A. Westenberger, Michael Gabb, M. Muntzinger, M. Fritzsche, K. Dietmayer
{"title":"State and existence estimation with out-of-sequence measurements for a collision avoidance system","authors":"A. Westenberger, Michael Gabb, M. Muntzinger, M. Fritzsche, K. Dietmayer","doi":"10.1109/IVS.2013.6629534","DOIUrl":"https://doi.org/10.1109/IVS.2013.6629534","url":null,"abstract":"As their functionality becomes more and more complex, future driver assistance systems rely on several different sensors in order to combine the advantages of different measurement principles. However, in multi-sensor fusion, measurements may arrive at the fusion unit out-of-sequence, the original order of the measurements may be lost. Whereas out-of-sequence measurement processing in state estimation has been studied extensively, their incorporation in existence estimation has not been solved in the past. This paper presents a new algorithm for state and existence estimation in time-critical applications, where out-of-sequence measurements are handled adequately. The derived algorithm is validated with real-world data from crash tests.","PeriodicalId":251198,"journal":{"name":"2013 IEEE Intelligent Vehicles Symposium (IV)","volume":"41 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":"116574846","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":"Prediction of driver's stop or go at yellow traffic signal from vehicle behavior","authors":"Ryuki Mabuchi, K. Yamada","doi":"10.1109/IVS.2013.6629623","DOIUrl":"https://doi.org/10.1109/IVS.2013.6629623","url":null,"abstract":"Many studies in the field of intelligent vehicles aim at preventing accidents or improving the traffic performance of vehicles. For realizing more effective advanced driver assistance systems estimating the driver's intention is important. This paper addresses the problem of estimating the driver's intent to stop or pass through when a signal turns yellow. This problem is addressed by proposing two different methods. One is for predicting whether the driver is going to stop when the signal changes to yellow before the driver actually determines or executes it, and the other is for estimating whether the driver has made the decision to stop after the driver has started to implement that decision. The two proposed methods are evaluated by using driving behavior data collected from actual roads to demonstrate their performance and characteristics.","PeriodicalId":251198,"journal":{"name":"2013 IEEE Intelligent Vehicles Symposium (IV)","volume":"103 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":"121943167","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":"Analysis of 3 and 4 branch epicyclic transmission systems for Hybrid Electrical Vehicles using matrix method and TSA tool","authors":"Q. Ren, A. Elmarakbi, R. Trimble","doi":"10.1109/IVS.2013.6629522","DOIUrl":"https://doi.org/10.1109/IVS.2013.6629522","url":null,"abstract":"This paper is focused on modeling and analysis of 3 and 4 branch epicyclic transmission systems for Hybrid Electrical Vehicles (HEVs) using the matrix method and transmission systems analysis (TSA) tool. The TSA tool is especially developed to analyse such systems. The application of the system to a typical hybrid electric vehicle driveline is modeled and a comparison of the performance characteristics of competing designs is discussed. In addition, the potential benefits of the 4 branch epicyclic system are presented.","PeriodicalId":251198,"journal":{"name":"2013 IEEE Intelligent Vehicles Symposium (IV)","volume":"142 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":"123417412","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}
Sarah Bonnin, Thomas H. Weisswange, F. Kummert, Jens Schmüdderich
{"title":"Accurate behavior prediction on highways based on a systematic combination of classifiers","authors":"Sarah Bonnin, Thomas H. Weisswange, F. Kummert, Jens Schmüdderich","doi":"10.1109/IVS.2013.6629477","DOIUrl":"https://doi.org/10.1109/IVS.2013.6629477","url":null,"abstract":"To drive safely, a good driver observes his surroundings, anticipates the actions of other traffic participants and then decides for a maneuver. But if a driver is inattentive or overloaded he may fail to include some relevant information. This can then lead to wrong decisions and potentially result in an accident. In order to assist a driver in his decision making, Advanced Driver Assistance Systems (ADAS) are becoming more and more popular in commercial cars. The quality of these existing systems compared to an experienced driver is weak, because they rely purely on physical observation and thus react shortly before an accident. For an earlier warning of the driver behavior prediction is used. We classify existing research in this area with respect to two