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On-road vehicle detection during dusk and at night 黄昏及夜间道路车辆侦测
2010 IEEE Intelligent Vehicles Symposium Pub Date : 2010-06-21 DOI: 10.1109/IVS.2010.5548013
T. Schamm, Christopher Carlowitz, Johann Marius Zöllner
{"title":"On-road vehicle detection during dusk and at night","authors":"T. Schamm, Christopher Carlowitz, Johann Marius Zöllner","doi":"10.1109/IVS.2010.5548013","DOIUrl":"https://doi.org/10.1109/IVS.2010.5548013","url":null,"abstract":"The video-based on-road detection of vehicles at daytime allows driver assistance systems to avoid collisions and thereby improve safety, and realize comfort functions, like the well known adaptive cruise control. However, at nighttime, common video sensor based vehicle detection algorithms can't be used, because most state-of-the-art features, like shadows, symmetry and others, cannot be measured. The on-road detection of vehicles at night is an obligatory feature for modern driver assistance systems, because those systems have to provide assistance functionality at day-time and at night-time, either. In this work, vehicles in front of the own car are recognized by detection of their front or rear lights, using a perspective blob filter and subsequently searching for corresponding light pairs. For preceding vehicles, the activity of the third break light is estimated, to distinguish the maneuver state of the vehicle. Experiments show the robustness of the approach during dusk and at night sequences.","PeriodicalId":123266,"journal":{"name":"2010 IEEE Intelligent Vehicles Symposium","volume":"130 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125348719","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
A prediction- and cost function-based algorithm for robust autonomous freeway driving 基于预测和成本函数的鲁棒高速公路自动驾驶算法
2010 IEEE Intelligent Vehicles Symposium Pub Date : 2010-06-21 DOI: 10.1109/IVS.2010.5547988
Junqing Wei, J. Dolan, B. Litkouhi
{"title":"A prediction- and cost function-based algorithm for robust autonomous freeway driving","authors":"Junqing Wei, J. Dolan, B. Litkouhi","doi":"10.1109/IVS.2010.5547988","DOIUrl":"https://doi.org/10.1109/IVS.2010.5547988","url":null,"abstract":"In this paper, a prediction- and cost function-based algorithm (PCB) is proposed to implement robust freeway driving in autonomous vehicles. A prediction engine is built to predict the future microscopic traffic scenarios. With the help of a human-understandable and representative cost function library, the predicted traffic scenarios are evaluated and the best control strategy is selected based on the lowest cost. The prediction- and cost function-based algorithm is verified using the simulator of the autonomous vehicle Boss from the DARPA Urban Challenge 2007. The results of both case tests and statistical tests using PCB show enhanced performance of the autonomous vehicle in performing distance keeping, lane selecting and merging on freeways.","PeriodicalId":123266,"journal":{"name":"2010 IEEE Intelligent Vehicles Symposium","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125301280","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: 76
The See-Through System: A VANET-enabled assistant for overtaking maneuvers 透视系统:一个启用vanet的超车助手
2010 IEEE Intelligent Vehicles Symposium Pub Date : 2010-06-21 DOI: 10.1109/IVS.2010.5548020
C. Olaverri-Monreal, P. Gomes, Ricardo Fernandes, F. Vieira, Michel Ferreira
{"title":"The See-Through System: A VANET-enabled assistant for overtaking maneuvers","authors":"C. Olaverri-Monreal, P. Gomes, Ricardo Fernandes, F. Vieira, Michel Ferreira","doi":"10.1109/IVS.2010.5548020","DOIUrl":"https://doi.org/10.1109/IVS.2010.5548020","url":null,"abstract":"The use of wireless technology based on Vehicular Ad hoc Networks (VANETs) for information exchange can influence the drivers' behavior towards improving driving performance and reducing road accidents. This information can even be more relevant if it is presented as a video stream. In this paper we propose a system that relies on VANET and video-streaming technology: the See-Through System (STS). The system enhances driver's visibility and supports the driver's overtaking decision in challenging situations, such as overtaking a vision-obstructing vehicle. The use of the See-Through System provides the driver with an additional tool for determining if traffic conditions permit starting an overtaking maneuver thus reducing the risk of overtaking. We tested the See-Through System on an experimental vehicle on the road as well as in the context of a driving simulator for real world environment. Results are promising, since the use of the 802.11p standard wireless communication protocol allows a vehicle-to-vehicle connection without significant delay and the totality of the participants regarded the information provided by the STS as useful.","PeriodicalId":123266,"journal":{"name":"2010 IEEE Intelligent Vehicles Symposium","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115918675","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: 96
Sensor fusion-based pedestrian collision warning system with crosswalk detection 基于传感器融合的人行横道行人碰撞预警系统
2010 IEEE Intelligent Vehicles Symposium Pub Date : 2010-06-21 DOI: 10.1109/IVS.2010.5548120
