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IEEE Intelligent Vehicles Symposium, 2004最新文献

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Dynamic cluster tracking technique for traffic monitoring using on-vehicle radar 基于车载雷达的交通监控动态聚类跟踪技术
IEEE Intelligent Vehicles Symposium, 2004 Pub Date : 2004-06-14 DOI: 10.1109/IVS.2004.1336474
N. Zorka, K. Cheok
{"title":"Dynamic cluster tracking technique for traffic monitoring using on-vehicle radar","authors":"N. Zorka, K. Cheok","doi":"10.1109/IVS.2004.1336474","DOIUrl":"https://doi.org/10.1109/IVS.2004.1336474","url":null,"abstract":"Predictive sensing applications are starting to find wide applications in automotive safety applications. In collision situations the need to alert the driver and to take effective countermeasures to meet the needs of the vehicle occupant safety is becoming increasingly more dependent on sensors. Electronic systems to provide warning and to implement active adaptation of occupant restraints to provide for enhanced safety protection are becoming more dependent on active safety sensors. This paper deals with a system that uses radar sensors that provides the ability to cluster the number of vehicles based on radar return signals and to actively track their movement with a Kalman filter.","PeriodicalId":296386,"journal":{"name":"IEEE Intelligent Vehicles Symposium, 2004","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116633847","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: 1
Modelling freeway networks by hybrid stochastic models 基于混合随机模型的高速公路网络建模
IEEE Intelligent Vehicles Symposium, 2004 Pub Date : 2004-06-14 DOI: 10.1109/IVS.2004.1336378
R. Boel, L. Mihaylova
{"title":"Modelling freeway networks by hybrid stochastic models","authors":"R. Boel, L. Mihaylova","doi":"10.1109/IVS.2004.1336378","DOIUrl":"https://doi.org/10.1109/IVS.2004.1336378","url":null,"abstract":"Traffic flow on freeways is a nonlinear, many-particle phenomenon, with complex interactions between the vehicles. This paper presents a stochastic hybrid model of freeway traffic at a time scale and at a level of detail suitable for on-line flow estimation, for routing and ramp metering control. The model describes the evolution of continuous and discrete state variables. The freeway is considered as a network of components, each component representing a different section of the network. The traffic model, designed from physical considerations, comprises sending and receiving functions describing the downstream and upstream propagation of perturbations to be controlled. Results from simulation investigations illustrate the effectiveness of our model compared to the well-known METANET model.","PeriodicalId":296386,"journal":{"name":"IEEE Intelligent Vehicles Symposium, 2004","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121821215","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: 20
Overtaking frequency and advanced driver assistance systems 超车频率和先进的驾驶员辅助系统
IEEE Intelligent Vehicles Symposium, 2004 Pub Date : 2004-06-14 DOI: 10.1109/IVS.2004.1336422
G. Hegeman
{"title":"Overtaking frequency and advanced driver assistance systems","authors":"G. Hegeman","doi":"10.1109/IVS.2004.1336422","DOIUrl":"https://doi.org/10.1109/IVS.2004.1336422","url":null,"abstract":"This paper shows results of an observation of overtaking frequencies on roads with opposing traffic. This observation is a first step of research regarding potential safety effects of advanced driver assistance systems on overtaking on two lane rural roads. We determine overtaking frequencies as a function of flow rates on both directions, distinguishing different vehicle types. Observed overtaking frequencies are lower than overtaking demand, especially when the directional split becomes more equal. Therefore we recommend adding directional split to the equation to calculate overtaking frequency.","PeriodicalId":296386,"journal":{"name":"IEEE Intelligent Vehicles Symposium, 2004","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125246498","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: 25
Multi-target multi-object tracking, sensor fusion of radar and infrared 多目标多目标跟踪，雷达与红外传感器融合
IEEE Intelligent Vehicles Symposium, 2004 Pub Date : 2004-06-14 DOI: 10.1109/IVS.2004.1336475
R. Mobus, U. Kolbe
