Method of evaluating people's performance under high cognitive load

A computer-implemented method for predicting driving performance based on one or more mental states, the method comprising:

• collecting one or more first biosignals during a variable cognitive load vehicle environment scenario, wherein the one or more first biosignals are collected using a vehicle simulation system configured to provide a controlled environment;
• collecting vehicle telemetry information during the variable cognitive load vehicle environment scenario with the vehicle simulation system;
• determining one or more mental states based on the one or more first biosignals;
• correlating the one or more mental states to the vehicle telemetry information to determine one or more driving performance metrics;
• building a driving performance evaluator based on the one or more driving performance metrics;
• and
• feeding one or more second biosignals acquired with a vehicle to the driving performance evaluator to predict driving performance, wherein the variable cognitive load vehicle environment scenario comprises a plurality of periods, including a calibration period, a rest period, and a driving period comprising city driving portions and highway driving portions.

A method of a vehicle computing system of a vehicle, comprising:

• collecting one or more first biosignals of a driver of the vehicle with one or more first biosensors of the vehicle;
• determining one or more mental states of the driver based on the one or more first biosignals;
• feeding the one or more mental states into a driving performance evaluator, wherein the driving performance evaluator is a neural network trained on data obtained with a vehicle simulation system, and wherein the vehicle simulation system comprises second biosensors configured to acquire second biosignals of one or more users of the vehicle simulation system during variable cognitive load testing;
• generating a predicted driving performance with the driving performance evaluator based on the one or more mental states;
• and
• determining one or more vehicle interventions based on the predicted driving performance.