Global Patent Index - EP 2610836 A1

EP 2610836 A1 20130703 - Device and method for the on-line prediction of the driving cycle in an automotive vehicle

Title (en)

Device and method for the on-line prediction of the driving cycle in an automotive vehicle

Title (de)

Verfahren und Vorrichtung zur Online-Vorhersage des Fahrzyklus in einem Automobil

Title (fr)

Dispositif et procédé pour la prédiction en ligne du cycle d'entraînement dans un véhicule automobile

Publication

EP 2610836 A1 20130703 (EN)

Application

EP 12382494 A 20121212

Priority

ES 201132144 A 20111230

Abstract (en)

The invention relates to a device and method for the on-line prediction of the driving cycle in an automotive vehicle. The method comprises: - a step of data pre-processing (200): €¢ receiving the vehicle speed (V sp ); €¢ receiving traffic information (HTI) of the expected path in a prediction horizon (H); €¢ obtaining (212) a reference driving cycle (V pat ); €¢ calculating (208) the deviation ( DV sp ) of the speed (V sp ) with respect to the reference driving cycle (V pat ); - a step of data processing by means of a neural network (202) for recursively obtaining the expected deviations ( D * V sp ) for the prediction horizon (H); - a step of data post-processing (204) which comprises obtaining the estimated speed (V* sp ) for said prediction horizon (H) from the expected deviations (D*V sp ) and the reference driving cycle (V pat ) for the prediction horizon (H).

IPC 8 full level

G08G 1/01 (2006.01)

CPC (source: EP ES)

G08G 1/0129 (2013.01 - EP ES)

Citation (applicant)

  • KIENCKE; NIELSEN, ROAD AND DRIVER MODELS, 2005
  • BOYRAZ, P.; SATHYANARAYANA, A.; HANSEN, J. H.: "Driver behavior modeling using hybrid dynamic systems for 'driver-aware' active vehicle safety", ESV) ENHANCED SAFETY FOR VEHICLES, 2009, pages 13 - 15
  • PANOU, M.; BEKIARIS, E.; PAPAKOSTOPOULOS, V.: "Modelling Driver Behaviour in Automotive Environments", 2007, SPRINGER, article "Modelling Driver Behaviour in European Union and International Projects", pages: 3 - 25
  • KIENCKE, U.; NIELSEN, L.: "Automotive Control ' Systems", 2005, SPRINGER, article "Road and Driver Models", pages: 425 - 464
  • ABE, M.: "Vehicle Handling Dynamics", 2009, EI SEVIER
  • KHODAYARI, A.; GHAFFARI, A.; AMELI, S.; FLAHATGAR, J., A HISTORICAL REVIEW ON LATERAL AND LONGITUDINAL CONTROL OF AUTONOMOUS VEHICLE MOTIONS, 2010, pages 421 - 429
  • FERNANDEZ, A., SIMULACIÓN DEL COMPORTAMIENTO DE LOS CONDUCTORES MEDIANTE AGENTES INTELIGENTES, 2010
  • FROBERG, A.; NIELSEN, L.: "Efficient Drive Cycle Simulation", VEHICULAR TECHNOLOGY, IEEE TRANSACTIONS, vol. 57, 2008, pages 1442 - 1453, XP011201857
  • MURPHEY, Y.: "Computational Intelligence in Automotive Applications", vol. 132, 2008, SPRINGER, article "Intelligent Vehicle Power Management - An Overview", pages: 223 - 251
  • LANGARI, R.; WON, J.-S.: "Intelligent energy management agent for a parallel hybrid vehicle-part I: system architecture and design of the driving situation identification process", VEHICULAR TECHNOLOGY, IEEE TRANSACTIONS, vol. 54, 2005, pages 925 - 934, XP011132647, DOI: doi:10.1109/TVT.2005.844685
  • MURPHEY, Y.; CHEN, Z. H; KILIARIS, L.; PARK, J.; KUANG, M.; MASRUR, A. ET AL., NEURAL LEARNING OF DRIVING ENVIRONMENT PREDICTION FOR VEHICLE POWER MANAGEMENT., 2008, pages 3755 - 3761
  • PARK, J.; CHEN, Z.; KILIARIS, L.; KUANG, M.; MASRUR, M.; PHILLIPS, A. ET AL.: "Intelligent Vehicle Power Control Based on Machine Learning of Optimal Control Parameters and Prediction of Road Type and Traffic Congestion", VEHICULAR TECHNOLOGY, IEEE TRANSACTIONS, vol. 58, 2009, pages 4741 - 4756, XP011270604, DOI: doi:10.1109/TVT.2009.2027710
  • HUANG, X.; TAN, Y.; HE, X: "An Intelligent Multifeature Statistical Approach for the Discrimination of Driving Conditions of a Hybrid Electric Vehicle", INTELLIGENT TRANSPORTATION SYSTEMS, IEEE TRANSACTIONS, 2010, pages 1 - 13
  • MONTAZERI-GH, M.; AHMADI, A.; ASADI, M., DRIVING CONDITION RECOGNITION FOR GENETIC FUZZY HEV CONTROL, 2008, pages 65 - 70
  • KOOT, M.; KESSELS, J.; JAGER, B. D.; HEEMELS, W.; DEN, P. V.; STEINBUCH, M.: "Energy management strategies for vehicular electric power systems", VEHICULAR TECHNOLOGY, IEEE TRANSACTIONS ON, vol. 54, 2005, pages 771 - 782, XP011132632, DOI: doi:10.1109/TVT.2005.847211

Citation (search report)

  • [Y] DE 10062856 A1 20020620 - DAIMLER CHRYSLER AG [DE]
  • [Y] WO 2010095357 A1 20100826 - AISIN AW CO [JP], et al
  • [YD] YI L MURPHEY ET AL: "Neural learning of driving environment prediction for vehicle power management", NEURAL NETWORKS, 2008. IJCNN 2008. (IEEE WORLD CONGRESS ON COMPUTATIONAL INTELLIGENCE). IEEE INTERNATIONAL JOINT CONFERENCE ON, IEEE, PISCATAWAY, NJ, USA, 1 June 2008 (2008-06-01), pages 3755 - 3761, XP031328073, ISBN: 978-1-4244-1820-6
  • [YD] JUNGME PARK ET AL: "Intelligent Vehicle Power Control Based on Machine Learning of Optimal Control Parameters and Prediction of Road Type and Traffic Congestion", IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, IEEE SERVICE CENTER, PISCATAWAY, NJ, US, vol. 58, no. 9, 1 November 2009 (2009-11-01), pages 4741 - 4756, XP011270604, ISSN: 0018-9545, DOI: 10.1109/TVT.2009.2027710

Designated contracting state (EPC)

AL AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO PL PT RO RS SE SI SK SM TR

Designated extension state (EPC)

BA ME

DOCDB simple family (publication)

EP 2610836 A1 20130703; EP 2610836 B1 20150218; ES 2411629 A2 20130705; ES 2411629 B1 20140311; ES 2411629 R1 20130828; ES 2535689 T3 20150513

DOCDB simple family (application)

EP 12382494 A 20121212; ES 12382494 T 20121212; ES 201132144 A 20111230