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Intelligent Transportation Systems, IEEE Transactions on

Issue 3 • Date June 2014

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Displaying Results 1 - 25 of 44
  • Table of contents

    Publication Year: 2014 , Page(s): C1 - C2
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  • IEEE Transactions on Intelligent Transportation Systems publication information

    Publication Year: 2014 , Page(s): C2
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  • Scanning the Issue and Beyond: Real-Time Social Transportation with Online Social Signals

    Publication Year: 2014 , Page(s): 909 - 914
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    Freely Available from IEEE
  • An Axiomatic Design Approach to Passenger Itinerary Enumeration in Reconfigurable Transportation Systems

    Publication Year: 2014 , Page(s): 915 - 924
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (304 KB) |  | HTML iconHTML  

    Transportation systems represent a critical infrastructure upon which nations' economies and national security depend. As infrastructure systems, they must be planned and operated to accommodate the uncertain and continually evolving needs of their passengers and freight. New roads are planned or existing roads are closed for maintenance or due to operational breakdowns. Reconfigurable transportation systems are those which adapt to these changes quickly and efficiently. They are not overdesigned with capabilities that may be left unused; instead, capabilities are added only when needed, thus supporting the need for resilient infrastructure. An axiomatic-design-for-large-flexible-systems approach is chosen as a methodology for its deep roots in engineering design. It addresses systems where the functionality not only evolves over time, but also can be fulfilled by one or more system resources, and is used here to enumerate passenger itineraries. This paper builds upon a recent work in which axiomatic design was used to develop a theory of degrees of freedom in transportation systems for their reconfigurable design and operation. The methodological developments are then demonstrated on a small subsection of the Mexico City transportation system to demonstrate its wide-ranging utility in reconfigurability decision-making at the planning and operation timescales. In addition, further comparisons of axiomatic design to traditional graph theory are made, indicating the mathematical basis of the former in the latter. View full abstract»

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  • Generation of a Precise Roadway Map for Autonomous Cars

    Publication Year: 2014 , Page(s): 925 - 937
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2013 KB) |  | HTML iconHTML  

    This paper proposes a map generation algorithm for a precise roadway map designed for autonomous cars. The roadway map generation algorithm is composed of three steps, namely, data acquisition, data processing, and road modeling. In the data acquisition step, raw trajectory and motion data for map generation are acquired through exploration using a probe vehicle equipped with GPS and on-board sensors. The data processing step then processes the acquired trajectory and motion data into roadway geometry data. GPS trajectory data are unsuitable for direct roadway map use by autonomous cars due to signal interruptions and multipath; therefore, motion information from the on-board sensors is applied to refine the GPS trajectory data. A fixed-interval optimal smoothing theory is used for a refinement algorithm that can improve the accuracy, continuity, and reliability of road geometry data. Refined road geometry data are represented into the B-spline road model. A gradual correction algorithm is proposed to accurately represent road geometry with a reduced amount of control parameters. The developed map generation algorithm is verified and evaluated through experimental studies under various road geometry conditions. The results show that the generated roadway map is sufficiently accurate and reliable to utilize for autonomous driving. View full abstract»

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  • Energy-Efficient Locomotive Operation for Chinese Mainline Railways by Fuzzy Predictive Control

    Publication Year: 2014 , Page(s): 938 - 948
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    With the increasing energy consumption in Chinese mainline railways amid the worldwide carbon emission concerns, the need for energy-efficient locomotive operation becomes urgent. Locomotive operation is directly linked to speed limits imposed by the train ahead through signaling. In China's mainline railways, speed limits for locomotive operation change frequently because of relatively short headways in a highly congested network. Whenever the speed limit changes, the locomotive operation must be determined again quickly to adapt to the new speed limit. As a result, the energy-efficient locomotive operation is a real-time optimization problem with time-varying constraints, in which the tradeoff between solution optimality and computational time is essential, but it has not been considered adequately in previous studies. This study develops a fuzzy predictive control approach, continuously providing locomotive operation instructions, with respect to the prevailing speed limits, to reduce energy consumption of train movement. The proposed approach is implemented in an onboard decision support system to assist drivers. The system is tested on the Ning'xi line in China. The results indicate that energy consumption on train operations is reduced by 4%, without increasing the runtime between stations, while the computational requirement satisfies the demand of real-time solutions. Extensive simulations show that the proposed approach is able to provide sufficient solution optimality in reasonable computational time under different operation settings. View full abstract»

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  • COTraMS: A Collaborative and Opportunistic Traffic Monitoring System

