Methods and systems for predicting driving conditions

• US 10,066,961 B2
• Filed: 03/21/2017
• Issued: 09/04/2018
• Est. Priority Date: 04/04/2016
• Status: Active Grant

• Current Assignee: Direct Cursus Technology LLC
• Original Assignee: Yandex Europe AG (Yandex N.V.)
• Inventors: Korzunov, Anton Vasilyevich
• Primary Examiner(s): Marc-Coleman, Marthe Y
• Application Number:
  US15/464,398
• Publication Number:
  US 20170284824A1
• Time in Patent Office: 532 Days
• Field of Search: 701 49
• CPC Class Codes: B60K 2360/566 Mobile devices displaying vehicle information
• CPC Class Codes: B60K 35/80 Arrangements for controlling instruments
• CPC Class Codes: B60W 2552/00 Input parameters relating to infrastructure
• CPC Class Codes: B60W 2554/804 Relative longitudinal speed
• CPC Class Codes: B60W 2555/20 Ambient conditions, e.g. wind or rain
• CPC Class Codes: B60W 2556/45 External transmission of data to or from the vehicle
• CPC Class Codes: B60W 2556/50 of positioning data, e.g. GPS [Global Positioning System] data
• CPC Class Codes: B60W 50/14 Means for informing the driver, warning the driver or prompting a driver intervention
• CPC Class Codes: G01C 21/362 received from an external device or application, e.g. PDA, mobile phone or calendar application
• CPC Class Codes: G01C 21/3629 Guidance using speech or audio output, e.g. text-to-speech text to speech systems per se G10L13/00
• CPC Class Codes: G01C 21/3652 Guidance using non-audiovisual output, e.g. tactile, haptic or electric stimuli
• CPC Class Codes: G01C 21/3661 Guidance output on an external device, e.g. car radio
• CPC Class Codes: G01C 21/3667 Display of a road map G01C21/3614 takes precedence; guidance using 3D or perspective road maps G01C21/3635
• CPC Class Codes: G01C 21/3694 Output thereof on a road map
• CPC Class Codes: G01C 21/3697 Output of additional, non-guidance related information, e.g. low fuel level G01C21/3679 takes precedence

Abstract

A method and system for providing a predicted driving condition to an electronic device associated with a current vehicle having a current vehicle characteristic. The method is executable on a server and comprises receiving an indication of the current vehicle approaching a road segment and the current vehicle characteristic; identifying a preceding vehicle which has a time of travel along the road segment before a current time, a time difference between the preceding vehicle time of travel and the current time being within a predetermined range, the preceding vehicle having a preceding vehicle characteristic; determining the predicted driving condition for the road segment, the predicted driving condition being based on the current vehicle characteristic and the preceding vehicle characteristic; and providing to the electronic device before the current vehicle reaches the road segment, the predicted driving condition for the current vehicle on the road segment.

Claims

1. A method for providing a predicted driving condition to an electronic device, the electronic device being associated with a current vehicle having a current vehicle characteristic, the method executable on a server, the method comprising:

receiving, by the server, an indication of the current vehicle approaching a road segment and the current vehicle characteristic of the current vehicle;

identifying, by the server, at least one preceding vehicle which has a time of travel along the road segment which is before a current time, a time difference between the preceding vehicle time of travel and the current time being within an acceptable predetermined range, the preceding vehicle having a preceding vehicle characteristic;

determining, by the server, the predicted driving condition for the current vehicle for the road segment, the predicted driving condition being based on the current vehicle characteristic of the current vehicle and the preceding vehicle characteristic of the preceding vehicle; and

providing, by the server, to the electronic device associated with the current vehicle before the current vehicle reaches the road segment, the predicted driving condition for the current vehicle on the road segment.

2. The method of claim 1, further comprising obtaining a preceding vehicle performance of the at least one preceding vehicle along the road segment, and wherein the determining of the predicted driving condition for the current vehicle for the road segment is also based on the preceding vehicle performance of the preceding vehicle.

3. The method of claim 1, further comprising obtaining a current road condition at the time of receiving the indication of the current vehicle approaching the road segment, and wherein the determining of the predicted driving condition for the current vehicle for the road segment is also based on the current road condition.

4. The method of claim 1, further comprising obtaining a current weather condition at the time of receiving the indication of the current vehicle approaching the road segment, and wherein the determining of the predicted driving condition for the current vehicle for the road segment is also based on the current weather condition.

5. The method of claim 1, wherein the determining the predicted driving condition comprises inputting a current input comprising the current vehicle characteristic and the preceding vehicle characteristic into a machine-learning algorithm, the machine-learning algorithm having been trained on training inputs comprising datasets from a plurality of training vehicles which had traveled along the road segment, each dataset comprising, for a given training vehicle from the plurality of training vehicles, a training vehicle characteristic of the given training vehicle and a training vehicle performance of the given training vehicle whilst it had traveled along the road segment.

