{"title":"A statistical based UWB multipath channel model for the indoor environments WPAN applications","authors":"Chia-Chin Chong, S. Yong","doi":"10.1109/PIMRC.2005.1651575","DOIUrl":"https://doi.org/10.1109/PIMRC.2005.1651575","url":null,"abstract":"In this paper, a statistical-based ultra-wideband (UWB) indoor channel model which incorporates the clustering of multipath components (MPCs) is proposed. The model is derived based on measurement data collected in the frequency band of 3-10 GHz in various types of high-rise apartments under different propagation scenarios. The aim is to investigate in more detail the clustering of MPCs phenomenon. The description of clustering observed within the channel relies on two classes of parameters, namely, inter-cluster and intra-cluster parameters which characterize the cluster and MPC, respectively. All parameters are described by a set of empirical probability density functions derived from the measured data such as the distribution of clusters and MPCs, clusters and MPCs arrivals and amplitudes statistics. In addition, the measurement procedure and data analysis techniques are also discussed. This model is suitable for performance analysis of WPAN systems that employ UWB technology e.g. IEEE 802.15.3a and IEEE 802.15.4a.","PeriodicalId":386189,"journal":{"name":"IEEE Proceedings. Intelligent Vehicles Symposium, 2005.","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132298397","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}
{"title":"OSGi-based service gateway architecture for intelligent automobiles","authors":"Yuantao Li, F. Wang, Feng He, Z. Li","doi":"10.1109/IVS.2005.1505213","DOIUrl":"https://doi.org/10.1109/IVS.2005.1505213","url":null,"abstract":"This paper describes the OSGi-based automotive specifications that improves the standard and integrates a great many existing automotive protocols and automotive networks. A key element of this specification is the OSGi-based automotive framework, which is open standard based, service-oriented infrastructure for provisioning, managing and developing telematics services. By using the technology of J2ME and extending the dynamic service deployment of OSGi, and integrating intelligent agent society, the mobile devices of automobile can access, download and use the various services from plenty of various service provider. The OSGi-based oriented-service automotive architecture is analyzed from the application and implementation points of view. Finally, the authors depict the tremendous benefits that OSGi platform technology offers in automotive networks and briefly discuss potential future work in this field.","PeriodicalId":386189,"journal":{"name":"IEEE Proceedings. Intelligent Vehicles Symposium, 2005.","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115187278","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}
{"title":"Vehicle lane keeping of adaptive PID control with BP neural network self-tuning","authors":"G. Zhenhai, Z. Bo","doi":"10.1109/IVS.2005.1505082","DOIUrl":"https://doi.org/10.1109/IVS.2005.1505082","url":null,"abstract":"According to the nonlinear and parameter time-varying characteristics of vehicle lateral dynamics, a novel algorithm of vehicle lateral adaptive PID control with BP neural network was proposed, using the approximate ability to any nonlinear function of the neural network. The results of the simulation in different velocities and lane curvature conditions show that the algorithm can effectively control vehicle to keep and track the pre-given trajectory and the good robustness and adaptability for the changing of velocity and path curvature is also shown.","PeriodicalId":386189,"journal":{"name":"IEEE Proceedings. Intelligent Vehicles Symposium, 2005.","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114423936","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}
{"title":"Performance evaluation of a vision based lane tracker designed for driver assistance systems","authors":"J. McCall, M. Trivedi","doi":"10.1109/IVS.2005.1505094","DOIUrl":"https://doi.org/10.1109/IVS.2005.1505094","url":null,"abstract":"Driver assistance systems that monitor driver intent, warn drivers of lane departures, or assist in vehicle guidance are all being actively research and even put into commercial production. It is therefore important to take a critical look at key aspects of these systems, one of which being lane position tracking. In this paper we present an analysis of lane position tracking in the context of driver support systems and examine previous research in this area. Using this analysis we present a lane tracking system designed to work well under a variety of road and environmental conditions. We examine what types of metrics are important for evaluating lane position accuracy for specific overall system objectives. A detailed quantitative evaluation of the system is presented in this paper using a variety of metrics and test conditions.","PeriodicalId":386189,"journal":{"name":"IEEE Proceedings. Intelligent Vehicles Symposium, 2005.","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116846097","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}
S. Wender, M. Schoenherr, N. Kaempchen, K. Dietmayer
{"title":"Classification of laserscanner measurements at intersection scenarios with automatic parameter optimization","authors":"S. Wender, M. Schoenherr, N. Kaempchen, K. Dietmayer","doi":"10.1109/IVS.2005.1505084","DOIUrl":"https://doi.org/10.1109/IVS.2005.1505084","url":null,"abstract":"Object classification at intersection scenarios is necessary in order to provide a general environment description. Objects are observed using a multilayer laserscanner. Significant features for object classification are identified and their extraction is described. Classification is performed using well-known techniques of statistical learning. Classification results of several neural networks are described and compared with classification performance of support vector machines.","PeriodicalId":386189,"journal":{"name":"IEEE Proceedings. Intelligent Vehicles Symposium, 2005.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128532435","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}
