A computer-implemented method, system, and/or computer program product controls a driving mode of a self-driving vehicle (SDV). One or more processors compare a control processor competence level of an on-board SDV control processor in controlling the SDV to a human driver competence level of a human driver in controlling the SDV while the SDV encounters a current roadway condition which is a result of current weather conditions of the roadway on which the SDV is currently traveling. One or more processors then selectively assign control of the SDV to the SDV control processor or to the human driver while the SDV encounters the current roadway condition based on which of the control processor competence level and the human driver competence level is relatively higher to one another.

Among other things, one or more techniques and/or systems are provided for providing users with access to a route for travelling. A user, of a client device, may send a request for access to the route to a route planning service. The route may correspond to a starting location and an ending location. The route planning service may query a route database to identify an entry indicating that a restricted access road segment (e.g., a high occupancy vehicle lane, a shoulder lane, a bus lane, etc.) and/or a road segment (e.g., comprising a traffic light alteration capability) exists between the starting location and the ending location. Responsive to successfully authorizing the user for travelling the restricted access road segment and/or the road segment, the route, comprising the restricted access road segment and/or the road segment, may be provided to the client device.

Methods, systems, apparatuses, and computer program products are provided for altering the behavior of an electronic personal assistant based on a situation associated with a mobile device. A situation is sensed with a plurality of sensors to generate sensor data. A situation score is calculated based on the sensor data. Behavior of an electronic personal assistant is altered based on the calculated situation score. In one aspect, the situation is a driving situation in which a driver drives a vehicle on a roadway. In such case, a driving situation score is calculated based on the sensor data, and behavior of the electronic personal assistant is altered based on the calculated driving situation score, such as suspending interactions by the electronic personal assistant with the driver to avoid the driver being distracted.

It is presented a method performed in a vehicle action determiner for determining an undesired action of a first vehicle and a resulting action. The method comprises: detecting that a first user is focusing on the first vehicle; acquiring brain activity data of the first user; determining a negative reaction of the first user based on the brain activity data; determining when the first vehicle is performing an undesired action based on the first user focusing on the first vehicle and the negative reaction of the first user; determining the resulting action taken by an autonomous vehicle, based on the first vehicle performing the undesired action; and triggering the autonomous vehicle to perform the resulting action.

The invention relates to a device for determining the driving behavior of a driver, the device comprising at least means for receiving data from two or more data sources, of which at least one produces data relating to changes in the state of motion of a vehicle and at least one other produces measured data on the well-being of the driver; means for scoring the received data by comparing it with data-specific reference values; means for forming a respective sub-index from each scored item of data; means for determining a driving behavior index on the basis of the formed sub-indices; and means for controlling control equipment of the vehicle on the basis of the driving behavior index and/or for storing the driving behavior index in a database.

A method for adaptively optimizing an autonomous driving system includes obtaining a driving intent of a driver of a target vehicle, wherein the target vehicle is an autonomous driving vehicle controlled by the autonomous driving system, detecting, based on the driver's driving intent, that a conflict exists between a first driving behavior of the target vehicle controlled by the autonomous driving system and the driver's driving intent, and updating the autonomous driving system such that a driving behavior of the target vehicle controlled by an updated autonomous driving system matches the driving intent.

An autonomous driving system includes a normal driving situation determination unit configured to determine whether or not autonomous driving is in a normal driving situation, a driver situation recognition unit configured to recognize a driver situation, a distrust determination unit configured to determine whether or not the driver is in a system distrust state, based on a recognition result obtained by the driver situation recognition unit, and a warning control unit configured to output an alert in accordance with the external environment of the vehicle when the normal driving situation determination unit determines that autonomous driving is in the normal driving situation and the distrust determination unit determines that the driver is in the system distrust state.

Disclosed embodiments include techniques for providing alerts to a driver of a vehicle. The techniques include detecting a condition that exceeds a threshold hazard potential; detecting a predetermined gesture of a driver, the predetermined gesture indicating that the driver has acknowledged the detected condition; in response to detecting the predetermined gesture, reducing an urgency level for alerting the driver of the detected condition; and determining whether to issue an alert to the driver based on the reduced urgency level.

A vehicle having one or more cameras, configured to record one or more images of a driver of the vehicle. The camera(s) can be configured to send biometric image data derived from the image(s). The vehicle can include a computing system configured to receive the biometric data and to determine a risk score of the driver based on the received biometric data and an AI technique, such as an ANN or a decision tree. The received biometric data or a derivative thereof can be input for the AI technique. The computing system can also be configured to transmit the risk score of the driver to the customer so that the customer can decide whether to book the vehicle for a ride.

A vehicular control system includes a forward-viewing camera, a forward-sensing sensor and an in-cabin-sensing sensor. With the system controlling driving of the vehicle, the system determines a triggering event that triggers handing over driving of the vehicle to a driver of the vehicle before the vehicle encounters an event point associated with the triggering event. The vehicular control system (i) determines a total action time available before the vehicle encounters the event point, (ii) estimates a driver takeover time for the driver to take over control of the vehicle and (iii) estimates a handling time for the driver to control the vehicle to avoid encountering the event point. Responsive to the vehicular control system determining that the estimated driver takeover time is less than the difference between the determined total action time and the estimated handling time, control of the vehicle is handed over to the driver of the vehicle.