A method that may include receiving driving information and environmental metadata indicative of information sensed by the vehicle; detecting multiple driving events encountered during the driving over the path; determining driving events; for each driving event, determining a comfort based autonomous driving pattern information; for each driving event, determining an driving event identifier; and storing in at least one data structure a driving event identifier for each one of the multiple types of driving events, and a comfort based autonomous driving pattern information.

A power adjustment system and a power adjustment method of an autonomous mobile device are provided. In the power adjustment method, two first current control signals respectively transmitted to two drivers are outputted by a control module. A tilt angle of the autonomous mobile device is detected by an inertial measurement module. A travel route is planned by a navigation module, and the control module obtains a steering angle of the autonomous mobile device during a traveling process. According to different weight values of the autonomous mobile device stored in a database module, a weight of the autonomous mobile device is estimated by the control module. According to the two first current control signals and the weight, the steering angle, and the tilt angle of the autonomous mobile device, two second current control signals respectively transmitted to the two drivers are outputted by the control module.

Vehicle manipulation is performed using crowdsourced data. A camera within a vehicle is used to collect cognitive state data, including facial data, on a plurality of occupants in a plurality of vehicles. A first computing device is used to learn a plurality of cognitive state profiles for the plurality of occupants, based on the cognitive state data. The cognitive state profiles include information on an absolute time or a trip duration time. Voice data is collected and is used to augment the cognitive state data. A second computing device is used to capture further cognitive state data on an individual occupant in an individual vehicle. A third computing device is used to compare the further cognitive state data with the cognitive state profiles that were learned. The individual vehicle is manipulated based on the comparing of the further cognitive state data.

The disclosure provides for a method for determining a route for passenger comfort and operating a vehicle according to the determined route. To start, a set of routes from a start location to an end location may be determined. Each route includes one or more portions. For each route of the set of routes, a total motion sickness value is determined based on a sway motion sickness value, a surge motion sickness value, and a heave motion sickness value for each of the given portions. The total motion sickness value for a route reflects a likelihood that a user will experience motion sickness while in a vehicle along the route. A route may then be selected from the set of routes based on the total motion sickness value of each route of the set of routes, and the vehicle may be maneuvered according to the selected route.

A system and method for learning naturalistic driving behavior based on vehicle dynamic data that include receiving vehicle dynamic data and image data and analyzing the vehicle dynamic data and the image data to detect a plurality of behavioral events. The system and method also include classifying at least one behavioral event as a stimulus-driven action and building a naturalistic driving behavior data set that includes annotations that are based on the at least one behavioral event that is classified as the stimulus-driven action. The system and method further include controlling a vehicle to be autonomously driven based on the naturalistic driving behavior data set.

A vehicle control device includes a first inputter, a second inputter, a mode controller configured to, when the first inputter is operated by a user, determine a driving mode of a vehicle as a first mode, and when the second inputter is operated by the user in the first mode, switch the driving mode from the first mode to a second mode, and a driving controller configured to control at least one of a steering and speed of the vehicle, and the driving controller is configured to control a steering and speed of the vehicle and prohibit change of a path of the vehicle when the driving mode is the first mode, and control a steering and speed of the vehicle and change of the path of the vehicle is allowed when the driving mode is the second mode.

A trajectory generation device configured to generate a branch trajectory as a trajectory of a first vehicle traveling from a main lane to a branch lane includes a determination unit and an adjustment unit. The determination unit is configured to determine whether a second vehicle different from the first vehicle is present in the branch lane. The adjustment unit is configured to adjust a sharpness of the branch trajectory based. The branch trajectory in a scene where it is determined that the second vehicle is present in the branch lane is a branch following trajectory. The branch trajectory in a scene where it is determined that the second vehicle is not present in the branch lane is a branch release trajectory. The branch release trajectory guides the first vehicle to the branch lane less sharply than the branch following trajectory.

A control method for an autonomous driving vehicle is provided. The method includes: obtaining perception information of road conditions around a vehicle; determining a first control decision based on the perception information and autonomous driving decision logic; controlling the vehicle to perform autonomous driving according to the first control decision; determining, in response to detecting an assisted driving instruction, a second control decision that is different from the first control decision based on the perception information, the autonomous driving decision logic, and the assisted driving instruction; and controlling the vehicle to perform autonomous driving according to the second control decision.

Enclosed are embodiments of motion control operations in various traffic scenarios in consideration of the kinematic factor for trajectory planning. In some embodiments, a method includes: determining a danger rating for at least one object identified in an environment, wherein the danger rating represents a perceived risk associated with a respective object; evaluating a set of hierarchical factors with respect to a traffic scenario, wherein a metric is derived for trajectories of the traffic scenario that quantifies passenger ride comfort based on the danger rating and the set of hierarchical factors; determining a motion control operation in the traffic scenario to increase the passenger ride comfort based on the metric; and augmenting a route planner of an autonomous vehicle with motion control operations in different traffic scenarios to increase the passenger ride comfort.

A vehicle control device, a vehicle control method, and a vehicle suitable for an automatic/manual driving mode vehicle that employs brakes capable of controlling braking forces of four wheels. A vehicle control device including a pitch angle adjustment unit that adjusts a pitch angle, which is an inclination of a vehicle generated in the vehicle when braking the vehicle, or a change amount of the pitch angle, the pitch angle adjustment unit adjusting the pitch angle according to a traveling mode of the vehicle instructed by a host controller provided in the vehicle.