Providing autonomous vehicle maintenance
Systems and methods for providing autonomous vehicle assistance are disclosed. In one embodiment, a method is disclosed comprising detecting a service condition in response to a fault occurring at an autonomous vehicle at a first location; coordinating service with a nearby service provider, the service provider providing a time window and a second location; predicting that the autonomous vehicle will be free to fulfill the service; driving the autonomous vehicle to the second location of the service provider during the time window; and returning the autonomous vehicle to the first location after the service is completed.
1. A method comprising:
detecting, by a computing device, a service condition in response to a fault occurring at an autonomous vehicle at a first location;
coordinating, by the computing device, service with a nearby service provider, the service provider providing a time window and a second location;
transmitting, by the computing device, the time window to a predictive model to identify one or more available time periods of the autonomous vehicle;
determining, by the computing device, a suitable time period from the one or more available time periods, the suitable time period exceeding a predefined confidence level;
predicting, by the computing device, that the autonomous vehicle will be free to fulfill the service during the suitable time period;
driving, by the computing device, the autonomous vehicle to the second location of the service provider during the time window; and
returning, by the computing device, the autonomous vehicle to the first location after the service is completed.
2. The method of claim 1 , the detecting a service condition comprising:
setting a timer for a part of an autonomous vehicle, the timer comprising one of a mileage timer or a duration timer;
determining that the timer has expired; and
triggering the fault after the timer has expired.
3. The method of claim 1 , the detecting a service condition comprising:
monitoring the status of a part of the autonomous vehicle;
determining that the status of the part indicates a fault; and
triggering the fault after determining that a fault is likely.
4. The method of claim 1 , the detecting a service condition comprising:
receiving an interrupt from a sensor of the autonomous vehicle;
determining if the interrupt represents a critical event; and
triggering the fault after determining if the interrupt represents a critical event.
5. The method of claim 1 , the detecting a service condition comprising:
generating a predictive model of at least one part of the autonomous vehicle;
inputting status information of the at least one part into the predictive model; and
triggering the fault after determining if the output of the predictive model exceeds a predefined threshold.
6. The method of claim 1 , further comprising building a predictive model of autonomous vehicle availability using a time series of availability measurements.
7. The method of claim 6 , the predicting that the autonomous vehicle further comprising:
generating a candidate time series of availability measurements;
inputting the time series to the predictive model;
determining if a predicted availability measurement met exceeds a predefined confidence level; and
scheduling a pickup time based on the predicted availability.
8. The method of claim 1 , the service comprising one or more of part replacement, refueling, or manual assistance.
9. The method of claim 1 , the coordinating service with a nearby service provider further comprising:
generating a freshness indicator, the freshness indicator used to prevent a replay attack;
generating a session key;
generating a payload, the payload including the freshness indicator;
generating a signature by executing a message authentication code (MAC) algorithm using the session key and the payload;
generating a packet comprising the payload and the signature, the signature generated; and
transmitting the packet to the service provider.
10. A method comprising:
generating a freshness indicator, the freshness indicator comprising an incrementing message counter;
generating a session key based on a vehicle-specific key and the freshness indicator;
generating a payload, the payload including the freshness indicator;
generating a signature by executing a message authentication code (MAC) algorithm using the session key and the payload;
generating a packet comprising the payload and the signature, the signature generated;
transmitting the packet to the service provider to generate a time window;
transmitting the time window to a predictive model to identify one or more available time periods of an autonomous vehicle;
determining a suitable time period from the one or more available time periods, the suitable time period exceeding a predefined confidence level; and
predicting that the autonomous vehicle will be free to fulfill a service during the suitable time period.
11. The method of claim 10 , wherein the session key is re-calculated prior to at least one subsequent transmission of a packet.
12. A system comprising:
a processor; and
a storage medium for tangibly storing thereon program logic for execution by the processor, the stored program logic comprising:
logic, executed by the processor, for detecting a service condition in response to a fault occurring at an autonomous vehicle at a first location;
logic, executed by the processor, for coordinating service with a nearby service provider, the service provider providing a time window and a second location;
logic, executed by the processor, for transmitting the time window to a predictive model to identify one or more available time periods of the autonomous vehicle;
logic, executed by the processor, for determining a suitable time period from the one or more available time periods, the suitable time period exceeding a predefined confidence level;
logic, executed by the processor, for predicting that the autonomous vehicle will be free to fulfill the service during the suitable time period;
logic, executed by the processor, for driving the autonomous vehicle to the second location of the service provider during the time window; and
logic, executed by the processor, for returning the autonomous vehicle to the first location after the service is completed.
13. The system of claim 12 , the logic for detecting a service condition comprising:
logic, executed by the processor, for setting a timer for a part of an autonomous vehicle, the timer comprising one of a mileage timer or a duration timer;
logic, executed by the processor, for determining that the timer has expired; and
logic, executed by the processor, for triggering the fault after the timer has expired.
14. The system of claim 12 , the logic for detecting a service condition comprising:
logic, executed by the processor, for monitoring the status of a part of the autonomous vehicle;
logic, executed by the processor, for determining that the status of the part indicates a fault; and
logic, executed by the processor, for triggering the fault after determining that a fault is likely.
15. The system of claim 12 , the logic for detecting a service condition comprising:
logic, executed by the processor, for receiving an interrupt from a sensor of the autonomous vehicle;
logic, executed by the processor, for determining if the interrupt represents a critical event; and
logic, executed by the processor, for triggering the fault after determining if the interrupt represents a critical event.
16. The system of claim 12 , the logic for detecting a service condition comprising:
logic, executed by the processor, for generating a predictive model of at least one part of the autonomous vehicle;
logic, executed by the processor, for inputting status information of the at least one part into the predictive model; and
logic, executed by the processor, for triggering the fault after determining if the output of the predictive model exceeds a predefined threshold.
17. The system of claim 12 , further comprising logic, executed by the processor, for building a predictive model of autonomous vehicle availability using a time series of availability measurements.
18. The system of claim 17 , the logic for predicting that the autonomous vehicle further comprising:
logic, executed by the processor, for generating a candidate time series of availability measurements;
logic, executed by the processor, for inputting the time series to the predictive model;
logic, executed by the processor, for determining if a predicted availability measurement met exceeds a predefined confidence level; and
logic, executed by the processor, for scheduling a pickup time based on the predicted availability.
19. The system of claim 12 , the service comprising one or more of part replacement, refueling, or manual assistance.
20. The system of claim 12 , the logic for coordinating service with a nearby service provider further comprising:
logic, executed by the processor, for generating a freshness indicator;
logic, executed by the processor, for generating a session key;
logic, executed by the processor, for generating a payload, the payload including the freshness indicator;
logic, executed by the processor, for generating a signature by executing a message authentication code (MAC) algorithm using the session key and the payload;
logic, executed by the processor, for generating a packet comprising the payload and the signature, the signature generated; and
logic, executed by the processor, for transmitting the packet to the service provider.