{"title":"Multi-target multi-object tracking, sensor fusion of radar and infrared","authors":"R. Mobus, U. Kolbe","doi":"10.1109/IVS.2004.1336475","DOIUrl":"https://doi.org/10.1109/IVS.2004.1336475","url":null,"abstract":"This paper presents algorithms and techniques for single-sensor tracking and multi-sensor fusion of infrared and radar data. The results show that fusing radar data with infrared data considerably increases detection range, reliability and accuracy of the object tracking. This is mandatory for further development of driver assistance systems. Using multiple model filtering for sensor fusion applications helps to capture the dynamics of maneuvering objects while still achieving smooth object tracking for not maneuvering objects. This is important when safety and comfort systems have to make use of the same sensor information. Comfort systems generally require smoothly filtered data whereas for safety systems it is crucial to capture maneuvers of other road users as fast as possible. Multiple model filtering and probabilistic data association techniques are presented and all presented algorithms are tested in real-time on standard PC systems.","PeriodicalId":296386,"journal":{"name":"IEEE Intelligent Vehicles Symposium, 2004","volume":"65 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126986177","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: 113
Multiple-model tracking for the detection of lane change maneuvers 多模型跟踪检测变道机动
IEEE Intelligent Vehicles Symposium, 2004 Pub Date : 2004-06-14 DOI: 10.1109/IVS.2004.1336511
K. Weiß, N. Kaempchen, A. Kirchner
{"title":"Multiple-model tracking for the detection of lane change maneuvers","authors":"K. Weiß, N. Kaempchen, A. Kirchner","doi":"10.1109/IVS.2004.1336511","DOIUrl":"https://doi.org/10.1109/IVS.2004.1336511","url":null,"abstract":"Volkswagen research has developed a system for vehicle surround perception which integrates different sensor data of the environment into a combined description by using a single model Kalman tracker. This paper deals with the extension of the tracking system by means of an interacting multiple-model algorithm (IMM) to improve the tracking stability during curves and to detect lane changes of the observed target vehicle. The applied IMM-tracker uses specialized models for lateral and longitudinal motion that are partly affected by curvature estimation. The technique is tested with recorded sequences of measurement data and shows robust tracking and well-fitting classification of the dynamical behavior of the targets.","PeriodicalId":296386,"journal":{"name":"IEEE Intelligent Vehicles Symposium, 2004","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134192701","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: 45
Multi sensor based tracking of pedestrians: a survey of suitable movement models 基于多传感器的行人跟踪:合适的运动模型综述
IEEE Intelligent Vehicles Symposium, 2004 Pub Date : 2004-06-14 DOI: 10.1109/IVS.2004.1336482
U. Scheunert, H. Cramer, Gerd Wanielik
{"title":"Multi sensor based tracking of pedestrians: a survey of suitable movement models","authors":"U. Scheunert, H. Cramer, Gerd Wanielik","doi":"10.1109/IVS.2004.1336482","DOIUrl":"https://doi.org/10.1109/IVS.2004.1336482","url":null,"abstract":"This article presents a multi sensor approach for driver assistance systems: the detection and tracking of pedestrians in a road environment. A multi sensor system consisting of a far infrared camera and a laser scanning device is used for the detection and precise localization of pedestrians. Kalman filter based data fusion handles the combination of the sensor information of the infrared camera and of the laser scanner. Arranging a set of Kalman filters in parallel, a multi sensor/multi target tracking system was created. The usage of suitable movement models has a great influence on the performance of the tracking system. Several types of models are discussed focussing on the typical behavior of pedestrians in road environments. The multi sensor/multi target tracking system is installed on a test vehicle to obtain practical results which is discussed in this article too.","PeriodicalId":296386,"journal":{"name":"IEEE Intelligent Vehicles Symposium, 2004","volume":"123 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134424900","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: 33
A tool for vision based pedestrian detection performance evaluation 基于视觉的行人检测性能评价工具
IEEE Intelligent Vehicles Symposium, 2004 Pub Date : 2004-06-14 DOI: 10.1109/IVS.2004.1336484
M. Bertozzi, A. Broggi, P. Grisleri, A. Tibaldi, Michael Rose
{"title":"A tool for vision based pedestrian detection performance evaluation","authors":"M. Bertozzi, A. Broggi, P. Grisleri, A. Tibaldi, Michael Rose","doi":"10.1109/IVS.2004.1336484","DOIUrl":"https://doi.org/10.1109/IVS.2004.1336484","url":null,"abstract":"This paper describes a system for evaluating pedestrian detection algorithm results. The developed tool allows a human operator to annotate on a file all pedestrians in a previously acquired video sequence. A similar file is produced by the algorithm being tested using the same annotation engine. A matching rule has been established to validate the association between items of the two files. For each frame a statistical analyzer extracts the number of mis-detections, both positive and negative, and correct detections. Using these data, statistics about the algorithm behavior are computed with the aim of tuning parameters and pointing out recognition weaknesses in particular situations.","PeriodicalId":296386,"journal":{"name":"IEEE Intelligent Vehicles Symposium, 2004","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133383193","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: 27
