to the vehicles fleet, and develops a model of vehicle group with realistic restrictions based on the existed fish algorithms, the mobile behavioral model and cluster behavior model, and then demonstrates the feasibility of applying the fish behavior to the cooperative movement of vehicle groups through analyzing the trajectory, velocity and spacing of vehicles. © 2018, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Vehicles

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A Novel Intrusion Detection System Based on Advanced Naive Bayesian Classification 1st

A Novel Intrusion Detection System Based on Advanced Naive B...

引用

1st International Conference on 5G for Future Wireless Networks, 5GWN 2017

作者： Wang, Yunpeng Li, Yuzhou Tian, Daxin Wang, Congyu Wang, Wenyang Hui, Rong Guo, Peng Zhang, Haijun Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University XueYuan Road No. 37 Beijing100191 China China Automotive Technology and Research Center Automotive Engineering Research Institute East Xianfeng Road No. 68 Tianjin300300 China School of Computer and Communication Engineering University of Science and Technology Beijing XueYuan Road No. 30 Beijing100083 China XueYuan Road No. 37 Beijing100191 China Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies Si Pai Lou. 2 Nanjing210096 China Key Lab of Urban ITS Technology Optimization and Integration The Ministry of Public Security of China Hefei230088 China

ISBN: (纸本)9783319728223

Intrusion Detection System is a pattern recognition task whose aim is to detect and report the occurrence of abnormal or unknown network behaviors in a given network system being monitored. In this paper, we propose a machine learning model, advanced Naive Bayesian Classification (NBC-A) which is based on NBC and ReliefF algorithm, to be used in the novel IDS. We use ReliefF algorithm to give every attribute of network behavior in KDD’99 dataset a weight that reflects the relationship between attributes and final class for better classification results. The novel IDS has a higher True Positive (TP) rate and a lower False Positive (FP) rate in detection performance. © 2018, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Intrusion detection

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A freeway travel time predicting method based on IoV

A freeway travel time predicting method based on IoV

引用

IEEE World Forum on Internet of Things (WF-IoT)

作者： Daxin Tian Chao Liu Yunpeng Wang Guohui Zhang Haiying Xia Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies Nanjing China Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems & Safety Control Beihang University Beijing China Ministry of Public Security of China Key Lab of Urban ITS Technology Optimization and Integration Hefei China Academy of Armored Forces Engineering School of Information Engineering Beijing China Research Institute of Highway Ministry Transport Beijing China

ISBN: (纸本)9781509003679

Real-time travel time is one of the important value for traffic management and traffic control. With the help of Internet of Vehicles (IOV), the dynamic traffic information can be collected and distributed more correctly. In this paper, we propose a method to predict the remaining travel time (RTT) for a vehicle on the freeway in the IOV environment. The Markov chains are adopted to predict a vehicle's remaining travel time in real-time. The experimental results prove that the mean absolute percent error (MAPE) is less than 10%.

关键词： Vehicles Traffic control Intelligent vehicles Markov processes Computational modeling Cloud computing

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Optimizing RSUs Network against Cascading Failure

Optimizing RSUs Network against Cascading Failure

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Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing, UIC-ATC

作者： Wenzhong Tang Xiongyu Shan Daxin Tian Zhengguo Sheng Haiying Xia Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control Beihang University Beijing China The Ministry of Public Security of China ITS Technology Optimization and Integration Hefei China Department of Engineering and Design The University of Sussex Richmond UK Research Institute of Highway Ministry Transport Beijing China

ISBN: (纸本)9781467372121

Nowadays, with the development of the vehicular ad hoc network, the reliability and stability of the communication network between RSUs has become a critical issue. So in the case of cascading failure, what topological structure can generate a relatively robust network with a relatively low cost? In this paper, we take advantage of a cascading failure model to simulate the cascading failure process of the network, at the same time, we make use of an evolution algorithm to evolve the network. Thus can obtain the network with relatively best comprehensive properties. Then take advantage of the statistical characteristics to analyze the topological structure of the network. The analysis shows that, the high clustering, high assortativity and the relatively large average shortest path length are all beneficial to improve the comprehensive properties of the network, while the network with good comprehensive properties also has a relatively homogeneous degree distribution.

关键词： Power system faults Power system protection Complex networks Communication networks Vehicles Vehicular ad hoc networks Load modeling

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