    Publication Year: 2014 , Page(s): 949 - 958
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2133 KB) |  | HTML iconHTML  

    Traffic monitoring and control are becoming more and more important as the number of vehicles and traffic jams grow. Nevertheless, these tasks are still predominantly performed by visual means using strategically placed video cameras. For more effectiveness, proposals to improve traffic monitoring and control should consider automated systems. In this paper, we propose the Collaborative and Opportunistic Traffic Monitoring System (COTraMS), which is a system that monitors traffic using available IEEE 802.11 networks. COTraMS is collaborative because user participation is essential in defining the vehicle movement and opportunistic because it uses existing information. To evaluate the performance of COTraMS, a prototype is implemented using an IEEE 802.11 b/g network. Measurements from a real public wireless network in Rio de Janeiro, Brazil, demonstrate the possibility of obtaining traffic conditions with our proposed monitoring system. In addition, we analyze COTraMS via simulation to evaluate its performance in scenarios with a larger number of vehicles. The comparison of the obtained results with data obtained from Global Positioning System shows high accuracy in detecting both the position of the vehicle and the estimation of the road condition, using a simple architecture and a small amount of network bandwidth. View full abstract»

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  • Using a Head-up Display-Based Steady-State Visually Evoked Potential Brain–Computer Interface to Control a Simulated Vehicle

    Publication Year: 2014 , Page(s): 959 - 966
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (704 KB) |  | HTML iconHTML  

    In this paper, we propose a new steady-state visually evoked potential (SSVEP) brain-computer interface (BCI) with visual stimuli presented on a windshield via a head-up display, and we apply this BCI in conjunction with an alpha rhythm to control a simulated vehicle with a 14-DOF vehicle dynamics model. A linear discriminant analysis classifier is applied to detect the alpha rhythm, which is used to control the starting and stopping of the vehicle. The classification models of the SSVEP BCI with three commands (i.e., turning left, turning right, and going forward) are built by using a support vector machine with frequency domain features. A real-time brain-controlled simulated vehicle is developed and tested by using four participants to perform a driving task online, including vehicle starting and stopping, lane keeping, avoiding obstacles, and curve negotiation. Experimental results show the feasibility of using the human “mind” alone to control a vehicle, at least for some users. View full abstract»

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  • Using Delayed Observations for Long-Term Vehicle Tracking in Large Environments

    Publication Year: 2014 , Page(s): 967 - 981
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2217 KB) |  | HTML iconHTML  

    The tracking of vehicles over large areas with limited position observations is of significant importance in many industrial applications. This paper presents algorithms for long-term vehicle motion estimation based on a vehicle motion model that incorporates the properties of the working environment and information collected by other mobile agents and fixed infrastructure collection points. The prediction algorithm provides long-term estimates of vehicle positions using speed and timing profiles built for a particular environment and considering the probability of a vehicle stopping. A limited number of data collection points distributed around the field are used to update the estimates, with negative information (no communication) also used to improve the prediction. This paper introduces the concept of observation harvesting, a process in which peer-to-peer communication between vehicles allows egocentric position updates to be relayed among vehicles and finally conveyed to the collection point for an improved position estimate. Positive and negative communication information is incorporated into the fusion stage, and a particle filter is used to incorporate the delayed observations harvested from vehicles in the field to improve the position estimates. The contributions of this work enable the optimization of fleet scheduling using discrete observations. Experimental results from a typical large-scale mining operation are presented to validate the algorithms. View full abstract»

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  • Overcoming Drowsiness by Inducing Cardiorespiratory Phase Synchronization

    Publication Year: 2014 , Page(s): 982 - 991
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1325 KB) |  | HTML iconHTML  

    Drowsiness is one of the major factors leading to car accidents. Many automobile companies and institutions have been studying ways to monitor drowsiness and keep drivers awake. When drowsiness is detected during driving, audible sound, vibrations, or messages on a display are generally used to warn the driver to concentrate on driving or to take a rest. These methods help to prevent drowsiness-related crashes to some extent, but for greater safety, methods need to be developed to physiologically overcome drowsiness. The key to overcoming drowsiness is to keep the body constantly supplied with oxygen. We focused on cardiorespiratory phase synchronization (CRPS) to recover from oxygen desaturation during drowsiness. This study found it possible to induce CRPS by paced breathing (PB) using pulse sound, which synchronized with heartbeats. The experiment results showed SpO2 measured from forehead increased during this PB. The increase in SpO2 was larger than that of yawns, deep breathing, or a period of drowsiness spontaneously reduced. In conclusion, inducing CRPS by PB using pulse sound synchronized with the heartbeat has the potential to reduce drowsiness physiologically. View full abstract»

