A computer-implemented method for modifying a self-driving model based on data associated with at least one user of a vehicle, the method comprising: computing at least one value for a psychological metric based on first sensor data that is associated with a user of the vehicle and is acquired while the self-driving model operates the vehicle; determining a description of the user over a first time period based on the at least one value for the psychological metric, wherein determining the description of the user comprises: comparing the at least one value for the psychological metric with a first threshold for the description to determine a first time where the at least one value of the psychological metric exceeds the first threshold; comparing the at least one value for the psychological metric with a second threshold for the description to determine a second time where the least one value for the psychological metric falls below the second threshold, wherein the second threshold is different from the first threshold; and comparing the at least one value for the psychological metric with the second threshold for the description to determine a third time at which the at least one value for the psychological metric exceeded the second threshold, wherein the third time precedes the first time and the second time, and wherein said first time period is the time period between the third time and the second time; generating a first dataset based on the description, second sensor data that is associated with the vehicle and is acquired over the first time period, and a self-driving action performed during the first time period; adding the first dataset to a training database to generate an updated training database; and re-training the self-driving model based on the updated training database to generate a modified self-driving model. computing at least one value for a psychological metric based on first sensor data that is associated with a user of the vehicle and is acquired while the self-driving model operates the vehicle; determining a description of the user over a first time period based on the at least one value for the psychological metric, wherein determining the description of the user comprises: comparing the at least one value for the psychological metric with a first threshold for the description to determine a first time where the at least one value of the psychological metric exceeds the first threshold; comparing the at least one value for the psychological metric with a second threshold for the description to determine a second time where the least one value for the psychological metric falls below the second threshold, wherein the second threshold is different from the first threshold; and comparing the at least one value for the psychological metric with the second threshold for the description to determine a third time at which the at least one value for the psychological metric exceeded the second threshold, wherein the third time precedes the first time and the second time, and wherein said first time period is the time period between the third time and the second time; comparing the at least one value for the psychological metric with a first threshold for the description to determine a first time where the at least one value of the psychological metric exceeds the first threshold; comparing the at least one value for the psychological metric with a second threshold for the description to determine a second time where the least one value for the psychological metric falls below the second threshold, wherein the second threshold is different from the first threshold; and comparing the at least one value for the psychological metric with the second threshold for the description to determine a third time at which the at least one value for the psychological metric exceeded the second threshold, wherein the third time precedes the first time and the second time, and wherein said first time period is the time period between the third time and the second time; generating a first dataset based on the description, second sensor data that is associated with the vehicle and is acquired over the first time period, and a self-driving action performed during the first time period; adding the first dataset to a training database to generate an updated training database; and re-training the self-driving model based on the updated training database to generate a modified self-driving model.