Pub Date : 2004-06-14DOI: 10.1109/IVS.2004.1336424
J. Douret, R. Benosman
This paper deals with the issue of using multi-cameras for road traffic monitoring. The aim is to remove the classic monocular ambiguities and to retrieve the objects' height. An efficient and simple calibration method is introduced. It has the particularity to be connected to the geometry constraints of the road. The method relies on projective geometry and uses the structure of the plane at infinity. In a second stage, a high speed matching procedure is introduced. It is based on an altitude planar decomposition of the road scene. The method naturally achieves two tasks due to altitudes sampling. Match and reconstruction become simultaneous. Finally, experimental results are presented.
{"title":"A volumetric multi-cameras method dedicated to road traffic monitoring","authors":"J. Douret, R. Benosman","doi":"10.1109/IVS.2004.1336424","DOIUrl":"https://doi.org/10.1109/IVS.2004.1336424","url":null,"abstract":"This paper deals with the issue of using multi-cameras for road traffic monitoring. The aim is to remove the classic monocular ambiguities and to retrieve the objects' height. An efficient and simple calibration method is introduced. It has the particularity to be connected to the geometry constraints of the road. The method relies on projective geometry and uses the structure of the plane at infinity. In a second stage, a high speed matching procedure is introduced. It is based on an altitude planar decomposition of the road scene. The method naturally achieves two tasks due to altitudes sampling. Match and reconstruction become simultaneous. Finally, experimental results are presented.","PeriodicalId":296386,"journal":{"name":"IEEE Intelligent Vehicles Symposium, 2004","volume":"189 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":"116334369","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}
Pub Date : 2004-06-14DOI: 10.1109/IVS.2004.1336428
M. Tideman, M. van der Voort, F. van Houten
When a customer buys a new car, he or she wants it to address personal preferences with respect to its driving behavior. By utilizing virtual reality technology, a virtual prototyping environment (VPE) can be created in which the behavior of a vehicle or part of a vehicle can be evaluated and adjusted to match the driver's desires. This paper describes the design and the evaluation of a VPE for manually operated gearboxes. The test group considered the simulated "virtual" gearshift feel to be quite similar to the "real" gearshift feel of a test vehicle. By further developing this VPE, it should become possible to define gearshift feel by customer assessment through haptic simulation, after which the physical gearbox is designed in such a way that it matches the preferred shifting behavior.
{"title":"Design and evaluation of a virtual gearshift application","authors":"M. Tideman, M. van der Voort, F. van Houten","doi":"10.1109/IVS.2004.1336428","DOIUrl":"https://doi.org/10.1109/IVS.2004.1336428","url":null,"abstract":"When a customer buys a new car, he or she wants it to address personal preferences with respect to its driving behavior. By utilizing virtual reality technology, a virtual prototyping environment (VPE) can be created in which the behavior of a vehicle or part of a vehicle can be evaluated and adjusted to match the driver's desires. This paper describes the design and the evaluation of a VPE for manually operated gearboxes. The test group considered the simulated \"virtual\" gearshift feel to be quite similar to the \"real\" gearshift feel of a test vehicle. By further developing this VPE, it should become possible to define gearshift feel by customer assessment through haptic simulation, after which the physical gearbox is designed in such a way that it matches the preferred shifting behavior.","PeriodicalId":296386,"journal":{"name":"IEEE Intelligent Vehicles Symposium, 2004","volume":"57 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":"125706517","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}
Pub Date : 2004-06-14DOI: 10.1109/IVS.2004.1336493
K. Lee, W. S. Wijesoma, J. Ibañez-Guzmán
Robust and accurate localization is a very important issue for the application of smart vehicles in neighbourhood environments such as theme parks, industrial estates, university campuses, etc. Conventional and classical approaches based on global positioning system (GPS) when used in closed spaces like neighbourhood environments pose problems due to signal blockages and multiple path effects. Feature based localization techniques suffer from feature detection failures, especially when features are sparse or not recognisable. Dead reckoning and inertial methods have to deal with the problem of drift in the sensors to be able to localize reliably over long periods of operation. To localize a vehicle reliably, robustly and accurately, a framework that enables the fusion of the different localization techniques is thus required, for this purpose, a road network topology constrained unified localization scheme is proposed based on the general Bayesian probabilistic estimation theoretic framework. The experimental results obtained from a vehicle driven in a large neighbourhood environment are presented to demonstrate the effectiveness of the proposed methodology.
