2012 IEEE Intelligent Vehicles Symposium最新文献_第3页

Dealing with occlusions with multi targets tracking algorithms for the real road context 真实道路环境下的多目标遮挡跟踪算法

2012 IEEE Intelligent Vehicles Symposium Pub Date : 2012-06-03 DOI: 10.1109/IVS.2012.6232169

L. Lamard, R. Chapuis, Jean-Philippe Boyer

引用次数: 22

May I enter the roundabout? A time-to-contact computation based on stereo-vision 我可以进入环岛吗?基于立体视觉的接触时间计算

2012 IEEE Intelligent Vehicles Symposium Pub Date : 2012-06-03 DOI: 10.1109/IVS.2012.6232178

M. Muffert, Timo Milbich, D. Pfeiffer, Uwe Franke

引用次数: 33

Advanced intersection management for connected vehicles using a multi-agent systems approach 基于多智能体系统方法的互联车辆高级交叉口管理

2012 IEEE Intelligent Vehicles Symposium Pub Date : 2012-06-03 DOI: 10.1109/IVS.2012.6232287

Qiu Jin, Guoyuan Wu, K. Boriboonsomsin, M. Barth

{"title":"Advanced intersection management for connected vehicles using a multi-agent systems approach","authors":"Qiu Jin, Guoyuan Wu, K. Boriboonsomsin, M. Barth","doi":"10.1109/IVS.2012.6232287","DOIUrl":"https://doi.org/10.1109/IVS.2012.6232287","url":null,"abstract":"Transportation is responsible for approximately a third of greenhouse gases (GHG) and a major source of other pollutants including hydrocarbons (HC), carbon monoxide (CO), and oxides of nitrogen (NOx). Intelligent Transportation System (ITS) technology can be used to lower vehicle emissions and fuel consumption, in addition to reducing traffic congestion, smoothing traffic flow, and improving roadway safety. As wireless communication advances, connected-vehicles-based Advanced Traffic Management Systems (ATMS) have gained significant research interest due to their high potential. In this study, we examine the concept of ATMS for connected vehicles using a multi-agent systems approach, where both vehicle agents and an intersection management agent can take advantage of real-time traffic information exchange. This dynamic strategy allows an intersection management agent to receive state information from vehicle agents, reserve the associated intersection time-space occupancies, and then provide feedback to the vehicles. The vehicle agents then adjust their trajectories to meet their assigned time slot. Based on preliminary simulation experiments, the proposed strategy can significantly reduce fuel consumption and vehicle emissions compared to traditional signal control systems.","PeriodicalId":402389,"journal":{"name":"2012 IEEE Intelligent Vehicles Symposium","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114735421","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: 59

Obstacle detection using sparse stereovision and clustering techniques 基于稀疏立体视觉和聚类技术的障碍物检测

2012 IEEE Intelligent Vehicles Symposium Pub Date : 2012-06-03 DOI: 10.1109/IVS.2012.6232283

Sébastien Kramm, A. Bensrhair

引用次数: 19

Risk indicators anticipation based on the vehicle dynamics anticipation to avoid accidents 基于车辆动态预测的风险指标预测，避免事故发生

2012 IEEE Intelligent Vehicles Symposium Pub Date : 2012-06-03 DOI: 10.1109/IVS.2012.6232224

Raymond Ghandour, A. Victorino, A. Charara, D. Lechner

引用次数: 7

An evaluation of boosted features for vehicle detection 车辆检测中增强特征的评价

2012 IEEE Intelligent Vehicles Symposium Pub Date : 2012-06-03 DOI: 10.1109/IVS.2012.6232185

Liwei Liu, Genquan Duan, H. Ai, S. Lao

{"title":"An evaluation of boosted features for vehicle detection","authors":"Liwei Liu, Genquan Duan, H. Ai, S. Lao","doi":"10.1109/IVS.2012.6232185","DOIUrl":"https://doi.org/10.1109/IVS.2012.6232185","url":null,"abstract":"Vehicle detection in traffic scenes is a fundamental task for intelligent transportation system and has many practical applications as diverse as traffic monitoring, intelligent scheduling and autonomous navigation. In recent years, the number of detection approaches in monocular images has grown rapidly. However, most of them focus on detecting other objects (such as face, pedestrian, cat, dog, etc.) and also there lacks of vehicle datasets with various conditions for vehicle detection and comprehensive comparisons. To address these problems, we perform an extensive evaluation of many state-of-the-art detection approaches on vehicles. Our main contributions are: (1) we collect a large dataset of real-world vehicles in frontal/rear view with 30° ~ -30° yaw changes and 5° ~ 45° pitch changes under different weather conditions (snowy, rainy, sunny and cloudy) and illumination variations, and then (2) we evaluate six types of state-of-the-art features in Real AdaBoost framework on the adequate dataset collected by ourselves and a public dataset using the same evaluation protocol. Our study presents a fair comparison and deep analysis of these features in vehicle detection. From these experiments, we explore the characteristics of good features for vehicle detection. (3) Finally, we exploit these characteristics and propose a relatively effective and efficient detector, balancing performance, speed and memory cost which can be put into practical use.","PeriodicalId":402389,"journal":{"name":"2012 IEEE Intelligent Vehicles Symposium","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128564028","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