aspects: quality and scope. Quality means the ability to warn a driver early before a dangerous situation. Scope means the diversity of scenes in which the approach can work. In general we see two tendencies, methods targeting for broad scope but having low quality and those targeting for narrow scope but high quality. Our goal is to have a system with high quality and wide scope. To achieve this, we propose a system that combines classifiers to predict behaviors for many scenarios. To show that a combination of general and specific classifiers is a solution to improve quality and scope, this paper will introduce the generic concept of our system followed by a concrete implementation for lane change prediction for highway scenarios.","PeriodicalId":251198,"journal":{"name":"2013 IEEE Intelligent Vehicles Symposium (IV)","volume":"359 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":"122343833","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}
C. Rößing, Axel Reker, Michael Gabb, K. Dietmayer, H. Lensch
{"title":"Intuitive visualization of vehicle distance, velocity and risk potential in rear-view camera applications","authors":"C. Rößing, Axel Reker, Michael Gabb, K. Dietmayer, H. Lensch","doi":"10.1109/IVS.2013.6629529","DOIUrl":"https://doi.org/10.1109/IVS.2013.6629529","url":null,"abstract":"Many serious collisions on highways happen while changing lanes. One of the main causes for these accidents is the driver's incorrect assessment of the current rear traffic situation. To support the driver, we propose a framework to intuitively visualize distance, speed and risk potential of approaching vehicles in a rear-view camera application. The proposed visualization techniques are based on color coding, artificial motion blur and depth-of-field rendering, which are motivated by sensory effects of the human eye and interpreted intuitively by the human visual system. The impact on the human assessment of the moving speed of an object rendered with artificial motion enhancement is evaluated in a user study. The required distance and motion estimation of the vehicles are extracted out of monocular video images, by combining lane recognition, vehicle detection and segmentation machine vision algorithms.","PeriodicalId":251198,"journal":{"name":"2013 IEEE Intelligent Vehicles Symposium (IV)","volume":"42 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":"125457144","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":"Towards the development of a laserscanner-based collision avoidance system for trams","authors":"R. Katz, R. Schulz","doi":"10.1109/IVS.2013.6629553","DOIUrl":"https://doi.org/10.1109/IVS.2013.6629553","url":null,"abstract":"This paper presents the development of a Traffic Collision Avoidance System (TCAS) for trams based on state-of-the-art automotive laser scanning technology. Our work investigates TCAS regarding required functionalities and current efforts, and proposes an innovative solution for trams that is based on Ibeo laserscanners and digital maps. The different components of the proposed system are presented together with a description of upcoming field tests to be carried out in several European countries.","PeriodicalId":251198,"journal":{"name":"2013 IEEE Intelligent Vehicles Symposium (IV)","volume":"1 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":"125899514","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":"Classification of images in fog and fog-free scenes for use in vehicles","authors":"M. Pavlic, G. Rigoll, Slobodan Ilic","doi":"10.1109/IVS.2013.6629514","DOIUrl":"https://doi.org/10.1109/IVS.2013.6629514","url":null,"abstract":"Today modern vehicles are often equipped with a camera, which captures the scene in front of the vehicle. The recognition of weather conditions with this camera can help to improve many applications as well as establish new ones. In this article we will show how it is possible to distinguish between scenes with clear and foggy weather situations. The proposed method uses only gray-scale images as input signal and is running in real time. Using spectral features and a simple linear classifier, we can achieve high detection rates in both daytime and night-time scenes. Furthermore, we will show that in our application area these features outperform others.","PeriodicalId":251198,"journal":{"name":"2013 IEEE Intelligent Vehicles Symposium (IV)","volume":"53 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":"130194058","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. Köhler, Brian Schreiner, Steffen Ronalter, Konrad Doll, U. Brunsmann, K. Zindler