{"title":"Map aided SLAM in neighbourhood environments","authors":"K. Lee, W. S. Wijesoma, J. Ibañez-Guzmán","doi":"10.1109/IVS.2004.1336493","DOIUrl":"https://doi.org/10.1109/IVS.2004.1336493","url":null,"abstract":"Robust and accurate localization is a very important issue for the application of smart vehicles in neighbourhood environments such as theme parks, industrial estates, university campuses, etc. Conventional and classical approaches based on global positioning system (GPS) when used in closed spaces like neighbourhood environments pose problems due to signal blockages and multiple path effects. Feature based localization techniques suffer from feature detection failures, especially when features are sparse or not recognisable. Dead reckoning and inertial methods have to deal with the problem of drift in the sensors to be able to localize reliably over long periods of operation. To localize a vehicle reliably, robustly and accurately, a framework that enables the fusion of the different localization techniques is thus required, for this purpose, a road network topology constrained unified localization scheme is proposed based on the general Bayesian probabilistic estimation theoretic framework. The experimental results obtained from a vehicle driven in a large neighbourhood environment are presented to demonstrate the effectiveness of the proposed methodology.","PeriodicalId":296386,"journal":{"name":"IEEE Intelligent Vehicles Symposium, 2004","volume":"220 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":"125849793","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}
Pub Date : 2004-06-14DOI: 10.1109/IVS.2004.1336393
T. Dang, C. Hoffmann
In this paper we present a self-calibration approach that updates the extrinsic parameters and the focal lengths of a stereo vision sensor. We employ a recursive estimation algorithm based on an Extended Kalman Filter. To improve the self-calibration process, we introduce a robust innovation stage for the Kalman filter: A Least Median Squares estimator is employed to eliminate outliers and thus to achieve better performance. The algorithm gives promising results on experiments with synthetic and natural imagery.
{"title":"Stereo calibration in vehicles","authors":"T. Dang, C. Hoffmann","doi":"10.1109/IVS.2004.1336393","DOIUrl":"https://doi.org/10.1109/IVS.2004.1336393","url":null,"abstract":"In this paper we present a self-calibration approach that updates the extrinsic parameters and the focal lengths of a stereo vision sensor. We employ a recursive estimation algorithm based on an Extended Kalman Filter. To improve the self-calibration process, we introduce a robust innovation stage for the Kalman filter: A Least Median Squares estimator is employed to eliminate outliers and thus to achieve better performance. The algorithm gives promising results on experiments with synthetic and natural imagery.","PeriodicalId":296386,"journal":{"name":"IEEE Intelligent Vehicles Symposium, 2004","volume":"27 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":"126487779","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}
Pub Date : 2004-06-14DOI: 10.1109/IVS.2004.1336459
A. Miene, Andreas D. Lattner, Ubbo Visser, O. Herzog
Planning, acting, and recognizing intentions of participants in traffic situations requires the processing of complex spatio-temporal situations. If spatio-temporal information was represented quantitatively it would result in a huge amount of data. We claim that an abstraction to a qualitative description leads to more stable representations as similar situations at the quantitative level are mapped to one qualitative representation. Our approach is evaluated by emulating traffic situations with settings in the Robocup small-sized league.
