发布求助
文献互助 智能选刊 最新文献

2007 IEEE Intelligent Transportation Systems Conference最新文献

筛选
英文 中文
Context-Adaptive Approach for Vehicle Detection Under Varying Lighting Conditions 不同光照条件下车辆检测的环境自适应方法
2007 IEEE Intelligent Transportation Systems Conference Pub Date : 2007-10-22 DOI: 10.1109/ITSC.2007.4357724
David Acunzo, Ying Zhu, B. Xie, G. Baratoff
{"title":"Context-Adaptive Approach for Vehicle Detection Under Varying Lighting Conditions","authors":"David Acunzo, Ying Zhu, B. Xie, G. Baratoff","doi":"10.1109/ITSC.2007.4357724","DOIUrl":"https://doi.org/10.1109/ITSC.2007.4357724","url":null,"abstract":"This paper presents a vision-based vehicle detection method, taking into account the lighting context of the images. The adaptability of a vehicle detection system to lighting conditions is an important characteristic on which little research has been carried out. The scheme presented here categorizes the scenes according to their lighting conditions and switches between specialized classifiers for different scene contexts. In our implementation, four categories of lighting conditions have been identified using a clustering algorithm in the space of image histograms: Daylight, Low Light, Night, and Saturation. Classifiers trained with AdaBoost are used for both Daylight and Low Light categories, and a tail-light detector is used for the Night category. No detection is made for the Saturation case. Experiments have shown a considerate improvement in the detection performance when using the proposed context-adaptive scheme compared to a single vehicle detector for all lighting conditions.","PeriodicalId":211095,"journal":{"name":"2007 IEEE Intelligent Transportation Systems Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2007-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125358753","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 26
Improved training algorithm for tree-like classifiers and its application to vehicle detection 改进的树状分类器训练算法及其在车辆检测中的应用
2007 IEEE Intelligent Transportation Systems Conference Pub Date : 2007-10-22 DOI: 10.1109/ITSC.2007.4357644
D. Withopf, B. Jähne
{"title":"Improved training algorithm for tree-like classifiers and its application to vehicle detection","authors":"D. Withopf, B. Jähne","doi":"10.1109/ITSC.2007.4357644","DOIUrl":"https://doi.org/10.1109/ITSC.2007.4357644","url":null,"abstract":"We propose a new training algorithm for tree classifiers and cascades for object detection and compare it to a standard algorithm for cascade training. Our experiments show that the proposed algorithm significantly reduces the number of features needed per stage by incorporating the output of the previous stage as a weak learner into the next stage. This approach also speeds up the classification while maintaining the same detection accuracy. The analysis of the features selected by the algorithm provides further insights into its functioning.","PeriodicalId":211095,"journal":{"name":"2007 IEEE Intelligent Transportation Systems Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2007-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122400974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 7
High Speed Combined Micro/Macro Simulation of Traffic Flow 高速结合微观/宏观交通流模拟
2007 IEEE Intelligent Transportation Systems Conference Pub Date : 2007-10-22 DOI: 10.1109/ITSC.2007.4357782
Gunnar Flötteröd, K. Nagel
{"title":"High Speed Combined Micro/Macro Simulation of Traffic Flow","authors":"Gunnar Flötteröd, K. Nagel","doi":"10.1109/ITSC.2007.4357782","DOIUrl":"https://doi.org/10.1109/ITSC.2007.4357782","url":null,"abstract":"We describe two new and practically relevant simulation techniques related to the kinematic wave model of traffic flow. Firstly, we demonstrate how the well-known Godunov solution scheme can be run on variable time scales in a computationally very efficient way. Secondly, we demonstrate how the resulting macroscopic traffic flow model can be run in conjunction with a microscopic model of driver behavior while maintaining high computational performance.","PeriodicalId":211095,"journal":{"name":"2007 IEEE Intelligent Transportation Systems Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2007-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122752088","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 16
Conflict Probability Estimations Based on Geometrical and Bayesian Approaches 基于几何和贝叶斯方法的冲突概率估计
2007 IEEE Intelligent Transportation Systems Conference Pub Date : 2007-10-22 DOI: 10.1109/ITSC.2007.4357787
Alfred Bashllari, N. Kaciroti, D. Nace, A. Fundo
{"title":"Conflict Probability Estimations Based on Geometrical and Bayesian Approaches","authors":"Alfred Bashllari, N. Kaciroti, D. Nace, A. Fundo","doi":"10.1109/ITSC.2007.4357787","DOIUrl":"https://doi.org/10.1109/ITSC.2007.4357787","url":null,"abstract":"In this paper, we present two approaches to calculate the probability of conflict between two aircrafts in the airspace. The problem is concerned with a more general problem, that is minimizing the delay caused by airspace congestion. The long-term objective of this work is to reduce the number of potential en-route conflicts through a better assignment of flight levels (flight-level assignment problem). For this, we first need to have a reliable method for conflict probability calculation taking into account the uncertainties. Hence, we focus here on the probability conflict calculation problem and provide two approaches. In the first one, called geometrical approach, we study the distribution of minimum distance between two aircrafts and then calculate the conflict probability as the cumulative probability with respect to this distribution. The second approach is based on Bayesian network principle using Gibbs sampling.","PeriodicalId":211095,"journal":{"name":"2007 IEEE Intelligent Transportation Systems Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2007-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122223673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 7
