Notification:
We are currently experiencing intermittent issues impacting performance. We apologize for the inconvenience.
By Topic

Intelligent Transportation Systems, IEEE Transactions on

Issue 1 • Date March 2013

Filter Results

Displaying Results 1 - 25 of 51
  • Table of Contents

    Publication Year: 2013 , Page(s): C1 - C4
    Save to Project icon | Request Permissions | PDF file iconPDF (52 KB)  
    Freely Available from IEEE
  • IEEE Transactions on Intelligent Transportation Systems publication information

    Publication Year: 2013 , Page(s): C2
    Save to Project icon | Request Permissions | PDF file iconPDF (137 KB)  
    Freely Available from IEEE
  • An Adaptive Longitudinal Driving Assistance System Based on Driver Characteristics

    Publication Year: 2013 , Page(s): 1 - 12
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1340 KB) |  | HTML iconHTML  

    A prototype of a longitudinal driving-assistance system, which is adaptive to driver behavior, is developed. Its functions include adaptive cruise control and forward collision warning/avoidance. The research data came from driver car-following tests in real traffic environments. Based on the data analysis, a driver model imitating the driver's operation is established to generate the desired throttle depression and braking pressure. Algorithms for collision warning and automatic braking activation are designed based on the driver's pedal deflection timing during approach (gap closing). A self-learning algorithm for driver characteristics is proposed based on the recursive least-square method with a forgetting factor. Using this algorithm, the parameters of the driver model can be identified from the data in the manual operation phase, and the identification result is applied during the automatic control phase in real time. A test bed with an electronic throttle and an electrohydraulic brake actuator is developed for system validation. The experimental results show that the self-learning algorithm is effective and that the system can, to some extent, adapt to individual characteristics. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Stochastic Lane Shape Estimation Using Local Image Descriptors

    Publication Year: 2013 , Page(s): 13 - 21
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (832 KB) |  | HTML iconHTML  

    In this paper, we present a novel measurement model for particle-filter-based lane shape estimation. Recently, the particle filter has been widely used to solve lane detection and tracking problems, due to its simplicity, robustness, and efficiency. The key part of the particle filter is the measurement model, which describes how well a generated hypothesis (a particle) fits current visual cues in the image. Previous methods often simply combine multiple visual cues in a likelihood function without considering the uncertainties of local visual cues and the accurate probability relationship between visual cues and the lane model. In contrast, this paper derives a new measurement model by utilizing multiple kernel density to precisely estimate this probability relationship. The uncertainties of local visual cues are considered and modeled by Gaussian kernels. Specifically, we use a linear-parabolic model to describe the shape of lane boundaries on a top-view image and a partitioned particle filter (PPF), integrating it with our novel measurement model to estimate lane shapes in consecutive frames. Finally, the robustness of the proposed algorithm with the new measurement model is demonstrated on the DRIVSCO data sets. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Distributed Modeling in a MapReduce Framework for Data-Driven Traffic Flow Forecasting

    Publication Year: 2013 , Page(s): 22 - 33
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1660 KB) |  | HTML iconHTML  

    With the availability of increasingly more new data sources collected for transportation in recent years, the computational effort for traffic flow forecasting in standalone modes has become increasingly demanding for large-scale networks. Distributed modeling strategies can be utilized to reduce the computational effort. In this paper, we present a MapReduce-based approach to processing distributed data to design a MapReduce framework of a traffic forecasting system, including its system architecture and data-processing algorithms. The work presented here can be applied to many traffic forecasting systems with models requiring a learning process (e.g., the neural network approach). We show that the learning process of the forecasting model under our framework can be accelerated from a computational perspective. Meanwhile, model fusion, which is the key problem of distributed modeling, is explicitly treated in this paper to enhance the capability of the forecasting system in data processing and storage. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Vehicle Positioning Using GSM and Cascade-Connected ANN Structures

    Publication Year: 2013 , Page(s): 34 - 46
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1796 KB) |  | HTML iconHTML  

