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检索条件"机构=Key Laboratory of Geotechnical Engineering Infrastructure Safety and Control in Jiangxi Province"

共 65 条记录，以下是51-60 订阅

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Freeway Travel Time Prediction Research Based on A Deep Learning Approach

Freeway Travel Time Prediction Research Based on A Deep Lear...

引用

2016 4th International Conference on Advanced Materials and Information Technology Processing(AMITP 2016)

作者： Junfeng Zhang Hongxi Chen Hong Zhou Zhihai Wu School of Transportation Science and Engineering Beihang UniversityBeijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control Jiangsu Province Collaborative Innovation Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies Jiangsu Communications Holdings Co.Ltd

Accurate prediction of freeway travel time is quite significant for traffic management and travelers’ trip decisions. A model of stacked automatic encodersforfreeway travel time prediction is proposed. First, obtain the hourly average travel time by processingfreeway toll data. Considering data quantity and travel time scheduling,a travel timeprediction model based on stacked automatic encodersis established then. The automatic encoder is trained with unsupervised learning step by stepby using historical travel time data, adjust the parameters of prediction layer with gradient descent *** the one-hour travel time is predicted using the past three-hours’ average travel time. Compared to the traditional BP neural network prediction model, the Root Mean Square Error of this methoddrops by 13.6%,verifying the validity of the model.

关键词： Deep learning Toll data Travel time prediction Automatic encoder

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Cooperative Lane Change Model for Connected Vehicles under Congested Traffic Conditions 15

Cooperative Lane Change Model for Connected Vehicles under C...

引用

15th COTA International Conference of Transportation Professionals: Efficient, Safe, and Green Multimodal Transportation, CICTP 2015

作者： Wang, Di Wang, Jianqiang Wang, Yunpeng Tian, Song Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control Beihang University Beijing100191 China School of Transportation Science and Engineering Beihang University Beijing100191 China Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies Nanjing210096 China State Key Laboratory of Automotive Safety and Energy Tsinghua University Beijing100084 China

ISBN: (数字)9780784479292

ISBN: (纸本)9780784479292

This paper proposes a cooperative lane change (CLC) model for connected vehicles to reduce the adverse impact onthe following vehicle in the target lane,and increase the chances of feasible lane change under congested traffic *** this model, the leading vehicles in both lanes are typically considered as active agents. The feasibility criteria for CLC are designed to promise security and acceptable acceleration/deceleration of each involved vehicle, and an objective function is applied to obtain the desired acceleration of each involved vehicle during cooperation, which can reduce the deceleration of the following vehicle in the target lane and balance the kinematic change of each vehicle. The simulation results validate the improvement of the CLC model by employing the traditional lane changemodeland the partial cooperative lane changemodel as comparisonsin a large amount of lane change scenarios. © ASCE.

关键词： Vehicles

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A Dynamic Traffic control Method for an Oversaturated Arterial Road Using High-Resolution Data 15

A Dynamic Traffic Control Method for an Oversaturated Arteri...

引用

15th COTA International Conference of Transportation Professionals: Efficient, Safe, and Green Multimodal Transportation, CICTP 2015

作者： Hu, Yawen Wang, Yunpeng Yu, Haiyang School of Transportation Science and Engineering Beihang University Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control Haidian District Beijing100191 China Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies SiPaiLou #2 Nanjing 210096 China

ISBN: (数字)9780784479292

ISBN: (纸本)9780784479292

The traffic signal control for oversaturated arterial roads is a long-standing problem. This problem gets even more difficult when signal links are congested. The traditional methods have poor control effect for oversaturated arterial road because of low-resolution data. In this paper, a simplified model to describe oversaturation at signalized links based on high-resolution traffic signal data is established. In order to maximize the number of through vehicle in the coordinated direction of arterial road, the signal timing plan is optimized. This method is evaluated by a simulation test in which the control method is applied to a simulation arterial road with 5 intersections. The results demonstrate that the proposed method can effectively improve the capacity of arterial road and dissolve the oversaturated condition. © ASCE.

关键词： Traffic signals

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Feature Extraction of Urban Traffic Network Data Based on Locally Sensitive Discriminant Analysis Algorithm 15

Feature Extraction of Urban Traffic Network Data Based on Lo...

引用

15th COTA International Conference of Transportation Professionals: Efficient, Safe, and Green Multimodal Transportation, CICTP 2015

作者： Xu, Lixiang Wang, Yunpeng Yu, Haiyang Li, Hongbo School of Transportation Science and Engineering Beihang University Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control 37 Xueyuan Road Beijing100191 China Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies SiPaiLou #2 Nanjing210096 China

ISBN: (数字)9780784479292

ISBN: (纸本)9780784479292

The urban road network state can be characterized by diversiform parameters of all links;however, it is difficult to directly express the road network's state by these parameters. Thus, a synthetic evaluation index should be extracted from various parameters to express the road network's state comprehensively and intuitively. This paper proposes a novel model for extracting temporal and spatial features in a networked traffic system, Locality Sensitive Discriminant Analysis (LSDA) is used to reduce data dimensionality and extract features from traffic data analysis. Selected link and parameter data points are compressed and the output matrix has fewer dimensions than the original data. The corresponding relationship between the synthetic evaluation index and various parameters is analyzed. Simulation results prove that this method is effective in revealing hidden patterns in traffic data and the synthetic evaluation index can express the evolution of road network state comprehensively and accurately. © ASCE.

