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Intelligent Transportation Systems, IEEE Transactions on

Issue 1 • Date March 2005

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Displaying Results 1 - 18 of 18
  • Table of contents

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  • IEEE Transactions on Intelligent Transportation Systems publication information

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  • Geometric travel planning

    Page(s): 5 - 16
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1200 KB) |  | HTML iconHTML  

    This paper provides a novel approach for optimal route planning by making efficient use of the underlying geometrical structure. It combines classical artificial intelligence exploration with computational geometry. Given a set of global positioning system (GPS) trajectories, the input is refined by geometric filtering and rounding algorithms. For constructing the graph and the according point-localization structure, fast scan line and divide-and-conquer algorithms are applied. For speeding up the optimal online search algorithms, the geometrical structure of the inferred weighted graph is exploited in two ways; it is compressed while retaining the original information for unfolding resulting shortest paths and is then annotated by lower bounds and refined topographic information (for example, by the bounding boxes of all shortest paths that start with a given edge). Traffic disturbances can result in an increase in travel time for the affected area that, in turn, can affect the precomputed information. This paper discusses two models of introducing dynamics in a navigation system. The online planning system GPS-ROUTE implements the above techniques and provides a client-server web interface to answer a series of shortest-path or shortest-time queries. View full abstract»

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  • A stimulus-response model of day-to-day network dynamics

    Page(s): 17 - 25
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3376 KB) |  | HTML iconHTML  

    A general structure of stimulus-response formula is presented to specify the interacted network dynamics under the assumption of a daily learning and adaptive travel behavior. By taking the time derivative of system variable as a response term, the evolution is formulated as a dynamic system. Issues of existence, uniqueness, and stability for the proposed differential equations are briefly discussed. Approximation of a time-varying route-choice model is derived from the addressed path-flow dynamics. Threshold effects on path-flow dynamics are encapsulated into the proposed general structure by incorporating a discontinuous stimulus term. Then, the quasi user equilibrium is achieved when all users feel indifferent between the experienced and predicted travel time provided by intelligent transportation systems, i.e., the whole system dynamics stay within a bounded range. The derived quasi user equilibrium is reduced to Wardrop's user equilibrium as the threshold effects of path-flow dynamics vanish. View full abstract»

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  • Advanced traveler information system for Hyderabad City

    Page(s): 26 - 37
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (4432 KB) |  | HTML iconHTML  

    The advanced traveler information system (ATIS) is a type of intelligent transportation system application areas that implements emerging computer, communication, and information technologies to provide vital information to the users of a system regarding traffic regulation, route and location guidance, hazardous situations and safety advisory, and warning messages. ATIS requires a large amount of data for processing, analysis, and storage for effective dissemination of traveler information to users. A geographical information system (GIS) allows large data to be effectively processed, stored, analyzed, logically associated, and graphical displayed. Thus, GIS-based ATIS provides a convenient and powerful tool for storage and graphical representation of information, which can be useful users. Further, by availing the powerful GIS functionalities, a user can conceive a problem and allow the appropriate software to assist him in the decision-making process regarding optimum route selection and trip planning. In this paper, the authors present a GIS-based ATIS for Hyderabad City, India. Development of this GIS-based ATIS has been carried under the ArcView GIS environment. This user-friendly system provides comprehensive information about Hyderabad City, such as road networks, hospitals, government and private offices, stadiums, bus and railway stations, and tourist places within the city limits. This system can be used effectively in bus stations, railway stations, airports, and tourist information centers, as well as in personal computers to provide information to travelers and to facilitate travel. View full abstract»

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  • Traffic-incident detection-algorithm based on nonparametric regression

    Page(s): 38 - 42
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (632 KB) |  | HTML iconHTML  

    This paper proposes an improved nonparametric regression (INPR) algorithm for forecasting traffic flows and its application in automatic detection of traffic incidents. The INPRA is constructed based on the searching method of nearest neighbors for a traffic-state vector and its main advantage lies in forecasting through possible trends of traffic flows, instead of just current traffic states, as commonly used in previous forecasting algorithms. Various simulation results have indicated the viability and effectiveness of the proposed new algorithm. Several performance tests have been conducted using actual traffic data sets and results demonstrate that INPRs average absolute forecast errors, average relative forecast errors, and average computing times are the smallest comparing with other forecasting algorithms. View full abstract»

