Navigation via predictive task scheduling interruption for autonomous vehicles

A computer system the computer system comprising:

• one or more driverless vehicles, one or more processors, one or more computer-readable memories, one or more computer-readable tangible storage medium, and program instructions stored on at least one of the one or more tangible storage medium for execution by at least one of the one or more processors via at least one of the one or more memories, wherein the computer system is capable of performing a method comprising:
• quantifying an availability risk associated with one or more predicted events on a user's schedule, wherein quantifying the availability risk comprises utilizing a data normalization function to generate a normalized time-based location matrix of the user's planned destinations based on real-time GPS location data;
• predicting a next fueling time and location of a driverless vehicle based on a battery threshold of the driverless vehicle;
• finding an availability window for scheduling each of the one or more predicted events on the user's schedule, wherein the scheduling is based at least on the availability risk and a buffer time that is based on environmental data, wherein the environmental data comprises traffic data and weather data;
• and
• navigating the driverless vehicle based on scheduling at least one time to perform at least one predicted task, wherein the performing includes automatically returning to the location from which the driverless vehicle departed;
• comparing parking and energy costs to pick a best parking location when arriving at or returning from a task;
• and
• receiving user feedback to assess and refine accuracy of future availability risk calculations, together with task predicting and scheduling.

A computer program product, the computer program product comprising:

• one or more computer-readable tangible storage medium and program instructions stored on at least one of the one or more tangible storage medium, the program instructions executable by a processor to cause the processor to perform a method comprising:
• quantifying an availability risk associated with one or more predicted events on a user's schedule, wherein quantifying the availability risk comprises utilizing a data normalization function to generate a normalized time-based location matrix of the user's planned destinations based on real-time GPS location data;
• predicting a next fueling time and location of a driverless vehicle based on a battery threshold of the driverless vehicle;
• finding an availability window for scheduling each of the one or more predicted events on the user's schedule, wherein the scheduling is based at least on the availability risk and a buffer time that is based on environmental data, wherein the environmental data comprises traffic data and weather data;
• and
• navigating the driverless vehicle based on scheduling at least one time to perform at least one predicted task, wherein the performing includes automatically returning to the location from which the at least one the driverless vehicle departed;
• comparing parking and energy costs to pick a best parking location when arriving at or returning from a task;
• and
• receiving user feedback to assess and refine accuracy of future availability risk calculations, together with task predicting and scheduling.