EV route optimization through crowdsourcing

A method of determining charging equipment availability through crowdsourcing, the method comprising;

• gathering information from a plurality of electrically powered vehicles in a geographical region, wherein the gathering of the information comprises gathering behavioral pattern of drivers of the electrically powered vehicles;
• displaying a plurality of charging stations in the geographical region, wherein the charging stations each provide electrical charging equipment configured to charge the electrically powered vehicles;
• receiving, from a user, a request to obtain an occupancy status of the electrical charging equipment at one or more of the charging stations during a specified future time window;
• calculating, based on the information gathered from the plurality of electrically powered vehicles, a likelihood of the electrical charging equipment at the one or more charging stations being unoccupied during the specified future time window, wherein the calculating comprises assigning a weighted probability to each charging station of being visited by at least one of the electrically powered vehicles, and wherein the calculating is performed such that the weighted probability is a function of the behavioral pattern of the drivers;
• and
• communicating the likelihood to the user;
• wherein at least one of the gathering, the displaying, the receiving, the calculating, and the communicating is performed using one or more electronic processors.

A non-transitory computer readable medium comprising executable instructions that when executed by a processor, causes the processor to perform the steps of:

• gathering information from a plurality of electrically powered vehicles in a geographical region, wherein the gathering of the information comprises gathering behavioral pattern of drivers of the electrically powered vehicles;
• displaying a plurality of charging stations in the geographical region, wherein the charging stations each provide electrical charging equipment configured to charge the electrically powered vehicles;
• receiving, from a user, a request to obtain an occupancy status of the electrical charging equipment at one or more of the charging stations during a specified future time window;
• calculating, based on the information gathered from the plurality of electrically powered vehicles, a likelihood of the electrical charging equipment at the one or more charging stations being unoccupied during the specified future time window, wherein the calculating comprises assigning a weighted probability to each charging station of being visited by at least one of the electrically powered vehicles, and wherein the calculating is performed such that the weighted probability is a function of the behavioral pattern of the drivers;
• and
• communicating the likelihood to the user.