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  • An Agent-Based Microscopic Pedestrian Flow Simulation Model for Pedestrian Traffic Problems

    Publication Year: 2014 , Page(s): 992 - 1001
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    Guaranteeing a safe, efficient, and comfortable traveling system for pedestrians is one of the most important aspects of an intelligent transportation system. The microscopic simulation of pedestrian flow has attracted increasing research attention in recent years since a reliable simulation model for pedestrian flow may greatly benefit engineers and operators in mass transportation management, as well as designers and planners in urban planning and architecture. This paper introduces CityFlow, an agent-based microscopic pedestrian flow simulation model. The building floor plan in the model is represented by a continuous space constructed in a network approach, and each pedestrian is regarded as a self-adapted agent. Agent movement is implemented in a utility maximization approach by considering various human behaviors. The influences of parameters in the model on the simulation results are investigated. Typical pedestrian flow phenomena, including the unidirectional and bidirectional flow in a corridor as well as the flow through bottlenecks, are simulated. The simulation results are further compared with empirical study results. The comparison reveals that the model can approach the density-speed fundamental diagrams and the empirical flow rates at bottlenecks within acceptable system dimensions. The simulation results of the bidirectional pedestrian flow also show that the model can reproduce the lane-formation phenomenon. View full abstract»

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  • A Particle-Based Solution for Modeling and Tracking Dynamic Digital Elevation Maps

    Publication Year: 2014 , Page(s): 1002 - 1015
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2210 KB) |  | HTML iconHTML  

    Digital elevation maps are simple yet powerful representations of complex 3-D environments. These maps can be built and updated using various sensors and sensorial data processing algorithms. This paper describes a novel approach for modeling the dynamic 3-D driving environment, the particle-based dynamic elevation map, each cell in this map having, in addition to height, a probability distribution of speed in order to correctly describe moving obstacles. The dynamic elevation map is represented by a population of particles, each particle having a position, a height, and a speed. Particles move from one cell to another based on their speed vectors, and they are created, multiplied, or destroyed using an importance resampling mechanism. The importance resampling mechanism is driven by the measurement data provided by a stereovision sensor. The proposed model is highly descriptive for the driving environment, as it can easily provide an estimation of the height, speed, and occupancy of each cell in the grid. The system was proven robust and accurate in real driving scenarios, by comparison with ground truth data. View full abstract»

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  • Energy-Sustainable Traffic Signal Timings for a Congested Road Network With Heterogeneous Users

    Publication Year: 2014 , Page(s): 1016 - 1025
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (427 KB) |  | HTML iconHTML  

    This paper proposes a novel model to address the energy-efficient traffic signal timing problem for a congested road network with heterogeneous users. In the proposed model, two types of agents, i.e., the authority and road users, are considered together with the interaction between traffic signal settings and energy policy (e.g., fuel surcharges). To model the route choice behavior of heterogeneous users, a multiclass stochastic traffic network equilibrium problem that considers vehicle delays at signalized intersections and travel demand elasticity is described and formulated as a variational inequality formulation. The authority aims to maximize social welfare of the transportation system by optimizing the traffic signal timings and fuel surcharges. A simulated-annealing-based solution algorithm is developed to solve the proposed model. The findings show that the implementation of the fuel surcharge policy can cause spatial and social inequity issues. View full abstract»

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  • Modeling and Simulating a Narrow Tilting Car Using Robotics Formalism

    Publication Year: 2014 , Page(s): 1026 - 1038
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    Modeling and simulation are fundamental tools to develop new urban vehicles. The aim of this work is to model and simulate a narrow urban tilting car, which should significantly decrease traffic congestion, pollution, and parking problems. The structure of the vehicle contains closed kinematic chains. The modeling approach is based on the modified Denavit and Hartenberg description, which is commonly used in robotics, by considering the vehicle as a mobile robot composed of a multibody poly-articulated system in which the terminal links are the wheels. This description allows automatic calculating of the symbolic expressions of the geometric, kinematic, and dynamic models. A simulator is developed with MATLAB/Simulink, and the simulation of different scenarios is performed and analyzed. View full abstract»

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  • Intelligent Trip Modeling for the Prediction of an Origin–Destination Traveling Speed Profile

    Publication Year: 2014 , Page(s): 1039 - 1053
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3188 KB) |  | HTML iconHTML  

