Determining traffic control features based on telemetry patterns within digital image representations of vehicle telemetry data

A non-transitory computer readable medium comprising instructions that, when executed by at least one processor, cause a computer device to:

• generate a training telemetry digital image comprising pixels representing telemetry information for a traffic area;
• determine a predicted traffic control feature associated with the traffic area by processing the pixels representing the telemetry information from the training telemetry digital image utilizing a machine learning model;
• and
• train the machine learning model by comparing the predicted traffic control feature to a ground truth traffic control feature associated with the traffic area.

A system comprising:

• at least one processor;
• and
• a non-transitory computer readable medium comprising instructions that, when executed by the at least one processor, cause the system to:
• generate a training telemetry digital image comprising pixels representing telemetry information for a traffic area;
• determine a predicted traffic control feature associated with the traffic area by processing the pixels representing the telemetry information from the training telemetry digital image utilizing a machine learning model;
• and
• train the machine learning model by comparing the predicted traffic control feature to a ground truth traffic control feature associated with the traffic area.