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  • Framework for real-time behavior interpretation from traffic video

    Page(s): 43 - 53
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1936 KB) |  | HTML iconHTML  

    Video-based surveillance systems have a wide range of applications for traffic monitoring, as they provide more information as compared to other sensors. In this paper, we present a rule-based framework for behavior and activity detection in traffic videos obtained from stationary video cameras. Moving targets are segmented from the images and tracked in real time. These are classified into different categories using a novel Bayesian network approach, which makes use of image features and image-sequence-based tracking results for robust classification. Tracking and classification results are used in a programmed context to analyze behavior. For behavior recognition, two types of interactions have mainly been considered. One is interaction between two or more mobile targets in the field of view (FoV) of the camera. The other is interaction between targets and stationary objects in the environment. The framework is based on two types of a priori information: 1) the contextual information of the camera's FoV, in terms of the different stationary objects in the scene and 2) sets of predefined behavior scenarios, which need to be analyzed in different contexts. The system can recognize behavior from videos and give a lexical output of the detected behavior. It also is capable of handling uncertainties that arise due to errors in visual signal processing. We demonstrate successful behavior recognition results for pedestrian-vehicle interaction and vehicle-checkpost interactions. View full abstract»

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  • Multilevel- and neural-network-based stereo-matching method for real-time obstacle detection using linear cameras

    Page(s): 54 - 62
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1024 KB) |  | HTML iconHTML  

    The focus of this paper is on real-time obstacle detection using linear stereo vision. This paper presents a multilevel neural method for matching edges extracted from stereo linear images. The method described performs edge stereo matching at different levels with a neural-network-based procedure. At each level, the process starts by selecting, in the left and right linear images, the most significant edges, i.e., those with the largest gradient magnitudes. The selected edges are then matched and the obtained pairs are used as reference pairs for matching less significant edges in the next level. In each level, the matching problem is formulated as an optimization task in which an objective function, representing the constraints on the solution, is minimized thanks to a Hopfield neural network. View full abstract»

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  • Pedestrian detection and tracking with night vision

    Page(s): 63 - 71
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3976 KB) |  | HTML iconHTML  

    This paper presents a method for pedestrian detection and tracking using a single night-vision video camera installed on the vehicle. To deal with the nonrigid nature of human appearance on the road, a two-step detection/tracking method is proposed. The detection phase is performed by a support vector machine (SVM) with size-normalized pedestrian candidates and the tracking phase is a combination of Kalman filter prediction and mean shift tracking. The detection phase is further strengthened by information obtained by a road-detection module that provides key information for pedestrian validation. Experimental comparisons (e.g., grayscale SVM recognition versus binary SVM recognition and entire-body detection versus upper-body detection) have been carried out to illustrate the feasibility of our approach. View full abstract»

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  • A new automatic extraction method of container identity codes

    Page(s): 72 - 78
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1744 KB) |  | HTML iconHTML  

    An automatic extraction method of container identity codes based on template matching is proposed. With different kinds of noises on the image, the container code can hardly be extracted. Initially, the container image is filtered with both adaptive linear and nonlinear filters in order to reduce noise so that the candidate text lines can be properly located. Then, a series of standard templates has been brought forward according to the standard align modes of the container identification (ID) codes. Finally, the align mode of each candidate text line is obtained and then matched with those standard templates and the container ID codes can be extracted automatically. Results show that this method can segment the container ID codes with high performance. View full abstract»

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  • Evaluation of ACC vehicles in mixed traffic: lane change effects and sensitivity analysis

    Page(s): 79 - 89
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (440 KB) |  | HTML iconHTML  

