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Intelligent Transportation Systems, IEEE Transactions on

Issue 1 • Date March 2010

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Displaying Results 1 - 25 of 29
  • Table of contents

    Page(s): C1 - 1
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  • IEEE Transactions on Intelligent Transportation Systems publication information

    Page(s): C2
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  • Building an Intellectual Highway for ITS Research and Development

    Page(s): 2 - 3
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  • A General Framework to Detect Unsafe System States From Multisensor Data Stream

    Page(s): 4 - 15
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (701 KB) |  | HTML iconHTML  

    This paper proposes a general framework for detecting unsafe states of a system whose basic real-time parameters are captured by multiple sensors. Our approach is to learn a danger-level function that can be used to alert the users of dangerous situations in advance so that certain measures can be taken to avoid the collapse. The main challenge to this learning problem is the labeling issue, i.e., it is difficult to assign an objective danger level at each time step to the training data, except at the collapse points, where a definitive penalty can be assigned, and at the successful ends, where a certain reward can be assigned. In this paper, we treat the danger level as an expected future reward (a penalty is regarded as a negative reward) and use temporal difference (TD) learning to learn a function for approximating the expected future reward, given the current and historical sensor readings. The TD learning obtains the approximation by propagating the penalties/rewards observable at collapse points or successful ends to the entire feature space following some constraints. This avoids the labeling issue and naturally allows a general framework to detect unsafe states. Our approach is applied to, but not limited to, the application of monitoring driving safety, and the experimental results demonstrate the effectiveness of the approach. View full abstract»

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  • On Exploration of Classifier Ensemble Synergism in Pedestrian Detection

    Page(s): 16 - 27
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (959 KB) |  | HTML iconHTML  

    A single feature extractor-classifier is not usually able to deal with the diversity of multiple image scenarios. Therefore, integration of features and classifiers can bring benefits to cope with this problem, particularly when the parts are carefully chosen and synergistically combined. In this paper, we address the problem of pedestrian detection by a novel ensemble method. Initially, histograms of oriented gradients (HOGs) and local receptive fields (LRFs), which are provided by a convolutional neural network, have been both classified by multilayer perceptrons (MLPs) and support vector machines (SVMs). A diversity measure is used to refine the initial set of feature extractors and classifiers. A final classifier ensemble was then structured by an HOG and an LRF as features, classified by two SVMs and one MLP. We have analyzed the following two classes of fusion methods of combining the outputs of the component classifiers: (1) majority vote and (2) fuzzy integral. The first part of the performance evaluation consisted of running the final proposed ensemble over the DaimlerChrysler cropwise data set, which was also artificially modified to simulate sunny and shadowy illumination conditions, which is typical of outdoor scenarios. Then, a window-wise study has been performed over a collected video sequence. Experiments have highlighted a state-of-the-art classification system, performing consistently better than the component classifiers and other methods. View full abstract»

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  • Driver Steering Assistance for Lane-Departure Avoidance Based on Hybrid Automata and Composite Lyapunov Function

    Page(s): 28 - 39
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (410 KB) |  | HTML iconHTML  

    This paper presents the design and the practical implementation of vehicle steering assistance that helps the driver avoid unintended lane departure. A switching strategy is built to govern the driver-assistance interaction, and the resulting hybrid system is formalized as an input/output (I/O) hybrid automaton. Composite Lyapunov functions, polyhedral-like invariant sets, and linear matrix inequality (LMI) methods constitute the heart of the approach used to design the lane-departure avoidance (LDA) system. The practical implementation of this steering assistance in a prototype vehicle confirms the effectiveness of this approach. View full abstract»

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  • Extraction of Moving Objects From Their Background Based on Multiple Adaptive Thresholds and Boundary Evaluation

    Page(s): 40 - 51
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    The extraction of moving objects from their background is a challenging task in visual surveillance. As a single threshold often fails to resolve ambiguities and correctly segment the object, in this paper, we propose a new method that uses three thresholds to accurately classify pixels as foreground or background. These thresholds are adaptively determined by considering the distributions of differences between the input and background images and are used to generate three boundary sets. These boundary sets are then merged to produce a final boundary set that represents the boundaries of the moving objects. The merging step proceeds by first identifying boundary segment pairs that are significantly inconsistent. Then, for each inconsistent boundary segment pair, its associated curvature, edge response, and shadow index are used as criteria to evaluate the probable location of the true boundary. The resulting boundary is finally refined by estimating the width of the halo-like boundary and referring to the foreground edge map. Experimental results show that the proposed method consistently performs well under different illumination conditions, including indoor, outdoor, moderate, sunny, rainy, and dim cases. By comparing with a ground truth in each case, both the classification error rate and the displacement error indicate an accurate detection, which show substantial improvement in comparison with other existing methods. View full abstract»

