Facilitation of predictive simulation of planned environment

Edge node equipment, comprising:

• a processor;
• and
• a memory that stores executable instructions that, when executed by the processor, facilitate performance of operations, comprising:
• receiving, from a first network access point, first location data representative of a first location of a first object that is at a first distance from the first network access point;
• receiving, from a second network access point, second location data representative of a second location of a second object that is at a second distance from the second network access point;
• based on the first location data, predicting, using a machine learning model trained, using a training dataset comprising historical data associated with objects, to predict locations of the objects at future times, a third location of the first object at a third distance from the first network access point at a later time, resulting in a first predicted location applicable to the first object, the later time being a first time after receiving the first location data and the second location data;
• based on the second location data, predicting, using the machine learning model, a fourth location of the second object at a fourth distance from the second network access point at the later time, resulting in a second predicted location applicable to the second object, wherein the second object is associated with a first user equipment comprising sensing equipment to detect whether the first object has arrived at the first predicted location;
• in response to predicting the third location and the fourth location, generating simulated route data representative of a simulated route to be rendered in connection with a travel simulation request, wherein the simulated route comprises the first object at the first predicted location at the third distance from the first network access point at the later time within the simulated route and the second object at the second predicted location at the fourth distance from the second network access point at the later time within the simulated route;
• receiving, from the first user equipment, perception data representative of a perception of the first object captured by the sensing equipment of the first user equipment, at the first predicted location at the later time;
• in response to receiving the perception data, comparing the perception data to the simulated route data to determine whether the first object arrived at the first predicted location at the later time;
• in response to a condition associated with a result of the comparing being determined to be satisfied:
• retraining, using the result of the comparing, the machine learning model to predict the locations of the objects at the future times, resulting in a retrained machine learning model;
• and
• altering, using the retrained machine learning model, the simulated route in accordance with an alteration corresponding to the condition, resulting in an altered simulated route to be further rendered in connection with the travel simulation request;
• determining a first classification for the first object;
• determining a second classification for the second object, wherein generating the simulated route data comprises, based on the first classification, applying a first render rule for use in rendering the first object in the simulated route and, based on the second classification, applying a second render rule, different than the first render rule, for use in rendering the second object in the simulated route;
• and
• rendering the simulated route via a display device.

A non-transitory machine-readable medium, comprising executable instructions that, when executed by a processor, facilitate performance of operations, comprising:

• training, using a training dataset comprising historical data associated with objects, an artificial intelligence model to predict locations of the objects at future times;
• obtaining, from a first network access point, first location data representative of a first location of a first object that is at a first distance from the first network access point;
• obtaining, from a second network access point, second location data representative of a second location of a second object that is at a second distance from the second network access point;
• based on the first location data, forecasting, using the artificial intelligence model, a third location of the first object at a third distance from the first network access point at a later time, resulting in a first forecasted location applicable to the first object, the later time being a first time after receiving the first location data and the second location data;
• based on the second location data, forecasting, using the artificial intelligence model, a fourth location of the second object at a fourth distance from the second network access point at the later time, resulting in a second forecasted location applicable to the second object, wherein the second object is associated with a first user equipment comprising sensing equipment to detect whether the first object has arrived at the first forecasted location;
• in response to forecasting the third location and the fourth location, generating simulated route data representative of a simulated route to be rendered in connection with a travel simulation request, wherein the simulated route comprises the first object at the first forecasted location at the third distance from the first network access point at the later time within the simulated route and the second object at the second forecasted location at the fourth distance from the second network access point at the later time within the simulated route;
• obtaining, from the first user equipment, perception data representative of a perception of the first object at the first forecasted location at the later time;
• in response to receiving the perception data, comparing the perception data to the simulated route data to determine whether the first object arrived at the first forecasted location at the later time;
• in response to a condition associated with a result of the comparing being determined to be present:
• retraining, using the result of the comparing, the artificial intelligence model to predict the locations of the objects at the future times, the retraining resulting in a retrained artificial model, and
• modifying, using the retrained artificial intelligence model, the simulated route in accordance with a modification corresponding to the condition, resulting in a modified simulated route to be further rendered in connection with the travel simulation request;
• determining a first classification for the first object;
• determining a second classification for the second object, wherein generating the simulated route data comprises, based on the first classification, applying a first render rule for use in rendering the first object in the simulated route and, based on the second classification, applying a second render rule, different than the first render rule, for use in rendering the second object in the simulated route;
• and
• rendering the simulated route via a display device.