Context-aware vehicle communications system and control logic with adaptive crowd-sensing capabilities

• US 10,330,486 B2
• Filed: 08/08/2017
• Issued: 06/25/2019
• Est. Priority Date: 08/08/2017
• Status: Active Grant

• Current Assignee: GM Global Technology Operations LLC (General Motors Company)
• Original Assignee: GM Global Technology Operations LLC (General Motors Company)
• Inventors: Grimm, Donald K., Bai, Fan, Bojanowski, David E., Tsimhoni, Omer
• Primary Examiner(s): Soofi, Yazan A
• Application Number:
  US15/671,935
• Publication Number:
  US 20190049262A1
• Time in Patent Office: 686 Days
• Field of Search: 701418
• CPC Class Codes: G01C 21/3415 Dynamic re-routing, e.g. recalculating the route when the user deviates from calculated route or after detecting real-time traffic data or accidents
• CPC Class Codes: G01C 21/3484 Personalized, e.g. from learned user behaviour or user-defined profiles
• CPC Class Codes: G01C 21/3492 employing speed data or traffic data, e.g. real-time or historical traffic control systems for road vehicles involving transmission of navigation instructions to the vehicle G08G1/0968
• CPC Class Codes: G01C 21/3697 Output of additional, non-guidance related information, e.g. low fuel level G01C21/3679 takes precedence
• CPC Class Codes: G07C 5/004 Indicating the operating range of the engine economical driving B60R16/0236, F02B77/084; measuring liquid fuel of an engine G01F9/00
• CPC Class Codes: G07C 5/008 communicating information to a remotely located station transmission systems for measured values G08C
• CPC Class Codes: G08G 1/00 Traffic control systems for road vehicles arrangement of road signs or traffic signals E01F9/00 ; automatic vehicle control B62D
• CPC Class Codes: G08G 1/0112 from the vehicle, e.g. floating car data [FCD]
• CPC Class Codes: G08G 1/0129 for creating historical data or processing based on historical data
• CPC Class Codes: G08G 1/0141 for traffic information dissemination
• CPC Class Codes: G08G 1/096716 where the received information does not generate an automatic action on the vehicle control
• CPC Class Codes: G08G 1/096775 where the origin of the information is a central station
• CPC Class Codes: H04W 4/80 Services using short range communication, e.g. near-field communication [NFC], radio-frequency identification [RFID] or low energy communication
• CPC Class Codes: H04W 4/90 Services for handling of emergency or hazardous situations, e.g. earthquake and tsunami warning systems [ETWS]

Abstract

Disclosed are vehicle communications networks for adapting user information using crowd-sensed contextual data, computer-executable instructions for provisioning such content/information, and vehicles equipped with a telematics system for adapting driver information using contextual data from vehicle participatory sensing systems. A disclosed method for provisioning information to occupants of a motor vehicle includes determining trip characteristics, including vehicle and driver data, for a current trip of the vehicle, and determining trip characteristics for previous trips that correspond to the current trip. The vehicle'"'"'s communications system receives, over a distributed computer network from a vehicle participatory sensing system aggregating data from participative vehicles, operational data for the current trip as sensed by the participative vehicles. The received operational data is analyzed with the current and previous trip characteristics to determine a predicted trip duration and/or a predicted trip route. An electronic user interface of the vehicle outputs the predicted trip duration and/or route.

Claims

1. A method for controlling operation of a motor vehicle, the motor vehicle including a prime mover, a sensor, an electronic user interface (EUI), a vehicle controller governing operation of the EUI, and a vehicle communications system wirelessly connecting the vehicle controller and EUI to a distributed computer network, the method comprising:

determining, via the vehicle controller based on a signal received from the sensor, if the prime mover of the motor vehicle is in an on state;

determining, via the vehicle controller responsive to the prime mover being in the on state, current trip characteristics, including start and destination locations, real-time vehicle data specific to the motor vehicle, and driver data specific to a driver of the motor vehicle, for a current trip of the motor vehicle;

determining, via the vehicle controller, previous trip characteristics including respective duration data and routing data for each of one or more previous trips of the motor vehicle corresponding to the current trip;

receiving, via the vehicle communications system over the distributed computer network from a vehicle participatory sensing system aggregating data from multiple participative vehicles, operational data, including road surface conditions, traffic conditions, and unexpected driving scenarios, for the current trip as sensed by the participative vehicles;

analyzing the received operational data with the current trip characteristics and the previous trip characteristics to determine a predicted trip duration and/or a predicted trip route; and

directing, via the vehicle controller, a safety system of the motor vehicle to change safety settings and/or the EUI to output to the driver of the motor vehicle the predicted trip duration and/or trip route determined from the analyzed operational data.

2. The method of claim 1, further comprising adapting a data fidelity and/or a data sampling frequency of the received operational data based on a determined user expectation of the driver of the motor vehicle and/or a determined aggregate expectation of a group of the participative vehicles.

3. The method of claim 1, further comprising adapting a presentation of the predicted trip duration and/or trip route based on a time context data and/or a location context data, the time context data including a designation of the current trip as either rush hour or midday and either nighttime or daytime, and the location context data including a designation of the current trip as either on commute or off commute and either familiar or unfamiliar.

4. The method of claim 1, wherein the operational data further includes ambient lighting conditions data, weather conditions data, and/or driving intersection data collected by the participative vehicles.