{"title":"Dynamic-preserving qualitative motion description for intelligent vehicles","authors":"A. Miene, Andreas D. Lattner, Ubbo Visser, O. Herzog","doi":"10.1109/IVS.2004.1336459","DOIUrl":"https://doi.org/10.1109/IVS.2004.1336459","url":null,"abstract":"Planning, acting, and recognizing intentions of participants in traffic situations requires the processing of complex spatio-temporal situations. If spatio-temporal information was represented quantitatively it would result in a huge amount of data. We claim that an abstraction to a qualitative description leads to more stable representations as similar situations at the quantitative level are mapped to one qualitative representation. Our approach is evaluated by emulating traffic situations with settings in the Robocup small-sized league.","PeriodicalId":296386,"journal":{"name":"IEEE Intelligent Vehicles Symposium, 2004","volume":"13 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":"121437814","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}
Pub Date : 2004-06-14DOI: 10.1109/IVS.2004.1336478
Chu Jiangwei, Jin Lisheng, Guo Lie, Libibing, Wang Rongben
This article describes systemically the method of detecting the preceding vehicle based on a monocular camera. The main content is as follows: first, a primary area of interest is found by the lane borderlines that are identified in a camera image, and a likelihood target vehicle is searched by the gray difference between the target vehicle and the background; second, an identifying area of interest is found again based on the area of a likelihood target vehicle, a target vehicle is affirmed by a symmetry character of the vehicle outline and a position of the vehicle symmetrical axis is ascertained; third, the object vehicle is tracked by Kalman forecast principle in the sequence images; fourth, a method of detecting distance in a frame of image is introduced. The calibration of the camera's interior parameters and the results of some experiments are given.
{"title":"Study on method of detecting preceding vehicle based on monocular camera","authors":"Chu Jiangwei, Jin Lisheng, Guo Lie, Libibing, Wang Rongben","doi":"10.1109/IVS.2004.1336478","DOIUrl":"https://doi.org/10.1109/IVS.2004.1336478","url":null,"abstract":"This article describes systemically the method of detecting the preceding vehicle based on a monocular camera. The main content is as follows: first, a primary area of interest is found by the lane borderlines that are identified in a camera image, and a likelihood target vehicle is searched by the gray difference between the target vehicle and the background; second, an identifying area of interest is found again based on the area of a likelihood target vehicle, a target vehicle is affirmed by a symmetry character of the vehicle outline and a position of the vehicle symmetrical axis is ascertained; third, the object vehicle is tracked by Kalman forecast principle in the sequence images; fourth, a method of detecting distance in a frame of image is introduced. The calibration of the camera's interior parameters and the results of some experiments are given.","PeriodicalId":296386,"journal":{"name":"IEEE Intelligent Vehicles Symposium, 2004","volume":"68 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":"127796980","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}
Pub Date : 2004-06-14DOI: 10.1109/IVS.2004.1336397
S. Nedevschi, R. Danescu, D. Frentiu, T. Mariţa, F. Oniga, C. Pocol, R. Schmidt, T. Graf
This paper presents a high accuracy stereo vision system for obstacle detection and vehicle environment perception in a large variety of traffic scenarios, from highway to urban. The system detects obstacles of all types, even at high distance, outputting them as a list of cuboids having a position in 3D coordinates, size and speed.
{"title":"High accuracy stereo vision system for far distance obstacle detection","authors":"S. Nedevschi, R. Danescu, D. Frentiu, T. Mariţa, F. Oniga, C. Pocol, R. Schmidt, T. Graf","doi":"10.1109/IVS.2004.1336397","DOIUrl":"https://doi.org/10.1109/IVS.2004.1336397","url":null,"abstract":"This paper presents a high accuracy stereo vision system for obstacle detection and vehicle environment perception in a large variety of traffic scenarios, from highway to urban. The system detects obstacles of all types, even at high distance, outputting them as a list of cuboids having a position in 3D coordinates, size and speed.","PeriodicalId":296386,"journal":{"name":"IEEE Intelligent Vehicles Symposium, 2004","volume":"74 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":"127979477","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}
Pub Date : 2004-06-14DOI: 10.1109/IVS.2004.1336413
M. Krodel, K. Kuhnert
Reinforcement learning (RL) is a method which provides true learning capabilities regarding situation-based actions. RL-systems explore and self-optimise actions for situations in a defined environment. This paper describes the research of a driver (assistance) system based on pure reinforcement learning in the framework of an autonomous vehicle. The target of this research is to determine to what extent RL-based systems serve as an enhancement or even an alternative to classical concepts of autonomous intelligent vehicles such as modelling or neural nets.