    Procuring location information for intelligent transportation systems is a popular topic among researchers. This paper investigates the vehicle location algorithm based on the received signal strength (RSS) from available Global System for Mobile Communications (GSM) networks. The performances of positioning models, which consisted of cascade-connected (C-C) artificial neural network (ANN) multilayer feedforward structures employing the space-partitioning principle, are compared with the single-ANN multilayer feedforward model in terms of accuracy, the number of subspaces, and other positioning relevant parameters. C-C ANN structures make use of the fact that a vehicle can be found only in a subspace of the entire environment (roads) to improve the positioning accuracy. The best-performing C-C ANN structure achieved an average error of 26 m and a median error of less than 5 m, which is accurate enough for most of the vehicle location services. Using the same RSS database obtained by measurements, it was shown that the proposed model outperforms kNN and extended Kalman filter (EKF)-trained ANN positioning algorithms. Moreover, the presented ANN structures replace not only the positioning algorithms but the overloaded map-matching process as well. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Relative Positioning Enhancement in VANETs: A Tight Integration Approach

    Publication Year: 2013 , Page(s): 47 - 55
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1535 KB) |  | HTML iconHTML  

    Position information is a fundamental requirement for many vehicular applications such as navigation, intelligent transportation systems (ITSs), collision avoidance, and location-based services (LBSs). Relative positioning is effective for many applications, including collision avoidance and LBSs. Although Global Navigation Satellite Systems (GNSSs) can be used for absolute or relative positioning, the level of accuracy does not meet the requirements of many applications. Cooperative positioning (CP) techniques, fusing data from different sources, can be used to improve the performance of absolute or relative positioning in a vehicular ad hoc network (VANET). VANET CP systems are mostly based on radio ranging, which is not viable, despite being assumed in much of the literature. Considering this and emerging vehicular communication technologies, a CP method is presented to improve the relative positioning between two vehicles within a VANET, fusing the available low-level Global Positioning System (GPS) data. The proposed method depends on no radio ranging technique. The performance of the proposed method is verified by analytical and experimental results. Although the principles of the proposed method are similar to those of differential solutions such as differential GPS (DGPS), the proposed technique outperforms DGPS with about 37% and 45% enhancement in accuracy and precision of relative positioning, respectively. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Predictive Prevention of Loss of Vehicle Control for Roadway Departure Avoidance

    Publication Year: 2013 , Page(s): 56 - 68
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1065 KB) |  | HTML iconHTML  

    In this paper, we investigate predictive approaches to the problem of roadway departure prevention via automated steering and braking. We assume a sensing infrastructure detecting road geometry and consider a two-layer accident avoidance framework consisting of a threat assessment and an intervention layer. A novel active safety function for prevention of loss of vehicle control is proposed and implemented using the considered accident avoidance framework. Simulation and experimental results are presented, showing that the proposed approach effectively exploits road preview information to prevent the vehicle from operating in regions of the state space where standard electronic stability control systems are normally activated. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Classification and Counting of Composite Objects in Traffic Scenes Using Global and Local Image Analysis

    Publication Year: 2013 , Page(s): 69 - 81
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1364 KB) |  | HTML iconHTML  

    Object recognition algorithms often focus on determining the class of a detected object in a scene. Two significant phases are usually involved in object recognition. The first phase is the object representation phase, in which the most suitable features that provide the best discriminative power under constraints such as lighting, resolution, scale, and view variations are chosen to describe the objects. The second phase is to use this representation space to develop models for each object class using discriminative classifiers. In this paper, we focus on composite objects, i.e., objects with two or more simpler classes that are interconnected in a complicated manner. One classic example of such a scenario is a bicyclist. A bicyclist consists of a bicycle and a human who rides the bicycle. When we are faced with the task of classifying bicyclists and pedestrians, it is counterintuitive and often hard to come up with a discriminative classifier to distinguish the two classes. We explore global image analysis based on bag of visual words to compare the results with local image analysis, in which we attempt to distinguish the individual parts of the composite object. We also propose a unified naive Bayes framework and a combined histogram feature method for combining the individual classifiers for enhanced performance. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • VIP-WAVE: On the Feasibility of IP Communications in 802.11p Vehicular Networks

    Publication Year: 2013 , Page(s): 82 - 97
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1672 KB) |  | HTML iconHTML  

