Pub Date : 2005-06-06DOI: 10.1109/IVS.2005.1505176
Sangho Park, M. Trivedi
This paper examines the feasibility of a semantic-level driver activity analysis system. Several new considerations are made to construct the hierarchy of driver activity. Driver activity is represented and recognized at multiple levels: individual body-part pose/gesture at the low level, single body-part action at the middle level, and the driver interaction with the vehicle at the high level. Driving is represented in terms of the interactions among driver, vehicle, and surround, and driver activity is recognized by a rule-based decision tree. Our system works with a single color camera data, and it can be easily expanded to incorporate multimodal sensor data.
{"title":"Driver activity analysis for intelligent vehicles: issues and development framework","authors":"Sangho Park, M. Trivedi","doi":"10.1109/IVS.2005.1505176","DOIUrl":"https://doi.org/10.1109/IVS.2005.1505176","url":null,"abstract":"This paper examines the feasibility of a semantic-level driver activity analysis system. Several new considerations are made to construct the hierarchy of driver activity. Driver activity is represented and recognized at multiple levels: individual body-part pose/gesture at the low level, single body-part action at the middle level, and the driver interaction with the vehicle at the high level. Driving is represented in terms of the interactions among driver, vehicle, and surround, and driver activity is recognized by a rule-based decision tree. Our system works with a single color camera data, and it can be easily expanded to incorporate multimodal sensor data.","PeriodicalId":386189,"journal":{"name":"IEEE Proceedings. Intelligent Vehicles Symposium, 2005.","volume":"37 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":"114712713","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 : 2005-06-06DOI: 10.1109/IVS.2005.1505139
L. Li, F.-Y. Wang, Qunzhi Zhou
Lateral control of vehicles on automated highways often requires accurate estimation of sideslip angle, yaw rate and lateral velocity, which are difficult to measure directly. Thus, several observers (virtual sensors) were developed in the last decade. In order to solve the unhandled estimation inaccuracy problem caused by system parameter variation and/or model uncertainty, a robust observer has been proposed in this paper. It maintains the good disturbance rejection property that derived form previous research, and simultaneously provides acceptable tolerance to model variance and uncertainty. Specially, effects of displacements of sensory, dynamics variance caused by mass/velocity/friction-coefficients change or nonlinear characteristics are studied. Simulations demonstrate the usefulness of the proposed observer.
{"title":"A robust observer designed for vehicle lateral motion estimation","authors":"L. Li, F.-Y. Wang, Qunzhi Zhou","doi":"10.1109/IVS.2005.1505139","DOIUrl":"https://doi.org/10.1109/IVS.2005.1505139","url":null,"abstract":"Lateral control of vehicles on automated highways often requires accurate estimation of sideslip angle, yaw rate and lateral velocity, which are difficult to measure directly. Thus, several observers (virtual sensors) were developed in the last decade. In order to solve the unhandled estimation inaccuracy problem caused by system parameter variation and/or model uncertainty, a robust observer has been proposed in this paper. It maintains the good disturbance rejection property that derived form previous research, and simultaneously provides acceptable tolerance to model variance and uncertainty. Specially, effects of displacements of sensory, dynamics variance caused by mass/velocity/friction-coefficients change or nonlinear characteristics are studied. Simulations demonstrate the usefulness of the proposed observer.","PeriodicalId":386189,"journal":{"name":"IEEE Proceedings. Intelligent Vehicles Symposium, 2005.","volume":"30 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":"124072815","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 : 2005-06-06DOI: 10.1109/IVS.2005.1505126
W. Travis, A. Simmons, D. Bevly, Broun Hall
Autonomous capability requires reliable and robust navigation solutions in multiple environments. GPS has become an effective tool but is not suitable for all environments. Laser scanners are quickly making their presence known in the navigation field and are proven to have a variety of uses. This paper investigates the use of LiDAR within an indoor corridor environment (i.e. hallway) to update IMU measurements. The LiDAR is combined with an IMU in a Kalman filter to produce estimates of vehicle velocity, heading, lateral error, and sensor biases. It is shown how this combination is effective in providing accurate state estimates while removing sensor errors due to noise and bias.
