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Intelligent Transportation Systems Magazine, IEEE

Issue 1 • Date Spring 2015

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Displaying Results 1 - 25 of 26
  • [Front cover]

    Publication Year: 2015 , Page(s): C1
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  • Call for Papers IEEE Intelligent Transportation Systems Magazine

    Publication Year: 2015 , Page(s): C2
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  • Table of contents

    Publication Year: 2015 , Page(s): 1 - 2
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  • Editorial Board

    Publication Year: 2015 , Page(s): 3
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  • A Growing Magazine for a Growing Society [Editor's Column]

    Publication Year: 2015 , Page(s): 3
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  • Connected and Automated Vehicles [President's Message]

    Publication Year: 2015 , Page(s): 4 - 5
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  • Employment Opportunities Solicitation

    Publication Year: 2015 , Page(s): 5
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  • Perception and Planning for Autonomous Vehicles [Guest Editorial]

    Publication Year: 2015 , Page(s): 6 - 7
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  • Special Issue on ITSC2013 [Guest Editorial]

    Publication Year: 2015 , Page(s): 7
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  • Physical Layer Aspects of Information Exchange in the NOTICE Architecture

    Publication Year: 2015 , Page(s): 8 - 18
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3411 KB)  

    Recently, Yan et al. [1] introduced NOTICE, a scalable, secure and privacy-aware architecture for the notification of traffic-related incidents, such as congestion and other similar events. NOTICE uses belts of piezo-electric elements embedded in the highways to detect variations in the characteristics of traffic flow. NOTICE uses very short-range wireless communications between vehicles and belts. In turn, these very short-range communications impose constraints on the time available for connection establishment and data exchange. While understanding the physical layer requirements for communication is key to a successful implementation of NOTICE, these requirements were not specifically addressed in [1]. The main goal of this work is to investigate physical layer requirements for successful communication in the NOTICE architecture. Our main contribution is to study the probabilities of establishing the wireless link and of successfully exchanging information between a belt and a vehicle passing over it. We derive analytical expressions for these probabilities as functions of several parameters such as the time available for handshaking/information exchange, average speed of the vehicle, data rate and amount of information to be exchanged between the vehicle and belt, and we evaluate their values for specific parameters corresponding to practical scenarios. Our results indicate that inexpensive short-range ZigBee radios, when combined with probabilistic data collection, are good candidates for the physical layer of NOTICE. View full abstract»

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  • Generation of Accurate Lane-Level Maps from Coarse Prior Maps and Lidar

    Publication Year: 2015 , Page(s): 19 - 29
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3399 KB)  

    While many research projects on autonomous driving and advanced driver support systems make heavy use of highly accurate maps covering large areas, there is relatively little work on methods for automatically generating such maps. These maps require accuracy in both the number of lanes and positioning of every lane, which we call lanelevel maps. Here, we present a method that combines coarse, inaccurate prior maps from OpenStreetMap (OSM) with local sensor information from 3D Lidar and a positioning system. We formulate a probabilistic model of lane structure using such information, and develop a number of tractable inference algorithms. These algorithms leverage the coarse structural information present in OSM, and integrates it with the highly accurate local sensor measurements. The resulting maps have extremely good alignment with manually constructed baseline maps generated for autonomous driving experiments. View full abstract»

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  • Map-Aided Evidential Grids for Driving Scene Understanding

    Publication Year: 2015 , Page(s): 30 - 41
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3858 KB)  

    Evidential grids have recently been shown to have interesting properties for mobile object perception. Possessing only partial information is a frequent situation when driving in complex urban areas, and by making use of the Dempster-Shafer framework, evidential grids are able to handle partial information efficiently. This article deals with a lidar perception scheme that is enhanced by geo-referenced maps used as an additional source of information in a multi-grid fusion framework. The paper looks at the key stages of such a data fusion process and presents an adaptation of the conjunctive combination rule for refining the analysis of conflicting information. This method relies on temporal accumulation to distinguish between stationary and moving objects, and applies contextual discounting for modeling information obsolescence. As a result, the method is able to better characterize the state of the occupied cells by differentiating moving objects, parked cars, urban infrastructure and buildings. Another advantage of this approach is its ability to separate the drivable from the non-drivable free space. Experiments carried out in real traffic conditions with a specially equipped car illustrate the performance of this approach. View full abstract»

