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2013 IEEE Intelligent Vehicles Symposium (IV)最新文献

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Reliability evaluation of steering system using dynamic fault tree 基于动态故障树的转向系统可靠性评估
2013 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2013-06-23 DOI: 10.1109/IVS.2013.6629665
Sungil Byun, Inseok Yang, Moogeun Song, Dongik Lee
{"title":"Reliability evaluation of steering system using dynamic fault tree","authors":"Sungil Byun, Inseok Yang, Moogeun Song, Dongik Lee","doi":"10.1109/IVS.2013.6629665","DOIUrl":"https://doi.org/10.1109/IVS.2013.6629665","url":null,"abstract":"This paper addresses a dynamic fault tree analysis (DFTA) to predict the reliability of a steering system. Reliability evaluation is a vital task to prevent any potential failure in a system by identifying vulnerable parts of the system and managing them effectively. Safety-critical systems, such as electric vehicles, have many components whose failure may cause a catastrophic accident. The steering system in a vehicle is one of the most critical subsystems requiring a high level of reliability. In this paper, a DFTA method using the Simpson's rule is proposed to evaluate the reliability of a steering system. A set of simulation results shows that the proposed method can overcome the problem of low accuracy with the existing approximation method while requiring no excessive calculation time of the Markov chain method.","PeriodicalId":251198,"journal":{"name":"2013 IEEE Intelligent Vehicles Symposium (IV)","volume":"333 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":"122542723","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: 4
Full auto-calibration of a smartphone on board a vehicle using IMU and GPS embedded sensors 使用IMU和GPS嵌入式传感器对车载智能手机进行全自动校准
2013 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2013-06-23 DOI: 10.1109/IVS.2013.6629658
J. Almazán, L. Bergasa, J. J. Torres, R. Barea, R. Arroyo
{"title":"Full auto-calibration of a smartphone on board a vehicle using IMU and GPS embedded sensors","authors":"J. Almazán, L. Bergasa, J. J. Torres, R. Barea, R. Arroyo","doi":"10.1109/IVS.2013.6629658","DOIUrl":"https://doi.org/10.1109/IVS.2013.6629658","url":null,"abstract":"Nowadays, smartphones are widely used in the world, and generally, they are equipped with many sensors. In this paper we study how powerful the low-cost embedded IMU and GPS could become for Intelligent Vehicles. The information given by accelerometer and gyroscope is useful if the relations between the smartphone reference system, the vehicle reference system and the world reference system are known. Commonly, the magnetometer sensor is used to determine the orientation of the smartphone, but its main drawback is the high influence of electromagnetic interference. In view of this, we propose a novel automatic method to calibrate a smartphone on board a vehicle using its embedded IMU and GPS, based on longitudinal vehicle acceleration. To the best of our knowledge, this is the first attempt to estimate the yaw angle of a smartphone relative to a vehicle in every case, even on non-zero slope roads. Furthermore, in order to decrease the impact of IMU noise, an algorithm based on Kalman Filter and fitting a mixture of Gaussians is introduced. The results show that the system achieves high accuracy, the typical error is 1%, and is immune to electromagnetic interference.","PeriodicalId":251198,"journal":{"name":"2013 IEEE Intelligent Vehicles Symposium (IV)","volume":"160 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":"123025711","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: 50
Step and curb detection for autonomous vehicles with an algebraic derivative-based approach applied on laser rangefinder data 基于激光测距仪数据的代数导数方法在自动驾驶车辆步距和路缘检测中的应用
2013 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2013-06-23 DOI: 10.1109/IVS.2013.6629546
Evangeline Pollard, Joshué Pérez, F. Nashashibi
{"title":"Step and curb detection for autonomous vehicles with an algebraic derivative-based approach applied on laser rangefinder data","authors":"Evangeline Pollard, Joshué Pérez, F. Nashashibi","doi":"10.1109/IVS.2013.6629546","DOIUrl":"https://doi.org/10.1109/IVS.2013.6629546","url":null,"abstract":"Personal Mobility Vehicles (PMV) is is an important part of the Intelligent Transportation System (ITS) domain. These new transport systems have been designed for urban traffic areas, pedestrian streets, green zones and private parks. In these areas, steps and curbs make the movement of disable or mobility reduced people with PMV, and with standard chair wheels difficult. In this paper, we present a step and curb detection system based on laser sensors. This system is dedicated to vehicles able to cross over steps, for transportation systems, as well as for mobile robots. The system is based on the study of the first derivative of the altitude and highlights the use of a new algebraic derivative method adapted to laser sensor data. The system has been tested on several real scenarios. It provides the distance, altitude and orientation of the steps in front of the vehicle and offers a high level of precision, even with small steps and challenging scenarios such as stairs.","PeriodicalId":251198,"journal":{"name":"2013 IEEE Intelligent Vehicles Symposium (IV)","volume":"61 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":"133229063","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: 7
Fast road detection from color images 快速道路检测从彩色图像
2013 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2013-06-23 DOI: 10.1109/IVS.2013.6629631
Bihao Wang, V. Fremont