{"title":"Corridor navigation with a LiDAR/INS Kalman filter solution","authors":"W. Travis, A. Simmons, D. Bevly, Broun Hall","doi":"10.1109/IVS.2005.1505126","DOIUrl":"https://doi.org/10.1109/IVS.2005.1505126","url":null,"abstract":"Autonomous capability requires reliable and robust navigation solutions in multiple environments. GPS has become an effective tool but is not suitable for all environments. Laser scanners are quickly making their presence known in the navigation field and are proven to have a variety of uses. This paper investigates the use of LiDAR within an indoor corridor environment (i.e. hallway) to update IMU measurements. The LiDAR is combined with an IMU in a Kalman filter to produce estimates of vehicle velocity, heading, lateral error, and sensor biases. It is shown how this combination is effective in providing accurate state estimates while removing sensor errors due to noise and bias.","PeriodicalId":386189,"journal":{"name":"IEEE Proceedings. Intelligent Vehicles Symposium, 2005.","volume":"57 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":"124175665","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 : 2005-06-06DOI: 10.1109/IVS.2005.1505073
S.Y. Kim, K. Wilson-Remmer, A. Kun, W. Miller
We describe two prototype remote fleet management software modules for police cruisers. One of the modules is used for automatic vehicle location (AVL) the other is used for cruiser status monitoring. The software modules leverage the existing Project54 infrastructure that integrates electronic devices in cruisers and connects cruisers to each other and to headquarters. This infrastructure allows client-server connections over 802.11 wireless networks as well as over police radio networks. The AVL module transmits GPS information to headquarters over the radio network. In order not to overwhelm the radio network, heuristic rules are used to decide when to transmit data and when to discard it. The AVL module was successfully tested in the field. The status monitoring module is designed to use the on-board diagnostics II (OBD II) standard to connect to the vehicle's internal bus. The prototype was successfully tested in laboratory conditions with simulated OBD II data.
{"title":"Remote fleet management for police cruisers","authors":"S.Y. Kim, K. Wilson-Remmer, A. Kun, W. Miller","doi":"10.1109/IVS.2005.1505073","DOIUrl":"https://doi.org/10.1109/IVS.2005.1505073","url":null,"abstract":"We describe two prototype remote fleet management software modules for police cruisers. One of the modules is used for automatic vehicle location (AVL) the other is used for cruiser status monitoring. The software modules leverage the existing Project54 infrastructure that integrates electronic devices in cruisers and connects cruisers to each other and to headquarters. This infrastructure allows client-server connections over 802.11 wireless networks as well as over police radio networks. The AVL module transmits GPS information to headquarters over the radio network. In order not to overwhelm the radio network, heuristic rules are used to decide when to transmit data and when to discard it. The AVL module was successfully tested in the field. The status monitoring module is designed to use the on-board diagnostics II (OBD II) standard to connect to the vehicle's internal bus. The prototype was successfully tested in laboratory conditions with simulated OBD II data.","PeriodicalId":386189,"journal":{"name":"IEEE Proceedings. Intelligent Vehicles Symposium, 2005.","volume":"37 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":"115075050","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 : 2005-06-06DOI: 10.1109/IVS.2005.1505218
Y. Lin, F.-Y. Wang
Predicting traffic flow is of extreme importance in traffic modeling and congestion control. The traffic data usually exhibit chaotic dynamics that can be readily modeled and analyzed using time series. Traditional tools for time series analysis have been focused on exploring the statistical properties of the data. On the other hand, it has been long observed that times series can be considered as the output of nonlinear dynamic system. The development of computational intelligence methodology and its composing methods including fuzzy logic and neural networks has provided a new powerful tool for time series analysis. The paper represents a novel method of using a hybrid networks following the fuzzy logic inference mechanism to predict chaotic times series.
