Fallback requests for autonomous vehicles

• US 10,796,581 B2
• Filed: 05/15/2019
• Issued: 10/06/2020
• Est. Priority Date: 05/26/2015
• Status: Active Grant

• Current Assignee: Waymo LLC (Alphabet Inc.)
• Original Assignee: Waymo LLC (Alphabet Inc.)
• Inventors: Herbach, Joshua Seth, Nemec, Philip, Fairfield, Nathaniel
• Primary Examiner(s): Rampuria, Satish
• Application Number:
  US16/412,944
• Publication Number:
  US 20190287409A1
• Time in Patent Office: 510 Days
• Field of Search: 718 1-108
• CPC Class Codes: B60W 2050/0005 Processor details or data handling, e.g. memory registers or chip architecture
• CPC Class Codes: B60W 2050/0006 Digital architecture hierarchy
• CPC Class Codes: B60W 2530/209 Fuel quantity remaining in tank
• CPC Class Codes: B60W 2556/45 External transmission of data to or from the vehicle
• CPC Class Codes: B60W 50/029 Adapting to failures or work around with other constraints, e.g. circumvention by avoiding use of failed parts
• CPC Class Codes: B60W 60/00253 Taxi operations
• CPC Class Codes: G05D 1/0088 characterized by the autonomous decision making process, e.g. artificial intelligence, predefined behaviours using knowledge based models G06N5/00
• CPC Class Codes: G05D 1/0297 by controlling means in a control room
• CPC Class Codes: G06F 9/46 Multiprogramming arrangements
• CPC Class Codes: G06F 9/4881 Scheduling strategies for dispatcher, e.g. round robin, multi-level priority queues
• CPC Class Codes: G06F 9/546 Message passing systems or structures, e.g. queues
• 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 1/202 Dispatching vehicles on the basis of a location, e.g. taxi dispatching

Abstract

Aspects of the present disclosure relate to a system having a memory, a plurality of self-driving systems for controlling a vehicle, and one or more processors. The processors are configured to receive at least one fallback task in association with a request for a primary task and at least one trigger of each fallback task. Each trigger is a set of conditions that, when satisfied, indicate when a vehicle requires attention for proper operation. The processors are also configured to send instructions to the self-driving systems to execute the primary task and receive status updates from the self-driving systems. The processors are configured to determine that a set of conditions of a trigger is satisfied based on the status updates and send further instructions based on the associated fallback task to the self-driving systems.

Claims

1. A system comprising one or more processors configured to:

store, in a memory, a fallback task including instructions for an autonomous vehicle to drive to a fueling or charging station;

store, in the memory, a corresponding trigger for the fallback task, wherein the corresponding trigger includes a threshold for a fuel or energy level of the autonomous vehicle;

receive status updates from one or more self-driving systems that control the autonomous vehicle to drive to the fueling or charging station;

determine that the corresponding trigger is satisfied based at least in part on the status updates;

determine a level of urgency for the corresponding trigger based on an amount of fuel or energy required for a current task being executed by the autonomous vehicle;

determine an execution time for the fallback task according to the level of urgency for the corresponding trigger;

determine a location of a particular fueling or charging station based on the execution time for the fallback task according to the level of urgency for the corresponding trigger; and

cause a given self-driving system of the one or more self-driving systems to control the autonomous vehicle according to the fallback task to drive to the particular fueling or charging station at the execution time.

2. The system of claim 1, wherein the one or more processors are configured to determine that the corresponding trigger is satisfied using an indicator that monitors the fuel or energy level of the autonomous vehicle.

3. The system of claim 1, wherein the one or more processors are further configured to set the threshold for the fuel or energy level based on a fuel or energy economy of the autonomous vehicle.

4. The system of claim 1, wherein the one or more processors are further configured to set the threshold for the fuel or energy level based on a density of fueling or charging stations around the autonomous vehicle.

5. The system of claim 1, further comprising the autonomous vehicle.

6. The system of claim 1, wherein the one or more processors are configured to determine a level of urgency for the corresponding trigger further based on whether the current task is passenger-related or non-passenger related.

