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Joint Meeting Panagiotis Lytrivis ( panagiotis.lytrivis@iccs.gr )

Joint Meeting Panagiotis Lytrivis ( panagiotis.lytrivis@iccs.gr ) George Vafeiadis ( gvaf @iccs.gr ) ICCS. SP1-SP4. Outline. Status of the deliverables (D1.4.2 & D1.5.1) Performance of SR cycle (timing diagrams) Status of SR algorithms (implementation). Status of the deliverables.

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Joint Meeting Panagiotis Lytrivis ( panagiotis.lytrivis@iccs.gr )

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  1. Joint Meeting Panagiotis Lytrivis (panagiotis.lytrivis@iccs.gr) George Vafeiadis (gvaf@iccs.gr) ICCS SP1-SP4

  2. Outline • Status of the deliverables (D1.4.2 & D1.5.1) • Performance of SR cycle (timing diagrams) • Status of SR algorithms (implementation)

  3. Status of the deliverables • D1.4.2 • Executive summary changes • Under review from Christian • Some information is still not sufficient (e.g. test sites description) • D1.5.1 • Finalize first the D1.4.2 • Include usage of MARS and update the test cases? • Criteria for evaluation & validation (indicators) • Template in compliance with MMSE? • Number and quality of test cases sufficient? • BOSCH, CRF, VOLVO, IBEO, ICCS • CONTINENTAL, RENAULT, PIAGGIO, MMSE?

  4. SR status report • Working on fog detection and traffic estimation modules (Bayesian Networks) • AlongRoadElement table for Ego, other vehicles. • Benchmarking of SR modules and queries to the LDM • LDM queries time consuming • SafeFusion simulator (update, integration of other modules) • MARS successfully connected to the LDM (own scenarios?) • Paper for the ITS in Stockholm 2009

  5. Query performance (1 query/vehicle)

  6. Notes about LDM testing Main PC - eBox638-FL • The LDM had only the static map features and randomly positioned vehicles (no other data) • No other process (e.g. applications or IP) were connected and using the LDM • Multiple threads usage investigated

  7. New Proposed Internal Architecture SR SR module Thread-1: Ego Vehicle (path prediction, maneuver, etc) Thread-2: other vehicle (path prediction, maneuver, etc) . . . OR module IP/LDM Thread-n: other vehicle (path prediction, maneuver, etc) Thread n+1: Fog Detection Thread n+2: Traffic Estimation

  8. Path prediction performance

  9. MARS & Simulation • MARS successfully connected with LDP and in turn with LDM (observation of the changes in the LDM table egomotorvehicle) • How to run our own scenarios? • The incorporation of Orbassano track in MARS would be helpful

  10. Bayesian Network Season Fog (t-1) temperature Fog (t) fog light speed VANET info

  11. Hugin BN

  12. Paper to be submitted to ITS 2009

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