Determining changes in a driving environment based on vehicle behavior

Patent metadata

Field	Value
Publication number	US-9633564-B2
Application number	US-201213628905-A
Country	US
Kind code	B2
Filing date	Sep 27, 2012
Priority date	Sep 27, 2012
Publication date	Apr 25, 2017
Grant date	Apr 25, 2017

Abstract

A method and apparatus are provided for determining whether a driving environment has changed relative to previously stored information about the driving environment. The apparatus may include an autonomous driving computer system configured to detect one or more vehicles in the driving environment, and determine corresponding trajectories for those detected vehicles. The autonomous driving computer system may then compare the determined trajectories to an expected trajectory of a hypothetical vehicle in the driving environment. Based on the comparison, the autonomous driving computer system may determine whether the driving environment has changed and/or a probability that the driving environment has changed, relative to the previously stored information about the driving environment.

First claim

The invention claimed is:

1. An apparatus comprising:
a laser-based sensing system configured to identify information about a first vehicle in a driving environment of a second vehicle;
a computer-readable memory that stores:
detailed map information for the driving environment, the detailed map information comprising information about a road on which the first vehicle travels; and
first state information for the first vehicle, the first state information identifying positions traveled for the first vehicle over time; and

one or more processors of the second vehicle in communication with the computer-readable memory and the sensor, the one or more processors being configured to:
use the detailed map information to control the second vehicle in an autonomous driving mode;
receive sensor information from the laser-based sensing system, the sensor information including information about the first vehicle in the driving environment for a predetermined period of time;
determine the first state information based on the received sensor information;
determine a first trajectory based on the first state information, the first trajectory corresponding to an actual path taken by the first vehicle for the predetermined period of time;
determine an expected trajectory for the first vehicle based on the detailed map information;
compare the determined expected trajectory with the determined first trajectory; and
stop using the detailed map information to control the second vehicle in the autonomous driving mode based on the comparison.

2. The apparatus of claim 1 , wherein the one or more processors are further configured to:
determine a deviation metric value by comparing the determined expected trajectory with the determined first trajectory;
wherein the one or more processors are further configured to determine that the driving environment has changed from the detailed map information to the extent that the detailed map information is no longer accurate when the deviation metric value exceeds a deviation metric threshold.

3. The apparatus of claim 2 , wherein the determined deviation metric value comprises a maximum deviation metric value representing a maximum difference between the determined first trajectory and the determined expected trajectory.

4. The apparatus of claim 2 , wherein each of the determined first trajectory and the determined expected trajectory include a plurality of positions the determined deviation metric value comprises an average signed deviation metric value, the average signed deviation metric value representing a magnitude and direction of a difference between the plurality of positions of the determined first trajectory and the plurality of positions of the determined expected trajectory.

5. The apparatus of claim 1 , wherein the determined first trajectory comprises an average trajectory, the average trajectory having been averaged over a predetermined time period.

6. The apparatus of claim 1 , wherein the determined expected trajectory is based on a centerline rail of the road indicating the direction in which vehicles travel in a respective lane , the centerline rail being defined in the detailed map information.

7. The apparatus of claim 1 , wherein the computer-readable memory further stores:
a probability model that defines a probability that the driving environment has changed relative to the detailed map information based on at least one deviation metric value determined from the comparison of the determined first trajectory with the determined expected trajectory;
a probability function that determines the probability that the driving environment has changed relative to the detailed map information based on the probability model; and
wherein the one or more processors are further configured to:
determine the probability that the driving environment has changed relative to the detailed map information based on the probability function; and
determine that the driving environment has changed from the detailed map information to the extent that the detailed map information is no longer accurate is further based on the determined probability.

8. The apparatus of claim 7 , wherein the probability model is one of a plurality of probability models; and
the one or more processors are further configured to select the probability model from the plurality of probability models based on a first geographic location.

9. The apparatus of claim 1 , wherein:
the determined first trajectory comprises a plurality of trajectories, each of the trajectories of the plurality of trajectories corresponding to a vehicle in the driving environment; and
the one or more processors are further configured to consolidate the plurality of trajectories as the determined first trajectory based on at least one consolidation factor.

10. The apparatus of claim 9 , wherein the one or more processors are further configured to:
determine a consolidated trajectory quality value for the plurality of trajectories, the consolidated trajectory quality value representing a quality of the determined first trajectory; and
determine the determined probability further based on the determined consolidated trajectory quality value.

11. A method for controlling a first vehicle, the method comprising:
using, by one or more processors, detailed map information to control the first vehicle in an autonomous driving mode;
receiving, with the one or more processors, sensor information including information about a second vehicle in a driving environment of the first vehicle for a predetermined period of time;
determining, with the one or more processors of the first vehicle, first state information based on the received sensor information, the first state information identifying positions traveled for the second vehicle over time;
determining, with the one or more processors of the first vehicle, a first trajectory based on the first state information, the first trajectory corresponding to an actual path taken by the second vehicle for the predetermined period of time;
determining, with the one or more processors of the first vehicle, an expected trajectory for the second vehicle based on detailed map information, the detailed map information comprising information about the driving environment;
comparing the determined expected trajectory with the determined first trajectory; and
stopping, by the one or more processors, using the detailed map information to control the first vehicle in the autonomous driving mode based on the comparison.

12. The method of claim 11 , further comprising:
determining, with the one or more processors of the first vehicle, a deviation metric value by comparing the determined expected trajectory with the determined first trajectory; and
determining, with the one or more processors of the first vehicle, that the driving environment has changed from the detailed map information to the extent that the detailed map information is no longer accurate when the deviation metric value exceeds a deviation metric threshold.

13. The method of claim 12 , wherein the determined deviation metric value comprises a maximum deviation metric value representing a maximum difference between the determined first trajectory and the determined expected trajectory.

14. The method of claim 12 , wherein each of the determined first trajectory and the determined expected trajectory include a plurality of positions and the determined deviation metric value comprises an average signed deviation metric value, the average signed deviation metric value representing a magnitude and direction of a difference between the plurality o

Assignees

• Google Inc

Inventors

• Ferguson David I

Classifications

• G08G1/166 Primary

  for active traffic, e.g. moving vehicles, pedestrians, bikes · CPC title

• G01C21/32

  Structuring or formatting of map data · CPC title

• G01C21/3819

  Road shape data, e.g. outline of a route · CPC title

• G01C21/3848

  Data obtained from both position sensors and additional sensors · CPC title