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  • Modeling of Audiofrequency Track Circuits for Validation, Tuning, and Conducted Interference Prediction

    Page(s): 52 - 60
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (772 KB) |  | HTML iconHTML  

    The modeling of track circuit (TC) signaling systems is considered to be a valuable tool for their validation (check of operation for exceptional and extreme network conditions and configurations), compatibility assessment (with respect to sources of conducted interference), and pretuning (before on-site tuning). The model can replace a series of preliminary measurements and speed up the on-site tuning procedure. The results of model verification and validation on the Torino-Novara trunk of the Italian High Speed Railway Line are presented. The accuracy and reliability are quite good from an absolute viewpoint and are compared with the traditional on-site TC tuning; the time saving is of an order of magnitude. View full abstract»

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  • Privacy-Aware Traffic Monitoring

    Page(s): 61 - 70
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (730 KB) |  | HTML iconHTML  

    Traffic-monitoring systems (TMSs) are vital for safety and traffic optimization. However, these systems may compromise the privacy of drivers once they track the position of each driver with a high degree of temporal precision. In this paper, we argue that aggregated data can protect location privacy while providing accurate information for traffic monitoring. We identify a range of aggregate query types. Our proposed privacy-aware monitoring system (PAMS) works as an aggregate query processor that protects the location privacy of drivers as it anonymizes the IDs of cars. Our experiments show that PAMS answers queries with high accuracy and efficiency. View full abstract»

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  • Predictions of Urban Volumes in Single Time Series

    Page(s): 71 - 80
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    Congestion is increasing in many urban areas. This has led to a growing awareness of the importance of accurate traffic-flow predictions. In this paper, we introduce a prediction scheme that is based on an extensive study of volume patterns that were collected at about 20 urban intersections in the city of Almelo, The Netherlands. The scheme can be used for both short- and long-term predictions. It consists of 1) baseline predictions for a given preselected day, 2) predictions for the next 24 h, and 3) short-term predictions with horizons smaller than 80 min. We show that the predictions significantly improve when we adopt some straightforward assumptions about the correlations between and the noise levels within volumes. We conclude that 24-h predictions are much more accurate than baseline predictions and that errors in short-term predictions are even negligibly small during working days. We used a heuristic approach to optimize the model. As a consequence, our model is quite simple so that it can easily be used for practical applications. View full abstract»

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  • Stochastic Optimization Model and Solution Algorithm for Robust Double-Track Train-Timetabling Problem

    Page(s): 81 - 89
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (253 KB) |  | HTML iconHTML  

    By considering various stochastic disturbances unfolding in a real-time dispatching environment, this paper develops a stochastic optimization formulation for incorporating segment travel-time uncertainty and dispatching policies into a medium-term train-timetabling process that aims to minimize the total trip time in a published timetable and reduce the expected schedule delay. Based on a heuristic sequential solution framework, this study decomposes the robust timetabling problem into a series of subproblems that optimize the slack-time allocation for individual trains. A number of illustrative examples are provided to demonstrate the proposed model and solution algorithms using data collected from a Beijing-Shanghai high-speed rail corridor in China. View full abstract»

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  • An Intervehicular Communication Architecture for Safety and Entertainment

    Page(s): 90 - 99
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (945 KB) |  | HTML iconHTML  

    Intervehicle communication (IVC) is emerging in research prominence for the interest that it is generating in all major car manufacturers and for the benefits that its inception will produce. The specific features of IVC will allow the deployment of a wide set of possible applications, which span from road safety to entertainment. Even if, on the one hand, these applications share the common need for fast multihop message propagation, on the other hand, they possess distinct characteristics in terms of generated network traffic. The state of the art of current research only proposes solutions specifically designed for a single application (or class) that is not directly extendable to a general IVC context. Instead, we claim that a privileged architecture exists, which is able to support the whole spectrum of application classes. To this aim, we propose a novel IVC architecture that adapts its functionalities to efficiently serve applications by quickly propagating their messages over a vehicular network. We conducted an extensive set of experiments that demonstrate the efficacy of our approach. As representative case studies, we considered two application classes that, for their network traffic characteristics, are at the opposite boundaries of the application spectrum: safety and entertainment. View full abstract»

