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Intelligent Transportation Systems, IEEE Transactions on

Issue 4 • Date Dec. 2007

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Displaying Results 1 - 19 of 19
  • Table of contents

    Page(s): C1
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    Freely Available from IEEE
  • IEEE Transactions on Intelligent Transportation Systems publication information

    Page(s): C2
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    Freely Available from IEEE
  • Information Service Architecture for International Multimodal Logistic Corridor

    Page(s): 565 - 574
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1096 KB) |  | HTML iconHTML  

    This paper describes how an information service architecture was developed for the international multimodal logistic corridor Pol-Corridor. It describes how the information services needed by Pol-Corridor were identified and how these service needs were transformed into system component requirements. An analysis was carried out to investigate how existing off-the-shelf and already-operational systems can fulfil these information needs by ldquomappingrdquo several information systems into the service architecture. The theory and trends in the research of software architectures are discussed in order to explain the foundation for defining the service architecture for Pol-Corridor. European Union policies concerning interoperability of technical systems in international transport, as well as their efficiency, are also discussed in this paper. View full abstract»

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  • A Dynamic Network Loading Model for Traffic Dynamics Modeling

    Page(s): 575 - 583
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (244 KB) |  | HTML iconHTML  

    The need for a better representation of traffic dynamics and the reproduction of traffic flow motion on the network have been the main reasons to seek solutions for dynamic network loading (DNL) models. In this paper, a neural network (NN) approximator that supports the DNL model is utilized to model link flow dynamics on a sample network. The presented DNL model is constructed with a linear travel time function for link performances and an algorithm written with a set of rules considering the constraints of link dynamics, flow conservation, flow propagation, and boundary conditions. Each of the three selected NN methods, i.e., feedforward back-propagation NN, radial basis function NN, and generalized regression NN, is utilized in the integrated model structure in order to determine the most appropriate one, and hence, three DNL processes are simulated. Traffic dynamics such as inflow rates, outflow rates, and delays are selected to evaluate the performance of the proposed model. View full abstract»

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  • PATH at 20—History and Major Milestones

    Page(s): 584 - 592
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (547 KB) |  | HTML iconHTML  

    The California partners for advanced transit and highways (PATH) program was founded in 1986, as the first research program in North America focused on the subject now known as intelligent transportation systems (ITS). This paper reviews the history of the founding of PATH and of the national ITS program in the U.S., providing perspective on the changes that have occurred during the past 20 years. View full abstract»

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  • Modeling and Recognition of Driving Behavior Based on Stochastic Switched ARX Model

    Page(s): 593 - 606
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1961 KB) |  | HTML iconHTML  

    This paper presents the development of the modeling and recognition of human driving behavior based on a stochastic switched autoregressive exogenous (SS-ARX) model. First, a parameter estimation algorithm for the SS-ARX model with multiple measured input-output sequences is developed based on the expectation-maximization algorithm. This can be achieved by extending the parameter estimation technique for the conventional hidden Markov model. Second, the developed parameter estimation algorithm is applied to driving data with the focus being on driver's collision avoidance behavior. The driving data were collected using a driving simulator based on the cave automatic virtual environment, which is a stereoscopic immersive virtual reality system. Then, the parameter set for each driver is obtained, and certain driving characteristics are identified from the viewpoint of switched control mechanism. Finally, the performance of the SS-ARX model as a behavior recognizer is examined. The results show that the SS-ARX model holds remarkable potential to function as a behavior recognizer. View full abstract»

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  • Off-Road Path and Obstacle Detection Using Decision Networks and Stereo Vision

    Page(s): 607 - 618
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1356 KB) |  | HTML iconHTML  

    Autonomous driving in off-road environments requires an exceptionally capable sensor system, particularly given that the unstructured environment does not provide many of the cues available in on-road environments. This paper presents a complex vision system, which is able to provide the two basic sensorial capabilities needed by autonomous vehicle navigation in extreme environments: obstacle detection and path detection. A variable-width-baseline (up to 1.5 m) single-frame stereo system is used for pitch estimation and obstacle detection, whereas a decision-network approach is used to detect the drivable path by a monocular vision system. The system has been field tested on the TerraMax vehicle, which is one of the only five vehicles to complete the 2005 Defense Advanced Research Projects Agency (DARPA) Grand Challenge course. View full abstract»

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  • On Color-, Infrared-, and Multimodal-Stereo Approaches to Pedestrian Detection

    Page(s): 619 - 629
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1355 KB) |  | HTML iconHTML  