关键词： Discriminant analysis

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Vehicle Detection and Tracking from Airborne Images 15

Vehicle Detection and Tracking from Airborne Images

引用

15th COTA International Conference of Transportation Professionals: Efficient, Safe, and Green Multimodal Transportation, CICTP 2015

作者： Xu, Yongzheng Yu, Guizhen Wang, Yunpeng Wu, Xinkai Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control School of Transportation Science and Engineering Beihang University Xue Yuan Road No.37 Beijing100191 China Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies Nanjing210096 China

ISBN: (数字)9780784479292

ISBN: (纸本)9780784479292

For road traffic monitoring from aerial videos, vehicle detection and tracking are the basic tasks. However, background motions, scene complexity, and congested road conditions increase the difficulty. To address these issues, a system for vehicle detection and tracking was developed. The Viola-Jones object detection scheme is applied to vehicle detection, and vehicle tracking is proposed based on rectangular region prediction and similarity of gray-level histogram. Experiments in different scenarios showed that the system can achieve a high detection rate and tracking rate with a low false alarm rate. © ASCE.

关键词： Object detection

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An Adaptive Signal control Scheme for Intersections Experiencing Railroad Blockage 15

An Adaptive Signal Control Scheme for Intersections Experien...

引用

15th COTA International Conference of Transportation Professionals: Efficient, Safe, and Green Multimodal Transportation, CICTP 2015

作者： Ren, Yilong Wang, Yunpeng Yu, Haiyang School of Transportation Science and Engineering Beihang University Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control 37 Xueyuan Road Beijing100191 China Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies SiPaiLou #2 Nanjing210096 China

ISBN: (数字)9780784479292

ISBN: (纸本)9780784479292

The presence of an at-grade railroad crossing nearing a signalized intersection has a significant effect on traffic flow. When trains cross at grade, traffic flow can be significantly restricted. Vehicle queues may spillback to the upstream intersection and block it. In this paper, an adaptive signal control scheme is proposed to prevent this type of intersection traffic jam. This adaptive control scheme requires a speed detection system on the downstream link. The detectors should be strategically located such that a signal switching could be triggered when an intersection traffic jam is about to happen. This adaptive control scheme is based on the status of the downstream queue status and the traffic signal state. At the end, a microscopic traffic simulation software is used to evaluate the proposed adaptive control scheme. The simulation results show that the adaptive signal control scheme can work effectively to prevent this type of intersection traffic jam. © ASCE.

关键词： Computer software

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A Vehicular Positioning Enhancement with Connected Vehicle Assistance

A Vehicular Positioning Enhancement with Connected Vehicle A...

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IEEE Conference on Vehicular Technology (VTC)

作者： Xuting Duan Yunpeng Wang Daxin Tian Liang Sun David G. Michelson Victor C. M. Leung 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 Department of Electrical and Computer Engineering The University of British Columbia Vancouver BC Canada

ISBN: (纸本)9781479980925

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.

关键词： Vehicles Global Positioning System TV Covariance matrices Frequency measurement Doppler effect Kalman filters

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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 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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Analysis of traffic accident temporal and spatial impact based on shockwave theory

Analysis of traffic accident temporal and spatial impact bas...

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12th COTA International Conference of Transportation Professionals: Multimodal Transportation Systems - Convenient, Safe, Cost-Effective, Efficient, CICTP 2012

作者： Yu, Guizhen Liu, Yumin Wang, Yunpeng Zhu, Xiaoguang Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control Beihang University Beijing 100191 China School of Transportation Science and Engineering Beihang University Beijing 100191 China AnHui Province Key Laboratory of Intelligent Transportation System Anhui Keli Information Industry Co. LTD Anhui 230088. China

ISBN: (纸本)9780784412442

The study on the traffic impact of highway accident plays an important role in highway incident management. The paper aims to analyze the accumulation and dissipation process of an accident upstream on a two-lane highway by applying the shockwave theory. According to the number of impacted lanes, the clear-up time, and the upstream traffic flow, a mathematical model named highway traffic accident impact model (HTAIM) is established. Comparing numerical models analysis with professional microscopic traffic simulation software under the same traffic conditions, the deviation turns out to be smaller than other previous models. The results show that the model is proper and efficient for analyzing the impact of traffic accidents on upstream flow. © 2012 American Society of Civil engineering.

关键词： Highway accidents

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