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  • Lane-Level Integrity Provision for Navigation and Map Matching With GNSS, Dead Reckoning, and Enhanced Maps

    Page(s): 100 - 112
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1315 KB) |  | HTML iconHTML  

    Lane-level positioning and map matching are some of the biggest challenges for navigation systems. Additionally, in safety applications or in those with critical performance requirements (such as satellite-based electronic fee collection), integrity becomes a key word for the navigation community. In this scenario, it is clear that a navigation system that can operate at the lane level while providing integrity parameters that are capable of monitoring the quality of the solution can bring important benefits to these applications. This paper presents a pioneering novel solution to the problem of combined positioning and map matching with integrity provision at the lane level. The system under consideration hybridizes measurements from a global navigation satellite system (GNSS) receiver, an odometer, and a gyroscope, along with the road information stored in enhanced digital maps, by means of a multiple-hypothesis particle-filter-based algorithm. A set of experiments in real environments in France and Germany shows the very good results obtained in terms of positioning, map matching, and integrity consistency, proving the feasibility of our proposal. View full abstract»

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  • Dynamic Data Regulation for Fixed Vehicle Detectors

    Page(s): 113 - 121
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    This paper describes a novel methodology regarding dynamic data regulation for vehicle passage detectors. A vehicle detector is generally fixed at a specific location, but this location may not, at all times, be the optimal place for efficient data collection. If the detector is occupied by queues during a specific period, it will produce irregular data for traffic control and management. Therefore, the optimal location should be dynamic. This paper develops a regulator to track the optimal vehicle-detector location in a variety of traffic conditions and an algorithm to adjust the detected data from the original fixed detector as if they were detected by the detector at its time-dependent optimal location. Without moving the fixed detectors from time to time, this method allows vehicle detectors to issue more reliable data that reflect the actual traffic demand and are not corrupted by traffic signals or queues. Statistical tests at a significant level support the method presented in this study. The results of this study will help existing vehicle detectors generate more accurate data for traffic control and management. View full abstract»

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  • Wheel Slip Control via Second-Order Sliding-Mode Generation

    Page(s): 122 - 131
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (306 KB) |  | HTML iconHTML  

    During skid braking and spin acceleration, the driving force exerted by the tires is reduced considerably, and the vehicle cannot speed up or brake as desired. It may become very difficult to control the vehicle under these conditions. To solve this problem, a second-order sliding-mode traction controller is presented in this paper. The controller design is coupled with the design of a suitable sliding-mode observer to estimate the tire-road adhesion coefficient. The traction control is achieved by maintaining the wheel slip at a desired value. In particular, by controlling the wheel slip at the optimal value, the proposed traction control enables antiskid braking and antispin acceleration, thus improving safety in difficult weather conditions, as well as stability during high-performance driving. The choice of second-order sliding-mode control methodology is motivated by its robustness feature with respect to parameter uncertainties and disturbances, which are typical of the automotive context. Moreover, the proposed second-order sliding-mode controller, in contrast to conventional sliding-mode controllers, generates continuous control actions, thus being particularly suitable for application to automotive systems. View full abstract»

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  • Traffic Signal Optimization in “La Almozara” District in Saragossa Under Congestion Conditions, Using Genetic Algorithms, Traffic Microsimulation, and Cluster Computing

    Page(s): 132 - 141
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    Urban traffic congestion is a pandemic illness affecting many cities around the world. We have developed and tested a new model for traffic signal optimization based on the combination of three key techniques: 1) genetic algorithms (GAs) for the optimization task; 2) cellular-automata-based microsimulators for evaluating every possible solution for traffic-light programming times; and 3) a Beowulf Cluster, which is a multiple-instruction-multiple-data (MIMD) multicomputer of excellent price/performance ratio. This paper presents the results of applying this architecture to a large-scale real-world test case in a congestion situation, using four different variables as fitness function of the GA. We have simulated a set of congested scenarios for ??La Almozara?? in Saragossa, Spain. Our results in this extreme case are encouraging: As we increase the incoming volume of vehicles entering the traffic network - from 36 up to 3600 vehicles per hour - we get better performance from our architecture. Finally, we present new research directions in this area. View full abstract»

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  • CyberC3: A Prototype Cybernetic Transportation System for Urban Applications

    Page(s): 142 - 152
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1382 KB) |  | HTML iconHTML  

