The present application relates to a method for performing off road adaptive cruise control in a host vehicle including controlling a vehicle speed at a first speed according to an adaptive cruise control algorithm, detecting an obstacle, using a sensor, within a host vehicle path, reducing the vehicle speed to a reduced speed in response to the detection of the obstacle, detecting a vehicle contact with the obstacle in response to a first inertial measurement unit measurement, applying a brake friction force and increasing an engine torque in response to detecting the vehicle contact with the obstacle, determining a traverse of the obstacle in response to a second inertial measurement unit measurement, and resuming the control of the vehicle speed at the first speed in response to the traverse of the obstacle.

A radar system for a vehicle, having at least one central control unit for transmitting data and for processing received data, at least one radar sensor head, which is set apart from the at least one central control unit and has at least one transmitting antenna for generating and at least one receiving antenna for receiving radar waves. The radar system includes at least one data line between the at least one central control unit and the at least one radar sensor head, with the at least one data line having at least one security unit for the encryption, decryption and/or signing of measuring data or control instructions.

Systems and methods are provided for vehicle navigation. In one implementation, at least one processor may receive, from a camera, at least one captured image representative of features in an environment of the vehicle. The processor may identify an intersection and a pedestrian in a vicinity of the intersection represented in the image. The processor may determine a navigational action for the vehicle relative to the intersection based on routing information for the vehicle; and determine a predicted path for the vehicle relative to the intersection based on the determined navigational action and a predicted path for the pedestrian based on analysis of the image. The processor may further determine whether the vehicle is projected to collide with the pedestrian based on the projected paths; and, in response, cause a system associated with the vehicle to implement a collision mitigation action.

An improved circuit configuration is disclosed for calibrating and/or verifying the operation of phase shifters in a phased array radar system. In one illustrative embodiment, a method includes: (i) programming a set of phase shifters to convert a radio frequency signal into a set of channel signals; (ii) splitting off a monitor signal from each channel signal while coupling the set of channel signals to a set of antenna feeds; and (iii) while taking the monitor signals in pairs associated with adjacent channels, measuring a relative phase between each pair of monitor signals.

A vehicle includes a communicator that is mounted on the vehicle to perform wireless communication with a server and a controller operates the communicator to transmit an accident reception request signal and image data acquired by another vehicle to the server when the vehicle has an accident with an accident target vehicle. The controller operates the communicator to receive a fault ratio from the server when the server generates fault ratio data between the vehicle and the accident target vehicle based on the image data.

Aspects of the disclosure relate to generating simulated degraded sensor data. For instance, first sensor data collected by a sensor of a perception system of an autonomous vehicle may be received. The first sensor data may be inputted into simulated degraded sensor data for a particular degrading condition. The simulated degraded sensor data may be used to evaluate or train a model for detecting objects of the perception system.

A method is described for determining the position of a vehicle equipped with a radar system that includes at least one radar sensor adapted to receive radar signals emitted from at least one radar emitter of the radar system and reflected the radar sensor. The method comprises: acquiring at least one radar scan comprising a plurality of radar detection points, wherein each radar detection point is evaluated from a radar signal received at the radar sensor and representing a location in the vicinity of the vehicle; determining, from a database, a predefined map, wherein the map comprises at least one element representing a static landmark in the vicinity of the vehicle; matching at least a subset of the plurality of radar detection points of the at least one scan and the at least one element of the map; deter-mining the position of the vehicle based on the matching.

Embodiments of the present disclosure are directed to a method for object detection. The method includes receiving sensor data indicative of one or more objects for each of a camera subsystem, a LiDAR subsystem, and an imaging RADAR subsystem. The sensor data is received simultaneously and within one frame for each of the subsystems. The method also includes extracting one or more feature representations of the objects from camera image data, LiDAR point cloud data and imaging RADAR point cloud data and generating image feature maps, LiDAR feature maps and imaging RADAR feature maps. The method further includes combining the image feature maps, the LiDAR feature maps and the imaging RADAR feature maps to generate merged feature maps and generating object classification, object position, object dimensions, object heading and object velocity from the merged feature maps.

A system of the present disclosure includes a coarse observation sensor configured to observe a range around a vehicle, high-accuracy observation object identification means configured to identify a high-accuracy observation object that is an object detected by the coarse observation sensor in the observation range and is an object to be observed at a higher resolution, object presence area prediction means configured to predict a range of an object future presence area where the high-accuracy observation object may be present after the identification, a fine observation sensor configured to observe the range of the object future presence area at the higher resolution, and object information output means configured to output information on the high-accuracy observation object observed by the fine observation sensor.

An autonomous vehicle (AV) includes a radar sensor system and a computing system that computes velocities of an object in a driving environment of the AV based upon radar data that is representative of radar returns received by the radar sensor system. The AV can be configured to compute a first velocity of the object based upon first radar data that is representative of the radar return from a first time to a second time. The AV can further be configured to compute a second velocity of the object based upon second radar data that includes at least a portion of the first radar data and further includes additional radar data representative of a radar return received subsequent to the second time. The AV can further be configured to control one of a propulsion system, a steering system, or a braking system to effectuate motion of the AV based upon the computed velocities.