7. The system of claim 6, wherein the one or more processors are configured to determine the execution time as a current time when the current task is non-passenger related, and the one or more processors are configured to determine the execution time for the fallback task is after completing the current task when the current task is passenger-related and the autonomous vehicle has enough fuel or energy to complete the current task and drive to a fueling or charging station.

8. A system comprising one or more processors configured to:

store, in a memory, a fallback task including instructions for an autonomous vehicle to drive to a parking spot;

store, in the memory, a corresponding trigger for the fallback task, wherein the corresponding trigger includes detecting that a current task being executed by the autonomous vehicle is completed;

receive status updates from one or more self-driving systems that control the autonomous vehicle to drive to the parking spot;

determine that the corresponding trigger is satisfied based at least in part on the status updates;

determine that the corresponding trigger has a level of urgency that indicates that the fallback task should not interrupt any task in a task queue;

determine an execution time for the fallback task according to the level of urgency for the corresponding trigger and whether any other tasks are in the task queue;

determine a location of a particular parking spot for the execution time based on a location of the autonomous vehicle at the execution time for the fallback task according to the level of urgency for the corresponding trigger; and

cause a given self-driving system of the one or more self-driving systems to control the autonomous vehicle according to the fallback task to drive to the particular parking spot at the execution time.

9. The system of claim 8, wherein the one or more processors are configured to detect that the current task is executed by the autonomous vehicle based on whether a passenger of the autonomous vehicle for a passenger-related task has been dropped off.

10. The system of claim 8, wherein the corresponding trigger indicates that a task queue is empty of all tasks.

11. The system of claim 8, wherein the one or more processors are configured to determine the location of the particular parking spot further based on a detection of an occupied status of one or more parking spots.

12. The system of claim 8, further comprising the autonomous vehicle.

13. A system comprising one or more processors configured to:

store, in a memory, a fallback task including instructions for an autonomous vehicle to drive to a maintenance depot;

store, in the memory, a corresponding trigger for the fallback task, wherein the corresponding trigger includes a sensor indication of a vehicle status that affects normal operation of the autonomous vehicle for one or more tasks;

receive status updates from one or more self-driving systems that control the autonomous vehicle to drive to the maintenance depot;

determine that the corresponding trigger is satisfied based at least in part on the status updates;

determine a level of urgency for the corresponding trigger based on the vehicle status;

determine an execution time for the fallback task according to the level of urgency for the corresponding trigger;

determine a location of a particular maintenance depot based on the execution time for the fallback task according to the level of urgency for the corresponding trigger; and

cause a given self-driving system of the one or more self-driving systems to control the autonomous vehicle according to the fallback task to drive to the particular maintenance depot at the execution time.

14. The system of claim 13, wherein the maintenance depot is for a sensor maintenance, and the sensor indication of the vehicle status indicates a degree of sensor degradation.

15. The system of claim 14, wherein the one or more processors are configured to determine the level of urgency based on a length of time or distance the autonomous vehicle can travel with the degree of sensor degradation.

16. The system of claim 15, wherein the one or more processors are configured to determine the level of urgency for the corresponding trigger indicates that the fallback task should be executed after a current task when the current task is passenger-related based when the length of time or distance is greater than required for the current task and driving to the maintenance depot.

17. The system of claim 13, wherein the maintenance depot is for replacing a tire, and the sensor indication of the vehicle status includes an amount of tire pressure that indicates a flat tire.

18. The system of claim 17, wherein the one or more processors are configured to determine the level of urgency based on a length of time or distance the autonomous vehicle can travel with the flat tire.

19. The system of claim 18, wherein the one or more processors are configured to determine the level of urgency for the corresponding trigger indicates that the fallback task should be executed immediately and interrupt any task being currently executed based on the length of time or distance the autonomous vehicle can travel with the flat tire.

20. The system of claim 13, further comprising the autonomous vehicle.