Real-time Traffic Prediction Using AOSVR and Cloud Model 基于AOSVR和云模型的实时交通预测
2007 IEEE Intelligent Transportation Systems Conference Pub Date : 2007-10-22 DOI: 10.1109/ITSC.2007.4357669
Mo Zhao, Kai Cao, Sogen Ho
{"title":"Real-time Traffic Prediction Using AOSVR and Cloud Model","authors":"Mo Zhao, Kai Cao, Sogen Ho","doi":"10.1109/ITSC.2007.4357669","DOIUrl":"https://doi.org/10.1109/ITSC.2007.4357669","url":null,"abstract":"Accuracy and time efficiency in prediction are couple of contradictions to be hard to resolve for real-time traffic information prediction. In order to improve time efficiency of prediction, we develop a real-time traffic information prediction model on the basis of Accurate On-line Support Vector Regression (AOSVR) in this paper, and a simplified computing method of sigmoid kernel based on cloud model is also proposed. Experiments are given to verify the performance of the developed predicting model, and the results obtained show that it obviously improves the time efficiency of predicting in spite of small decrease in precision due to simplifying computing of sigmoid kernel.","PeriodicalId":211095,"journal":{"name":"2007 IEEE Intelligent Transportation Systems Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2007-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129556950","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
A Lidar and Vision-based Approach for Pedestrian and Vehicle Detection and Tracking 基于激光雷达和视觉的行人和车辆检测与跟踪方法
2007 IEEE Intelligent Transportation Systems Conference Pub Date : 2007-10-22 DOI: 10.1109/ITSC.2007.4357637
C. Premebida, Gonçalo Monteiro, U. Nunes, P. Peixoto
{"title":"A Lidar and Vision-based Approach for Pedestrian and Vehicle Detection and Tracking","authors":"C. Premebida, Gonçalo Monteiro, U. Nunes, P. Peixoto","doi":"10.1109/ITSC.2007.4357637","DOIUrl":"https://doi.org/10.1109/ITSC.2007.4357637","url":null,"abstract":"This paper presents a sensorial-cooperative architecture to detect, track and classify entities in semi-structured outdoor scenarios for intelligent vehicles. In order to accomplish this task, information provided by in-vehicle Lidar and monocular vision is used. The detection and tracking phases are performed in the laser space, and the object classification methods work both in laser space (using a Gaussian Mixture Model classifier) and in vision spaces (AdaBoost classifier). A Bayesian-sum decision rule is used in order to combine the results of both classification techniques, and hence a more reliable object classification is achieved. Experiments confirm the effectiveness of the proposed architecture.","PeriodicalId":211095,"journal":{"name":"2007 IEEE Intelligent Transportation Systems Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2007-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128237453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 196
A Pedestrian Detector Using Histograms of Oriented Gradients and a Support Vector Machine Classifier 基于方向梯度直方图和支持向量机分类器的行人检测器
2007 IEEE Intelligent Transportation Systems Conference Pub Date : 2007-10-22 DOI: 10.1109/ITSC.2007.4357692
M. Bertozzi, A. Broggi, M. Rose, M. Felisa, A. Rakotomamonjy, F. Suard
{"title":"A Pedestrian Detector Using Histograms of Oriented Gradients and a Support Vector Machine Classifier","authors":"M. Bertozzi, A. Broggi, M. Rose, M. Felisa, A. Rakotomamonjy, F. Suard","doi":"10.1109/ITSC.2007.4357692","DOIUrl":"https://doi.org/10.1109/ITSC.2007.4357692","url":null,"abstract":"This paper details filtering subsystem for a tetra-vision based pedestrian detection system. The complete system is based on the use of both visible and far infrared cameras; in an initial phase it produces a list of areas of attention in the images which can contain pedestrians. This list is furtherly refined using symmetry-based assumptions. Then, this results is fed to a number of independent validators that evaluate the presence of human shapes inside the areas of attention. Histogram of oriented gradients and Support Vector Machines are used as a filter and demonstrated to be able to successfully classify up to 91% of pedestrians in the areas of attention.","PeriodicalId":211095,"journal":{"name":"2007 IEEE Intelligent Transportation Systems Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2007-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124565540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 123
Improved Haar Wavelet Feature Extraction Approaches for Vehicle Detection 基于改进Haar小波特征提取的车辆检测方法
2007 IEEE Intelligent Transportation Systems Conference Pub Date : 2007-10-22 DOI: 10.1109/ITSC.2007.4357743
Xuezhi Wen, Huai Yuan, Chunyang Yang, Chunyan Song, Bobo Duan, Hong Zhao
