2013 IEEE Intelligent Vehicles Symposium (IV)最新文献_第10页

Vehicle road navigation to minimize pollutant exposure 车辆道路导航，尽量减少污染物暴露

2013 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2013-06-23 DOI: 10.1109/IVS.2013.6629572

Ji Luo, Alexander Vu, M. Barth

{"title":"Vehicle road navigation to minimize pollutant exposure","authors":"Ji Luo, Alexander Vu, M. Barth","doi":"10.1109/IVS.2013.6629572","DOIUrl":"https://doi.org/10.1109/IVS.2013.6629572","url":null,"abstract":"Intelligent Transportation System (ITS) technology is often aimed at improving vehicle safety and mobility. Lately a number of ITS applications are also focusing on environmental issues such as reducing greenhouse gases (through improved fuel economy) and reducing overall pollutant emissions. Typical environmental ITS applications (e.g., eco-routing) focus on reducing total mass vehicle emissions for generalized areas. To date however, environmental ITS applications haven't considered emissions from a pollutant exposure point-of-view. In this paper, we introduce a new vehicle routing methodology that goes beyond minimizing overall pollutant emissions, instead minimizing pollutant exposure to localized populations along roadways. As part of this effort, a unique modeling suite has been developed to allow for the evaluation of environmental ITS applications from a traffic emissions exposure point of view. For the routing algorithm, the human intake fraction that is commonly used for quantifying emission exposure is modeled and used as a routing cost. Experimental modeling results show that the intake fraction of particulate matter for 5-14 year-old school children on school days can be reduced approximately 80%-90% on a typical schoolday with the implementation of intelligent routing algorithms.","PeriodicalId":251198,"journal":{"name":"2013 IEEE Intelligent Vehicles Symposium (IV)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126251556","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

Towards leveraging the driver's mobile device for an intelligent, sociable in-car robotic assistant 朝着利用驾驶员的移动设备作为智能的、善于交际的车内机器人助手的方向发展

2013 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2013-06-23 DOI: 10.1109/IVS.2013.6629497

Kenton Williams, J. C. Peters, C. Breazeal

引用次数: 39

Dynamic side-view mirror: Assisting situation awareness in blind spots 动态侧视镜:协助盲点的情况感知

2013 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2013-06-23 DOI: 10.1109/IVS.2013.6629510

J. Kuwana, M. Itoh, T. Inagaki

引用次数: 5

High-performance visual odometry with two-stage local binocular BA and GPU 基于两级局部双目BA和GPU的高性能视觉里程测量

2013 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2013-06-23 DOI: 10.1109/IVS.2013.6629614

W. Lu, Z. Xiang, Jilin Liu

引用次数: 27

CADAS: A multimodal advanced driver assistance system for normal urban streets based on road context understanding CADAS:一种基于道路背景理解的多模式高级驾驶员辅助系统

2013 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2013-06-23 DOI: 10.1109/IVS.2013.6629475

Chunzhao Guo, J. Meguro, Y. Kojima, T. Naito

引用次数: 15

Obstacle avoidance via social mediation in cooperative payload transportation 协同载荷运输中的社会中介避障

2013 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2013-06-23 DOI: 10.1109/IVS.2013.6629494

Ronal Singh, S. Lal, J. Vanualailai

引用次数: 0

Multi-lane detection in urban driving environments using conditional random fields 基于条件随机场的城市驾驶环境多车道检测

2013 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2013-06-23 DOI: 10.1109/IVS.2013.6629645

Junhwa Hur, Seung-Nam Kang, S. Seo

{"title":"Multi-lane detection in urban driving environments using conditional random fields","authors":"Junhwa Hur, Seung-Nam Kang, S. Seo","doi":"10.1109/IVS.2013.6629645","DOIUrl":"https://doi.org/10.1109/IVS.2013.6629645","url":null,"abstract":"Over the past few decades, the need has arisen for multi-lane detection algorithms for use in vehicle safety-related applications. In this paper we propose a new multi-lane detection algorithm that works well in urban situations. This algorithm detects four lane marks, including driving lane marks and adjacent lane marks. Conventional research assumes that lanes are parallel. In contrast, our approach does not require this assumption, thus enabling the algorithm to manage various non-parallel lane situations, such as are found at intersections, in splitting lanes, and in merging lanes. To detect multi-lane marks successfully in the absence of parallelism, we adopt Conditional Random Fields (CRFs), which are strong models for solving multiple association tasks. We show that CRFs are very effective tools for multi-lane detection because they find an optimal association of multiple lane marks in complex and challenging urban road situations. Through simulations, and by using video sequences with 752-480 resolution and Caltech Lane Datasets with runtime rates of 30 fps, we verify that our algorithm successfully detects non-parallel lanes as well as parallel lanes appearing in urban streets.","PeriodicalId":251198,"journal":{"name":"2013 IEEE Intelligent Vehicles Symposium (IV)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131097225","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: 101

Weighted V-disparity approach for obstacles localization in highway environments 公路环境中障碍物定位的加权v -视差方法

2013 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2013-06-23 DOI: 10.1109/IVS.2013.6629641

Nizar Fakhfakh, D. Gruyer, D. Aubert

{"title":"Weighted V-disparity approach for obstacles localization in highway environments","authors":"Nizar Fakhfakh, D. Gruyer, D. Aubert","doi":"10.1109/IVS.2013.6629641","DOIUrl":"https://doi.org/10.1109/IVS.2013.6629641","url":null,"abstract":"The employment of embedded passive sensors in order to perceive environment for reducing the accident risk level is a tendency of intelligent vehicles research. From such sensors, one can extract useful informations which can assist the driver to identify hazardous situations. While safety improvement is a substantial requirement for driving assistance, localizing and tracking obstacles in complex road environment became an important task. One promising approach is to use the V-disparity based on the stereovision technique. It is a cumulative space estimated from the disparity image. We propose a sound framework and a complete system based on a real-time stereovision for detection, 3D localization and tracking of dynamic obstacles in highway environment. The main contribution we propose is the improvement of the V-disparity approach by extending the basic approach by merging it with a confidence term. This consists on weighting each pixel in the V-disparity space according to a confidence value which measures the probability of associating a pair of pixels. Furthermore, we propose a tracking system which is based on the belief theory. The tracking task is done on the image space which takes into account uncertainties, handles conflicts, and automatically dealt with targets appearance and disappearce as well as their spatial and temporal propogation. Extensive experiments on simulated and real dataset demonstrate the effectiveness and the robustness of the weighted V-disparity approach.","PeriodicalId":251198,"journal":{"name":"2013 IEEE Intelligent Vehicles Symposium (IV)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130860051","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: 13

Active safety for vulnerable road users based on smartphone position data 基于智能手机位置数据的弱势道路使用者主动安全

2013 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2013-06-23 DOI: 10.1109/IVS.2013.6629479

Martin Liebner, F. Klanner, C. Stiller

引用次数: 57

Analytical study of the IEEE 802.11p EDCA mechanism IEEE 802.11p EDCA机制的分析研究

2013 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2013-06-23 DOI: 10.1109/IVS.2013.6629667

Wei Sun, Hesheng Zhang, Cheng Pan, Jun Yang

引用次数: 22