Geocast in vehicular environments: caching and transmission range control for improved efficiency 车辆环境中的地球广播:缓存和传输范围控制，以提高效率
IEEE Intelligent Vehicles Symposium, 2004 Pub Date : 2004-06-14 DOI: 10.1109/IVS.2004.1336514
C. Maihofer, R. Eberhardt
{"title":"Geocast in vehicular environments: caching and transmission range control for improved efficiency","authors":"C. Maihofer, R. Eberhardt","doi":"10.1109/IVS.2004.1336514","DOIUrl":"https://doi.org/10.1109/IVS.2004.1336514","url":null,"abstract":"Geocast in vehicular ad hoc networks allows to realize applications like virtual warning signs for improved road safety, which address a geographical area rather than an individual vehicle. In this paper we propose to include caching in the geocast forwarding scheme and improved neighborhood selection to address in particular the high velocities of vehicles. High velocities of vehicular networks are a major difference to usual mobile ad hoc networks which assume only moderate node movement. We show that a cache for presently unforwardable messages caused by network partitioning or unfavorable neighbors can significantly improve the geocast delivery success ratio. The improved neighborhood selection taking frequent neighborhood changes into account significantly decreases network load and decreased end-to-end delivery delay.","PeriodicalId":296386,"journal":{"name":"IEEE Intelligent Vehicles Symposium, 2004","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133821434","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: 84
Onboard diagnostics concept for fuel cell vehicles using adaptive modelling 基于自适应建模的燃料电池汽车车载诊断概念
IEEE Intelligent Vehicles Symposium, 2004 Pub Date : 2004-06-14 DOI: 10.1109/IVS.2004.1336368
C. Nitsche, S. Schroedl, W. Weiss
{"title":"Onboard diagnostics concept for fuel cell vehicles using adaptive modelling","authors":"C. Nitsche, S. Schroedl, W. Weiss","doi":"10.1109/IVS.2004.1336368","DOIUrl":"https://doi.org/10.1109/IVS.2004.1336368","url":null,"abstract":"Fuel cell vehicles and fuel cell research is one of the newer areas in automotive technology. This paper describes an approach that utilizes artificial neural networks to alleviate the task of onboard diagnostics for fuel cell vehicles. The basic idea is an online learning scenario that trains a power train model with every-day driving data; this model can then be used to estimate a characteristic curve by feeding it with predefined input variables corresponding to the constant conditions of a stationary workshop test. In this way, a major obstacle for on-line diagnosis, namely the multitude of varying nuisance variables, can be compensated for. For a diagnosis algorithm, it is considerably easier to compare the resulting predicted characteristic curve with an ideal reference curve, rather than to directly deal with all the influence factors.","PeriodicalId":296386,"journal":{"name":"IEEE Intelligent Vehicles Symposium, 2004","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127838287","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: 28
Dynamic situation and threat assessment for collision warning systems: the EUCLIDE approach 碰撞预警系统的动态态势和威胁评估:EUCLIDE方法
IEEE Intelligent Vehicles Symposium, 2004 Pub Date : 2004-06-14 DOI: 10.1109/IVS.2004.1336458
A. Polychronopoulos, M. Tsogas, A. Amditis, U. Scheunert, L. Andreone, F. Tango
{"title":"Dynamic situation and threat assessment for collision warning systems: the EUCLIDE approach","authors":"A. Polychronopoulos, M. Tsogas, A. Amditis, U. Scheunert, L. Andreone, F. Tango","doi":"10.1109/IVS.2004.1336458","DOIUrl":"https://doi.org/10.1109/IVS.2004.1336458","url":null,"abstract":"Situation and threat assessment is considered as the highest level of abstraction in the vehicle tracking processes. In this paper, a broad discussion is introduced on algorithms for active safety functions, whilst a new dynamic algorithm is proposed. This approach handles all objects' states as dynamic stochastic variables and based on a Kalman approach calculates in real time all trajectories respectively. Thus, a reconstruction of the traffic scene can be achieved in order to assess a level of threat for all moving and stationary obstacles in the longitudinal area of the subject vehicle. This approach is adopted in the European co-funded project \"EUCLIDE\", which develops a vision enhancement and collision warning system merging the functionality of an infrared camera and mmw radar sensor. Results are presented using simulated and real data sets from dedicated sessions.","PeriodicalId":296386,"journal":{"name":"IEEE Intelligent Vehicles Symposium, 2004","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121238578","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: 72
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