6. The method of claim 5, wherein each dataset has a time stamp representing a time when the given vehicle had traveled along the road segment, the machine-learning algorithm having been trained on datasets obtained within an acceptable predetermined time range of the time stamp relative to the current time.

7. The method of claim 5, wherein the plurality of datasets are from a plurality of vehicles traveling along a plurality of different road segments, each dataset including a geolocation of each one of the plurality of different road segments.

8. The method of claim 5, wherein at least one of the plurality of datasets includes at least one of:

a training road condition of the road segment whilst the given training vehicle was traveling along the road segment, a training weather condition at the road segment whilst the given training vehicle was traveling along the road segment.

9. The method of claim 5, wherein the training input also includes a weighting of a plurality of training vehicle characteristic parameters of the training vehicle characteristic and/or a weighting of a plurality of training vehicle performance parameters of the training vehicle performance.

10. The method of claim 1, further comprising determining by the server whether to send the predicted driving condition to the electronic device based on a trigger.

11. The method of claim 10, further comprising receiving, by the server, a current vehicle performance of the current vehicle, the current vehicle performance comprising a plurality of current vehicle performance parameters, wherein the trigger comprises at least one of the current performance parameters of the current vehicle being outside of a predetermined acceptable threshold range.

12. The method of claim 10, further comprising receiving, by the server, a current road condition of the road segment, the current road condition comprising a plurality of current road condition parameters, wherein the trigger comprises at least one of the current road condition parameters being outside of a predetermined acceptable threshold range.

13. The method of claim 10, further comprising receiving, by the server, a current weather condition at the road segment, the current weather condition comprising a plurality of current weather condition parameters, wherein the trigger comprises at least one of the current weather condition parameters being outside of a predetermined acceptable threshold range.

14. The method of claim 1, wherein the current road condition comprises at least one of the following parameters:

a temperature of a surface of the road segment, a continuity of a surface of the road segment, a grade of a surface of the road segment, a material of a surface of the road segment, and presence/extent of debris on a surface of the road segment.

15. The method of claim 1, wherein the current weather condition comprises at least one of the following parameters:

an air temperature, air pressure, air humidity, air quality, ultra-violet light levels, rain, snow, sleet, ice rain, fog, wind speed, wind direction, brightness levels, sun direction, glare, and shadow levels.

16. The method of claim 1, wherein the current vehicle performance and the preceding vehicle performance each comprise at least one of the following parameters:

a slippage of the vehicle, a speed of the vehicle, drifting of the vehicle, vibration of the vehicle, a pressure of a tyre of the vehicle, a pressure distribution in tyres of the vehicle, engine temperature, fuel consumption, a tipping of the vehicle, engine control unit (ECU) data, and sensor output data.

17. The method of claim 1, wherein the current vehicle characteristic and the preceding vehicle characteristic each comprise at least one of the following parameters:

vehicle manufacturer, vehicle model, vehicle year of manufacture, vehicle weight, vehicle dimensions, vehicle weight distribution, vehicle surface area, vehicle height, drive train type, tyre type, brake system, fuel system, mileage, vehicle identification number, and engine size.

18. The method of claim 1, wherein the predicted driving condition provided to the electronic device comprises an instruction to take a driving action, the instruction being at least one of:

reducing speed, increasing speed, maintaining speed, applying brakes, releasing brakes, stopping, taking an alternative route, switching gear, turning on/off headlights, adapting headlight angle, adapting the direction of travel, paying attention, and keeping a certain distance from a vehicle in front.

19. The method of claim 18, wherein the instruction comprises a command to display a visual representation of the driving action on a display of the electronic device and/or a command to communicate an audio representation of the driving action on the electronic device.

20. A computer-implemented system for providing a predicted driving condition to an electronic device, the electronic device being associated with a current vehicle having a current vehicle characteristic, the system comprising:

a receiver configured to receive an indication of the current vehicle approaching a road segment and the current vehicle characteristic of the current vehicle;

a processor configured to;

identify at least one preceding vehicle which has a time of travel along the road segment which is before a current time, a time difference between the preceding vehicle time of travel and the current time being within an acceptable predetermined range, the preceding vehicle having a preceding vehicle characteristic; and

determine by the server, the predicted driving condition for the current vehicle for the road segment, the predicted driving condition being based on the current vehicle characteristic of the current vehicle and the preceding vehicle characteristic of the preceding vehicle;

a transmitter for transmitting, to the electronic device associated with the current vehicle before the current vehicle reaches the road segment, the predicted driving condition for the current vehicle on the road segment.