{"title":"Autonomous evasive maneuvers triggered by infrastructure-based detection of pedestrian intentions","authors":"S. Köhler, Brian Schreiner, Steffen Ronalter, Konrad Doll, U. Brunsmann, K. Zindler","doi":"10.1109/IVS.2013.6629520","DOIUrl":"https://doi.org/10.1109/IVS.2013.6629520","url":null,"abstract":"We present an active pedestrian protection system that performs an autonomous lane-keeping evasive maneuver in urban traffic scenarios when collision avoidance by braking is no longer possible. The system focuses on pedestrians standing at the curb and intending to cross the street despite an approaching car. It is demonstrated that the evasive maneuver of the car can be initiated before the pedestrian's foot hits the lane, by means of video-based motion contour histograms of oriented gradients and stationary detection. Using clothoid-based real-time trajectory planning and a lateral control of the car, combining feedforward and feedback control, the difference between the driven and the calculated trajectories is kept below 10 cm at maximum lateral accelerations of 4 ms-2 and -5 ms-2. We present the technical realization of the system and its precision with respect to intention recognition and driven trajectories. A case study showed that the system reacted faster than human drivers in five out of 11 cases, with an average time gain of 214 ms, even though the drivers were able to pay the utmost attention to the behavior of the crossing pedestrian.","PeriodicalId":251198,"journal":{"name":"2013 IEEE Intelligent Vehicles Symposium (IV)","volume":"27 3 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":"130424908","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}
M. Enzweiler, Pierre Greiner, Carsten Knöppel, Uwe Franke
{"title":"Towards multi-cue urban curb recognition","authors":"M. Enzweiler, Pierre Greiner, Carsten Knöppel, Uwe Franke","doi":"10.1109/IVS.2013.6629581","DOIUrl":"https://doi.org/10.1109/IVS.2013.6629581","url":null,"abstract":"This paper presents a multi-cue approach to curb recognition in urban traffic. We propose a novel texture-based curb classifier using local receptive field (LRF) features in conjunction with a multi-layer neural network. This classification module operates on both intensity images and on three-dimensional height profile data derived from stereo vision. We integrate the proposed multi-cue curb classifier as an additional measurement module into a state-of-the-art Kaiman filter-based urban lane recognition system. Our experiments involve a challenging real-world dataset captured in urban traffic with manually labeled ground-truth. We quantify the benefit of the proposed multi-cue curb classifier in terms of the improvement in curb localization accuracy of the integrated system. Our results indicate a 25% reduction of the average curb localization error at real-time processing speeds.","PeriodicalId":251198,"journal":{"name":"2013 IEEE Intelligent Vehicles Symposium (IV)","volume":"11 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":"129976298","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":"Meeting the real-time constraints with standard Ethernet in an in-vehicle network","authors":"Youngwoo Lee, KyoungSoo Park","doi":"10.1109/IVS.2013.6629648","DOIUrl":"https://doi.org/10.1109/IVS.2013.6629648","url":null,"abstract":"Vehicular networks have traditionally focused on the real-time delivery of critical control messages for safe car operation. Unfortunately, the real-time requirements often cripple the development of flexible car applications by tying the application network stack to underlying physical networks. While popular real-time vehicular networks guarantee the timely delivery of prioritized messages, they often lack in bandwidth and flexibility, which limits the range of car network applications. In this work, we explore the idea of replacing the current vehicular network with standard switched Ethernet, the most popular LAN technology in computer networks. Ethernet is attractive in providing high bandwidth at a low cost with easy and flexible configuration. The most challenging part is to guarantee the real-time delivery of mission-critical messages. We first show that the soft message delivery latency of 10s to 100s milliseconds can be easily met in 100 Mbps switched Ethernet despite coexistence of high-bandwidth network applications. For meeting the hard delivery latency on the order of 100 microseconds for critical control messages, we propose limiting the path MTU to the destination node with priority queuing from IEEE 802.1Q. Our simulation shows that we can satisfy 100 microseconds of latency even in a rich set of vehicular applications without any modification of the application network stack.","PeriodicalId":251198,"journal":{"name":"2013 IEEE Intelligent Vehicles Symposium (IV)","volume":"55 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":"130022067","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}