Modifying a vehicle state based on the presence of a special-purpose vehicle

• US 8,838,321 B1
• Filed: 11/15/2012
• Issued: 09/16/2014
• Est. Priority Date: 11/15/2012
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Ferguson, David I.
• Primary Examiner(s): Tarcza, Thomas
• Assistant Examiner(s): Lee, Tyler J
• Application Number:
  US13/678,027
• Time in Patent Office: 670 Days
• Field of Search: 701/2, 701/23, 701/26, 701/27, 701/40, 701/41, 701/44, 701/77, 701/117, 701/150, 701/301, 701/411, 701445-450, 701/482, 701/514, 340/425.5, 340/435, 340/436, 340/438, 340/522, 340/901, 340/903, 702/150
• US Class Current: 701/23
• CPC Class Codes: B60W 10/04 including control of propulsion units
• CPC Class Codes: B60W 10/18 including control of braking systems
• CPC Class Codes: B60W 10/20 including control of steering systems
• CPC Class Codes: B60W 2050/146 Display means
• CPC Class Codes: B60W 2554/00 Input parameters relating to objects
• CPC Class Codes: B60W 2554/4023 large-size vehicles, e.g. trucks
• CPC Class Codes: B60W 2554/4041 Position
• CPC Class Codes: B60W 2710/18 Braking system
• CPC Class Codes: B60W 2710/20 Steering systems
• CPC Class Codes: B60W 2720/10 Longitudinal speed
• CPC Class Codes: B60W 30/18009 related to particular drive situations
• CPC Class Codes: B60W 30/18163 Lane change; Overtaking manoeuvres
• CPC Class Codes: B60W 50/14 Means for informing the driver, warning the driver or prompting a driver intervention
• CPC Class Codes: B60W 60/001 Planning or execution of driving tasks
• 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: 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 1/0214 in accordance with safety or protection criteria, e.g. avoiding hazardous areas monitoring the location of vehicles within a certain area, e.g. forbidden or allowed areas, in traffic control systems for road vehicles G08G1/13
• CPC Class Codes: G05D 1/0289 with means for avoiding collisions between vehicles vehicle fittings for automatically controlling speed including means for detecting potential obstacles B60K31/0008; avoiding obstacles by action on the steering system B62D; radar, sonar, lidar systems designed for anti-collision purposes G01S13/93, G01S15/93, G01S17/93
• CPC Class Codes: G06F 17/00 Digital computing or data processing equipment or methods, specially adapted for specific functions information retrieval, database structures or file system structures therefor G06F16/00

Abstract

A method is provided that includes receiving user input identifying a travel destination for a first vehicle, determining, by a processor, a first route for the first vehicle to follow, and configuring the first vehicle to follow the first route. The method further includes obtaining a model for a second vehicle that shares a road with the first vehicle and comparing model to a pre-determined template for a vehicle that is known to be a special purpose vehicle in order to determine whether the first template and the second template match. The method further includes determining, by the processor, a second route that leads to the travel destination, when a match is found to exist, and switching the first vehicle from following the first route to following the second route.

Claims

1. A method comprising:

determining, a first route for a first vehicle to follow, the first route is determined using a first value for a cost associated with a road section;

receiving sensor data from a sensor of the first vehicle;

generating from the sensor data a model representing a characteristic for a second vehicle that shares a road with the first vehicle;

comparing the model to a pre-determined template representing a characteristic for a vehicle that is known to be a special purpose vehicle in order to determine whether the model and the pre-determined template match to a threshold degree;

upon the model matching the pre-determined template to the threshold degree, determining, by a processor, onboard the first vehicle a second route that leads to a travel destination, the second route is determined by using a second value for the cost associated with the road section, the second value being different from the first value; and

switching the first vehicle from following the first route to following the second route.

2. The method of claim 1, wherein the second value for the cost is determined based on at least one of a type and a state of the second vehicle.

3. The method of claim 1, wherein the special purpose vehicle is one of a police car, ambulance, and a fire truck.

4. The method of claim 1, further comprising:

after determining that the second vehicle is a special-purpose vehicle, determining a state of the second vehicle;

wherein the first vehicle is switched from following the first route to following the second route based on the state of the second vehicle.

5. The method of claim 1, further comprising:

detecting, by the processor, a set of special-purpose vehicles;

wherein the first vehicle is switched to following the second route based on a number of special-purpose vehicles in the set.

6. The method of claim 1, wherein the characteristic for the vehicle that is known to be a special purpose vehicle includes at least one of a shape, a color, or a sound.

7. The method of claim 1, further comprising:

prompting, via a user interface of the processor, a user to approve of the first vehicle following the second route;

wherein the first vehicle is switched to following the second route only when user approval is received.