{"title":"Predicting chaotic time series using adaptive wavelet-fuzzy inference system","authors":"Y. Lin, F.-Y. Wang","doi":"10.1109/IVS.2005.1505218","DOIUrl":"https://doi.org/10.1109/IVS.2005.1505218","url":null,"abstract":"Predicting traffic flow is of extreme importance in traffic modeling and congestion control. The traffic data usually exhibit chaotic dynamics that can be readily modeled and analyzed using time series. Traditional tools for time series analysis have been focused on exploring the statistical properties of the data. On the other hand, it has been long observed that times series can be considered as the output of nonlinear dynamic system. The development of computational intelligence methodology and its composing methods including fuzzy logic and neural networks has provided a new powerful tool for time series analysis. The paper represents a novel method of using a hybrid networks following the fuzzy logic inference mechanism to predict chaotic times series.","PeriodicalId":386189,"journal":{"name":"IEEE Proceedings. Intelligent Vehicles Symposium, 2005.","volume":"44 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":"115217884","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 : 2005-06-06DOI: 10.1109/IVS.2005.1505149
F. Holzmann, M. BeHino, S. Kolskit, A. Sulzmann, G. Spiegelberg, R. Siegwart
This paper introduces a new concept for advanced driver assistance by means of a redundant architecture including all system components spanning from environment perception to vehicle controllers. The first part of this paper is an overview of the project framework and the research platforms. After that the elements of the architecture themselves will be described. The use of sensors and the fusion of their outputs will be presented. Different controllers will be used depending on the scenarios around the vehicle in order to provide a theoric solution. This solution will be downsized after that with a dynamic vehicle model to the feasible safe motion vectors. This list of motion vectors will be compared to the driver's command and will lead to the choose of his/her command or an other safe motion vector if the driver does not react convenient to the situation. The final part describes some preliminary results and concludes towards future work and research issues.
{"title":"Robots go automotive - the SPARC approach","authors":"F. Holzmann, M. BeHino, S. Kolskit, A. Sulzmann, G. Spiegelberg, R. Siegwart","doi":"10.1109/IVS.2005.1505149","DOIUrl":"https://doi.org/10.1109/IVS.2005.1505149","url":null,"abstract":"This paper introduces a new concept for advanced driver assistance by means of a redundant architecture including all system components spanning from environment perception to vehicle controllers. The first part of this paper is an overview of the project framework and the research platforms. After that the elements of the architecture themselves will be described. The use of sensors and the fusion of their outputs will be presented. Different controllers will be used depending on the scenarios around the vehicle in order to provide a theoric solution. This solution will be downsized after that with a dynamic vehicle model to the feasible safe motion vectors. This list of motion vectors will be compared to the driver's command and will lead to the choose of his/her command or an other safe motion vector if the driver does not react convenient to the situation. The final part describes some preliminary results and concludes towards future work and research issues.","PeriodicalId":386189,"journal":{"name":"IEEE Proceedings. Intelligent Vehicles Symposium, 2005.","volume":"49 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":"129603255","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 : 2005-06-06DOI: 10.1109/IVS.2005.1505133
J. Perng, H. Chin, Bing-Fei Wu, Tsu-Tian Lee
The main purpose of this paper is to analyze the stability for a fuzzy vehicle steering control system. In general, fuzzy control system is a nonlinear control system. Therefore, the fuzzy controller may be linearized by the use of describing function first. After then, the traditional frequency domain method i.e. parameter plane, is then applied to determine the condition of stability when the system has perturbed or adjustable parameters. A systematic procedure is proposed to solve this problem. The stability problem under the effects of plant parameters and control factors are both considered here. Furthermore, the effect of transport delay is also addressed. The limit cycles provided by a static fuzzy controller can be easily suppressed if the system parameters are chosen properly. Simulation results show the efficiency of our approach.
{"title":"Stability analysis of a robust fuzzy vehicle steering control system","authors":"J. Perng, H. Chin, Bing-Fei Wu, Tsu-Tian Lee","doi":"10.1109/IVS.2005.1505133","DOIUrl":"https://doi.org/10.1109/IVS.2005.1505133","url":null,"abstract":"The main purpose of this paper is to analyze the stability for a fuzzy vehicle steering control system. In general, fuzzy control system is a nonlinear control system. Therefore, the fuzzy controller may be linearized by the use of describing function first. After then, the traditional frequency domain method i.e. parameter plane, is then applied to determine the condition of stability when the system has perturbed or adjustable parameters. A systematic procedure is proposed to solve this problem. The stability problem under the effects of plant parameters and control factors are both considered here. Furthermore, the effect of transport delay is also addressed. The limit cycles provided by a static fuzzy controller can be easily suppressed if the system parameters are chosen properly. Simulation results show the efficiency of our approach.","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":"128912559","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 : 2005-06-06DOI: 10.1109/IVS.2005.1505203
R. Anderson, D. Bevly, I. M O D U C T L O N
This paper demonstrates a method of obtaining key vehicle states using GPS and INS measurements with an adaptive model based estimator. A dual antenna GPS attitude system is used to estimate tire cornering stiffness. This estimated parameter is updated in the estimator model to provide more accurate estimates of the vehicle states. The experimental results for the estimate of sideslip and yaw rate using the updated estimator model compare favorable to values predicted by the theoretical model.