{"title":"Improved Haar Wavelet Feature Extraction Approaches for Vehicle Detection","authors":"Xuezhi Wen, Huai Yuan, Chunyang Yang, Chunyan Song, Bobo Duan, Hong Zhao","doi":"10.1109/ITSC.2007.4357743","DOIUrl":"https://doi.org/10.1109/ITSC.2007.4357743","url":null,"abstract":"Feature extraction is a key point of pattern recognition. Wavelet features are attractive for vehicle detection because they form a compact representation, encode edges, capture information from multi-resolution, and can be computed efficiently. This paper focuses on the improvement of wavelet features. The wavelet features directly based on signed coefficients are easily affected by the varied surroundings and illumination conditions and cause high intra-class variability. In order to deal with this problem, three improved approaches based on unsigned coefficients are proposed. The results of these proposed approaches are compared with the current three methods. The proposed approaches show super performance under various illuminations and different roads (different day time, different scenes: highway, urban common road, urban narrow road).","PeriodicalId":211095,"journal":{"name":"2007 IEEE Intelligent Transportation Systems Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2007-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130552141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 19
Car sharing system: what transaction datasets reveal on users' behaviors 汽车共享系统:交易数据集对用户行为的揭示
2007 IEEE Intelligent Transportation Systems Conference Pub Date : 2007-10-22 DOI: 10.1109/ITSC.2007.4357656
C. Morency, M. Trépanier, B. Agard, B. Martin, Joel Quashie
{"title":"Car sharing system: what transaction datasets reveal on users' behaviors","authors":"C. Morency, M. Trépanier, B. Agard, B. Martin, Joel Quashie","doi":"10.1109/ITSC.2007.4357656","DOIUrl":"https://doi.org/10.1109/ITSC.2007.4357656","url":null,"abstract":"Car sharing systems are gaining new members every month. However, few researches are conducted to better understand how these systems are used. In this paper, typical patterns of use of the car sharing system are identified using a transaction database covering a full year of operation. Data mining techniques are used to classify users according to their temporal patterns of car use frequency, traveled distance, and week use variability. The experiments reveal various classes of users. With respect to number of transactions throughout the year, users are segmented in two large classes: the regular and occasional ones, the majority of users belonging to the latter. The study of average trip length leads to the identification of 5 clusters of users. Finally, 8 types of typical weeks of use are described. Information about users' patterns could help the car sharing managers to optimize the use of the cars. It can also assist users in selecting the most advantageous subscription offer.","PeriodicalId":211095,"journal":{"name":"2007 IEEE Intelligent Transportation Systems Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2007-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116305860","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 56
Freeway Incident Management System Application in Jiangsu, China 高速公路事故管理系统在江苏省的应用
2007 IEEE Intelligent Transportation Systems Conference Pub Date : 2007-10-22 DOI: 10.1109/ITSC.2007.4357764
Shunxin Yang, F. Ni, Wei Wang
{"title":"Freeway Incident Management System Application in Jiangsu, China","authors":"Shunxin Yang, F. Ni, Wei Wang","doi":"10.1109/ITSC.2007.4357764","DOIUrl":"https://doi.org/10.1109/ITSC.2007.4357764","url":null,"abstract":"Incident management has already become an integral part of freeway traffic operations. Most of the departments of transportation have some kind of an operational incident management plan. However, no practical incident management systems have ever been developed in China, which is discordant with the rapid development of Chinese freeway and national economy. Therefore, in order to fill this gap, we develop a freeway incident management system, which is specially applied in the northern section of Nanjing-Lianyungang Freeway, combined with the status quo of China and our field study there. In this paper, detailed introductions of this system are illustrated, which help to provide a broad picture of the overall incident management process along with a quick review of this system for real-time operations. Among the five major aspects of this system, we first classify the freeway incidents according to the actual conditions of our country; next, we establish an expert system based on rules, which could generate preplans automatically. Then, we focus on the emergency treatment of incidents related to hazardous material (HAZMAT) on the basis of GIS. Subsequently, real-time management of these incidents with preplans has been carried out along with the log been recorded. Finally, information of traffic divergent and warning is disseminated accordingly. This incident management system is simple to use and has been successfully applied in the northern section of Nanjing-Lianyungang freeway for more than one year, and acclaimed a useful decision-making tool by its users.","PeriodicalId":211095,"journal":{"name":"2007 IEEE Intelligent Transportation Systems Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2007-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121707562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
下一页 尾页
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：481959085
Book学术官方微信