METHOD AND SYSTEM FOR LEARNING TRAFFIC EVENTS, AND USE OF THE SYSTEM

• US 20150317901A1
• Filed: 12/20/2013
• Published: 11/05/2015
• Est. Priority Date: 12/21/2012
• Status: Active Grant

• Current Assignee: Continental Teves AG & Co. OHG (Continental AG), Conti Temic Microelectronic GmbH (Continental AG)
• Original Assignee: Continental Teves AG & Co. OHG (Continental AG), Conti Temic Microelectronic GmbH (Continental AG)
• Inventors: Hegemann, Stefan, Sthlin, Ulrich
• Granted Patent: US 9,652,982 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G08G 1/0112 from the vehicle, e.g. floating car data [FCD]
• CPC Class Codes: G08G 1/0133 for classifying traffic situation
• CPC Class Codes: G08G 1/0141 for traffic information dissemination

Abstract

A method for learning traffic events, the traffic events being transmitted to a data network using vehicle-to-X communication. The traffic events include position data and time data assigned to the traffic events, and the traffic events are stored electronically in the data network. The method is characterized in that an individual storage duration is determined for each traffic event, and the traffic event is deleted from the data network after the storage duration expires. The invention further relates to a corresponding system and to the use thereof.

Claims

1. A method for learning traffic events, in which the traffic events are transmitted by vehicle-to-X communication to a data network, wherein the traffic events comprise position data and time data assigned to the traffic events and wherein the traffic events are retained electronically in the data network, wherein an individual retention period is defined for each traffic event and that the traffic event is deleted from the data network when the retention period expires.

2. The method as claimed in claim 1, wherein the traffic events describe hazard situations and the retention period is defined depending on a hazard factor and/or a frequency of the traffic event, wherein the retention period increases with increasing frequency and with an increasing hazard factor.

3. The method as claimed in claim 1, wherein a traffic event is not deleted if it describes a traffic accident.

4. The method as claimed in claim 1, wherein electronically retained traffic events of the same type, the position data and/or time data of which are not separated from one another by more than a spatial and/or temporal limit value, are combined to form a cumulated traffic event.

5. The method as claimed in claim 1, wherein the data network is a decentralized data network which comprises local network elements along a multiplicity of traffic routes.

6. The method as claimed in claim 5, wherein the traffic events are retained by the network elements which are located within a predefinable distance from the traffic events.

7. The method as claimed in claim 1, wherein the traffic events are detected by a multiplicity of vehicles by an environment sensor system and/or a driving state sensor system and are transmitted to the data network.

8. The method as claimed in claim 4, wherein the electronically retained traffic events and/or the cumulated traffic events are transmitted by vehicle-to-X communication to a vehicle if the vehicle comes within the predefinable distance to the traffic events.

9. The method as claimed in claim 5, wherein the network elements are mobile radio masts and/or traffic lights and/or traffic signs and/or beacons and/or marker posts and/or bridges and/or weather stations and/or separate infrastructure facilities.

10. The method as claimed in claim 1, wherein the traffic events are centrally retained and are retrievable via a database, are retrievable for route planning for vehicles.

11. The method as claimed in claim 1, wherein the plausibility of traffic events transmitted to the network is checked by traffic events retained in the data network before said traffic events are transmitted from the data network to the vehicle.

12. The method as claimed in claim 10, wherein traffic events detected by each of the multiplicity of vehicles are additionally retained electronically in each of the multiplicity of vehicles.

16. The method as claimed in claim 2, wherein a traffic event is not deleted if it describes a traffic accident.

13. A system for learning traffic events, comprising at least one electronic database, a multiplicity of vehicles which are equipped with vehicle-to-X communication means and with an environment sensor system and/or a driving state sensor system, and also a multiplicity of network elements of a data network which are arranged along a multiplicity of traffic routes and are equipped with vehicle-to-X communication means, wherein the multiplicity of vehicles detect traffic events by the environment sensor system and/or the driving state sensor system and transmit them by means of the vehicle-to-X communication means to the data network, wherein the traffic events comprise position data and time data assigned to the traffic events and wherein the at least one electronic database retains the traffic events electronically,

wherein evaluation means of the at least one electronic database define an individual retention period for each traffic event (212, 213, 214, 215) and that memory deletion means delete the traffic event (212, 213, 214, 215) from the at least one electronic database when the retention period expires.

14. The system as claimed in claim 13, wherein the system carries out a method for learning traffic events, in which the traffic events are transmitted by vehicle-to-X communication to a data network, wherein the traffic events comprise position data and time data assigned to the traffic events and wherein the traffic events are retained electronically in the data network, wherein an individual retention period is defined for each traffic event and that the traffic event is deleted from the data network when the retention period expires.

15. A use of the system as claimed in claim 13 for hazard warning in road traffic.

17. A use of the system as claimed in claim 14 for hazard warning in road traffic.