{"title":"Estimation of tire cornering stiffness using GPS to improve model based estimation of vehicle states","authors":"R. Anderson, D. Bevly, I. M O D U C T L O N","doi":"10.1109/IVS.2005.1505203","DOIUrl":"https://doi.org/10.1109/IVS.2005.1505203","url":null,"abstract":"This paper demonstrates a method of obtaining key vehicle states using GPS and INS measurements with an adaptive model based estimator. A dual antenna GPS attitude system is used to estimate tire cornering stiffness. This estimated parameter is updated in the estimator model to provide more accurate estimates of the vehicle states. The experimental results for the estimate of sideslip and yaw rate using the updated estimator model compare favorable to values predicted by the theoretical model.","PeriodicalId":386189,"journal":{"name":"IEEE Proceedings. Intelligent Vehicles Symposium, 2005.","volume":"39 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":"125316304","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 : 2005-06-06DOI: 10.1109/IVS.2005.1505127
Qingmei Yang, Jianmin Sun
The active control suspension system can improve both the riding comfort and handling safety in various operation conditions. In this paper, according to the evaluation method of riding comfort and handling safety of vehicle, the acceleration of the sprung mass, dynamic tyre load between wheels and road and dynamic deflection between the sprung mass and the unsprung mass are determined as the evaluation targets of suspension performance. For two-DOF vehicle suspension model, the generalized adaptive control, sky-hook control and least means squares (LMS) adaptive control are studied. The simulation results show that calculation of LMS adaptive control algorithm is much little, and the method is fit for the active control of the suspension system.
{"title":"Three control approaches for vehicle active suspension","authors":"Qingmei Yang, Jianmin Sun","doi":"10.1109/IVS.2005.1505127","DOIUrl":"https://doi.org/10.1109/IVS.2005.1505127","url":null,"abstract":"The active control suspension system can improve both the riding comfort and handling safety in various operation conditions. In this paper, according to the evaluation method of riding comfort and handling safety of vehicle, the acceleration of the sprung mass, dynamic tyre load between wheels and road and dynamic deflection between the sprung mass and the unsprung mass are determined as the evaluation targets of suspension performance. For two-DOF vehicle suspension model, the generalized adaptive control, sky-hook control and least means squares (LMS) adaptive control are studied. The simulation results show that calculation of LMS adaptive control algorithm is much little, and the method is fit for the active control of the suspension system.","PeriodicalId":386189,"journal":{"name":"IEEE Proceedings. Intelligent Vehicles Symposium, 2005.","volume":"76 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":"121047110","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 : 2005-06-06DOI: 10.1109/IVS.2005.1505190
M. Darms, H. Winner
In this article a modular system architecture for fusion of data from environment sensors for advanced driver-assistance systems (ADAS) is proposed. The architecture allows different applications to have access to the fused sensor data by processing the data with respect to specific demands of different application groups. In the article the growing interconnection of functions is illustrated by two examples and the most relevant consequences of this trend are given. The question, if an application independent processing of sensor data is feasible is discussed and the most important aspects for the design of the system architecture are given. This provides the basis for the explanation of the system architecture.
{"title":"A modular system architecture for sensor data processing of ADAS applications","authors":"M. Darms, H. Winner","doi":"10.1109/IVS.2005.1505190","DOIUrl":"https://doi.org/10.1109/IVS.2005.1505190","url":null,"abstract":"In this article a modular system architecture for fusion of data from environment sensors for advanced driver-assistance systems (ADAS) is proposed. The architecture allows different applications to have access to the fused sensor data by processing the data with respect to specific demands of different application groups. In the article the growing interconnection of functions is illustrated by two examples and the most relevant consequences of this trend are given. The question, if an application independent processing of sensor data is feasible is discussed and the most important aspects for the design of the system architecture are given. This provides the basis for the explanation of the system architecture.","PeriodicalId":386189,"journal":{"name":"IEEE Proceedings. Intelligent Vehicles Symposium, 2005.","volume":"71 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":"126263329","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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