Determining an action to be performed for a predicted road issue

A system, comprising:

• a processor;
• and
• a memory, wherein the processor and the memory are communicably coupled, wherein the processor:
• receives, at a vehicle, data from sensors on the vehicle as the vehicle travels on a road;
• implements a trained artificial intelligence (AI) model with a neural network train capability, with at least one of data related to road conditions, environmental conditions, or drive conditions;
• and model feedback data, to generate a plurality of road issues;
• executes the trained AI model to predict a road issue of the plurality of road issues based on the received data;
• determines an action to be performed based on the predicted road issue;
• determines a latest time the action is to be performed;
• and
• verifies that the action was performed by the latest time based on data from a sensor from at least one other vehicle that travels on the road proximate the predicted road issue.

A computer-readable storage medium comprising instructions that, when read by a processor, cause the processor to perform:

• receiving, by a vehicle, data from sensors on the vehicle as the vehicle travels on a road;
• implementing a trained artificial intelligence (AI) model using a neural network training capability with at least one of data related to road conditions, environmental conditions, or driving conditions;
• and model feedback data, to generate a plurality of road issues;
• executing the trained AI model to predict a road issue of the plurality of road issues based on the received data;
• determining an action to be performed based on the predicted road issue;
• determining a latest time the action is to be performed;
• and
• verifying that the action was performed by the latest time based on data from a sensor from at least one other vehicle traveling on the road proximate the predicted road issue.