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  • Experience, Results and Lessons Learned from Automated Driving on Germany's Highways

    Publication Year: 2015 , Page(s): 42 - 57
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (4437 KB)  

    The BMW Group Research and Technology has been testing automated vehicles on Germany's highways since Spring 2011. Since then, thousands of kilometers have been driven on the highways around Munich, Germany. Throughout this project, fundamental technologies, such as environment perception, localization, driving strategy and vehicle control, were developed in order to safely operate prototype automated vehicles in real traffic with speeds up to 130 km/h. The goal of this project was to learn what technologies are necessary for automated driving. This paper presents the architecture and algorithms developed during this project, results from real driving scenarios, the lessons learned throughout the project and a quick introduction into the latest developments for improving the system. View full abstract»

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  • The Flatbed Platoon Towing Model for Safe and Dense Platooning on Highways

    Publication Year: 2015 , Page(s): 58 - 68
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    Optimizing the inter-distances between vehicles is very important to reduce traffic congestion on highways. Variable spacing and constant spacing are the two policies for the longitudinal control of platoons. Variable spacing doesn't require a lot of data (position, speed...) from other vehicles, and string stability can be obtained using on-board information only. However, inter-vehicle distances are very large, and hence traffic density is low. Constant spacing offers string stability with high traffic density, but it requires data communication between the vehicles, at least from the leader. In this paper, a new platoon model and a modification of the variable spacing policy are proposed. This modification is effective to decrease the distances between the cars, making them nearly equal to the constant spacing policy. It also enables increasing string stability. This new approach doesn't require heavy communication between the vehicles. The new model is based on an unidirectional spring-damper model between vehicles, with the vehicles loaded on a virtual flatbed tow truck. From this configuration, conditions of stability and safety of a homogeneous platoon are derived. Based on this new model, a control has been derived and evaluated by simulation with a perfect system model using Matlab, and with a more realistic vehicle model using TORCS (The Open Racing Car Simulator). The simulation consists of a platoon of ten vehicles, moving on highways, with a desired inter-vehicle distance equal to 1 meter. The stability and the safety of the platoon are tested during platoon creation, changing the speed and emergency stop. The good results demonstrate the effectiveness of the new approach. View full abstract»

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  • Learning Driver Behavior Models from Traffic Observations for Decision Making and Planning

    Publication Year: 2015 , Page(s): 69 - 79
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    Estimating and predicting traffic situations over time is an essential capability for sophisticated driver assistance systems and autonomous driving. When longer prediction horizons are needed, e.g., in decision making or motion planning, the uncertainty induced by incomplete environment perception and stochastic situation development over time cannot be neglected without sacrificing robustness and safety. Building consistent probabilistic models of drivers interactions with the environment, the road network and other traffic participants poses a complex problem. In this paper, we model the decision making process of drivers by building a hierarchical Dynamic Bayesian Model that describes physical relationships as well as the driver's behaviors and plans. This way, the uncertainties in the process on all abstraction levels can be handled in a mathematically consistent way. As drivers behaviors are difficult to model, we present an approach for learning continuous, non-linear, context-dependent models for the behavior of traffic participants. We propose an Expectation Maximization (EM) approach for learning the models integrated in the DBN from unlabeled observations. Experiments show a significant improvement in estimation and prediction accuracy over standard models which only consider vehicle dynamics. Finally, a novel approach to tactical decision making for autonomous driving is outlined. It is based on a continuous Partially Observable Markov Decision Process (POMDP) that uses the presented model for prediction. View full abstract»

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  • SIMPATO - The Safety Impact Assessment Tool of interactive

