An on-board computing system for a vehicle is configured to generate and selectively present a set of autonomous-switching directions within a navigation user interface for the operator of the vehicle. The autonomous-switching directions can inform the operator regarding changes to the vehicle's mode of autonomous operation. The on-board computing system can generate the set of autonomy-switching directions based on the vehicle's route and other information associated with the route, such as autonomous operation permissions (AOPs) for route segments that comprise the route. The on-board computing device can selectively present the autonomy-switching directions based on locations associated with anticipated changes in autonomous operations determined for the route of the vehicle, the vehicle's location, and the vehicle's speed. In addition, the on-board computing device is further configured to present audio alerts associated with the autonomy-switching directions to the operator of the vehicle.

Systems and methods for controlling a head-up display (HUD) in a vehicle are disclosed herein. One embodiment deactivates the HUD in response to a command from a driver of the vehicle; assigns a level of urgency to an item of information associated with a current vehicular context; and activates the HUD to display the item of information to the driver, when the level of urgency exceeds a predetermined threshold.

A system and method for estimating road conditions ahead of a vehicle, including: a LIDAR sensor operable for generating a LIDAR point cloud; a processor executing a road condition estimation algorithm stored in a memory, the road condition estimation algorithm performing the steps including: detecting a ground plane or drivable surface in the LIDAR point cloud; superimposing an M×N matrix on at least a portion of the LIDAR point cloud; for each patch of the LIDAR point cloud defined by the M×N matrix, statistically evaluating a relative position, a feature elevation, and a scaled reflectance index; and, from the statistically evaluated relative position, feature elevation, and scaled reflectance index, determining a slipperiness probability for each patch of the LIDAR point cloud; and a vehicle control system operable for, based on the determined slipperiness probability for each patch of the LIDAR point cloud, affecting an operation of the vehicle.

Systems and methods are described for an adaptive user interface system for a vehicle with an automatic vehicle system. The adaptive user interface system includes a display and an electronic controller. The controller is configured to generate a graphical user interface indicative of operation of the automatic vehicle system, output the graphical user interface on the display, monitor an indicia of a driver's comfort level, and determine, based on the monitored indicia, when the driver is not comfortable with the operation of the automatic vehicle system. In response to determining that the driver is not comfortable with the operation of the automatic vehicle system, the electronic controller modifies the graphical user interface to provide an increased level of detail.

A driver assistance system for motor vehicles, including at least one sensor for detecting object properties of objects which are located in the surroundings of the motor vehicle; a first interface; an output unit for transmitting the object properties to a user; and a control unit. The sensor transmits the object properties in a form of a first signal to the first interface. The first interface transmits the object properties, received in the form of the first signal, to the control unit in the form of a second signal, the control unit being configured to forward the object properties, received in the form of a second signal, to the output unit and to control the output of the object properties by the output unit.

In one embodiment, a cognitive load driving assistant increases driving safety based on cognitive loads. In operation, the cognitive load driving assistant computes a current cognitive load of a driver based on sensor data. If the current cognitive load exceeds a threshold cognitive load, then the cognitive load driving assistant modifies the driving environment to reduce the cognitive load required to perform the primary driving task and/secondary task(s), such as texting via a cellular phone. The cognitive load driving assistant may modify the driving environment indirectly via sensory feedback to the driver or directly through reducing the complexity of the primary driving task and/or secondary tasks. In particular, if the driver is exhibiting elevated cognitive loads typically associated with distracted driving, then the cognitive load driving assistant modifies the driving environment to allow the driver to devote appropriate mental resources to the primary driving task, thereby increasing driving safety.

Synchronized work zone traffic management systems and methods are disclosed herein. An example method includes synchronizing, by a first vehicle, communication with a second vehicle over a wireless link, and displaying alternatingly, by the first vehicle, one of two messages on a first external display according to an alternating schema. A first message indicates to drivers to drive slowly and a second message indicates to the drivers to stop. The first message being displayed on the first external display when the second vehicle is displaying the second message on a second external display. The first vehicle displaying the second message on the first external display when the second vehicle is displaying the first message on the second external display. The alternating displaying of the first and second messages being used to control flow of traffic on a one-way street.

An operation device for an autonomous vehicle includes a touch panel configured to display at least one of a start button and a deceleration button, a notification button, and a tab switch on the same screen, the autonomous vehicle being autonomously drivable, the start button being a button for starting driving of the autonomous vehicle in an autonomous drive mode, the deceleration button being a button for decelerating the autonomous vehicle during the autonomous drive mode, the notification button being a button for performing notification to an outside of the autonomous vehicle, and the tab switch being a switch for displaying or enlarging an equipment control button group for controlling equipment mounted on the autonomous vehicle.

A racing coach device stores a first path of travel along a racetrack over a first time period and a second path of travel along the racetrack over a second time period. The racing coach device identifies, for each of a plurality of geolocations along the racetrack, one of the first path of travel or the second path of travel that is associated with a shorter duration of time over which the user traversed a segment of the path of travel associated with each of the plurality of geolocations. The device determines an optimal path of travel along the racetrack based on the identified first and second path of travel for each segment of the path of travel at each of the plurality of geolocations that results in a calculated lap time to traverse the racetrack that is less than the first time period and the second time period.

A system, a method and a device for planning a driving path for a vehicle are described. In one example aspect, the device is configured to: analyze sense data to obtain positioning data of vehicles; assign vehicle transportation tasks to an unmanned vehicle and a manned vehicle in the predetermined area in accordance with a predetermined transportation task, each vehicle transportation task including a transportation start point and a transportation end point; plan driving paths for the unmanned vehicle and the manned vehicle based on the assigned vehicle transportation tasks, the vehicle positioning data and map data; transmit the assigned transportation task and the planned driving path for the unmanned vehicle to the unmanned vehicle; and transmit the assigned transportation task and the planned driving path for the manned vehicle to a mobile device corresponding to the manned vehicle.