    Vehicular communication networks, such as the 802.11p and Wireless Access in Vehicular Environments (WAVE) technologies, are becoming a fundamental platform for providing real-time access to safety and entertainment information. In particular, infotainment applications and, consequently, IP-based communications, are key to leverage market penetration and deployment costs of the 802.11p/WAVE network. However, the operation and performance of IP in 802.11p/WAVE are still unclear as the WAVE standard guidelines for being IP compliant are rather minimal. This paper studies the 802.11p/WAVE standard and its limitations for the support of infrastructure-based IP applications, and proposes the Vehicular IP in WAVE (VIP-WAVE) framework. VIP-WAVE defines the IP configuration for extended and non-extended IP services, and a mobility management scheme supported by Proxy Mobile IPv6 over WAVE. It also exploits multi-hop communications to improve the network performance along roads with different levels of infrastructure presence. Furthermore, an analytical model considering mobility, handoff delays, collisions, and channel conditions is developed for evaluating the performance of IP communications in WAVE. Extensive simulations are performed to demonstrate the accuracy of our analytical model and the effectiveness of VIP-WAVE in making feasible the deployment of IP applications in the vehicular network. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Modeling and Analysis of Driving Behavior Based on a Probability-Weighted ARX Model

    Publication Year: 2013 , Page(s): 98 - 112
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2474 KB) |  | HTML iconHTML  

    This paper proposes a probability-weighted autoregressive exogenous (PrARX) model wherein the multiple ARX models are composed of the probabilistic weighting functions. This model can represent both the motion-control and decision-making aspects of the driving behavior. As the probabilistic weighting function, a “softmax” function is introduced. Then, the parameter estimation problem for the proposed model is formulated as a single optimization problem. The “soft” partition defined by the PrARX model can represent the decision-making characteristics of the driver with vagueness. This vagueness can be quantified by introducing the “decision entropy.” In addition, it can be easily extended to the online estimation scheme due to its small computational cost. Finally, the proposed model is applied to the modeling of the vehicle-following task, and the usefulness of the model is verified and discussed. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Land-Use Classification Using Taxi GPS Traces

    Publication Year: 2013 , Page(s): 113 - 123
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1060 KB) |  | HTML iconHTML  

    Detailed land use, which is difficult to obtain, is an integral part of urban planning. Currently, GPS traces of vehicles are becoming readily available. It conveys human mobility and activity information, which can be closely related to the land use of a region. This paper discusses the potential use of taxi traces for urban land-use classification, particularly for recognizing the social function of urban land by using one year's trace data from 4000 taxis. First, we found that pick-up/set-down dynamics, extracted from taxi traces, exhibited clear patterns corresponding to the land-use classes of these regions. Second, with six features designed to characterize the pick-up/set-down pattern, land-use classes of regions could be recognized. Classification results using the best combination of features achieved a recognition accuracy of 95%. Third, the classification results also highlighted regions that changed land-use class from one to another, and such land-use class transition dynamics of regions revealed unusual real-world social events. Moreover, the pick-up/set-down dynamics could further reflect to what extent each region is used as a certain class. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • On Secure VANET-Based Ad Dissemination With Pragmatic Cost and Effect Control

    Publication Year: 2013 , Page(s): 124 - 135
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (801 KB) |  | HTML iconHTML  

    Allowing commercial service providers (SPs) to promote their businesses, ad dissemination in vehicular ad hoc networks (VANETs) shows great application potential. In this paper, a VANET-based Ambient Ad-Dissemination scheme (VAAD) is proposed to support secure ad disseminations with pragmatic cost and effect control. VAAD provides an incentive-centered architecture for the involved parties to trade off their conflicting requirements regarding ad dissemination. Given realistic advertising effect and cost requirements of an SP, VAAD adopts a distance-based gradient ad dissemination algorithm to maximize the achievable ad effect by emulating the ad-posting patterns in the physical world. To facilitate vehicular nodes' participation in VAAD, efficient, secure, and privacy-preserving incentive cash-in is ensured to support financial transactions in VAAD. Thus, with proper cost and effect control, VAAD is a novel and comprehensive solution to secure ad dissemination in VANETs. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Changes in the Correlation Between Eye and Steering Movements Indicate Driver Distraction

    Publication Year: 2013 , Page(s): 136 - 145
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (484 KB) |  | HTML iconHTML  