{"title":"Feature-level fusion for free-form object tracking using laserscanner and video","authors":"N. Kaempchen, M. Buehler, K. Dietmayer","doi":"10.1109/IVS.2005.1505145","DOIUrl":"https://doi.org/10.1109/IVS.2005.1505145","url":null,"abstract":"A scalable feature-level sensor fusion architecture combining the data of a multi-layer laserscanner and a monocular video has been developed. The approach aims at a maximization of synergetic effects by combining low-level measurement features and at the same time trying to keep the fusion architecture as general as possible. A new concept for the geometric modeling of diverse object shapes found in real traffic scenes, including free form models, enhances the precision of the object tracking. Results from real sensor data demonstrate the performance of the new algorithms compared to robust algorithms known from the literature.","PeriodicalId":386189,"journal":{"name":"IEEE Proceedings. Intelligent Vehicles Symposium, 2005.","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121453998","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}
{"title":"A 3D positioning system for off-road autonomous vehicles","authors":"Z. Xiang, U. Ozguner","doi":"10.1109/IVS.2005.1505090","DOIUrl":"https://doi.org/10.1109/IVS.2005.1505090","url":null,"abstract":"To navigate efficiently on uneven off-road terrain, autonomous vehicles must have reliable 3D positioning capability. Currently most of the positioning systems for autonomous vehicle assume the vehicle runs on a 2D planar plane and ignores the attitude change on pitch and roll. The main problem for 3D positioning over that of ID is accurate 3D attitude estimation. Gyros are subject to drift with changes in temperature. In recent experiments, we employed a new self-calibrated INS system, which is able to bound the attitude errors by complying the integrated attitude with those obtained from the measurements of accelerometers due to the effect of the gravity. Together with the highly precise GPS information, a reliable 3D positioning system was realized by fusing the information from GPS, INS and digital compass together. A direct configured extend Kalman filter was adopted for its simplicity on the implementation. The validity of the proposed system is checked using the experimental results.","PeriodicalId":386189,"journal":{"name":"IEEE Proceedings. Intelligent Vehicles Symposium, 2005.","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132250521","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}
Wang Rong-ben, Yu Tian-hong, Jin Li-sheng, Chu Jiang-wei, Gu Bai-yuan
{"title":"Edge extraction method study based on maximum entropy for linear lane identifying and tracking","authors":"Wang Rong-ben, Yu Tian-hong, Jin Li-sheng, Chu Jiang-wei, Gu Bai-yuan","doi":"10.1109/IVS.2005.1505211","DOIUrl":"https://doi.org/10.1109/IVS.2005.1505211","url":null,"abstract":"In order to better abstract lane mark edge and identify it, this paper proposes a new edge extraction method based on maximum entropy. This method combines both one-dimension and two-dimension entropy information. Meanwhile, image window variation technology is also applied for lane mark edge extraction and lane mark parameters can be acquired based on the bi-normalized adjustable template. Finally lane mark real-time tracking is realized by applying trapezia AOI method.","PeriodicalId":386189,"journal":{"name":"IEEE Proceedings. Intelligent Vehicles Symposium, 2005.","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131538744","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}
{"title":"Lane detection using color-based segmentation","authors":"Kuo-Yu Chiu, Sheng-Fuu Lin","doi":"10.1109/IVS.2005.1505186","DOIUrl":"https://doi.org/10.1109/IVS.2005.1505186","url":null,"abstract":"Lane boundary detection is the problem of estimating the geometric structure of the lane boundaries of a road on the images captured by a camera. To be an intelligent vehicle, lane boundary is necessary information, so the system and the algorithm should be as simple and fast as possible. In this paper, we propose a new method based on color information and this method is applicable in complex environment. In this system, we first choose a region of interest to find out a threshold using statistical method in a color image. The threshold then will be used to distinguish possible lane boundary from the road. We use color-based segmentation to find out the lane boundary and use a quadratic function to approach it. This system demands low computational power and memory requirements, and is robust in the presence of noise, shadows, pavement, and obstacles such like cars, motorcycles and pedestrians conditions. The result images can be used as pre-processed images for lane tracking, road following or obstacle detection.","PeriodicalId":386189,"journal":{"name":"IEEE Proceedings. Intelligent Vehicles Symposium, 2005.","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128955535","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}
{"title":"An advanced driver speed assistance in curves: risk function, cooperation modes, system architecture and experimental validation","authors":"V. Aguilera, S. Glaser, A. von Arnim","doi":"10.1109/IVS.2005.1505204","DOIUrl":"https://doi.org/10.1109/IVS.2005.1505204","url":null,"abstract":"This paper presents the development of the ARCOS driver speed assistance in curves (ADSAC). It illustrates how this development integrated into the ARCOS project framework. A strong emphasis is put on the definition of the ADSAC risk function, which is the fundamental building block on which several interaction modes with the driver have been implemented. Also, the study of experimental data confirms the validity of the hypothesis made while defining of the ADSAC risk function.","PeriodicalId":386189,"journal":{"name":"IEEE Proceedings. Intelligent Vehicles Symposium, 2005.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130858027","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}