{"title":"3D triangulation based extrinsic calibration between a stereo vision system and a LIDAR","authors":"You Li, Y. Ruichek, C. Cappelle","doi":"10.1109/ITSC.2011.6082899","DOIUrl":"https://doi.org/10.1109/ITSC.2011.6082899","url":null,"abstract":"This paper presents a novel extrinsic calibration algorithm between a binocular stereo vision system and a 2D LIDAR (laser range finder). Extrinsic calibration of these heterogeneous sensors is required to fuse information obtained separately by vision sensor and LIDAR in the context of intelligent vehicle. By placing a planar chessboard at different positions and orientations in front of the sensors, the proposed method solves the problem based on 3D reconstruction of the chessboard and geometric constraints between views from the stereovision system and the LIDAR. The three principle steps of the approach are: 3D corner points triangulation, 3D plane least-squares estimation, solving extrinsic parameters by applying a non-linear optimization algorithm based on the geometric constraints. To evaluate the performance of the algorithm, experiments based on computer simulation and real data are performed. The proposed approach is also compared with a popular calibration method to show its advantages.","PeriodicalId":186596,"journal":{"name":"2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC)","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131791161","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":"Joint maximum-likelihood estimation of speed and acceleration from existing roadway vehicle detectors","authors":"J. Ernst, J. Krogmeier, D. Bullock","doi":"10.1109/ITSC.2011.6082861","DOIUrl":"https://doi.org/10.1109/ITSC.2011.6082861","url":null,"abstract":"Transportation agencies have invested in extensive infrastructure for vehicle detection and speed estimation. It is of interest to measure vehicle accelerations at an intersection to evaluate the impact of traffic signal control on energy, emissions and safety. This paper explains how to use inductive loops and magnetometers in speed trap configurations to measure acceleration in addition to speed and develops an algorithm for doing so. The algorithm was tested using approximately 7,000 vehicles and a GPS probe vehicle was used to provide ground truth. It was found that the root mean squared error (RMSE) between GPS and algorithm estimates is approximately 0.04g.","PeriodicalId":186596,"journal":{"name":"2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC)","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133047731","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 contour classifying Kalman filter based on evidence theory","authors":"S. Ohl, M. Maurer","doi":"10.1109/ITSC.2011.6082816","DOIUrl":"https://doi.org/10.1109/ITSC.2011.6082816","url":null,"abstract":"In the project Stadtpilot, introduced in [1], the object based environment perception system developed by the urban challenge team CarOLO at Technische Universita¨t Braunschweig, as presented in [2], has been enhanced. The context of this new project is more challenging as now because it includes public traffic on large inner-city loops. Other vehicles are described by the project's sensor data fusion by an open polyline (contour) with many points. Some of these points lie on straight lines or they represent noise of the contour which do not contribute to the object's description. These extra points complicate an effective tracking and deform the contour of the object hypothesis. Because of the numerous traffic and due to the change in the environment's type, surrounded vehicles very often create a change of view. This results in no or less measurement updates of some points in the contour and can result in its deformation. In an effort to overcome this problem, the contour estimating Kalman filter, presented in [3], has been enhanced by improved point update algorithms as well as a contour classifier based upon evidence theory. These enhancements allow the decrease of the used points. Changes of view, due to passing traffic, are better identified because the classifier identifies the most likely shape explicitly.","PeriodicalId":186596,"journal":{"name":"2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC)","volume":"1 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133673725","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":"On-board wireless sensor for collision avoidance: Vehicle and pedestrian detection at intersection","authors":"Shoma Hisaka, S. Kamijo","doi":"10.1109/ITSC.2011.6082853","DOIUrl":"https://doi.org/10.1109/ITSC.2011.6082853","url":null,"abstract":"In this paper, a dedicated on-board ‘sensor’ utilizing wireless communication devices was developed for the collision avoidance around intersection. Four wireless receivers of Zigbee are installed in the four corners of the driver's vehicle. Each receiver is shielded and has slightly directivity. These effects enable ‘sensor’ to estimate positions of transmitters, which is brought by pedestrians, bicycles, motor cycles, and vehicles based on comparison of four signal strength of four receivers. Positions are obtained relative to the driver's vehicle as combinations of four directions, near or far, and approaching or leaving. Since the estimation algorithm is focusing on relative values among four wireless receivers, the detection results should not be affected by the transmission power. On-board sensors utilizing vision, LIDAR and radar cannot detect objects hidden by road facilities and other vehicle. Although infrastructure sensors for Vehicle-to-Infrastructure cooperative systems can detect such the hidden objects, they are much expensive than on-board sensors. The on-board wireless ‘sensor’ developed in this paper would be an alternative method for the collision avoidance around intersections.","PeriodicalId":186596,"journal":{"name":"2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132764197","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":"Tactical driver behavior prediction and intent inference: A review","authors":"A. Doshi, M. Trivedi","doi":"10.1109/ITSC.2011.6083128","DOIUrl":"https://doi.org/10.1109/ITSC.2011.6083128","url":null,"abstract":"Drawing upon fundamental research in human behavior prediction, recently there has been a research focus on how to predict driver behaviors. In this paper we review the field of driver