A method for performing an at least partially automatic vehicle function of a vehicle depending on a travel route to be assessed by means of a driver assistance system is disclosed. The method comprises providing a plurality of clusters from route data with respect to at least one known travel route, wherein the clusters group the route data sectionwise according to predefined geometric parameters. The method comprises providing recorded course data that indicate a course of the travel route to be assessed and applying the clusters to the course data in order to divide the travel route to be assessed into route sections corresponding to the clusters. The method comprises determining at least one uncertainty quantity which is characteristic of an uncertainty with respect to the assignment made and determining a control quantity as a function of the uncertainty quantity and providing the control quantity for performing the vehicle function.

A method for quantifying vehicle path following performance, the method comprising; obtaining samples of path following performance (I), selecting a subset of the path following performance samples such that the selected samples follow a pre-determined statistical extreme value distribution, parameterizing the pre-determined statistical extreme value distribution based on the selected samples of path following performance, and quantifying vehicle path following performance based on the parameterized statistical extreme value distribution.

A method for determining a speed profile to be followed by a vehicle, including acquiring event data including a distance from an event and a target speed at this event for the vehicle, and determining a speed profile to be followed as a function of time, between an initial speed and the target speed in three successive distinct phases, respectively a first phase in which the jerk is set constant at a predetermined maximum jerk value to reach an optimal target acceleration value, a second phase in which the optimal target acceleration value is kept constant, and a third phase in which the jerk is again set constant to reach a zero acceleration value at the end of the third phase. The optimal target acceleration value is such that the distance required to carry out the three phases of the profile is equal to the distance from the event.

A vehicle control device, a vehicle control method, and a vehicle control system according to the present invention obtain an inter-vehicle time based on a relative distance between a first vehicle traveling, in front of an own vehicle, in a second lane adjacent to a first lane in which the own vehicle travels and a second vehicle traveling in the second lane in front of the first vehicle and based on a relative velocity of the first vehicle relative to the second vehicle, obtain a relative acceleration of the first vehicle relative to the second vehicle, set the first vehicle as a high-stress vehicle based on a lane change space that is based on the inter-vehicle time, the relative acceleration, and a relative distance between the second vehicle and a third vehicle traveling in the first lane in front of the own vehicle, and output a control command for changing a driving state of the own vehicle based on a relative distance between the high-stress vehicle and the own vehicle. This makes it possible to improve the driving safety of a vehicle on a road with multiple lanes in each direction.

A control device includes a video data acquisition unit, an orientation detection unit that determines whether a first condition that the driver faces a direction other than a traveling direction of the vehicle is met, an event detection unit, and a recording control unit that, if an event is detected, stores first video data including at least an event detection time point as event recording data.

Aspects of the disclosure provide for generating distributions for hypothetical or potentially occluded objects. For instance, a location for which to generate one or more distributions may be identified. Observations of road users by perception systems of a plurality of autonomous vehicles may be accessed. Each of these observations may identify a characteristic of one of the road users. A distribution of the characteristic for the location may be determined based on the observations. The distribution may be provided to one or more autonomous vehicles in order to enable the one or more autonomous vehicles to use the distribution to generate a characteristic for a hypothetical occluded road user and to respond to the hypothetical occluded road user.

An apparatus includes at least one camera configured to capture an image of a traffic lane in front of a vehicle. The apparatus also includes a radar transceiver configured to detect one or more target vehicles proximate to the vehicle. The apparatus further includes a path prediction and vehicle detection controller configured to determine first parameters for predicting a path of the vehicle; determine second parameters for predicting the path of the vehicle; predict the path of the vehicle using a combination of the first parameters and the second parameters, where the combination is weighted based on a speed of the vehicle; identify one of the one or more target vehicles as a closest in path vehicle based on the predicted path of the vehicle; and activate at least one of a braking control and a steering control based on a proximity of the identified closest in path vehicle.

A vehicle dash cam may be configured to execute one or more neural networks (and/or other artificial intelligence), such as based on input from one or more of the cameras and/or other sensors associated with the dash cam, to intelligently detect safety events in real-time. Detection of a safety event may trigger an in-cab alert to make the driver aware of the safety risk. The dash cam may include logic for determining which asset data to transmit to a backend server in response to detection of a safety event, as well as which asset data to transmit to the backend server in response to analysis of sensor data that did not trigger a safety event. The asset data transmitted to the backend server may be further analyzed to determine if further alerts should be provided to the driver and/or to a safety manager.

A vehicular breaking force control system that includes a control device including a processor that acquires a plurality of longitudinal accelerations from a driving assistance system, and calculates a driving/braking request when the vehicle is in a coasting state in which an acceleration operation or a deceleration operation are not performed during running of the vehicle. The processor further acquires a driving force lower limit set for a powertrain actuator having a set gear ratio, and distributes the driving/braking request to at least one of (i) a powertrain system including the powertrain actuator and (ii) a brake system including a brake actuator. The driving/braking request is distributed to the at least one of the powertrain system and the brake system based on the acquired driving force lower limit.

The disclosure relates to assessing and responding to wheel slippage and estimating road friction for a road surface. For instance, a vehicle may be controlled in an autonomous driving mode in order to follow a trajectory. A wheel of the vehicle may be determined to be slipping such that the vehicle has limited steering control. In response to determining that the wheel is slipping, steering of one or more wheels may be controlled in order to orient the one or more wheels towards the trajectory in order to allow the vehicle to proceed towards the trajectory when the wheel is no longer slipping. In addition, the road friction may be estimated based on the determination that the wheel is slipping. The vehicle may be controlled in the autonomous driving mode based on the estimated road friction.