    Accurate prediction of the traffic information in real time such as flow, density, speed, and travel time has important applications in many areas, including intelligent traffic control systems, optimizing vehicle operations, and the routing selection for individual drivers on the road. This is also a challenging problem due to dynamic changes of traffic states by many uncertain factors along a traveling route. In this paper, we present an Intelligent Trip Modeling System (ITMS) that was developed using machine learning to predict the traveling speed profile for a selected route based on the traffic information available at the trip starting time. The ITMS contains neural networks to predict short-term traffic speed based on the traveling day of the week, the traffic congestion levels at the sensor locations along the route, and the traveling time and distances to reach individual sensor locations. The ITMS was trained and evaluated by using ten months of traffic data provided by the California Freeway Performance Measurement System along a California Interstate I-405 route that is 26 mi long and contains 52 traffic sensors. The ITMS was also evaluated by the traffic data acquired from a 32-mi-long freeway section in the state of Michigan. Experimental results show that the proposed system, i.e., ITMS, has the capability of providing accurate predictions of dynamic traffic changes and traveling speed at the beginning of a trip and can generalize well to prediction of speed profiles on the freeway routes other than the routes the system was trained on. View full abstract»

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  • Research on a DSRC-Based Rear-End Collision Warning Model

    Publication Year: 2014 , Page(s): 1054 - 1065
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    Dedicated short-range communication (DSRC) is an emerging technology that allows vehicles to communicate with each other. The rear-end collision warning system based on DSRC has its unique advantages. However, there are problems (e.g., high rates of false alarms and missing alarms in emergency warnings) in the system due to uncertain measurement errors. In this paper, we propose to address the problems by establishing a robust rear-end collision warning model without using expensive high-end devices. Simulations have shown that high rates (up to 56%) of missing alarms occur in the vehicle kinematics (VK) model, as well as false alarms (most of which exceed 70%) in the VK model with maximum compensation (VK-MC). Pertaining to these rates, a novel model based on the neural network (NN) approach is implemented. Through training and validation, the NN model is able to provide emergency warnings with an improved performance of false alarm probability under 20% and the missing alarm probability under 10% for all test cases. View full abstract»

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  • Multilevel Modeling of the Traffic Dynamic

    Publication Year: 2014 , Page(s): 1066 - 1082
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2369 KB) |  | HTML iconHTML  

    Currently traffic management is becoming more important to achieve the goal of sustainable transport, and a good traffic model can describe the traffic behavior efficiently. The traffic models can be classified based on level of details as submicroscopic-, microscopic-, mesoscopic-, and macroscopic-level models. In this paper, we provide a review of the four types of models (submicro, micro, meso, and macro) and then propose a multilevel model of traffic, which combines submicroscopic, microscopic, and macroscopic levels of traffic model. In this work, we do not consider the mesoscopic-level model. At the submicroscopic level, we develop a bond graph model of a four-wheeled vehicle considering the longitudinal, lateral, yaw, and actuator dynamics. At the microscopic level, we develop a car-following model based on virtual interconnections between the submicroscopic bond graph models of vehicles. Then, at the macroscopic level, we deduce macroscopic variables (average speed, density, and flow) from the submicroscopic and microscopic models. Having a multilevel model of traffic allows combining two properties of modeling simulation, one in real-time mode at microscopic and submicroscopic levels and the other at offline mode at macroscopic level. Thus, the whole supervision of the road traffic can be performed. Finally, the multilevel model of traffic is validated on a real-time simulator of vehicle dynamics, based on experimental measurements acquired from intelligent autonomous vehicles (IAVs). In addition, real experiments on IAVs are performed to validate the model. View full abstract»

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  • Finite-State Markov Modeling for Wireless Channels in Tunnel Communication-Based Train Control Systems

    Publication Year: 2014 , Page(s): 1083 - 1090
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (928 KB) |  | HTML iconHTML  

    Communication-based train control (CBTC) is being rapidly adopted in urban rail transit systems, as it can significantly enhance railway network efficiency, safety, and capacity. Since CBTC systems are mostly deployed in underground tunnels and trains move at high speeds, building a train-ground wireless communication system for CBTC is a challenging task. Modeling the tunnel channels is very important in designing the wireless networks and evaluating the performance of CBTC systems. Most existing works on channel modeling do not consider the unique characteristics of CBTC systems, such as high mobility speed, deterministic moving direction, and accurate train-location information. In this paper, we develop a finite-state Markov channel (FSMC) model for tunnel channels in CBTC systems. The proposed FSMC model is based on real field CBTC channel measurements obtained from a business-operating subway line. Unlike most existing channel models, which are not related to specific locations, the proposed FSMC channel model takes train locations into account to have a more accurate channel model. The distance between the transmitter and the receiver is divided into intervals and an FSMC model is applied in each interval. The accuracy of the proposed FSMC model is illustrated by the simulation results generated from the model and the real field measurement results. View full abstract»

