Systems and methods for a scenario tagger for autonomous vehicles

A computing system comprising:

• one or more processors;
• and
• one or more non-transitory computer-readable media that store instructions that, when executed by the one or more processors, cause the computing system to perform operations, the operations comprising:
• obtaining log data that describes, based on a plurality of attributes, a plurality of observations collected during real-world operation of one or more vehicles;
• extracting, from the log data, an attribute combination comprising one or more attributes of the plurality of attributes, wherein the one or more attributes comprise a vehicle maneuver attribute indicative of an action the vehicle performs;
• determining, based at least in part on the attribute combination, a scenario associated with operating an autonomous vehicle, wherein the scenario is represented by the one or more attributes of the attribute combination,
• wherein the one or more attributes comprise a lane geometry attribute, wherein the lane geometry attribute is associated with one or more lanes of a travel way, wherein the scenario is represented by the one or more lanes of the travel way, and
• wherein the one or more attributes comprise an object attribute, wherein the object attribute is associated with a vehicle, a pedestrian, or a bicycle, wherein the scenario is represented by the vehicle, the pedestrian, or the bicycle;
• and
• generating a simulation scenario for testing the autonomous vehicle based at least in part on the scenario associated with operating the autonomous vehicle, wherein the simulation scenario is indicative of the one or more attributes of the attribute combination.

One or more tangible, non-transitory, computer readable media that store instructions that when executed by one or more processors cause the one or more processors to perform operations comprising:

• obtaining log data that describes, based on a plurality of attributes, a plurality of observations collected during real-world operation of one or more vehicles;
• extracting, from the log data, an attribute combination comprising one or more attributes of the plurality of attributes, wherein the one or more attributes comprise a vehicle maneuver attribute indicative of an action the vehicle performs;
• determining, based at least in part on the attribute combination, a scenario associated with operating an autonomous vehicle, wherein the scenario is represented by the one or more attributes of the attribute combination, and wherein the attribute combination is a new attribute combination occurring in the log data,
• wherein the one or more attributes comprise a lane geometry attribute, wherein the lane geometry attribute is associated with one or more lanes of a travel way, wherein the scenario is represented by the one or more lanes of the travel way, and
• wherein the one or more attributes comprise an object attribute, wherein the object attribute is associated with a vehicle, a pedestrian, or a bicycle, wherein the scenario is represented by the vehicle, the pedestrian, or the bicycle;
• and
• generating at least one of:
• (i) a simulation scenario for testing the autonomous vehicle based at least in part on the scenario associated with operating the autonomous vehicle, wherein the simulation scenario is indicative of the one or more attributes of the attribute combination, or (ii) training data based at least in part on the scenario associated with operating the autonomous vehicle, wherein the training data is indicative of the one or more attributes of the attribute combination.