System and Method for Identifying Travel Way Features for Autonomous Vehicle Motion Control

A computer-implemented method for identifying travel way features, the method comprising:

• obtaining two-dimensional data and three-dimensional data associated with an environment of an autonomous vehicle at a current time;
• processing the two-dimensional data with a machine-learned segmentation model to generate a two-dimensional segmentation for the environment;
• generating a current three-dimensional segmentation based at least in part on the three-dimensional data and the two-dimensional segmentation;
• identifying one or more historical three-dimensional datapoints previously generated for the environment at one or more times preceding the current time;
• and
• determining one or more travel way features within the environment at the current time based on the current three-dimensional segmentation and the one or more historical three-dimensional datapoints previously generated for the environment at the one or more times preceding the current time.

An autonomous vehicle control system comprising:

• one or more processors;
• and
• one or more tangible, non-transitory, computer readable media that collectively store instructions that when executed by the one or more processors cause the autonomous vehicle control system to perform operations comprising:
• obtaining two-dimensional data and three-dimensional data associated with an environment of an autonomous vehicle at a current time;
• processing the two-dimensional data with a machine-learned segmentation model to generate a two-dimensional segmentation for the environment;
• generating a current three-dimensional segmentation based at least in part on the three-dimensional data and the two-dimensional segmentation;
• identifying one or more historical three-dimensional datapoints previously generated for the environment at one or more times preceding the current time;
• and
• determining one or more travel way features within the environment at the current time based on the current three-dimensional segmentation and the one or more historical three-dimensional datapoints previously generated for the environment at the one or more times preceding the current time.

An autonomous vehicle comprising:

• one or more processors;
• one or more tangible, non-transitory, computer readable media that collectively store instructions that when executed by the one or more processors cause the one or more processors to perform operations comprising:
• obtaining two-dimensional data and three-dimensional data associated with an environment of the autonomous vehicle at a current time;
• processing the two-dimensional data with a machine-learned segmentation model to generate a two-dimensional segmentation for the environment;
• generating a current three-dimensional segmentation based at least in part on the three-dimensional data and the two-dimensional segmentation;
• identifying one or more historical three-dimensional datapoints previously generated for the environment at one or more times preceding the current time;
• and
• determining one or more travel way features within the environment at the current time based on the current three-dimensional segmentation and the one or more historical three-dimensional datapoints previously generated for the environment at the one or more times preceding the current time.