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  • Development and Evaluation of an Intelligent Energy-Management Strategy for Plug-in Hybrid Electric Vehicles

    Publication Year: 2014 , Page(s): 1091 - 1100
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1289 KB) |  | HTML iconHTML  

    There has been significant interest in plug-in hybrid electric vehicles (PHEVs) as a means to decrease dependence on imported oil and to reduce greenhouse gases as well as other pollutant emissions. One of the critical considerations in PHEV development is the design of its energy-management strategy, which determines how energy in a hybrid powertrain should be produced and utilized as a function of various vehicle parameters. In this paper, we propose an intelligent energy-management strategy for PHEVs. At the trip level, the strategy takes into account a priori knowledge of vehicle location, roadway characteristics, and real-time traffic conditions on the travel route from intelligent transportation system technologies in generating a synthesized velocity trajectory for the trip. The synthesized velocity trajectory is then used to determine battery's charge-depleting control that is formulated as a mixed-integer linear programming problem to minimize the total trip fuel consumption. The strategy can be extended to optimize vehicle fuel consumption at the tour level if a preplanned travel itinerary for the tour and the information about available battery recharging opportunities at intermediate stops along the tour are available. The effectiveness of the proposed strategy, both for the trip- and tour-based controls, was evaluated against the existing binary-mode energy-management strategy using real-world trip/tour examples in southern California. The evaluation results show that the fuel savings of the proposed strategy over the binary-mode strategy are around 10%-15%. View full abstract»

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  • Improving Group Transit Schemes to Minimize Negative Effects of Maritime Piracy

    Publication Year: 2014 , Page(s): 1101 - 1112
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (736 KB) |  | HTML iconHTML  

    Contemporary maritime piracy around the Horn of Africa presents a serious threat to the global shipping industry. A number of countermeasures were deployed to minimize the probability of a successful ship hijack, one of them being the establishment of the International Recommended Transit Corridor (IRTC). Currently, all ships transiting the Gulf of Aden are recommended to follow the IRTC and take part in group transit schemes (GTSs)-prescribed fixed schedules stating a time of arrival to the beginning of the corridor and a speed at which to sail through the corridor. We provide a number of contributions that improve the GTS: we formalize the grouping problem, we design an efficient algorithm able to compute optimal fixed GTSs with respect to the distribution of ships' speeds, we provide a real-world data set with speeds of ships transiting the IRTC, and we compare the optimal fixed schedules with the currently deployed schedule and quantify possible savings. Additionally, we propose on-demand GTSs-customized schedules for a group of arriving ships-that take into account speeds, risk aversion, and actual positions of arriving ships. We formulate the problem of the optimal on-demand grouping as a biobjective mixed integer program, and we compute a set of Pareto optimal solutions. We evaluate the scalability of the approach, the structure of the solution, and quantify an improvement over the current GTS with respect to the number of ships grouped and the time saved. View full abstract»

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  • GNSS Accuracy Improvement Using Rapid Shadow Transitions

    Publication Year: 2014 , Page(s): 1113 - 1122
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1482 KB) |  | HTML iconHTML  

    Receiver modules in Global Navigation Satellite Systems (GNSS) are capable of providing positioning and velocity estimations that are sufficiently accurate for the purpose of road navigation. However, even in optimal open-sky conditions, GNSS-based positioning carries an average error of 2-4 m. This imposes an effective limitation on GNSS-based vehicle lane detection, a desired functionality for various navigation and safety applications. In this paper, we present a novel framework for lane-level accuracy using GNSS devices and 3-D shadow matching. The suggested framework is based on detection and analysis of rapid changes in navigation satellites' signal strength, which are caused by momentary blockages due to utility and light poles. A method for detecting such momentary changes between line of sight and non line of sight is presented, followed by a geometric algorithm that improves location accuracy of commercial GNSS devices. We have tested the framework's applicability using both simulations and field experiments. We provide the results of these tests and discuss receiver-side sampling rate requirements for high-performance lane-level positioning. View full abstract»

