Systems and methods for inferring information about stationary elements based on semantic relationships

A non-transitory computer-readable medium comprising program instructions stored thereon that are executable to cause a computing system to:

• after one or more sensor-equipped vehicles have traversed a real-world environment and captured sensor data that is representative of the real-world environment, perform an analysis of the sensor data;
• based on the analysis of the sensor data, derive a set of information about a traffic light within the real-world environment that includes one or more of (i) signal-face information that comprises an identification of each signal face of the traffic light or (ii) traffic-rule information that comprises an indication of at least one traffic rule that is applicable to the traffic light;
• and
• encode the derived set of information about the traffic light into a map for the real-world environment.

A computing system comprising:

• at least one processor;
• a non-transitory computer-readable medium;
• and
• program instructions stored on the non-transitory computer-readable medium that are executable by the at least one processor such that the computing system is capable of:
• after one or more sensor-equipped vehicles have traversed a real-world environment and captured sensor data that is representative of the real-world environment, performing an analysis of the sensor data;
• based on the analysis of the sensor data, deriving a set of information about a traffic light within the real-world environment that includes one or more of (i) signal-face information that comprises an identification of each signal face of the traffic light or (ii) traffic-rule information that comprises an indication of at least one traffic rule that is applicable to the traffic light;
• and
• encoding the derived set of information about the traffic light into a map for the real-world environment.