    Almost every automobile company is producing vehicles with adaptive cruise control (ACC) system onboard that enables a vehicle to do automatic vehicle following in the longitudinal direction. The ACC system is designed for driver's comfort and safety and to operate with manually driven vehicles. These characteristics of ACC were found to have beneficial effects on the environment and traffic flow characteristics by acting as filters of a wide class of traffic disturbances. It has been argued that the smooth response of ACC vehicles to high-acceleration disturbances or large position errors creates large gaps between the ACC vehicle and the vehicle ahead inviting cut-ins and therefore generating additional disturbances that would not have been created if all vehicles had been manually driven. In this paper, we examine the effect of lane changes on the benefits suggested by Bose and Ioannou as well as the sensitivity of these benefits with respect to various variables such as the penetration of the ACC vehicles, level of traffic disturbances etc. We demonstrate, using theory, simulations, and experiments, that during lane changes, the smoothness of the ACC vehicle response attenuates the disturbances introduced by a cut-in or an exiting vehicle in a way that is beneficial to the environment when compared with similar situations where all vehicles are manually driven. We concluded that a higher number of possible cut-ins that may occur due to the larger gaps created during high-acceleration maneuvers by the vehicle in front of the ACC vehicle, will not annul the benefits obtained in the absence of such cut-ins when compared with the situation of similar maneuvers but with no cut-ins in the case of 100% manually driven vehicles. View full abstract»

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  • Information dissemination in self-organizing intervehicle networks

    Page(s): 90 - 101
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    Intervehicle communication (IVC) is an emerging topic in research and application that is getting increasing attention from all major car manufacturers. In this paper, a novel method for scalable information dissemination in highly mobile ad hoc networks is proposed: segment-oriented data abstraction and dissemination (SODAD). With SODAD, information can be distributed in an information range multiple orders of magnitude larger than the transmission range of the air interface, even if only 1%-3% of all vehicles are equipped with an IVC system, e.g., during market introduction. By restricting the method to the dissemination of map/position-based data, scalability is achieved. In the second half of this paper, an example application for the SODAD method is presented: a self-organizing traffic-information system (SOTIS). In SOTIS, a car is equipped with a satellite navigation receiver, an IVC system, and a digital map. Each individual vehicle collects traffic information for its local area. Using the digital map, the traffic information is analyzed based on road segments. By distributing the information in the ad hoc intervehicle network using the SODAD method, a decentralized traffic information system is created. The performance of the proposed methods is evaluated using network simulation with vehicular mobility models. Simulation results for typical scenarios are presented. Furthermore, a prototype implementation based on commercially available standard hardware demonstrates the feasibility of the proposed approach. View full abstract»

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  • Optimal coordination of variable speed limits to suppress shock waves

    Page(s): 102 - 112
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (976 KB) |  | HTML iconHTML  

    When freeway traffic is dense, shock waves may appear. These shock waves result in longer travel times and in sudden large variations in the speeds of the vehicles, which could lead to unsafe situations. Dynamic speed limits can be used to eliminate or at least to reduce the effects of shock waves. However, coordination of the variable speed limits is necessary in order to prevent the occurrence of new shock waves and/or a negative impact on the traffic flows in other locations. In this paper, we present a model predictive control approach to optimally coordinate variable speed limits for freeway traffic with the aim of suppressing shock waves. First, we optimize continuous valued speed limits, such that the total travel time is minimal. Next, we include a safety constraint that prevents drivers from encountering speed limit drops larger than, e.g., 10 km/h. Furthermore, to get a better correspondence between the computed and applied control signals, we also consider discrete speed limits. We illustrate our approach with a benchmark problem. View full abstract»

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  • Motion generation and adaptive control method of automated guided vehicles in road following

    Page(s): 113 - 123
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (768 KB) |  | HTML iconHTML  

    Dynamics of automated guided vehicles (AGVs) are described by a nonlinear nonholonomic model with two inputs: the rear axle torque and the steering angle torque. This model uses integrated longitudinal and lateral behavior. The first part of this paper is concerned with motion generation, taking into account kinodynamics and motor's constraints. Usual kinematics constraints are not always sufficient to provide feasible trajectories; thus, we focus on velocity limitation and the motor's current and slew rate constraints. Optimal velocity is determined for AGVs along a specified path with a known curvature. The main result concerns the realistic situation when the parameters of the model describing the movement of the vehicle are not well known. A nonlinear strategy is proposed to ensure control of the vehicle even if the knowledge of the AGV's constant parameters is not perfect. The proof of the main result is based on the Lyapunov concept and the proposed results are illustrated by simulations and some comments. View full abstract»

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  • IEEE Intelligent Transportation Systems Society Information

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  • IEEE Transactions on Intelligent Transportation Systems Information for authors

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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.

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