{"title":"Driver Braking Behavior during Intersection Approaches and Implications for Warning Strategies for Driver Assistant Systems","authors":"H. Berndt, S. Wender, K. Dietmayer","doi":"10.1109/IVS.2007.4290122","DOIUrl":"https://doi.org/10.1109/IVS.2007.4290122","url":null,"abstract":"Data from vehicles approaching an intersection during a red-light phase has been recorded by measuring real traffic in urban areas. Using a laser scanner based tracking system, vehicle velocities during approaches to the red light have been estimated and various metadata (such as object class, distance to the intersection when the traffic light turned from green to orange and weather data) has been collected. The experimental setup is validated using a Real-Time Kinematic (RTK) GPS system. The resulting information can be used when designing warning strategies for Advanced Driver Assistant Systems (ADAS). Examples of a warning strategy estimation for a misinterpretation of the traffic situation for both the host vehicle's driver as well as other drivers endangering the host vehicle are presented.","PeriodicalId":190903,"journal":{"name":"2007 IEEE Intelligent Vehicles Symposium","volume":"130 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115294581","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. Tsugawa, S. Kato, N. Hashimoto, N. Minobe, M. Kawai
{"title":"Elderly Driver Assistance Systems with Cooperation between Vehicles: the Concept and Experiments","authors":"S. Tsugawa, S. Kato, N. Hashimoto, N. Minobe, M. Kawai","doi":"10.1109/IVS.2007.4290193","DOIUrl":"https://doi.org/10.1109/IVS.2007.4290193","url":null,"abstract":"This paper proposes a new concept of elderly driver assistance systems, which performs the assistance by the cooperative driving between two vehicles, and describes some experiments with elderly drivers. The assistance consists of one vehicle driven by an elderly driver called a guest vehicle and the other driven by a assisting driver called a host vehicle, and the host vehicle assists or escorts the guest vehicle through the inter-vehicle communications. The functions of the systems installed on a single-seat electric vehicle are highly evaluated by subjects of elderly drivers in virtual streets on a test track.","PeriodicalId":190903,"journal":{"name":"2007 IEEE Intelligent Vehicles Symposium","volume":"646 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115830621","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":"Congestion Prediction based on NexRad Radar with Application to In-vehicle Information","authors":"D. Dailey","doi":"10.1109/IVS.2007.4290297","DOIUrl":"https://doi.org/10.1109/IVS.2007.4290297","url":null,"abstract":"This paper develops a quantitative relationship between Nexrad radar reflectivity and surface traffic conditions. Data from two data mines on the University of Washington campus are combined to evaluate the quantitative relationship between freeway speed reduction and rain fall rate as measured by Doppler radar. Radar data are converted into rainfall rates and speed data from the inductance loop speed traps are converted into a deviations from a normal performance measure. The deviation from normal and the rainfall rate are used to construct an impulse response function that can be applied to radar measurements to predict traffic speed reduction. These data can then be made available in-vehicle as a new form of real-time traveler information.","PeriodicalId":190903,"journal":{"name":"2007 IEEE Intelligent Vehicles Symposium","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124273357","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":"The Obstacle Detection Method using Optical Flow Estimation at the Edge Image","authors":"T. Naito, T. Ito, Y. Kaneda","doi":"10.1109/IVS.2007.4290217","DOIUrl":"https://doi.org/10.1109/IVS.2007.4290217","url":null,"abstract":"The purpose of this study is to develop an algorithm for the detection of the obstacle ahead of a host vehicle by image processing using a monocular onboard camera, and to show that this algorithm is able to apply the prevention of the collision accident. It can be supposed that there is some important information on the edge of the image. In this paper we show an obstacle detection method by extracting optical flow along the edge of the image, and estimated result of the three dimensional (3D) information in the world coordinate system from the optical flow.","PeriodicalId":190903,"journal":{"name":"2007 IEEE Intelligent Vehicles Symposium","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116693489","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":"State of Intelligent Vehicle Research/Deployment around the World","authors":"U. Ozguner","doi":"10.1109/IVS.2007.4290070","DOIUrl":"https://doi.org/10.1109/IVS.2007.4290070","url":null,"abstract":"Umit Ozguner is Professor of Electrical and Computer Engineering at the Ohio State University and holds the T.R.C. Inc. Chair on Intelligent Transportation Research. His areas of research interest are in intelligent mobile systems, decentralization and autonomy issues, applied automotive control and ITS. Professor Ozguner was the first President of the IEEE ITS Council. He participated in the organization of many conferences and was the Program Chair for the 1997 IEEE ITS Conference, the General Chair of the 2002 IEEE CDC in Las Vegas and the 2003 IEEE IV Symposium. The team he coordinated participated successfully in the 1997 Automated Highway Demonstration in San Diego (Demo'97), where they demonstrated 3 fully automated cars doing lane-keeping, convoying and passing using radar and vision based guidance. He has recently been working on airborne detection and tracking of mobile ground based systems for both military and civilian applications. His team also recently developed the autonomous off road truck TerraMax, which participated in the 2004 DARPA Grand Challenge.","PeriodicalId":190903,"journal":{"name":"2007 IEEE Intelligent Vehicles Symposium","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121066800","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":"A Real-Time-capable Hard-and Software Architecture for Joint Image and Knowledge Processing