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  • Two-Half-Barrier Level Crossings Versus Four-Half-Barrier Level Crossings: A Comparative Risk Analysis Study

    Publication Year: 2014 , Page(s): 1123 - 1133
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1080 KB) |  | HTML iconHTML  

    Safety is a key issue in railway operation. In this context, level crossings (LCs) are one of the most critical points in railway networks. In some countries, accidents at LC account for up to 50% of railway accidents. In this paper, we conduct a risk assessment comparative study involving two main types of Automatic Protection Systems (APSs), the first using a pair of half-barriers and the second with four half-barriers. So far, the choice of such LC protection systems has been exclusively done on the basis of qualitative expertise. The study we carry out here is based on some parameterizable behavioral models we have developed, which describe the global dynamics within the LC area. In contrast to existing studies on LC safety, our models take into account not only railway and road traffic but also the risk due to human factors while focusing on two major risky situations. The simulation results clearly show the potential risk with each of the investigated APSs, according to various features of the dynamics within the LC area. To the best of our knowledge, this is the first work dealing with a quantitative comparison between different types of LCs. The developed models can be easily accommodated in order to describe existing infrastructures. View full abstract»

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  • Sizing Finite-Population Vehicle Pools

    Publication Year: 2014 , Page(s): 1134 - 1144
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (630 KB) |  | HTML iconHTML  

    We refer to a vehicle pool as a number of vehicles at a single location used for the same purpose. We focus on the problem of sizing vehicle pools for a finite set of subscribers who can use the pool. Our goal is to minimize the number of vehicles in the pool while still meeting nearly all subscriber requests. Formally, we propose three analytical techniques to size a vehicle pool for a finite population of subscribers, according to the pools' busy period demand to guarantee all requests are served with probability 1 - ε, i.e., a quality-of-service (QOS) guarantee. Moreover, we propose an additional heuristic sizing method, which requires no prior data about pool demand. Although this method does not provide probabilistic bounds on QOS, we show in practice that it still achieves a high QOS. We evaluate our sizing methodologies using seven years of data from a local car share, using three performance metrics: availability (percentage of requests served), utilization (the percentage of time that vehicles in the pool are used) and member-to-vehicle ratio (the size of the pool relative to the size of its user population). We show that our methods perform well with respect to these metrics. View full abstract»

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  • Commuter Route Optimized Energy Management of Hybrid Electric Vehicles

    Publication Year: 2014 , Page(s): 1145 - 1154
    Cited by:  Papers (1)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1760 KB) |  | HTML iconHTML  

    Optimal energy management of hybrid electric vehicles requires a priori information regarding future driving conditions; the acquisition and processing of this information is nevertheless often neglected in academic research. This paper introduces a commuter route optimized energy management system, where the bulk of the computations are performed on a server. The idea is to identify commuter routes from historical driving data, using hierarchical agglomerative clustering, and then precompute an optimal solution to the energy management control problem with dynamic programming; the obtained solution can then be transmitted to the vehicle in the form of a lookup table. To investigate the potential of such a system, a simulation study is performed using a detailed vehicle model implemented in the Autonomie simulation environment for MATLAB/Simulink. The simulation results for a plug-in hybrid electric vehicle indicate that the average fuel consumption along the commuter route(s) can be reduced by 4%-9% and battery usage by 10%-15%. View full abstract»

    Open Access
  • Modeling and Analysis of an Infrastructure Service Request Queue in Multichannel V2I Communications

    Publication Year: 2014 , Page(s): 1155 - 1167
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1222 KB) |  | HTML iconHTML  

    This paper presents a concise yet comprehensive description of a multichannel vehicle-to-infrastructure communication system. Existing mathematical models for such a system overlook some of its essential behavioral characteristics such as the reneging, force termination, and, ultimately, blocking of service requests (SRs). Thus, the reported performance results obtained from these models seem to be unrealistically overoptimistic. Accordingly, in this paper, a multiserver queueing model is proposed for the purpose of accurately capturing the dynamics of the aforementioned communication system and evaluating its performance. The proposed model is renowned for its complexity and the nonexistence of closed-form analytical expressions that characterize its fundamental performance metrics. Hence, approximations were exploited as a means to enhance this model's mathematical tractability. Simulations are conducted in the context of a realistic scenario with the objective of validating the proposed approximate model, verifying its accuracy, and characterizing the system's performance in terms of several new metrics. The simulations' results indicate a cataclysmic SR blocking probability in the range of 65%-85%. 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.

Full Aims & Scope

Meet Our Editors

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