    This paper presents an analysis of color-, infrared-, and multimodal-stereo approaches to pedestrian detection. We design a four-camera experimental testbed consisting of two color and two infrared cameras for capturing and analyzing various configuration permutations for pedestrian detection. We incorporate this four-camera system in a test vehicle and conduct comparative experiments of stereo-based approaches to obstacle detection using unimodal color and infrared imageries. A detailed analysis of the color and infrared features used to classify detected obstacles into pedestrian regions is used to motivate the development of a multimodal solution to pedestrian detection. We propose a multimodal trifocal framework consisting of a stereo pair of color cameras coupled with an infrared camera. We use this framework to combine multimodal-image features for pedestrian detection and to demonstrate that the detection performance is significantly higher when color, disparity, and infrared features are used together. This result motivates experiments and discussion toward achieving multimodal-feature combination using a single color and a single infrared camera arranged in a cross-spectral stereo pair. We demonstrate an approach to registering multiple objects across modalities and provide an experimental analysis that highlights issues and challenges of pursuing the cross-spectral approach to multimodal and multiperspective pedestrian analysis. View full abstract»

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  • Characterizing Driver Behavior on Signalized Intersection Approaches at the Onset of a Yellow-Phase Trigger

    Page(s): 630 - 640
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (777 KB) |  | HTML iconHTML  

    This paper involves a field test on 60 test participants to characterize driver behavior (perception-reaction time (PRT) and stopping/running decisions) at the onset of a yellow phase. Driver behavior is analyzed for five trigger distances that are measured from the vehicle position at the start of the yellow indication to the stop bar. This paper demonstrates that the 1.0-s 85th-percentile PRT that is recommended in traffic-signal-design procedures is valid and consistent with the field observations. Furthermore, this paper clearly shows that brake PRTs are impacted by the vehicle's time to intersection (TTI) at the onset of a yellow-indication introduction. This paper also demonstrates that either a lognormal or a beta distribution is sufficient to model the stochastic nature of the brake PRT. In terms of stopping decisions, this paper demonstrates that the probability of stopping varies from 100% at a TTI of 5.5 s to 9% at a TTI of 1.6 s. This paper also indicates a decrease in the probability of stopping for male drivers when compared with female drivers. Furthermore, this study suggests that drivers 65 years of age and older are significantly less likely to clear the intersection at short yellow-indication trigger distances when compared with other age groups. The dilemma zone for the less than 40 year old group is found to range from 3.9 to 1.85 s, whereas the dilemma zone for the greater than 70 year old group is found to range from 3.2 to 1.5 s. View full abstract»

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  • Markov-Based Lane Positioning Using Intervehicle Communication

    Page(s): 641 - 650
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (922 KB) |  | HTML iconHTML  

    The majority of today's navigation techniques for intelligent transportation systems use global positioning systems (GPS) that can provide position information with bounded errors. However, due to the low accuracy that is experienced with standard GPS, it is difficult to determine a vehicle's position at lane level. Using a Markov-based approach based on sharing information among a group of vehicles that are traveling within communication range, the lane positions of vehicles can be found. The algorithm's effectiveness is shown in both simulations and experiments with real data. View full abstract»

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  • Online Extrinsic Parameters Calibration for Stereovision Systems Used in Far-Range Detection Vehicle Applications

    Page(s): 651 - 660
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (925 KB) |  | HTML iconHTML  

    This paper presents a high-accuracy online calibration method for the absolute extrinsic parameters of a stereovision system that is suited for far-distance, vision-based vehicle applications. The method uses as prior knowledge the intrinsic parameters and the relative extrinsic parameters (relative position and orientation) of the two cameras, which are calibrated using offline procedures. These parameters remain unchanged if the two cameras are mounted on a rigid frame (stereo rig). The absolute extrinsic parameters define the position and orientation of the stereo system relative to a world coordinate system. They must be calibrated every time after mounting the stereo rig in the vehicle and are subject to changes due to static load factors for the used car setup. The proposed method is able to perform online the estimation of the absolute extrinsic parameters by driving the car on a flat and straight road, parallel with the longitudinal lane markers. The edge points of the longitudinal lane markers are extracted after a 2-D image classification process and reconstructed by stereovision in the stereo-rig coordinate system. After filtering out the noisy 3-D points, the normal vectors of the world coordinate system axes are estimated in the stereo-rig coordinate system by 3-D data fitting. The output of the method is the height and the orientation of the stereo cameras that are relative to the world coordinate system. View full abstract»

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  • Nonlinear Kalman Filtering Algorithms for On-Line Calibration of Dynamic Traffic Assignment Models

