Abstract: A vehicle psychomotor driving skill assessment system includes an on-board inputs group in a vehicle including physiological sensors. An on-board computer receives input from the on-board inputs group. The on-board computer accesses one or more algorithms from a memory to perform a skill test, evaluates skill test data, accesses stored skill test results from previous performed skill tests and saved average skill test results, and generates a current skill test result including a psychomotor ability assessment. A vehicle screen is provided. A skill test image generated by the on-board computer and a current user skill test result including the psychomotor ability assessment are presented on the vehicle screen to assist the user in performing the skill test. The current user skill test result assists the user in determining a user capability to operate the vehicle following the skill test.

Abstract: A system for providing driver status to a driver of a vehicle includes a data processor, a plurality of sensors mounted within the vehicle and adapted to send vehicle information to the data processor, a driver monitoring system within the vehicle adapted to send driver information to the data processor, the data processor further adapted to collect information from external sources via a wireless data communication network, and a driver state display adapted to receive information from the data processor and to display a short-term status indicator, a long-term status indicator and contextual information.

Abstract: A full speed range adaptive cruise control system for a vehicle that stops at an intersection includes one or more controllers that execute instructions to receive localization data and situational data related to the vehicle. The one or more controllers determine, based on localization data and situational data, that the vehicle is approaching an intersection and will come to a stop at the intersection, where the vehicle is part of a queue including one or more surrounding vehicles. In response to determining the vehicle has come to a stop, the controller determines a position of the vehicle within the queue and an overall length of the queue. The controller calculates an adaptive launch time based on at least the position of the vehicle within the queue, the overall length of the queue, the situational data, and a timing delay associated with the queue.

Abstract: A method of monitoring a driver in an autonomous vehicle includes monitoring, with a driver monitoring system, a driver of a vehicle, collecting, with a data processor, data from the driver monitoring system related to gaze behavior of the driver, classifying, with the data processor, the driver as one of a plurality of driver statuses based on the data from the driver monitoring system, and sending, with the data processor, instructions to at least one vehicle system based on the classification of the driver.

Abstract: A system for providing driver status to a driver of a vehicle includes a data processor, a plurality of sensors mounted within the vehicle and adapted to send vehicle information to the data processor, a driver monitoring system within the vehicle adapted to send driver information to the data processor, the data processor further adapted to collect information from external sources via a wireless data communication network, and a driver state display adapted to receive information from the data processor and to display a short-term status indicator, a long-term status indicator and contextual information.

Abstract: A method of monitoring a driver in an autonomous vehicle includes monitoring, with a driver monitoring system, a driver of a vehicle, collecting, with a data processor, data from the driver monitoring system related to gaze behavior of the driver, classifying, with the data processor, the driver as one of a plurality of driver statuses based on the data from the driver monitoring system, and sending, with the data processor, instructions to at least one vehicle system based on the classification of the driver.

Abstract: A method of managing operator take-over of autonomous vehicle. The method includes gathering information on an external surrounding of the autonomous vehicle; analyzing the gathered information on the external surrounding of the autonomous vehicle to determine an upcoming traffic pattern; gathering information on an operator of the autonomous vehicle; analyzing the gathered information on the operator of the autonomous vehicle to determine an operator behavior; predicting an operator action based on the determined upcoming traffic pattern and the determined operator behavior; and initiating a predetermined vehicle response based on the predicted operator action. The predicting the operator action includes comparing the determined upcoming traffic pattern with a similar historic traffic pattern and retrieving a historical operator action in response to the similar historical pattern.