    Driver distraction represents an increasingly important contributor to crashes and fatalities. Technology that can detect and mitigate distraction by alerting distracted drivers could play a central role in maintaining safety. Based on either eye measures or driver performance measures, numerous algorithms to detect distraction have been developed. Combining both eye glance and vehicle data could enhance distraction detection. The goal of this paper is to evaluate whether changes in the eye-steering correlation structure can indicate distraction. Drivers performed visual, cognitive, and cognitive/visual tasks while driving in a simulator. The auto- and cross-correlations of horizontal eye position and steering wheel angle show that eye movements associated with road scanning produce a low eye-steering correlation. However, even this weak correlation is sensitive to distraction. Time lead associated with the maximum correlation is sensitive to all three types of distraction, and the maximum correlation coefficient is most strongly affected by off-road glances. These results demonstrate that eye-steering correlation statistics can detect distraction and differentiate between types of distraction. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Front Sensor and GPS-Based Lateral Control of Automated Vehicles

    Publication Year: 2013 , Page(s): 146 - 154
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (719 KB) |  | HTML iconHTML  

    This work proposes an automated steering control system for passenger cars. Feasibility of a control strategy based on a front sensor and a Global Positioning System (GPS) has been evaluated using computer simulations. First, the steering angles can be estimated by using the driving data provided by the front sensor and GPS. Second, the road curvature estimator for real-time situation is designed based on its relationship with the steering angle. Third, accurate and real-time estimation of the vehicle's lateral displacements with respect to the road is accomplished. Finally, a closed-loop controller is used to control the lateral dynamics of the vehicle. The proposed estimation and control algorithms are validated by computer simulation results. They show that this lateral steering control system achieves good and robust performance for vehicles to follow a reference path. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Automatic Road Crack Detection and Characterization

    Publication Year: 2013 , Page(s): 155 - 168
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1607 KB) |  | HTML iconHTML  

    A fully integrated system for the automatic detection and characterization of cracks in road flexible pavement surfaces, which does not require manually labeled samples, is proposed to minimize the human subjectivity resulting from traditional visual surveys. The first task addressed, i.e., crack detection, is based on a learning from samples paradigm, where a subset of the available image database is automatically selected and used for unsupervised training of the system. The system classifies nonoverlapping image blocks as either containing crack pixels or not. The second task deals with crack type characterization, for which another classification system is constructed, to characterize the detected cracks' connect components. Cracks are labeled according to the types defined in the Portuguese Distress Catalog, with each different crack present in a given image receiving the appropriate label. Moreover, a novel methodology for the assignment of crack severity levels is introduced, computing an estimate for the width of each detected crack. Experimental crack detection and characterization results are presented based on images captured during a visual road pavement surface survey over Portuguese roads, with promising results. This is shown by the quantitative evaluation methodology introduced for the evaluation of this type of system, including a comparison with human experts' manual labeling results. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Model-Independent Adaptive Fault-Tolerant Output Tracking Control of 4WS4WD Road Vehicles

    Publication Year: 2013 , Page(s): 169 - 179
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (310 KB) |  | HTML iconHTML  

    This paper investigates the path-tracking control problem of four-wheel-steering and four-wheel-driving (4WS4WD) road vehicles. Of particular interest is the development of an adaptive and fault-tolerant tracking control scheme capable of compensating vehicle uncertain dynamics/disturbances and actuation failures simultaneously. Control algorithms are derived without requiring detail system dynamic information. The control scheme is shown to be effective in coping with unexpected actuation faults without the need for analytically estimating bound on actuator failure variables. The proposed method is validated and demonstrated through its application to a wheeled vehicle with four steering wheels and four driving wheels, where high-precision path tracking is achieved in the face of steering faults. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Aircraft Ground-Taxiing Model for Congested Airport Using Cellular Automata

    Publication Year: 2013 , Page(s): 180 - 188
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (543 KB) |  | HTML iconHTML  

    Efficient airport surface operation is considered key to successful implementation of 4-D trajectories. Here, an airport surface aircraft model is developed to improve simulation accuracy. The new simulation method is developed based on the Nagel-Schreckenberg (NS) model, which is a car congestion model, and it considers the taxiing speed and the time histories of taxiing, particularly for a heavy traffic environment. To validate the model, airport surface surveillance data at Tokyo International Airport are used, and it is proven that the congestion phenomenon is modeled well with an average accuracy of about 30 s. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Computational Traffic Experiments Based on Artificial Transportation Systems: An Application of ACP Approach