Shigetaka Suzuki, P. Raksincharoensak, I. Shimizu, M. Nagai, R. Adomat
{"title":"Sensor fusion-based pedestrian collision warning system with crosswalk detection","authors":"Shigetaka Suzuki, P. Raksincharoensak, I. Shimizu, M. Nagai, R. Adomat","doi":"10.1109/IVS.2010.5548120","DOIUrl":"https://doi.org/10.1109/IVS.2010.5548120","url":null,"abstract":"This paper describes a pedestrian collision warning system with crosswalk detection feature based on sensor fusion of a monocular camera and a millimeter wave radar. The method to decide about the presence of a pedestrian is based on the assumption that objects moving along a crosswalk can be interpreted as pedestrians under certain circumstances. The advantage of the described solution is its robustness and effectiveness since it is limited to crosswalks. The camera can be used to detect the crosswalk. Data from both sensors can then be used to infer about the presence of a pedestrian. The sensor fusion algorithm which combines data from the sensors is explained. Then the paper describes a warning concept which provides auditory alarm and visual information about the presence of a crosswalk as well as pedestrians to a driver, depending on the estimated collision probability. Finally, test drives on an experimental vehicle are presented and the results verify that the proposed warning system is running in practice.","PeriodicalId":123266,"journal":{"name":"2010 IEEE Intelligent Vehicles Symposium","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129088921","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: 24
The effect of vehicular distance distributions and mobility on VANET communications 车辆距离分布和机动性对VANET通信的影响
2010 IEEE Intelligent Vehicles Symposium Pub Date : 2010-06-21 DOI: 10.1109/IVS.2010.5547971
R. Nagel
{"title":"The effect of vehicular distance distributions and mobility on VANET communications","authors":"R. Nagel","doi":"10.1109/IVS.2010.5547971","DOIUrl":"https://doi.org/10.1109/IVS.2010.5547971","url":null,"abstract":"In vehicular ad-hoc networks, physical parameters of traffic flow (traffic density and velocities), directly relate to networking parameters (node degree and duration of communication). While existing research on these relations has mainly focused on simulative work or on the free-flow regime of traffic, we discuss these relations for both free-flow and congested traffic and provide an analytical framework for the computation of relevant networking parameters. We also discuss some results and analyze their impact on vehicular communications.","PeriodicalId":123266,"journal":{"name":"2010 IEEE Intelligent Vehicles Symposium","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129154247","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: 31
Efficient occupancy grid computation on the GPU with lidar and radar for road boundary detection 基于GPU的高效占用网格计算与激光雷达和雷达的道路边界检测
2010 IEEE Intelligent Vehicles Symposium Pub Date : 2010-06-21 DOI: 10.1109/IVS.2010.5548091
Florian Homm, N. Kaempchen, Jeffrey M. Ota, Darius Burschka
{"title":"Efficient occupancy grid computation on the GPU with lidar and radar for road boundary detection","authors":"Florian Homm, N. Kaempchen, Jeffrey M. Ota, Darius Burschka","doi":"10.1109/IVS.2010.5548091","DOIUrl":"https://doi.org/10.1109/IVS.2010.5548091","url":null,"abstract":"Accurate maps of the static environment are essential for many advanced driver-assistance systems. A new method for the fast computation of occupancy grid maps with laser range-finders and radar sensors is proposed. The approach utilizes the Graphics Processing Unit to overcome the limitations of classical occupancy grid computation in automotive environments. It is possible to generate highly accurate grid maps in just a few milliseconds without the loss of sensor precision. Moreover, in the case of a lower resolution radar sensor it is shown that it is suitable to apply super-resolution algorithms to achieve the accuracy of a higher resolution laser-scanner. Finally, a novel histogram based approach for road boundary detection with lidar and radar sensors is presented.","PeriodicalId":123266,"journal":{"name":"2010 IEEE Intelligent Vehicles Symposium","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125285739","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: 133
Validation and benchmarking for pedestrian video detection based on a sensors simulation platform 基于传感器仿真平台的行人视频检测验证与基准测试
2010 IEEE Intelligent Vehicles Symposium Pub Date : 2010-06-21 DOI: 10.1109/IVS.2010.5548031
J. Bossu, D. Gruyer, Jean-Christophe Smal, J. Blosseville
{"title":"Validation and benchmarking for pedestrian video detection based on a sensors simulation platform","authors":"J. Bossu, D. Gruyer, Jean-Christophe Smal, J. Blosseville","doi":"10.1109/IVS.2010.5548031","DOIUrl":"https://doi.org/10.1109/IVS.2010.5548031","url":null,"abstract":"The evaluation stage is an important part in the validation of ADAS robustness. Moreover, the control and the repetitiveness of the experimentations were very difficult to conduct on real road due to safety reasons. Moreover, the lack of data/sensors or the complexity of the experiment are often very penalizing for a correct and exhaustive evaluation.","PeriodicalId":123266,"journal":{"name":"2010 IEEE Intelligent Vehicles Symposium","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128782979","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: 5