    In this paper, a prototype cybernetic transportation system called cybernetic technologies for cars in Chinese cities (CyberC3) is introduced. This system contains as many modules as necessary to evaluate the feasibility for its potential mass application in cities, including a central control room, five stations, three on-road monitoring cameras, three intelligent vehicles, and a green-energy power system. The entire system is centrally controlled and runs in two different modes - the ??shuttle mode?? and the ??on-demand mode.?? The control algorithm is divided into three logical layers: scheduling, planning, and executing. The scheduling layer manages the entire system, the planning layer navigates the vehicle, and the executing layer controls the vehicle in real time. The vehicle is powered by supercapacitor batteries. This system is a demonstration system, as well as a research platform, and has been open to the public in Shanghai, China, since May 2007, which has helped to evaluate the entire system and spread the concept of ??cybernetic transportation systems?? in China. View full abstract»

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  • A Simulation of Bonding Effects and Their Impacts on Pedestrian Dynamics

    Page(s): 153 - 161
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    This paper simulates bonding effects inside pedestrian crowds. Based on the social force model, this paper derives an exponential formulation of the bonding force, as opposed to the repulsive force, and surveys the degree of interpersonal cohesion under various circumstances. Parameters associated with the model are calibrated by preliminary simulation runs. With the proper simulation environment configuration, the effect of the bonding force is extensively demonstrated. Results show that the bonding force results in pedestrians' walking speeds being different from their initial intended ones. Specifically, delays in walking and the overtaking phenomenon, which are empirically observed, are explained using this model. In the zigzag walkway defined in the experiment, up to approximately 4% fewer pedestrians are able to escape in the prescribed time, due to bonding effects. To sum up, the bonding forces cause negative effects on pedestrian evacuation and should be taken into consideration for crowd dynamics research. View full abstract»

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  • The Reliability of Travel Time Forecasting

    Page(s): 162 - 171
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1246 KB) |  | HTML iconHTML  

    Travel time is a fundamental measure in transportation, and accurate travel time forecasting is crucial in intelligent transportation systems (ITSs). Currently, many techniques have been applied to travel time forecasting; however, the reliability of the prediction has not been studied in these approaches. In this paper, we propose an approach using the generalized autoregressive conditional heteroscedasticity (GARCH) model to study the volatility of travel time and supply the information about reliability for travel time forecasting. Three examples on real urban vehicular traffic data show the whole modeling process. In the experiments, we utilize the conditional predicted standard deviation (PSD) to express the reliability of travel time forecasting and screen out the sample points that are thought to be reliable forecasting. The results show that the root-mean-square error (RMSE), mean absolute error (MAE), and mean absolute percent error (MAPE) are all decreasing with an increase in the demand of the reliability. It proves that the model well depicts the reliability of travel time forecasting and that the proposed approach is feasible. View full abstract»

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  • Connectivity Statistics of Store-and-Forward Intervehicle Communication

    Page(s): 172 - 181
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (952 KB) |  | HTML iconHTML  

    Intervehicle communication (IVC) enables vehicles to exchange messages within a limited broadcast range and thus self-organize into dynamical vehicular ad hoc networks. For the foreseeable future, however, a direct connectivity between equipped vehicles in one direction is rarely possible. We therefore investigate an alternative mode in which messages are stored by relay vehicles traveling in the opposite direction and forwarded to vehicles in the original direction at a later time. The wireless communication consists of two ??transversal?? message hops across driving directions. Since direct connectivity for transversal hops and a successful message transmission to vehicles in the destination region are only a matter of time, the quality of this IVC strategy can be described in terms of the distribution function for the total transmission time. Assuming a Poissonian distance distribution between equipped vehicles, we derive analytical probability distributions for message transmission times and related propagation speeds for a deterministic and a stochastic model of the maximum range of direct communication. By means of integrated microscopic simulations of communication and bidirectional traffic flows, we validated the theoretical expectation for multilane roadways. We found little deviation of the analytical result for multilane scenarios but significant deviations for a single lane. This can be explained by vehicle platooning. We demonstrate the efficiency of the transverse hopping mechanism for a congestion-warning application in a microscopic traffic-simulation scenario. Messages are created on an event-driven basis by equipped vehicles getting into and out of a traffic jam. This application is operative for penetration levels as low as 1%. View full abstract»

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  • Feedback Control of Crowd Evacuation in One Dimension

    Page(s): 182 - 193
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (567 KB) |  | HTML iconHTML  