behavior and intent prediction, with a specific focus on tactical maneuvers, as opposed to operational or strategic maneuvers. The aim of a driver behavior prediction system is to forecast the trajectory of the vehicle prior in real-time, which could allow a Driver Assistance System to compensate for dangerous or uncomfortable circumstances. This review provides insights into the scope of the problem, as well as the inputs, algorithms, performance metrics, and shortcomings in the state-of-the-art systems.","PeriodicalId":186596,"journal":{"name":"2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133775247","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 Lagrangian state-space representation of a macroscopic traffic flow model","authors":"T. Tchrakian, O. Verscheure","doi":"10.1109/ITSC.2011.6083063","DOIUrl":"https://doi.org/10.1109/ITSC.2011.6083063","url":null,"abstract":"We obtain a state space representation of a first order macroscopic model from a Godunov discretization of its Lagrangian reformulation. The resulting model comprises four linear regimes, each of which comes into effect for the appropriate traffic conditions using a simple switching mechanism. Unlike previous state space models of traffic flow, ours is trajectory-based as opposed to density/velocity-based, although the latter quantities are nevertheless computed during the running of the model. The Lagrangian (moving) coordinates in this scheme should provide an ideal framework for the assimilation of GPS location data from probe vehicles.","PeriodicalId":186596,"journal":{"name":"2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC)","volume":"167 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115432197","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}
Pietro Cerri, Giacomo Soprani, P. Zani, Jaewoong Choi, Junyung Lee, Dongwook Kim, K. Yi, A. Broggi
{"title":"Computer vision at the hyundai autonomous challenge","authors":"Pietro Cerri, Giacomo Soprani, P. Zani, Jaewoong Choi, Junyung Lee, Dongwook Kim, K. Yi, A. Broggi","doi":"10.1109/ITSC.2011.6082859","DOIUrl":"https://doi.org/10.1109/ITSC.2011.6082859","url":null,"abstract":"As interest on autonomous vehicles is growing worldwide, different approaches, based on different perception technologies and concepts, are being followed. This paper exposes the importance of the use of vision technology in most of these approaches, and presents the experience of the SNUCLE autonomous vehicle which successfully completed the Hyundai Autonomous Challenge in November 2010.","PeriodicalId":186596,"journal":{"name":"2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115602802","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":"Low complexity algorithm for the extraction of vehicular traffic variables","authors":"C. Francisco, F. Alejandro","doi":"10.1109/ITSC.2011.6083059","DOIUrl":"https://doi.org/10.1109/ITSC.2011.6083059","url":null,"abstract":"We present an alternative technique for acquisition of traffic variables, using less computer resources and less processing time, by using a computer vision algorithm that process only non redundant information. The algorithm allows estimating vehicular mean speed and vehicular volume in 2 or 3 lanes roads. It distinguishes vehicles from the background using a single line of the image and estimates the mean speed of the vehicles by using two lines of the image. This minimizes both, the quantity of information that has to be processed, and the total processing time. The algorithm also uses a spatio-temporal transformation, allowing more time for the detection process, therefore reducing hardware requirements.","PeriodicalId":186596,"journal":{"name":"2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC)","volume":"46 7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124321163","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}
Mohamed El Ansari, Abdenbi Mazoul, A. Bensrhair, G. Bebis
{"title":"A real-time spatio-temporal stereo matching for road applications","authors":"Mohamed El Ansari, Abdenbi Mazoul, A. Bensrhair, G. Bebis","doi":"10.1109/ITSC.2011.6082875","DOIUrl":"https://doi.org/10.1109/ITSC.2011.6082875","url":null,"abstract":"This paper presents a real-time approach for matching stereo images acquired by a stereo sensor embedded in a moving vehicle. The new method consists of matching edge points extracted from stereo images using the temporal relationship, which exists between consecutive stereo pairs. Matching a current stereo pair takes into account the matching results of the preceding stereo pair. The method looks first for what we call matching control edge points (MCEPs) based on spatio-temporal matching of edge curves of consecutive stereo pairs. Dynamic programming is considered for matching edge points of the stereo images. The MCEPs drive the optimal path of the dynamic programming. The proposed approach has been tested on virtual and real stereo image sequences and the results are satisfactory.","PeriodicalId":186596,"journal":{"name":"2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114443652","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":"Vehicle stability control using individual brake force based on tire force information","authors":"Hyundong Her, W. Cho, K. Yi","doi":"10.1109/ITSC.2011.6082997","DOIUrl":"https://doi.org/10.1109/ITSC.2011.6082997","url":null,"abstract":"Development of an Electronic Stability Control using individual brake force distribution based on tire force information was presented in this paper. The objective of the proposed ESC algorithm is to determine the individual brake forces to improve the performance of the controller. This ESC algorithm consists of an upper level controller and a lower level controller. The upper level controller calculates the desired yaw moment for satisfying the driver's intention. The lateral dynamic model can be more accurate by getting rid of the uncertainties caused by complex tire model. In the lower level controller, the individual braking forces are determined by the optimal strategy. The closed loop computer simulation results with driver-vehicle-controller system confirm the effectiveness of the proposed control system and the improvements in vehicle stability.","PeriodicalId":186596,"journal":{"name":"2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114892644","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}