5. The method of claim 1, wherein the vehicle data includes respective operating states for one or more vehicle systems of the motor vehicle during the current trip.

6. The method of claim 1, wherein the driver data includes respective operating characteristics for one or more driving variables of the driver during the current trip.

7. The method of claim 1, wherein the driver data includes an indication that the driver is either a defensive or aggressive driver, either tends to speed or not speed, and/or a number of driving violations for the driver.

8. The method of claim 1, wherein the current trip characteristics for the current trip of the motor vehicle further include a start time, an intended route to reach the destination location from the start location, and/or a current location of the motor vehicle.

9. The method of claim 1, wherein the previous trip characteristics include a respective start time, a respective start location, a respective trip duration and/or a respective destination location for each of a plurality of the previous trips taken by the driver with the motor vehicle.

10. The method of claim 1, further comprising:

receiving, via the vehicle communications system from the vehicle participatory sensing system, historical trip duration data corresponding to the current trip as sensed by the participative vehicles; and

directing the EUI to output to the driver of the motor vehicle an indication of whether the current trip of the motor vehicle is predicted to be early, on time, or late based on a comparison of the historical trip duration data and the predicted trip duration.

11. The method of claim 10, further comprising:

responsive to the current trip of the motor vehicle being predicted to be early, directing the EUI to output to the driver of the motor vehicle an opportunistic route diversion; and

responsive to the current trip of the motor vehicle being predicted to be late, directing the EUI to output to the driver of the motor vehicle a calming measure, modifying operation a vehicle system to implement increased protection measures, and/or delaying presentation of non-critical information to the driver by the EUI.

12. The method of claim 1, wherein the analyzing includes aggregating the received operational data, current trip characteristics, and previous trip characteristics, filtering the aggregated data, and purging select portions of the aggregated data.

13. The method of claim 1, wherein the EUI is an audiovisual (AV) telematics unit mounted inside a passenger compartment of the motor vehicle, and wherein outputting the predicted trip duration and/or trip route is via the AV telematics unit.

14. A motor vehicle comprising:

a vehicle body with a passenger compartment;

a prime mover including an engine and/or a motor;

an audiovisual (AV) telematics unit mounted within the passenger compartment and operable to transmit audio and/or video information to a driver of the motor vehicle;

a vehicle communications system mounted to the vehicle body and operable to wirelessly connect the AV telematics unit to a distributed computer network; and

an AV electronic control unit (ECU) communicatively connected to the AV telematics unit and the vehicle communications system, the AV ECU being programmed to;

determine, via a signal received from a sensor, if the prime mover is in an on state;

responsive to the prime mover being in the on state, determine current trip characteristics, including start and destination locations, real-time vehicle data specific to the motor vehicle, and driver data specific to the driver of the motor vehicle, for a current trip of the motor vehicle;

determine previous trip characteristics including respective duration data and routing data for each of multiple previous trips of the motor vehicle corresponding to the current trip;

receive, via the vehicle communications system from a vehicle participatory sensing system aggregating data from multiple participative vehicles, operational data, including road surface conditions, traffic conditions, and unexpected driving scenarios, for the current trip as sensed by the participative vehicles;

analyze the received operational data with the current trip characteristics and the previous trip characteristics to determine a predicted trip duration and/or a predicted trip route; and

direct a safety system of the motor vehicle to change safety settings and/or the AV telematics unit to output to the driver of the motor vehicle the predicted trip duration and/or trip route determined from the analyzed operational data.

15. The motor vehicle of claim 14, wherein the AV ECU is further programmed to adapt a data fidelity and/or a data sampling frequency of the received operational data based on a determined user expectation of the driver of the motor vehicle and/or a determined aggregate expectation of a group of the participative vehicles.

16. The motor vehicle of claim 14, wherein the AV ECU is further programmed to adapt a presentation of the predicted trip duration and/or trip route based on a time context data and/or a location context data, the time context data including a designation of the current trip as either rush hour or midday and either nighttime or daytime, and the location context data including a designation of the current trip as either on commute or off commute and either familiar or unfamiliar.

17. The motor vehicle of claim 14, wherein the operational data further includes ambient lighting conditions data, weather conditions data, and/or driving intersection data collected by the participative vehicles.

18. The motor vehicle of claim 14, wherein the vehicle data includes respective operating states for one or more vehicle systems of the motor vehicle during the current trip, and wherein the driver data includes respective operating characteristics for one or more driving variables of the driver during the current trip.

19. The motor vehicle of claim 14, wherein the AV ECU is further programmed to:

receive, via the vehicle communications system from the vehicle participatory sensing system, historical trip duration data corresponding to the current trip as sensed by the participative vehicles; and

display, via AV telematics unit, an indication that the current trip of the motor vehicle is predicted to be either early, on time, or late based on a comparison of the historical trip duration data and the predicted trip duration.

20. The motor vehicle of claim 19, wherein the AV ECU is further programmed to:

responsive to the current trip of the motor vehicle being predicted to be early, display, via AV telematics unit, an opportunistic route diversion; and

responsive to the current trip of the motor vehicle being predicted to be late, display, via AV telematics unit, a calming measure, modifying operation a vehicle system to implement increased protection measures, and/or delaying presentation of non-critical information to the driver by the AV telematics unit.