2013 IEEE Intelligent Vehicles Symposium (IV)最新文献_第6页

A multimodal interaction concept for cooperative driving 合作驾驶的多模式交互概念

2013 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2013-06-23 DOI: 10.1109/IVS.2013.6629643

Markus Zimmermann, K. Bengler

引用次数: 19

Cyclostationary feature analysis of CEN-DSRC for cognitive vehicular networks 认知车辆网络cn - dsrc的周期平稳特征分析

2013 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2013-06-23 DOI: 10.1109/IVS.2013.6629473

K. Sithamparanathan, G. Baldini, D. Smely

{"title":"Cyclostationary feature analysis of CEN-DSRC for cognitive vehicular networks","authors":"K. Sithamparanathan, G. Baldini, D. Smely","doi":"10.1109/IVS.2013.6629473","DOIUrl":"https://doi.org/10.1109/IVS.2013.6629473","url":null,"abstract":"Cognitive vehicular networks provide the necessary intelligence for vehicular communication networks in order to optimally utilize the limited resources and maximize the performance. One of the important functions of cognitive networks is to learn the radio environment by means of detecting and identifying existing radios. In this context we use the cyclostationarity features of dedicated short range communication (DSRC) signals to blindly detect them in the environment. We present experimental results on the cyclostationarity properties of DSRC wireless transmissions considering the CEN (European) standards for both uplink and downlink signals. By performing cyclostationarity analysis we compute the cyclic power spectrum (CPS) of the CEN DSRC signals which is then used for detecting the presence of the CEN DSRC radios. We obtain CEN DSRC signals from experiments and use the recorded data to perform post-signal analysis to determine the detection performance. The probability of false alarm and the probability of missed detection are computed and the results are presented for different detection strategies. Results show that the cyclostationarity feature based detection can be robust compared to the well known energy based technique for low signal to noise ratio levels.","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":"131158290","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: 3

A case study on implementing future human-machine interfaces 实现未来人机界面的案例研究

2013 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2013-06-23 DOI: 10.1109/IVS.2013.6629609

L. Mercep, G. Spiegelberg, A. Knoll

引用次数: 5

Online extrinsic multi-camera calibration using ground plane induced homographies 利用地平面诱导同形异构词进行多相机在线标定

2013 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2013-06-23 DOI: 10.1109/IVS.2013.6629476

Moritz Knorr, W. Niehsen, C. Stiller

{"title":"Online extrinsic multi-camera calibration using ground plane induced homographies","authors":"Moritz Knorr, W. Niehsen, C. Stiller","doi":"10.1109/IVS.2013.6629476","DOIUrl":"https://doi.org/10.1109/IVS.2013.6629476","url":null,"abstract":"This paper presents an approach for online estimation of the extrinsic calibration parameters of a multi-camera rig. Given a coarse initial estimate of the parameters, the relative poses between cameras are refined through recursive filtering. The approach is purely vision based and relies on plane induced homographies between successive frames. Overlapping fields of view are not required. Instead, the ground plane serves as a natural reference object. In contrast to other approaches, motion, relative camera poses, and the ground plane are estimated simultaneously using a single iterated extended Kalman filter. This reduces not only the number of parameters but also the computational complexity. Furthermore, an arbitrary number of cameras can be incorporated. Several experiments on synthetic as well as real data were conducted using a setup of four synchronized wide angle fisheye cameras, mounted on a moving platform. Results were obtained, using both, a planar and a general motion model with full six degrees of freedom. Additionally, the effects of uncertain intrinsic parameters and nonplanar ground were evaluated experimentally.","PeriodicalId":251198,"journal":{"name":"2013 IEEE Intelligent Vehicles Symposium (IV)","volume":"31 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":"134131937","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: 31

Targeted trajectories optimization from 2D LIDAR measurements 2D激光雷达测量的目标轨迹优化

2013 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2013-06-23 DOI: 10.1109/IVS.2013.6629584

Anh Vu, S. Kato

引用次数: 2

Pilot study on pedestrian step frequency in naturalistic driving environment 自然驾驶环境下行人踏频的初步研究

2013 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2013-06-23 DOI: 10.1109/IVS.2013.6629632

Renran Tian, Yingzi Du, Kai Yang, Pingge Jiang, Feng Jiang, Yaobin Chen, Rini Sherony, Hiroyuki Takahashi

引用次数: 16

Strategic dynamic traffic routing algorithm for globally optimized urban traffic 城市交通全局优化的战略动态交通路由算法

2013 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2013-06-23 DOI: 10.1109/IVS.2013.6629558

M. Richter, H. Kabza

引用次数: 1

A linear lateral dynamic model of skid steered wheeled vehicle 滑移转向轮式车辆的线性横向动力学模型

2013 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2013-06-23 DOI: 10.1109/IVS.2013.6629591

Zhang Yu, Jibin Hu, Xueyuan Li, S. Lyu, Jing Guo

引用次数: 8

Comparison of trajectory tracking controllers for emergency situations 紧急情况下轨迹跟踪控制器的比较

2013 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2013-06-23 DOI: 10.1109/IVS.2013.6629465

Daniel Hess, M. Althoff, T. Sattel

{"title":"Comparison of trajectory tracking controllers for emergency situations","authors":"Daniel Hess, M. Althoff, T. Sattel","doi":"10.1109/IVS.2013.6629465","DOIUrl":"https://doi.org/10.1109/IVS.2013.6629465","url":null,"abstract":"Over the last years a number of different vehicle controllers has been proposed for tracking planned paths or trajectories. Most of previously published works do not compare their results with other approaches or limit the comparison to a few scenarios. Unfortunately, comparisons with existing controller concepts are very rare and a ranking is hard to establish from the literature. In this work, we rigorously compare inversion-based trajectory tracking controllers by systematically exploring the set of possible solutions when disturbances vary over time and initial states and parameters are uncertain. By using Monte-Carlo simulation, we determine the average performance and by using rapidly exploring random trees, we determine the worst-case performance, which is especially important in emergency situations when avoiding a crash is essential. The tested scenarios and the applied methodologies are documented in detail so that they serve as benchmark problems for other control concepts. The results show that the controller with smaller relative degree performs better with respect to the worst-case deviation computed by rapidly exploring random trees, while conventional simulations of random scenarios would not reveal any difference.","PeriodicalId":251198,"journal":{"name":"2013 IEEE Intelligent Vehicles Symposium (IV)","volume":"2020 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":"114578177","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: 24

An Extreme Learning Machine-based pedestrian detection method 一种基于极限学习机的行人检测方法

2013 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2013-06-23 DOI: 10.1109/IVS.2013.6629663

Kai Yang, Yingzi Du, E. Delp, Pingge Jiang, Feng Jiang, Yaobin Chen, Rini Sherony, Hiroyuki Takahashi

引用次数: 26