Omni-directional detection and tracking of on-road vehicles using multiple horizontal laser scanners 利用多个水平激光扫描仪对道路车辆进行全方位探测和跟踪

2012 IEEE Intelligent Vehicles Symposium Pub Date : 2012-06-03 DOI: 10.1109/IVS.2012.6232161

Huijing Zhao, Chao Wang, W. Yao, F. Davoine, J. Cui, H. Zha

引用次数: 23

Reference generation and control strategy for automated vehicle guidance 车辆自动制导参考生成与控制策略

2012 IEEE Intelligent Vehicles Symposium Pub Date : 2012-06-03 DOI: 10.1109/IVS.2012.6232248

R. Attia, Jérémie Daniel, Jean-Philippe Lauffenburger, R. Orjuela, M. Basset

引用次数: 18

Off-vehicle evaluation of camera-based pedestrian detection 基于摄像机的行人检测的车外评价

2012 IEEE Intelligent Vehicles Symposium Pub Date : 2012-06-03 DOI: 10.1109/IVS.2012.6232160

Y. Alon, Aharon Bar-Hillel

{"title":"Off-vehicle evaluation of camera-based pedestrian detection","authors":"Y. Alon, Aharon Bar-Hillel","doi":"10.1109/IVS.2012.6232160","DOIUrl":"https://doi.org/10.1109/IVS.2012.6232160","url":null,"abstract":"Performance evaluation and comparison of vision-based automotive modules is a growing need in automotive industry. Off-vehicle evaluation, using a database of video streams offers many advantages over on-vehicle evaluation in terms of reduced costs, repeatability and the ability to compare different modules under the same conditions. An off-vehicle evaluation platform for camera based pedestrian detection is presented, enabling evaluation of industrial modules and internally developed algorithms. In order to maintain a single video database despite variability in camera location and internal parameters, experiments were done with video warping techniques, in which a video is warped to look as if taken from a target camera. To obtain ground truth annotation, both manual and Lidar-based methods were tested. Lidar-based annotation was shown to achieve detection rate >; 80% without human intervention, which can go up to 97.5% using a semi-supervised methodology with moderate human effort. Finally, we examined several performance metrics, and found that the image-based detection criteria used in most of the literature does not fit certain automotive application well. A modified criterion based on real world coordinates is suggested.","PeriodicalId":402389,"journal":{"name":"2012 IEEE Intelligent Vehicles Symposium","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127310903","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

Motion-without-structure: Real-time multipose optimization for accurate visual odometry 无结构运动:实时多姿态优化精确视觉里程计

2012 IEEE Intelligent Vehicles Symposium Pub Date : 2012-06-03 DOI: 10.1109/IVS.2012.6232235

Henning Lategahn, Andreas Geiger, B. Kitt, C. Stiller

{"title":"Motion-without-structure: Real-time multipose optimization for accurate visual odometry","authors":"Henning Lategahn, Andreas Geiger, B. Kitt, C. Stiller","doi":"10.1109/IVS.2012.6232235","DOIUrl":"https://doi.org/10.1109/IVS.2012.6232235","url":null,"abstract":"State of the art visual odometry systems use bundle adjustment (BA) like methods to jointly optimize motion and scene structure. Fusing measurements from multiple time steps and optimizing an error criterion in a batch fashion seems to deliver the most accurate results. However, often the scene structure is of no interest and is a mere auxiliary quantity although it contributes heavily to the complexity of the problem. Herein we propose to use a recently developed incremental motion estimator which delivers relative pose displacements between each two frames within a sliding window inducing a pose graph. Moreover, we introduce a method to learn the uncertainty associated with each of the pose displacements. The pose graph is adjusted by non-linear least squares optimization while incorporating a motion model. Thereby we fuse measurements from multiple time steps much in the same sense as BA does. However, we obviate the need to estimate the scene structure yielding a very efficient estimator: Solving the nonlinear least squares problem by a Gauss-Newton method takes approximately 1ms. We show the effectiveness of our method on simulated and real world data and demonstrate substantial improvements over incremental methods.","PeriodicalId":402389,"journal":{"name":"2012 IEEE Intelligent Vehicles Symposium","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126916814","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