{"title":"Optimising situation-based behaviour of autonomous vehicles","authors":"M. Krodel, K. Kuhnert","doi":"10.1109/IVS.2004.1336413","DOIUrl":"https://doi.org/10.1109/IVS.2004.1336413","url":null,"abstract":"Reinforcement learning (RL) is a method which provides true learning capabilities regarding situation-based actions. RL-systems explore and self-optimise actions for situations in a defined environment. This paper describes the research of a driver (assistance) system based on pure reinforcement learning in the framework of an autonomous vehicle. The target of this research is to determine to what extent RL-based systems serve as an enhancement or even an alternative to classical concepts of autonomous intelligent vehicles such as modelling or neural nets.","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":"130801084","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}
Pub Date : 2004-06-14DOI: 10.1109/IVS.2004.1336398
C. Rotaru, T. Graf, Jianwei Zhang
This paper introduces a cognitive method for extracting significant road information (like road extents, lane markings) from mono-color images. The system is able to identify all traffic lanes and to distinguish between continuous and broken lane markings. Its output is useful in driver assistance systems (for example lane-departure warning). The cognitive aspects of the system are highlighted and the implemented algorithms are described. Finally, some results of the performed tests are introduced before drawing the conclusion.
{"title":"Extracting road features from color images using a cognitive approach","authors":"C. Rotaru, T. Graf, Jianwei Zhang","doi":"10.1109/IVS.2004.1336398","DOIUrl":"https://doi.org/10.1109/IVS.2004.1336398","url":null,"abstract":"This paper introduces a cognitive method for extracting significant road information (like road extents, lane markings) from mono-color images. The system is able to identify all traffic lanes and to distinguish between continuous and broken lane markings. Its output is useful in driver assistance systems (for example lane-departure warning). The cognitive aspects of the system are highlighted and the implemented algorithms are described. Finally, some results of the performed tests are introduced before drawing the conclusion.","PeriodicalId":296386,"journal":{"name":"IEEE Intelligent Vehicles Symposium, 2004","volume":"34 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":"132001486","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}
Pub Date : 2004-06-14DOI: 10.1109/IVS.2004.1336455
A. Eidehall, Fredrik Gustafsson
Detection and tracking of other vehicles and lane geometry will be required for many future intelligent driver assistance systems. By integrating the estimation of these two features into a single filter, a more optimal utilization of the available information can be achieved. For example, it is possible to improve the lane curvature estimate during bad visibility by studying the motion of other vehicles. This paper derives and evaluates various approximations that are needed in order to deal with the non-linearities that are introduced by such an approach.
{"title":"Combined road prediction and target tracking in collision avoidance","authors":"A. Eidehall, Fredrik Gustafsson","doi":"10.1109/IVS.2004.1336455","DOIUrl":"https://doi.org/10.1109/IVS.2004.1336455","url":null,"abstract":"Detection and tracking of other vehicles and lane geometry will be required for many future intelligent driver assistance systems. By integrating the estimation of these two features into a single filter, a more optimal utilization of the available information can be achieved. For example, it is possible to improve the lane curvature estimate during bad visibility by studying the motion of other vehicles. This paper derives and evaluates various approximations that are needed in order to deal with the non-linearities that are introduced by such an approach.","PeriodicalId":296386,"journal":{"name":"IEEE Intelligent Vehicles Symposium, 2004","volume":"45 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":"132190617","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}
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