    Publication Year: 2013 , Page(s): 189 - 198
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1163 KB) |  | HTML iconHTML  

    The Artificial societies, Computational experiments, and Parallel execution (ACP) approach provides us an opportunity to look into new methods that address transportation problems from new perspectives. In this paper, we present our work and results of applying the ACP approach on modeling and analyzing transportation systems, particularly carrying out computational experiments based on artificial transportation systems (ATSs). Two aspects in the modeling process are analyzed. The first is growing an ATS from the bottom up using agent-based technologies. The second is modeling environmental impacts under the principle of “simple is consistent.” Finally, three computational experiments are carried out on one specific ATS, i.e., Jinan-ATS, and numerical results are presented to illustrate the applications of our method. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • BAHG: Back-Bone-Assisted Hop Greedy Routing for VANET's City Environments

    Publication Year: 2013 , Page(s): 199 - 213
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1145 KB) |  | HTML iconHTML  

    Using advanced wireless local area network technologies, vehicular ad hoc networks (VANETs) have become viable and valuable for their wide variety of novel applications, such as road safety, multimedia content sharing, commerce on wheels, etc. Multihop information dissemination in VANETs is constrained by the high mobility of vehicles and the frequent disconnections. Currently, geographic routing protocols are widely adopted for VANETs as they do not require route construction and route maintenance phases. Again, with connectivity awareness, they perform well in terms of reliable delivery. To obtain destination position, some protocols use flooding, which can be detrimental in city environments. Further, in the case of sparse and void regions, frequent use of the recovery strategy elevates hop count. Some geographic routing protocols adopt the minimum weighted algorithm based on distance or connectivity to select intermediate intersections. However, the shortest path or the path with higher connectivity may include numerous intermediate intersections. As a result, these protocols yield routing paths with higher hop count. In this paper, we propose a hop greedy routing scheme that yields a routing path with the minimum number of intermediate intersection nodes while taking connectivity into consideration. Moreover, we introduce back-bone nodes that play a key role in providing connectivity status around an intersection. Apart from this, by tracking the movement of source as well as destination, the back-bone nodes enable a packet to be forwarded in the changed direction. Simulation results signify the benefits of the proposed routing strategy in terms of high packet delivery ratio and shorter end-to-end delay. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Heterogeneous Delay Embedding for Travel Time and Energy Cost Prediction Via Regression Analysis

    Publication Year: 2013 , Page(s): 214 - 224
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1426 KB) |  | HTML iconHTML  

    In this paper, we study travel time and energy cost prediction at any future departure time for a targeted road segment and vehicle. These two prediction tasks play an important part in the design of advanced driver-assistance systems (ADAS) that can automatically manage battery charging, energy saving, and route planning for fully electric vehicles. Compared with the fundamental problem of travel time prediction, which usually learns from the historical and current data of travel time itself, energy cost prediction is a more complex problem that involves multiple context conditions and vehicle status measured by various time-invariant and time-variant data. We define a general learning problem based on multiple time-invariant and time-variant inputs to unify these two prediction tasks. To solve the defined learning problem, we propose heterogeneous delay embedding (HDE), which extracts an informative feature space for regression analysis and aims at achieving satisfactory prediction for any future departure time. The proposed HDE first categorizes the historical and current data of a time-variant measurement into different types, then incorporates different delay settings for embedding multiple types of time-series data, and finally removes redundant information and noise from the generated features using orthogonal locality preserving projection. Experimental results demonstrate the effectiveness of the proposed method for both short- and long-term predictions of travel time and energy cost. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Parallel Traffic Management System and Its Application to the 2010 Asian Games

    Publication Year: 2013 , Page(s): 225 - 235
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1088 KB) |  | HTML iconHTML  

    Field data are important for convenient daily travel of urban residents, reducing traffic congestion and accidents, pursuing a low-carbon environment-friendly sustainable development strategy, and meeting the extra peak traffic demand of large sporting events or large business activities, etc. To meet the field data demand during the 2010 Asian (Para) Games held in Guangzhou, China, based on the novel Artificial systems, Computational experiments, and Parallel execution (ACP) approach, the Parallel Traffic Management System (PtMS) was developed. It successfully helps to achieve smoothness, safety, efficiency, and reliability of public transport management during the two games, supports public traffic management and decision making, and helps enhance the public traffic management level from experience-based policy formulation and manual implementation to scientific computing-based policy formulation and implementation. The PtMS represents another new milestone in solving the management difficulty of real-world complex systems. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A Task Assignment Algorithm for Multiple Aerial Vehicles to Attack Targets With Dynamic Values