    This paper studies crowd models in one dimension. The focus of this paper is on the design of nonlinear feedback controllers for these models. Two different models are studied where dynamics are represented by a single partial differential equation (PDE) in one case and a system of hyperbolic PDEs in another, and control models are proposed for both. These include advective, diffusive, and advective-diffusive controls. The models representing evacuation dynamics are based on the laws of conservation of mass and momentum and are described by nonlinear hyperbolic PDEs. As such, the system is distributed in nature. We address the design of feedback control for these models in a distributed setting where the problem of control and stability is formulated directly in the framework of PDEs. The control goal is to design feedback controllers to control the movement of people during evacuation and avoid jams and shocks. View full abstract»

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  • TerraMax Vision at the Urban Challenge 2007

    Page(s): 194 - 205
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    This paper presents the TerraMax vision systems used during the 2007 DARPA Urban Challenge. First, a description of the different vision systems is provided, focusing on their hardware configuration, calibration method, and tasks. Then, each component is described in detail, focusing on the algorithms and sensor fusion opportunities: obstacle detection, road marking detection, and vehicle detection. The conclusions summarize the lesson learned from the developing of the passive sensing suite and its successful fielding in the Urban Challenge. View full abstract»

    Open Access
  • Understanding Transit Scenes: A Survey on Human Behavior-Recognition Algorithms

    Page(s): 206 - 224
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (974 KB) |  | HTML iconHTML  

    Visual surveillance is an active research topic in image processing. Transit systems are actively seeking new or improved ways to use technology to deter and respond to accidents, crime, suspicious activities, terrorism, and vandalism. Human behavior-recognition algorithms can be used proactively for prevention of incidents or reactively for investigation after the fact. This paper describes the current state-of-the-art image-processing methods for automatic-behavior-recognition techniques, with focus on the surveillance of human activities in the context of transit applications. The main goal of this survey is to provide researchers in the field with a summary of progress achieved to date and to help identify areas where further research is needed. This paper provides a thorough description of the research on relevant human behavior-recognition methods for transit surveillance. Recognition methods include single person (e.g., loitering), multiple-person interactions (e.g., fighting and personal attacks), person-vehicle interactions (e.g., vehicle vandalism), and person-facility/location interactions (e.g., object left behind and trespassing). A list of relevant behavior-recognition papers is presented, including behaviors, data sets, implementation details, and results. In addition, algorithm's weaknesses, potential research directions, and contrast with commercial capabilities as advertised by manufacturers are discussed. This paper also provides a summary of literature surveys and developments of the core technologies (i.e., low-level processing techniques) used in visual surveillance systems, including motion detection, classification of moving objects, and tracking. View full abstract»

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  • Determining the Optimal Configuration of Highway Routes for Real-Time Traffic Information: A Case Study

    Page(s): 225 - 231
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (867 KB) |  | HTML iconHTML  

    This paper deals with a case study where the objective is to identify the optimal subset of routes for real-time traveler information in a highway network. It is assumed that the benefit of providing this information is directly related to the uncertainty of route travel times. The variance of travel times within a time period over consecutive days is employed as the indicator of this uncertainty. The New Jersey Turnpike is used as the study network due to the availability of vehicle-by-vehicle network-specific data. The data set covers travel times between ~ 630 origin-destination (OD) pairs during 2004. The problem of identifying the optimal number of subset of routes is modeled as a nonlinear integer-programming problem. The proposed model is then solved using the Network-Enabled Optimization Software server, which is a common optimization solver that is available over the Internet. A simple heuristic for the proposed model is also presented. View full abstract»

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  • Performance of Multiagent Taxi Dispatch on Extended-Runtime Taxi Availability: A Simulation Study

    Page(s): 231 - 236
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1088 KB) |  | HTML iconHTML  

    An empirical and comparative evaluation of multiagent taxi dispatch with extended (E) runtime taxi availability is presented. A taxi in operation is said to be E-runtime available if it has a passenger alighting in ??x > 0 minutes' time or is empty, but has no new committed taxi request to service next. In a multiagent architecture, we consider a new operation policy wherein agents of E-runtime available taxis are allowed to negotiate in individual groups of size N for new taxi requests. The main objective is to present an evaluation of the multiagent system performance gains provided by different times-to-arrival of ??x, under a discrete range of demand rates for several iV-group sizes, as compared with the base case when ??x = 0. It is shown that the proposed policy can effectively reduce customer waiting time and empty taxi cruising time by up to about 60% and 96%, respectively, when the service demand is high for a 1000-strong taxi fleet. It is observed that the value selection for the policy parameter ??x is an important aspect for improving the general performance of multiagent taxi dispatch. View full abstract»

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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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Meet Our Editors

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