LIDAR-based road and road-edge detection 基于激光雷达的道路和道路边缘检测
2010 IEEE Intelligent Vehicles Symposium Pub Date : 2010-06-21 DOI: 10.1109/IVS.2010.5548134
Wende Zhang
{"title":"LIDAR-based road and road-edge detection","authors":"Wende Zhang","doi":"10.1109/IVS.2010.5548134","DOIUrl":"https://doi.org/10.1109/IVS.2010.5548134","url":null,"abstract":"In this paper, a LIDAR-based road and road-edge detection method is proposed to identify road regions and road-edges, which is an essential component of autonomous vehicles. LIDAR range data is decomposed into signals in elevation and signals projected on the ground plane. First, the elevation-based signals are processed by filtering techniques to identify the road candidate region, and by pattern recognition techniques to determine whether the candidate region is a road segment. Then, the line representation of the projected signals on the ground plane is identified and compared to a simple road model in the top-down view to determine whether the candidate region is a road segment with its road-edges. The proposed method provides fast processing speed and reliable detection performance of road and road-edge detection. The proposed framework has been verified through the DARPA Urban Challenge to show its robustness and efficiency on the winning entry Boss vehicle.","PeriodicalId":123266,"journal":{"name":"2010 IEEE Intelligent Vehicles Symposium","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128639987","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: 163
Pedestrian recognition based on hierarchical codebook of SURF features in visible and infrared images 基于可见和红外图像SURF特征分层码本的行人识别
2010 IEEE Intelligent Vehicles Symposium Pub Date : 2010-06-21 DOI: 10.1109/IVS.2010.5547965
B. Besbes, A. Rogozan, A. Bensrhair
{"title":"Pedestrian recognition based on hierarchical codebook of SURF features in visible and infrared images","authors":"B. Besbes, A. Rogozan, A. Bensrhair","doi":"10.1109/IVS.2010.5547965","DOIUrl":"https://doi.org/10.1109/IVS.2010.5547965","url":null,"abstract":"One of the main challenges in Intelligent Vehicle is recognition of road obstacles. Our goal is to design a real-time, precise and robust pedestrian recognition system. We choose to use Speeded Up Robust Features (SURF) and a Support Vector Machine (SVM) classifier in order to perform the recognition task. Our main contribution is a method for fast computation of discriminative features for pedestrian recognition. Fast features extraction is assured by using a hierarchical codebook of scale and rotation-invariant SURF features. We evaluate our approach for pedestrian recognition in a set of images where people occur at different scales and in difficult recognition situations. The system shows good performance in visible and especially in infrared images. Besides, experimental results show that the hierarchical structure presents a major interest not only for maintaining a reasonable feature extraction time, but also for improving classification results.","PeriodicalId":123266,"journal":{"name":"2010 IEEE Intelligent Vehicles Symposium","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127638593","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
Vehicle tracking and motion prediction in complex urban scenarios 复杂城市场景下的车辆跟踪与运动预测
2010 IEEE Intelligent Vehicles Symposium Pub Date : 2010-06-21 DOI: 10.1109/IVS.2010.5548014
Christoph Hermes, Julian Einhaus, Markus Hahn, C. Wöhler, F. Kummert
{"title":"Vehicle tracking and motion prediction in complex urban scenarios","authors":"Christoph Hermes, Julian Einhaus, Markus Hahn, C. Wöhler, F. Kummert","doi":"10.1109/IVS.2010.5548014","DOIUrl":"https://doi.org/10.1109/IVS.2010.5548014","url":null,"abstract":"The recognition of potentially hazardous situations on road intersections is an indispensable skill of future driver assistance systems. In this context, this study focuses on the task of vehicle tracking in combination with a long-term motion prediction (1-2 s into the future) in a dynamic scenario. A motion-attributed stereo point cloud obtained using computationally efficient feature-based methods represents the scene, relying on images of a stereo camera system mounted on a vehicle. A two-stage mean-shift algorithm is used for detection and tracking of the traffic participants. A hierarchical setup depending on the history of the tracked object is applied for prediction. This includes prediction by optical flow, a standard kinematic prediction, and a particle filter based motion pattern method relying on learned object trajectories. The evaluation shows that the proposed system is able to track the road users in a stable manner and predict their positions at least one order of magnitude more accurately than a standard kinematic prediction method.","PeriodicalId":123266,"journal":{"name":"2010 IEEE Intelligent Vehicles Symposium","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121077459","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: 55
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