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Intelligent Transportation Systems Magazine, IEEE

Issue 4 • Date winter 2011

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Displaying Results 1 - 17 of 17
  • [Front cover]

    Page(s): C1
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  • [Table of Contents]

    Page(s): 1
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  • Looking Back at Three Years of ITS Magazine [Editor's Column]

    Page(s): 2 - 3
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  • Employment Opportunities Solicitation

    Page(s): 3
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  • Probabilistic Analysis of Dynamic Scenes and Collision Risks Assessment to Improve Driving Safety

    Page(s): 4 - 19
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (4671 KB) |  | HTML iconHTML  

    The article deals with the analysis and interpretation of dynamic scenes typical of urban driving. The key objective is to assess risks of collision for the ego-vehicle. We describe our concept and methods, which we have integrated and tested on our experimental platform on a Lexus car and a driving simulator. The on-board sensors deliver visual, telemetric and inertial data for environment monitoring. The sensor fusion uses our Bayesian Occupancy Filter for a spatio-temporal grid representation of the traffic scene. The underlying probabilistic approach is capable of dealing with uncertainties when modeling the environment as well as detecting and tracking dynamic objects. The collision risks are estimated as stochastic variables and are predicted for a short period ahead with the use of Hidden Markov Models and Gaussian processes. The software implementation takes advantage of our methods, which allow for parallel computation. Our tests have proven the relevance and feasibility of our approach for improving the safety of car driving. View full abstract»

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  • Task-Based Environment Interpretation and System Architecture for Next Generation ADAS

    Page(s): 20 - 33
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2131 KB) |  | HTML iconHTML  

    State-of-the-art advanced driver assistance systems (ADAS) typically focus on single tasks and therefore, have clearly defined functionalities. Although said ADAS functions (e.g. lane departure warning) show good performance, they lack the general ability to extract spatial relations of the environment. These spatial relations are required for scene analysis on a higher layer of abstraction, providing a new quality of scene understanding, e.g. for inner-city crash prevention when trying to detect a Stop sign violation in a complex situation. Otherwise, it will be difficult for an ADAS to deal with complex scenes and situations in a generic way. This contribution presents a novel approach of task-dependent generation of spatial representations, allowing task-specific extraction of knowledge from the environment based on our biologically motivated ADAS. The approach also incorporates stored knowledge in form of digital map data, introducing a new way of eHorizon integration. Additionally, the hierarchy of the approach provides advantages when dealing with heterogeneous processing modules, a large number of tasks and additional new input cues. The results show the reliability of the approach and also the increase of performance on the system level. View full abstract»

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  • [Technical Committees]

    Page(s): 34
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  • ICVES'12

    Page(s): 35
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  • From the IEEE ITSS Committees Artificial Transportation Systems and Simulation Technical Activities Committee [Technical Committees]

    Page(s): 36 - 37
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  • Best Paper Awards from IEEE Intelligent Vehicles Symposium 2011 (IV'11) [Society News]

    Page(s): 38
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  • Intelligent Transportation Systems Society

    Page(s): 39
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  • IEEE International Transportation Forum Draws Participants from Five Continents [Society News]

    Page(s): 40 - 42
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  • Join a Community of Innovators

    Page(s): 41
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  • [Calendar]

    Page(s): 43
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  • IEEE Intelligent Transportation Systems Magazine Vol. 3 [2011 Index]

    Page(s): 44 - 46
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  • ITSC 2012

    Page(s): 47
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  • IEEE Intelligent Vehicles Symposium

    Page(s): C3
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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