    Publication Year: 2015 , Page(s): 80 - 90
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    One step in the development of safety oriented Advanced Driver Assistance Systems (ADAS) is an ex ante assessment of the expected safety impacts. This requires a careful analysis combining models and data from various sources. This paper describes the Safety IMPact Assessment Tool, called SIMPATO, that was developed in the interactIVe project. This tool performs "what if" analysis for accident scenarios to determine the effect of an ADAS on the outcome. The unique quality of the tool is that it requires very little data on the ADAS itself, and uses in-depth accident data to obtain a representative result. View full abstract»

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  • Driver Behavior Profiling Using Smartphones: A Low-Cost Platform for Driver Monitoring

    Publication Year: 2015 , Page(s): 91 - 102
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    Today's smartphones and mobile devices typically embed advanced motion sensors. Due to their increasing market penetration, there is a potential for the development of distributed sensing platforms. In particular, over the last few years there has been an increasing interest in monitoring vehicles and driving data, aiming to identify risky driving maneuvers and to improve driver efficiency. Such a driver profiling system can be useful in fleet management, insurance premium adjustment, fuel consumption optimization or CO2 emission reduction. In this paper, we analyze how smartphone sensors can be used to identify driving maneuvers and propose SenseFleet, a driver profile platform that is able to detect risky driving events independently from the mobile device and vehicle. A fuzzy system is used to compute a score for the different drivers using real-time context information like route topology or weather conditions. To validate our platform, we present an evaluation study considering multiple drivers along a predefined path. The results show that our platform is able to accurately detect risky driving events and provide a representative score for each individual driver. View full abstract»

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  • Managing Large Flows in Metro Stations: The New Year Celebration in Copacabana

    Publication Year: 2015 , Page(s): 103 - 113
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    Around 2 million visitors visit the beach of Copacabana in Rio de Janeiro on New Years Eve every year. More than 100,000 visitors travel by Metro. This creates large pedestrian flows inside the station causing major discomfort due to crowding. With the steady increase of the flows in recent years a crowd management plan has been developed and applied to mitigate crowding problems. The plan identified the station as an open system with a feedback mechanism (crowd-management). The station system itself is connected to other systems such as the station surroundings and the trains. An offline analysis before the event identified the individual capacities of the station components, their dynamic properties, mutual influences and dependency to other systems. As a follow-up of these analyses, six crowd-management measures were. These measures and a new crowd-management plan enforced during the operations improved the safety and comfort of pedestrians during the 2012-2013 event. The bottlenecks were better understood and anticipated by their capacity increased causing significantly less crowding in the station and allowing a rapid action of marshals when an emergency occurred. The improved results obtained using few aspects of systems suggest that a methodology based on system engineering could be developed to plan and assess large crowds events. View full abstract»

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  • Nikolas Geroliminis [ITS People]

    Publication Year: 2015 , Page(s): 114 - 124
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  • Transport & Planning at Delft University of Technology [ITS Research Lab]

    Publication Year: 2015 , Page(s): 116 - 118
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  • Join the IEEE Intelligent Transportation Systems Society

    Publication Year: 2015 , Page(s): 119
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  • IEEE 2014 ITS Award Announcement [Society News]

    Publication Year: 2015 , Page(s): 120 - 122
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  • IEEE 2014 ITSS Best Ph.D. Dissertation Award Announcement [Society News]

    Publication Year: 2015 , Page(s): 122
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  • ITSS Governance and Recent Elections [Society News]

    Publication Year: 2015 , Page(s): 124
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  • [Calendar]

    Publication Year: 2015 , Page(s): 126
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Aims & Scope

The IEEE Intelligent Transportation Systems Magazine (ITSM) publishes peer-reviewed articles that provide innovative research ideas and application results, report significant application case studies, and raise awareness of pressing research and application challenges in all areas of intelligent transportation systems. 

Full Aims & Scope

Meet Our Editors

Editor-in-Chief


Miguel Ángel Sotelo

Department of Computer Engineering

University of Alcalá