8. A method comprising:

receiving sensor data from a sensor of a first vehicle;

determining, by a processor, onboard the first vehicle a first operational context for the first vehicle based on environmental information for the first vehicle determined from the sensor data, the first operational context including a first plurality of control rules for governing the operation of the first vehicle in a first environment type, wherein the first environment type is determined based on a weighted value for the sensor data, the weighted value for the sensor data being used to generate a first probability value that the first vehicle is present in the first environment type;

operating the first vehicle within the first operational context;

generating from the sensor data a model representing a characteristic for a second vehicle that shares a road with the first vehicle;

comparing the model to a pre-determined template representing a characteristic for a vehicle that is known to be a special-purpose vehicle to determine whether the first model and the pre-determined template match to a threshold degree;

upon the model matching the pre-determined template to the threshold degree, determining a second environment type that is different from the first environment type based on a second weighted value for the sensor data, the second weighted value for the sensor data being used to generate a second probability value that the second vehicle is present in a second environment type; and

determining the environment type based on a comparison of the first probability value and the second probability value;

in response to the determination of the environment type, switching the first vehicle from operating within the first operational context to operating within a second operational context, the second operational context including a second plurality of control rules for governing the operation of the first vehicle in a second environment type, the second plurality of control rules being different from the first plurality of control rules.

9. The method of claim 8, wherein:

the special-purpose vehicle is a construction vehicle; and

wherein the second plurality of rules govern the operation of the first vehicle safely in construction zones.

10. The method of claim 9, wherein switching the first vehicle to operating within the second operational context includes modifying the a weighted value for the sensor data and re-estimating, based on the modified weighted value, the probability of the first vehicle being present in the second type of environment.

11. The method of claim 10, wherein the weighted value for the sensor data is modified based on one of a type and a state of the second vehicle.

12. The method of claim 8, further comprising:

determining a state of the second vehicle; and

determining the second operational context based on the state of the second vehicle.

13. The method of claim 8, further comprising:

detecting a set of special purpose vehicles;

determining the second operational context based a number of special-purpose vehicles of the set.

14. The method of claim 8, wherein the characteristic for the vehicle that is known to be a special purpose vehicle includes at least one of a shape, a color, or a sound.

15. The method of claim 8, wherein second plurality of control rules for governing the operation of the first vehicle include a rule for determining a speed of the first vehicle, and operating within the second operational context includes adjusting the speed of the first vehicle.

16. The method of claim 8, wherein second plurality of control rules for governing the operation of the first vehicle include a rule for determining a direction of travel of the first vehicle, and operating within the second operational context includes adjusting the direction of travel for the first vehicle.

17. A system comprising:

a processor onboard a first vehicle, the processor being configured to;

determine a first route for a first vehicle to follow, the first route is determined using a first value for the cost associated with a road section;

receive sensor data from a sensor of the first vehicle;

generate from the sensor data a model representing a characteristic for a second vehicle that shares a road with the first vehicle;

compare the model to a pre-determined template representing a characteristic for a vehicle that is known to be a special purpose vehicle in order to determine whether the model and the pre-determined template match to a threshold degree;

upon the model matching the pre-determined template to the threshold degree, determine a second route that leads to a travel destination, the second route is determined by using a second value for the cost associated with the road section, the second value being different from the first value; and

switch the first vehicle from following the first route to following the second route.

18. A system comprising:

a processor onboard a first vehicle, the processor being configured to;

receive sensor data from a sensor of the first vehicle;

determine a first operational context for the first vehicle based on environmental information for the first vehicle determined from the sensor data, the first operational context including a first plurality of control rules for governing the operation of the first vehicle in a first environment type, wherein the first environment type is determined based on a weighted value for the sensor data, the weighted value for the sensor data being used to generate a first probability value that the first vehicle is present in the first environment type;

operate the first vehicle within the first operational context;

generate from the sensor data a model representing a characteristic for a second vehicle that shares a road with the first vehicle;

compare the model to a pre-determined template representing a characteristic for a vehicle that is known to be a special-purpose vehicle to determine whether the model and the pre-determined template match to a threshold degree;

upon the model matching the pre-determined template to the threshold degree, determining a second environment type that is different from the first environment type based on a second weighted value for the sensor data, the second weighted value for the sensor data being used to generate a second probability value that the second vehicle is present in a second environment type; and

in response to the determination of the environment type, switch the first vehicle from operating within the first operational context to operating within a second operational context, the second operational context including a second plurality of control rules for governing the operation of the first vehicle in a second environment type, the second plurality of control rules being different from the first plurality of control rules.