Assessing surprise for autonomous vehicles
AssigneeWaymo LLC
InventorsIsaac John Supeene, Azadeh Dinparastdjadid, Johan Engstrom
Life of this patent
Estimating the term…
Abstract
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for computing enhanced surprise metrics for autonomously driven vehicles. One of the methods includes receiving data representing a predicted state of an agent at a particular time, data representing an actual state of the agent for the particular time, and computing a surprise metric for the actual state of the agent based on a measure of the residual information between the predicted state of the agent and the actual state of the agent.
Claims20
A computer-implemented method comprising:
- receiving data representing a predicted state of an agent at a particular time;
- receiving data representing an actual state of the agent for the particular time;
- and
- computing a surprise metric for the actual state of the agent based on a measure of the residual information between the predicted state of the agent and the actual state of the agent.
A computer-implemented method comprising:
- receiving a prior probability distribution representing a predicted state of an agent at a particular time, wherein the prior probability distribution is based on a previous state of the agent at a previous time, and wherein the prior probability distribution has one or more associated expectation ranges that each represent a respective range of expected states of the agent at the particular time;
- receiving an updated state of the agent for the particular time;
- computing a posterior probability distribution based on the updated state of the agent;
- and
- computing an antithesis surprise metric using the posterior probability distribution, wherein the antithesis surprise metric represents how much of the posterior probability distribution exceeds the prior probability distribution in regions that do not belong to any of the expectation ranges associated with the prior probability distribution.
A system comprising one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising:
- receiving a prior probability distribution representing a predicted state of an agent at a particular time, wherein the prior probability distribution is based on a previous state of the agent at a previous time, and wherein the prior probability distribution has one or more associated expectation ranges that each represent a respective range of expected states of the agent at the particular time;
- receiving an updated state of the agent for the particular time;
- computing a posterior probability distribution based on the updated state of the agent;
- and
- computing an antithesis surprise metric using the posterior probability distribution, wherein the antithesis surprise metric represents how much of the posterior probability distribution exceeds the prior probability distribution in regions that do not belong to any of the expectation ranges associated with the prior probability distribution.
Dependencies are inferred from the claim text.