    Page(s): 661 - 670
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (365 KB) |  | HTML iconHTML  

    An online calibration approach that jointly estimates demand and supply parameters of dynamic traffic assignment (DTA) systems is presented and empirically validated through an extensive application. The problem can be formulated as a nonlinear state-space model. Because of its nonlinear nature, the resulting model cannot be solved by the Kalman filter, and therefore, nonlinear extensions need to be considered. The following three extensions to the Kalman filtering algorithm are presented: 1) the extended Kalman filter (EKF); 2) the limiting EKF (LimEKF); and 3) the unscented Kalman filter. The solution algorithms are applied to the on-line calibration of the state-of-the-art DynaMIT DTA model, and their use is demonstrated in a freeway network in Southampton, U.K. The LimEKF shows accuracy that is comparable to that of the best algorithm but with vastly superior computational performance. The robustness of the approach to varying weather conditions is demonstrated, and practical aspects are discussed. View full abstract»

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  • Variable Speed Limits: Safety and Operational Impacts of a Candidate Control Strategy for Freeway Applications

    Page(s): 671 - 680
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (676 KB) |  | HTML iconHTML  

    Variable-speed limit sign (VSLS) systems enable transportation managers to dynamically change the posted speed limit in response to prevailing traffic and/or weather conditions. Although VSLSs have been implemented in a limited number of jurisdictions throughout the world, there is currently very limited documentation that describes quantitative safety and operational impacts. Furthermore, the impacts reported are primarily from systems in Europe and may not be directly transferable to other jurisdictions such as North America. This paper presents the results of an evaluation of a candidate VSLS system for an urban freeway in Toronto, ON, Canada. The evaluation was conducted using a microscopic simulation model combined with a categorical crash potential model for estimating safety impacts. View full abstract»

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  • Vehicle-Component Identification Based on Multiscale Textural Couriers

    Page(s): 681 - 694
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2328 KB) |  | HTML iconHTML  

    This paper presents a novel method for identifying vehicle components in a monocular traffic image sequence. In the proposed method, the vehicles are first divided into multiscale regions based on the center of gravity of the foreground vehicle mask and the calibrated-camera parameters. With these multiscale regions, textural couriers are generated based on the localized variances of the foreground vehicle image. A new scale-space model is subsequently created based on the textural couriers to provide a topological structure of the vehicle. In this model, key feature points of the vehicle can significantly be described based on the topological structure to determine the regions that are homogenous in texture from which vehicle components can be identified by segmenting the key feature points. Since no motion information is required in order to segment the vehicles prior to recognition, the proposed system can be used in situations where extensive observation time is not available or motion information is unreliable. This novel method can be used in real-world systems such as vehicle-shape reconstruction, vehicle classification, and vehicle recognition. This method was demonstrated and tested on 200 different vehicle samples captured in routine outdoor traffic images and achieved an average error rate of 6.8% with a variety of vehicles and traffic scenes. View full abstract»

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  • 2007 Index IEEE Transactions on Intelligent Transportation Systems Vol. 8

    Page(s): 695 - 702
    Save to Project icon | Request Permissions | PDF file iconPDF (113 KB)  
    Freely Available from IEEE
  • Special Issue on the DARPA Urban Challenge Autonomous Vehicle Competition

    Page(s): 703
    Save to Project icon | Request Permissions | PDF file iconPDF (163 KB)  
    Freely Available from IEEE
  • IEEE ITSS Best Ph.D. Dissertation Award

    Page(s): 704
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    Freely Available from IEEE
  • IEEE Intelligent Transportation Systems Society Information

    Page(s): C3
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    Freely Available from IEEE
  • IEEE Transactions on Intelligent Transportation Systems Information for authors

    Page(s): C4
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    Freely Available from IEEE

Aims & Scope

The IEEE Transactions on ITS is concerned with the design, analysis, and control of information technology as it is applied to transportation systems. The IEEE ITS Transactions is focused on the numerous technical aspects of ITS technologies spanned by the IEEE. Transportation systems are invariably complex, and their complexity arises from many sources. Transportation systems can involve humans, vehicles, shipments, information technology, and the physical infrastructure, all interacting in complex ways. Many aspects of transportation systems are uncertain, dynamic and nonlinear, and such systems may be highly sensitive to perturbations. Controls can involve multiple agents that (and/or who) are distributed and hierarchical. Humans who invariably play critical roles in a transportation system have a diversity of objectives and a wide range of skills and education. Transportation systems are usually large-scale in nature and are invariably geographically distributed.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Fei-Yue Wang
Professor
University of Arizona