The present disclosure provides a method comprising receiving a rideshare request from a user, the rideshare request including a destination; transporting the passenger to the destination using an autonomous vehicle (AV) having a plurality of windows comprising electrically switchable smart glass; during the transporting, monitoring a metric related to arrival of the AV at the destination; and untinting the windows when the monitored metric has a prescribed relationship to a threshold value.

Controlling autonomous vehicle (AV) functions includes receiving occupant identification data from device(s) of an AV and identifying occupant(s) of the AV based on the received occupant identification data, determining a respective prioritization level for each occupant of the occupant(s), the prioritization level for each occupant dictating priority of the AV in performing commands provided to the AV by that occupant to control AV functions, receiving, from an occupant, input of a command for performance by the AV to control a function of the AV, determining whether to perform the command to control the function of the AV based on the prioritization level for the occupant, and performing processing based on the determining whether to perform the command.

A travel controller detects objects from an environmental image representing surroundings of a vehicle capable of traveling under autonomous driving control satisfying a predetermined safety standard; detects a looking direction of a driver of the vehicle from a face image of the driver; identifies an object in the looking direction of the driver out of the objects; stores the identified object and a situation condition indicating the situation at detection of the identified object in a memory in association with each other when a danger avoidance action performed by the driver is detected during travel of the vehicle; and changes the predetermined safety standard so that the driver can feel safer, in the case where an object stored in the memory is detected during travel of the vehicle under the autonomous driving control and where the situation at detection of the object satisfies the situation condition.

A method for controlling a driving assistance feature of a vehicle is disclosed. The method comprises determining a state of a driver of the vehicle by means of a driver monitoring system (DMS) the state of the driver comprising at least one attention parameter, and comparing the determined state of the driver with a predefined attention model. The predefined attention model comprises an independent threshold range for each attention parameter. The method further comprises controlling the driving assistance feature based on the comparison between the determined state of the driver and the predefined attention model.

A vehicle performance evaluation method, device and terminal are provided. The method includes: acquiring a labeled ADE score of an ADE item within a time period in which the ADE item occurs, and recording labeled data of an ADE index for indicating a vehicle state; acquiring a correlation between the ADE item and the vehicle state, according to the labeled ADE score and the labeled data of the ADE index; acquiring data of a target ADE index within a preset time period, and acquiring a target ADE score according to the data of the target ADE index and a correlation between the ADE item and the vehicle state; and acquiring a vehicle performance evaluation result according to the target ADE score. The passenger participation is not necessary, costs can be reduced and a vehicle evaluation efficiency can be improved.

Embodiments of the present disclosure relate to the technical field of autonomous driving, and in particular to methods for updating an autonomous driving system, autonomous driving systems, and on-board apparatuses. In the embodiments of the present disclosure, the autonomous driving system, in a manual driving mode, senses the surrounding environment of a vehicle, performs vehicle positioning, and plans a path for autonomous driving for the vehicle. However, the autonomous driving system does not issue an instruction to control the driving of the vehicle. Instead, it compares the path with a path along which a driver drives the vehicle in the manual driving mode to update a planning and control algorithm of the autonomous driving system. As such, the updated autonomous driving system better caters to the driving habits of the driver and improves the driving experience for the driver without compromising the reliability of planning and decision-making of autonomous driving.

An approach for adjusting driving parameters of an AV (autonomous vehicle) based on the driving style of the passenger is disclosed. The approach utilizes existing driving patterns of the passenger and perform a dynamic comparison and correlation with safe driving patterns of the passengers themselves. Based on that evaluation, the approach would suggest the parameters for adjusting the AV driving style in order to ensure AV riding experience meets the expected level of safe and stress-less riding. Furthermore, the approach can dynamically adjust the driving style during the trip based on the reaction and feedback from the passenger.

The present disclosure relates to an apparatus for controlling the motion of a vehicle to improve riding comfort, and a method thereof. According to an embodiment of the present disclosure, a processor may determine a boarding location for a user and may determine a vehicle control signal in consideration of riding comfort according to acceleration or jerk based on the boarding location. A controller may control the vehicle depending on the vehicle control signal.

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.

Enclosed are embodiments for scenario-based behavior specification and validation. In an embodiment, a method comprises: obtaining, using at least one processor, at least one trajectory associated with a driving scenario for an autonomous vehicle system; evaluating, using the at least one processor and at least one rulebook, the at least one trajectories to determine whether the at least one trajectory violates at least one rule in the at least one rulebook, wherein each rule in the rulebook is associated with at least one violation metric that is used to determine a degree to which the rule was satisfied or violated; determining, using the at least one processor and the at least one violation metric, a score for the at least one trajectory; and sending, using the at least one processor, the score to at least one of a software module in a software stack of the autonomous vehicle system, a simulation of the autonomous vehicle system or as a report or in a visual presented through a user interface of a cloud-based platform.