{"title":"Fast road detection from color images","authors":"Bihao Wang, V. Fremont","doi":"10.1109/IVS.2013.6629631","DOIUrl":"https://doi.org/10.1109/IVS.2013.6629631","url":null,"abstract":"In this paper, we present a method for drivable road detection by extracting its specular intrinsic feature from an image. The resulting detection is then used in a stereo vision-based 3D road parameters extraction algorithm. A substantial representation of the road surface, called axis-calibration, is represented as an angle in logchromaticity space. This feature provides an invariance to road surface under illuminant conditions with shadow or not. We also add a sky removal function in order to eliminate the negative effects of sky light on axis-calibration result. Then, a confidence interval calculation helps the pixels' classification to speed up the detection processing. At last, the approach is combined with a stereovision based method to filter out false detected pixels and to obtain precise 3D road parameters. The experimental results show that the proposed approach can be adapted for real-time ADAS system in various driving conditions.","PeriodicalId":251198,"journal":{"name":"2013 IEEE Intelligent Vehicles Symposium (IV)","volume":"18 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":"131871921","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: 39
Automated extrinsic laser and camera inter-calibration using triangular targets 基于三角目标的外源激光与相机间自动标定
2013 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2013-06-23 DOI: 10.1109/IVS.2013.6629548
S. Debattisti, L. Mazzei, M. Panciroli
{"title":"Automated extrinsic laser and camera inter-calibration using triangular targets","authors":"S. Debattisti, L. Mazzei, M. Panciroli","doi":"10.1109/IVS.2013.6629548","DOIUrl":"https://doi.org/10.1109/IVS.2013.6629548","url":null,"abstract":"This paper presents a method for solving the extrinsic calibration between camera and multi-layer laser scanner for outdoor multi-sensorized vehicles. The proposed method is designed for intelligent vehicles within the autonomous navigation task where usually distances between sensor and targets become relevant for safety reasons, therefore high accuracy across different measures must be kept. The calibration procedure takes advantage of triangular shapes still present in scenarios, it recovers three virtual points as target pose in the laser and camera reference frames and then compute extrinsic information of each camera sensor with respect to a laser scanner by minimizing a geometric distance in the image space. To test algorithm correctness, and accuracy a set of simulations are used reporting absolute error results and solution convergence, then tests on robustness and reliability (i.e., outliers management) are based on a wide set of datasets acquired by VIAC prototypes.","PeriodicalId":251198,"journal":{"name":"2013 IEEE Intelligent Vehicles Symposium (IV)","volume":"23 9","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133105877","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: 38
Merge recommendations for driver assistance: A cross-modal, cost-sensitive approach 合并驾驶员辅助建议:一种跨模式、成本敏感的方法
2013 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2013-06-23 DOI: 10.1109/IVS.2013.6629503
Sayanan Sivaraman, M. Trivedi, Mario Tippelhofer, T. Shannon
{"title":"Merge recommendations for driver assistance: A cross-modal, cost-sensitive approach","authors":"Sayanan Sivaraman, M. Trivedi, Mario Tippelhofer, T. Shannon","doi":"10.1109/IVS.2013.6629503","DOIUrl":"https://doi.org/10.1109/IVS.2013.6629503","url":null,"abstract":"In this study, we present novel work focused on assisting the driver during merge maneuvers. We use an automotive testbed instrumented with sensors for monitoring critical regions in the vehicle's surround. Fusing information from multiple sensor modalities, we integrate measurements into a contextually relevant, intuitive, general representation, which we term the Dynamic Probabilistic Drivability Map [DPDM]. We formulate the DPDM for driver assistance as a compact representation of the surround environment, integrating vehicle tracking information, lane information, road geometry, obstacle detection, and ego-vehicle dynamics. Given a robust understanding of the ego-vehicle's dynamics, other vehicles, and the on-road environment, our system recommends merge maneuvers to the driver, formulating the maneuver as a dynamic programming problem over the DPDM, searching for the minimum cost solution for merging. Based on the configuration of the road, lanes, and other vehicles on the road, the system recommends the appropriate acceleration or deceleration for merging into the adjacent lane, specifying when and how to merge.","PeriodicalId":251198,"journal":{"name":"2013 IEEE Intelligent Vehicles Symposium (IV)","volume":"46 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":"133784625","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: 26
Automatic vehicle classification and tracking method for vehicle movements at signalized intersections 信号交叉口车辆运动的自动分类和跟踪方法
2013 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2013-06-23 DOI: 10.1109/IVS.2013.6629536
C. Chai, Y. Wong
