A vehicle includes a communication device configured to receive current position information; a plurality of devices for recognizing an obstacle; a storage for storing strategy information corresponding to a failure of each of the plurality of devices; and an autonomous drive control apparatus configured to diagnose a failure of the plurality of devices during autonomous driving, when at least one device fails, identify strategy information corresponding to the at least one device stored in the storage, and perform restriction control on at least one of a driving speed, a lane change, or a backward movement of the autonomous driving based on the strategy information, wherein the plurality of devices includes a plurality of image obtainers, a first distance detector including a plurality of radars, and a second distance detector including a plurality of LiDARs.

A system and method are disclosed for overheight vehicle impact avoidance and incident detection. A detection subsystem of the system determines whether an incoming vehicle is clear to pass, depending at least on its height. The detection subsystem relies on distance sensors located along the freeway to detect the highest point of the vehicle and outputs an indication of whether the vehicle can pass. A warning subsystem receives the indication that a vehicle is overheight and provides a warning indication to the driver about the vehicle's inability to pass an upcoming structure. The warning subsystem may also perform a variety of other tasks, such as, for example, logging a variety of information about the vehicle and the incident, sending data about the incident locally to a central command, and generating reports.

Systems and methods for operating a vehicle automatically in real time may be provided. The system may receive and process real time sensor data from a sensing system via an arithmetic and control unit (ACU). The system may obtain, via the ACU, one or more tasks during the processing of the real time sensor data. The system may classify, via the ACU, the one or more tasks into real time vehicle controlling (VC) tasks and non real time VC tasks. The system may further send the real time VC tasks to at least one dedicated processing core of the ACU for processing the real time VC tasks and generating one or more real time VC commands accordingly.

According to an aspect of an embodiment, operations may comprise receiving, from a LIDAR mounted on a vehicle, a first 3D point cloud comprising points of a region around the vehicle as observed by the LIDAR. The operations may also comprise accessing an HD map comprising a second 3D point cloud comprising points of the region around the vehicle. The operations may also comprise segmenting LIDAR ground points from LIDAR non-ground points in the first 3D point cloud. The operations may also comprise segmenting map ground points from map non-ground points in the second 3D point cloud. The operations may also comprise determining a pose of the vehicle by matching the LIDAR ground points to the map ground points and by matching the LIDAR non-ground points to the map non-ground points.

A driver assistance system includes a detector configured to detect pedestrians or obstacles in a front detection area and a rear detection area of a vehicle; an accelerator pedal sensor configured to detect a position of an accelerator pedal of the vehicle; and a controller configured to selectively activate the front detection area and the rear detection area according to a gear state of the vehicle, when there is the pedestrians or the obstacles in the activated detection area, to recognize an acceleration pedal change amount from an acceleration pedal position detected through the accelerator pedal sensor, to determine whether emergency braking of the vehicle is necessary based on the recognized acceleration pedal change amount, and when the emergency braking is necessary, to perform the emergency braking for the vehicle.

Included are: a radar main unit for emitting a radar wave and receiving a reflection wave of the radar wave reflected by an object; and a dielectric substrate in which multiple matching layers each having a protruded shape are regularly arranged on one surface of the dielectric substrate, and the radar wave emitted from the radar main unit enters the multiple matching layers in a state where the other-surface side of the dielectric substrate is attached to a windshield.

A vehicle, system and method for operating the vehicle is disclose. The system includes a radar system and a processor. The radar system locates a gap between targets in a second lane adjoining a first lane, with the host vehicle residing in the first lane. The processor is configured to determine a viability value of the gap for a lane change, select the gap based on the viability value, align the host vehicle with the selected gap, and merge the host vehicle from the first lane into the selected gap in the second lane.

A remote control method for remote control of a driver assistance system of a motor vehicle by a remote control unit assigned to the motor vehicle, wherein the driver assistance system is designed to actuate the motor vehicle for carrying out an autonomous or piloted parking operation, and which includes an optical sensor apparatus having at least one sensor, an analysis unit and a control unit.

An autonomous system for loading or unloading an autonomous vehicle, in accordance with aspects of the present disclosure, includes one or more module(s) that include at least one of a compartment or a sub-compartment where the module(s) are located in an autonomous vehicle, a robotic movement apparatus configured to autonomously move items to or from the module(s), one or more processors, and at least one memory storing instructions which, when executed by the processor(s), cause the autonomous system to autonomously move an item, using the robotic movement apparatus, to or from the at least one module of the autonomous vehicle.

A method and device for determining a coefficient of friction of a passable supporting surface with the aid of an ego vehicle, including a step of acquiring first data values, which represent a moisture level in the surrounding area of the ego vehicle, a step of checking the plausibility of the acquired, first data values by comparison with at least one second data value, and a step of determining third data values, which represent the coefficient of friction of the passable supporting surface; the determination taking place as a function of the plausibility check of the first data values, using the at least one second data value.