System

A system comprising:

• circuitry configured to:
• receive, via a communication interface coupled to a packet-switched network, position information from a position detection device and map information including road information, obstacle information, and traffic information from a geographic information storage device;
• generate environment state data by integrating position information, map information, destination information, and constraint condition information as a spatial data structure encoded as a serialized text representation, and generate a prompt sentence assembling the environment state data, a movement objective specification, and a route output format specification;
• operate a transformer-based generative neural network model using the prompt sentence to generate route information comprising structured route point records with coordinate values and movement condition codes, verify each route point against no-go-zone information and road network connectivity, and correct infeasible route points;
• calculate an estimated arrival time by applying a travel time model to corrected route segments using road type and traffic information values, and transmit corrected route information and estimated arrival time to the mobile body and the terminal device via the communication interface;
• receive periodic position information and state information from the mobile body, compute perpendicular distance and heading deviation, and generate a re-planning prompt sentence when deviations exceed thresholds to dynamically update route information using the generative neural network model;
• and
• receive sensor data from sensors of the mobile body, apply a hazard detection procedure using a trained hazard classifier to detect hazard conditions, and generate evacuation route information with urgency-conditioned movement conditions for transmission to the mobile body and terminal device.

A method comprising:

• receiving, via a communication interface coupled to a packet-switched network, position information indicating a current position of a mobile body from a position detection device, and acquiring map information including road information, obstacle information, and traffic information from a geographic information storage device via the communication interface;
• generating environment state data by integrating the position information, the map information, destination information, and constraint condition information received from a terminal device, and generating a prompt sentence based on the environment state data;
• operating a generative neural network model using the prompt sentence to generate route information comprising a plurality of route points and a recommended movement condition corresponding to each route point for movement of the mobile body to a destination;
• verifying safety and feasibility of each route point in the route information against the map information and no-go-zone information stored in a storage device, correcting the route information to remove or replace infeasible route points, and calculating an estimated arrival time based on the corrected route information;
• and
• transmitting the corrected route information and the estimated arrival time to the mobile body and the terminal device via the communication interface, receiving position information and state information periodically from the mobile body, calculating a deviation between the received position information and the corrected route information, and generating a re-planning prompt sentence based on the deviation to operate the generative neural network model to dynamically update the route information.