Bus detection for an autonomous vehicle

1. A method comprising:

using, by one or more processors of a computing device, image data indicative of one or more vehicles in an environment to select a vehicle from the one or more vehicles to be a candidate school bus;

based on the selection of the vehicle to be the candidate school bus, the one or more processors comparing an estimated size of the vehicle to information indicative of a size of a school bus;

based on the estimated size of the vehicle being within a threshold size of the size of the school bus, the one or more processors comparing a color of the vehicle to a color of a given school bus; and

based on the vehicle being substantially the same color as the color of the given school bus, the one or more processors determining that the vehicle is representative of the given school bus.

2. The method of claim 1 , wherein comparing the color of the vehicle to the color of the school bus comprises:

determining a portion of the image data that depicts the vehicle;

dividing the portion of the image data into a plurality of sections;

for respective sections of the plurality of sections, determining a value of difference between a color of the respective section and a substantially orange color; and

determining a number of sections of the respective sections of which the value of difference is less than a difference threshold,

wherein determining that the vehicle is representative of the given school bus is further based on the number of sections of the respective sections being greater than a number threshold.

3. The method of claim 1 , further comprising:

the one or more processors determining a portion of the image data that depicts the vehicle; and

the one or more processors determining that the portion of the image data includes data indicative of a stop-sign,

wherein determining that the vehicle is representative of the given school bus is further based on the portion of the image data including data indicative of the stop-sign.

4. The method of claim 1 , further comprising:

the one or more processors determining a portion of the image data that depicts the vehicle; and

the one or more processors determining that the portion of the image data includes data indicative of a school-sign,

wherein determining that the vehicle is representative of the given school bus is further based on the portion of the image data including data indicative of the school-sign.

5. The method of claim 1 , further comprising:

the one or more processors receiving operational data indicative of an operation of the vehicle in the environment,

wherein determining that the vehicle is representative of the given school bus is further based on the operational data.

6. The method of claim 5 , wherein the operational data indicative of the operation of the vehicle in the environment comprises data indicative of a stop pattern of the vehicle, and

wherein determining that the vehicle is representative of the given school bus based on the operational data comprises determining that the vehicle is representative of the given school bus based on the data indicative of the stop pattern of the vehicle.

7. The method of claim 6 , wherein the data indicative of stop pattern includes data indicative of the vehicle operating a component of the vehicle to extend from a side portion of the vehicle as the vehicle stops.

8. The method of claim 1 , wherein the computing device resides in an autonomous vehicle operating in the environment, the method further comprising:

based on the vehicle being representative of the given school bus, the one or more processors providing instructions to control the autonomous vehicle in the environment.

9. The method of claim 1 , wherein using the image data indicative of the one or more vehicles in the environment to select the vehicle from the one or more vehicles to be the candidate school bus comprises:

using the image data to determine that the vehicle substantially fills a predetermined bounding box without exceeding the predetermined bounding box; and

based on the determination that the vehicle substantially fills the predetermined bounding box without exceeding the predetermined bounding box, selecting the vehicle to be the candidate school bus.

10. An autonomous vehicle comprising:

a computer system configured to:

use image data indicative of one or more vehicles in an environment of the autonomous vehicle to select a vehicle from the one or more vehicles to be a candidate school bus;

based on the selection of the vehicle to be the candidate school bus, compare an estimated size of the vehicle to information indicative of a size of a school bus;

based on the estimated size of the vehicle being within a threshold size of the size of the school bus, compare a color of the vehicle to a color of a given school bus; and

based on the vehicle being substantially the same color as the color of the given school bus, determine that the vehicle is representative of the given school bus.

11. The autonomous vehicle of claim 10 , further comprising at least one sensor configured to sense the environment of the autonomous vehicle, wherein the computer system is further configured to:

before using the image data, use the at least one sensor to determine the image data.

12. The autonomous vehicle of claim 10 , wherein the computer system is further configured to:

determine a portion of the image data that depicts the vehicle; and

determine that the portion of the image data includes data indicative of a stop-sign,

wherein determining that the vehicle is representative of the given school bus is further based on the portion of the image data including data indicative of the stop-sign.

13. The autonomous vehicle of claim 10 , wherein the computer system is further configured to:

determine a portion of the image data that depicts the vehicle; and

determine that the portion of the image data includes data indicative of a school-sign,

wherein determining that the vehicle is representative of the given school bus is further based on the portion of the image data including data indicative of the school-sign.

14. The autonomous vehicle of claim 10 , wherein the computer system is further configured to:

receive operational data indicative of an operation of the vehicle in the environment,

wherein determining that the vehicle is representative of the given school bus is further based on the operational data.

15. The autonomous vehicle of claim 14 , wherein the operational data indicative of the operation of the vehicle in the environment comprises data indicative of a stop pattern of the vehicle,

wherein the stop pattern includes data indicative of the vehicle operating a component of the vehicle to extend from a side portion of the vehicle as the vehicle stops, and

wherein determining that the vehicle is representative of the given school bus based on the operational data comprises determining that the vehicle is representative of the given school bus based on the data indicative of the stop pattern of the vehicle.

16. The autonomous vehicle of claim 10 , wherein using the image data indicative of the one or more vehicles in the environment to select the vehicle from the one or more vehicles to be the candidate school bus comprises:

using the image data to determine that the vehicle substantially fills a predetermined bounding box without exceeding the predetermined bounding box; and

based on the determination that the vehicle substantially fills the predetermined bounding box without exceeding the predetermined bounding box, selecting the vehicle to be the candidate school bus.

17. A non-transitory computer readable medium having stored therein instructions, that when executed by a computer system, cause the computer system to perform functions comprising:

using image data indicative of one or more vehicles in an environment to select a vehicle from the one or more vehicles to be a candidate school bus;

based on the selection of the vehicle to be the candidate school bus, comparing an estimated size of the vehicle to information indicative of a size of a school bus;

based on the estimated size of the vehicle being within a threshold size of the size of the school bus, comparing a color of the vehicle to a color of a given school bus; and

based on the vehicle being substantially the same color as the color of the given school bus, determining that the vehicle is representative of the given school bus.

18. The non-transitory computer readable medium of claim 17 , wherein using the image data indicative of the one or more vehicles in the environment to select the vehicle from the one or more vehicles to be the candidate school bus comprises:

using the image data to determine that the vehicle substantially fills a predetermined bounding box without exceeding the predetermined bounding box; and

based on the determination that the vehicle substantially fills the predetermined bounding box without exceeding the predetermined bounding box, selecting the vehicle to be the candidate school bus.

19. The non-transitory computer readable medium of claim 18 , the functions further comprising:

before comparing the estimated size of the vehicle to information indicative of the size of a school bus, the one or more processors determining the estimated size of the vehicle based on a size of the predetermined bounding box.

20. The non-transitory computer readable medium of claim 17 , wherein the computing system is configured to control an autonomous vehicle operating in the environment, the functions further comprising:

based on the vehicle being representative of the given school bus, providing instructions to control the autonomous vehicle in the environment.