{"title":"Automatic vehicle classification and tracking method for vehicle movements at signalized intersections","authors":"C. Chai, Y. Wong","doi":"10.1109/IVS.2013.6629536","DOIUrl":"https://doi.org/10.1109/IVS.2013.6629536","url":null,"abstract":"This paper presents an automatic vehicle classification and tracking method to estimate the traffic parameters of vehicle movements at signalized intersections. Different from traditional methods, this classification and tracking system is based on a projective transformation of video frames. The proposed method has a good ability to classify detected vehicles and calculate parameters of vehicle movements at intersection area. Experimental results show the proposed method is more accurate and powerful than feature-based detection algorithm to tackle the problem of changing shape and size of vehicles due to turning movements. Based on tracking results, vehicle movements, including turning paths and speed profile are analyzed. The proposed method is a valuable tool for building path and speed control strategy of intelligent vehicles.","PeriodicalId":251198,"journal":{"name":"2013 IEEE Intelligent Vehicles Symposium (IV)","volume":"29 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":"133854907","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: 10
Vehicle path planning with maximizing safe margin for driving using Lagrange multipliers 使用拉格朗日乘法器进行安全裕度最大化的车辆路径规划
2013 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2013-06-23 DOI: 10.1109/IVS.2013.6629466
Quoc Huy Do, Hossein Tehrani Niknejad, Keisuke Yoneda, Ryohei Sakai, S. Mita
{"title":"Vehicle path planning with maximizing safe margin for driving using Lagrange multipliers","authors":"Quoc Huy Do, Hossein Tehrani Niknejad, Keisuke Yoneda, Ryohei Sakai, S. Mita","doi":"10.1109/IVS.2013.6629466","DOIUrl":"https://doi.org/10.1109/IVS.2013.6629466","url":null,"abstract":"We propose a path planning method for autonomous vehicle in cluttered environment with narrow passages. Different from traditional methods, we use a learning approach based on RBF kernel SVM to maximize the safety margin for driving. We use the Lagrange multipliers of SVM dual model to find most critical points in map and generate optimized hyperplane for path. The method is implemented on autonomous vehicle for outdoor parking and compared to well-known method in autonomous vehicle literatures. The experiments prove that the method is able to generate smooth and safe path in shorter time compared to other methods.","PeriodicalId":251198,"journal":{"name":"2013 IEEE Intelligent Vehicles Symposium (IV)","volume":"7 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":"116540836","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: 7
Traffic panels detection using visual appearance 使用视觉外观检测交通面板
2013 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2013-06-23 DOI: 10.1109/IVS.2013.6629633
Álvaro González, L. Bergasa, J. J. Torres, J. Almazán
{"title":"Traffic panels detection using visual appearance","authors":"Álvaro González, L. Bergasa, J. J. Torres, J. Almazán","doi":"10.1109/IVS.2013.6629633","DOIUrl":"https://doi.org/10.1109/IVS.2013.6629633","url":null,"abstract":"Traffic signs detection has been thoroughly studied for a long time. However, road panels detection still remains a challenge in computer vision due to the huge variability of types of traffic panels, as the information depicted in them is not restricted. This paper presents a method to detect traffic panels in street-level images as an application to Intelligent Transportation Systems (ITS), since the main purpose can be to make an automatic inventory of the traffic panels located in a road to support maintenance and to assist drivers in order to improve human quality of life. The proposed method extracts local descriptors at some interest points after applying a color detection method for blue and white pixels. Then, the images are modeled using a Bag of Visual Words technique and classified using Naïve Bayes theory and SVM. Experimental results on real images from Google Street View prove the efficiency of the proposed method and give way to using street-level images for different applications on robotics and ITS.","PeriodicalId":251198,"journal":{"name":"2013 IEEE Intelligent Vehicles Symposium (IV)","volume":"9 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":"115014767","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: 2
Spatio-temporal prediction of collision candidates for static and dynamic objects in monocular image sequences 单眼图像序列中静态和动态目标候选碰撞的时空预测
2013 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2013-06-23 DOI: 10.1109/IVS.2013.6629605
A. Schaub, Darius Burschka
{"title":"Spatio-temporal prediction of collision candidates for static and dynamic objects in monocular image sequences","authors":"A. Schaub, Darius Burschka","doi":"10.1109/IVS.2013.6629605","DOIUrl":"https://doi.org/10.1109/IVS.2013.6629605","url":null,"abstract":"This paper presents a novel approach for reactive obstacle avoidance for static and dynamic objects using monocular image sequences. A sparse motion field is calculated by tracking point features using the Kanade-Lucas-Tomasi method. The rotational component of this sparse optical flow due to ego motion of the camera is compensated using motion parameters estimated directly from the images. A robust method for detection of static and dynamic objects in the scene is applied to identify collision candidates. The approach operates entirely in the image space of a monocular camera and does not require any extrinsic information about the configuration of the sensor or speed of the camera. The system prioritizes the detected collision candidates by their time to collision. Additionally, the spatial distribution of the candidates is calculated for non-degenerated conditions. We present the mathematical framework and the experimental validation of the suggested approach on simulated and real-world data.","PeriodicalId":251198,"journal":{"name":"2013 IEEE Intelligent Vehicles Symposium (IV)","volume":"77 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":"121891971","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: 11
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