in Cognitive Automobiles","authors":"M. Goebl, G. Färber","doi":"10.1109/IVS.2007.4290204","DOIUrl":"https://doi.org/10.1109/IVS.2007.4290204","url":null,"abstract":"Cognitive automobiles consist of a set of algorithms that cover a wide range of processing levels: from low-level image acquisition and feature extraction up to situation assessment and decision making. The modules implementing them are naturally characterized by decreasing data rates at higher levels, because raw data is discarded after evaluation, and increasing processing intervals, as knowledge based levels require longer computation times. The architecture presented in this papers offers a method to interchange information with different temporal resolutions liberally among modules with distinct cycle times and realtime demands. It allows effortless buffering of raw data for subsequent data fusion and verification, facilitating innovative processing structures. The paper is completed by measurements demonstrating the achieved real-time capabilities on our selected hardware architecture.","PeriodicalId":190903,"journal":{"name":"2007 IEEE Intelligent Vehicles Symposium","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127267106","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":"Light Stripe Projection based Parking Space Detection for Intelligent Parking Assist System","authors":"H. Jung, Dong Suk Kim, P. Yoon, J. Kim","doi":"10.1109/IVS.2007.4290241","DOIUrl":"https://doi.org/10.1109/IVS.2007.4290241","url":null,"abstract":"This paper proposes a novel light stripe projection based free parking space recognition method in order to overcome the common drawbacks of existing vision based target parking position designation methods in dark indoor parking site. 3D information of parking site is recognized by light stripe projection method. By analyzing the 3D information, system can recognize discontinuous points, pivot, and opposite-site reference point. Experiments show that the proposed method can successfully designate target position in spite of dark illumination condition and the black reflective surface of vehicle. Furthermore, because the proposed method can be implemented just by adding a low-cost light plane projector, it is economically practical solution.","PeriodicalId":190903,"journal":{"name":"2007 IEEE Intelligent Vehicles Symposium","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127459709","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":"A disturbance response decoupling controller for emulating vertical dynamics of vehicles","authors":"C. Villegas, D. Leith, R. Shorten, J. Kalkkuhl","doi":"10.1109/IVS.2007.4290227","DOIUrl":"https://doi.org/10.1109/IVS.2007.4290227","url":null,"abstract":"Vehicle emulation applications motivate the need for active suspension systems that not only isolate the cabin and its passengers from road disturbances, but also track desired roll dynamics. In this paper we present a novel control structure for achieving this objective and present an initial evaluation of its performance.","PeriodicalId":190903,"journal":{"name":"2007 IEEE Intelligent Vehicles Symposium","volume":"96 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123292278","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}
Philipp Woock, F. Pagel, Michael Grinberg, D. Willersinn
{"title":"Odometry-Based Structure from Motion","authors":"Philipp Woock, F. Pagel, Michael Grinberg, D. Willersinn","doi":"10.1109/IVS.2007.4290266","DOIUrl":"https://doi.org/10.1109/IVS.2007.4290266","url":null,"abstract":"Structure from motion refers to a technique to obtain 3D information from consecutive images taken with a moving monocular camera. In order to do this, the camera motion performed between two consecutive images needs to be known. In the work reported in this contribution, we investigated the precision of the odometry data of a commercially available passenger car. In order to identify the required precision, we developed an error model based on camera parameters and the bicycle model. We investigated two options, both being based on speed measurements. The first one uses steering angle measurements, the second one uses measurements of the yaw rate. Concluding, we found out that the specified precision of all odometry data available is sufficient to solve structure from motion. Long-term measurements empirically confirm the precision values given in the specification. This result encouraged us to actually implement a structure-from-motion approach which yields depth information as predicted from the theoretical considerations. Further work needs to be carried out in order to compensate for roll motions.","PeriodicalId":190903,"journal":{"name":"2007 IEEE Intelligent Vehicles Symposium","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116243252","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}
Jun Hong, Xuedan Zhang, Zhong Wei, Li Li, Yong Ren
{"title":"Spatial and Temporal Analysis of Probe Vehicle-based Sampling for Real-time Traffic Information System","authors":"Jun Hong, Xuedan Zhang, Zhong Wei, Li Li, Yong Ren","doi":"10.1109/IVS.2007.4290287","DOIUrl":"https://doi.org/10.1109/IVS.2007.4290287","url":null,"abstract":"Using vehicles as probes is a flexible and low-cost way to obtain real-time traffic information. This paper addresses the sampling issues of using probe vehicles for detecting traffic information in a road network. A spatial and temporal analysis model based on signal processing theory is established and used to derive bounds on the sampling period, transmitting period and sample sizes of probe vehicles. We also develop a traffic & information-collecting simulation platform (TISP), to simulate the traffic flows in a road network and generate probe vehicle data for analysis. The simulation results find that traffic flow has strong correlation in terms of time and space, which is critical to the sampling problem, and the system requires 2% probe penetration to guarantee the information integrity.","PeriodicalId":190903,"journal":{"name":"2007 IEEE Intelligent Vehicles Symposium","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122808482","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}