    Publication Year: 2013 , Page(s): 236 - 248
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1666 KB) |  | HTML iconHTML  

    A good task assignment is an important guarantee to achieve great combat effectiveness. This paper investigates the task assignment problem, where the value of the targets is time changing in the battlefield, and presents a solution approach that is a combination of two algorithms: the multidestination route planning algorithm based on dynamic programming and the multisubgroup ant colony algorithm (MSACO). The two algorithms coordinately solve the task assignment problem. The route planning algorithm can obtain available routes between any two targets and provide reasonable routing information for MSACO. Then, the ant colony algorithm is applied to solve the task assignment problem. To solve the task assignment problem in the battlefield environment, several key technologies are introduced to improve the traditional ant colony algorithm, which include the subgroup selection strategy, the dynamic candidate aggregate policy, the state transferring policy, and the information-element updating mechanism. Simulation results show that the proposed approach can produce a reasonable and available plan for all the test cases in short computational time. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • New paradigms for the integration of yaw stability and rollover prevention functions in vehicle stability control

    Publication Year: 2013 , Page(s): 249 - 261
    Cited by:  Papers (2)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1672 KB) |  | HTML iconHTML  

    The integration of rollover prevention and yaw stability control objectives in electronic stability control (ESC) has traditionally been done based on a priority calculation. The control system nominally focuses on yaw stability control until a danger of rollover is detected. When a danger of rollover is detected, the control system switches from yaw stability control to rollover prevention. This paper focuses on an integrated ESC system wherein the objectives of yaw stability and rollover prevention are addressed simultaneously, rather than one at a time. First, we show that staying on a desired planar trajectory at a specified speed results in an invariant rollover index. This implies that rollover prevention can be achieved whenever there is a danger of rollover only by reducing vehicle speed, since changing the desired vehicle trajectory is not a desirable option. In this regard, it is shown that a vehicle that reduces its speed before entering a sharp curve performs significantly better than a vehicle that uses differential braking during the turn for yaw stability control. Second, this paper explores how the use of steer-by-wire technology can address the tradeoff between yaw stability, speed, and rollover prevention performance. It is shown that the use of traditional steer-by-wire simply as an additional actuator cannot by itself ameliorate the tradeoff. However, this tradeoff can be eliminated if steer-by-wire is used to invert the direction of the roll angle of the vehicle. A new steer-by-wire algorithm that uses transient countersteering is shown to change the location of the rollover dynamics from the neighborhood of an unstable to a stable equilibrium. In this case, a desired trajectory can indeed be achieved by the vehicle at the same speed with a much smaller danger of rollover. This is a novel and viable approach to integrating the yaw stability and rollover prevention functions and eliminating the inherent tradeoffs in the performance of both. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • GPS Localization Accuracy Classification: A Context-Based Approach

    Publication Year: 2013 , Page(s): 262 - 273
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2158 KB) |  | HTML iconHTML  

    Global Positioning System (GPS) localization has been attracting attention recently in various areas, including intelligent transportation systems (ITSs), navigation systems, road tolling, smart parking, and collision avoidance. Although, various approaches for improving localization accuracy have been reported in the literature, there is still a need for more efficient and more effective measures that can ascribe some level of accuracy to the localization process. These measures will enable localization systems to manage the localization process and resources to achieve the highest accuracy possible and to mitigate the impact of inadequate accuracy on the target application. The localization accuracy of any GPS system depends heavily on both the technique it uses to compute locations and the measurement conditions in its surroundings. However, while localization techniques have recently started to demonstrate significant improvement in localization performance, they continue to be severely impacted by the measurement conditions in their environment. Indeed, the impact of the measurement conditions on the localization accuracy in itself is an ill-conditioned problem due to the incongruent nature of the measurement process. This paper proposes a scheme to address localization accuracy estimation. This scheme involves two steps, namely, measurement condition disambiguation and enhanced location accuracy classification. Real-life comparative experiments are presented to demonstrate the efficacy of the proposed scheme in classifying GPS localization accuracy under various measurement conditions. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.

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