The present disclosure relates to a driving control system and a method of controlling the same using sensor fusion between vehicles, and the driving control system allows vehicles to share sensor data, fuses the sensor data, matches the adjacent vehicle and the sensor data, improves recognition performance in respect to a periphery, controls driving in accordance with a change in peripheral environment and a traveling state of another vehicle, receives sensor data of another vehicle, converts a coordinate of sensor data of the matched vehicle, and fuses host vehicle sensor information, which makes it possible to improve recognition performance and accuracy in respect to a surrounding environment and object, enable stable autonomous driving, and improve stability of the vehicle.

The technology relates to determining general weather conditions affecting the roadway around a vehicle, and how such conditions may impact driving and route planning for the vehicle when operating in an autonomous mode. For instance, the on-board sensor system may detect whether the road is generally icy as opposed to a small ice patch on a specific portion of the road surface. The system may also evaluate specific driving actions taken by the vehicle and/or other nearby vehicles. Based on such information, the vehicle's control system is able to use the resultant information to select an appropriate braking level or braking strategy. As a result, the system can detect and respond to different levels of adverse weather conditions. The on-board computer system may share road condition information with nearby vehicles and with remote assistance, so that it may be employed with broader fleet planning operations.

A method and a system for generating a mesh representation of a surface. The method includes receiving a three-dimensional (3D) point cloud representing the surface, generating a reconstruction dataset having a higher resolution than the 3D point cloud in one or more regions corresponding to the surface from the 3D point cloud, and generate a polygon mesh representation of the surface by using a fine-to-coarse hash map for building polygons at a highest resolution first followed by progressively coarser resolution polygons, using the reconstruction dataset.

In an imaging system comprising an imaging sensor generating successive point clouds from detected objects, tracking points of interest, or targets, across multiple point clouds/frames can be performed to enable robust object detection by clustering the targets based on one or more tracking parameters. An imaging sensor may comprise a radar sensor or lidar sensor, and tracking the one or more parameters of a target may be performed by a state model of the target.

Methods and systems are provided for generating an on-demand distributed aperture by mechanical articulation. In some aspects, a process can include steps for determining a location of an autonomous vehicle, determining whether a maneuver requires long range detections or medium range detections based on the location of the autonomous vehicle, positioning at least two articulated radars based on the determining of whether the maneuver requires long range detections or medium range detections, and enabling a mode of resolution based on the positioning of the at least two articulated radars and by utilizing a static radar. Systems and machine-readable media are also provided.

The present disclosure is directed to the transmission and reception of sets of very high frequency electromagnetic (EM) signals in ways that allow a sensing apparatus to discriminate between different sets of transmitted EM signals. Here a sensing apparatus may sequentially transmit different sets of EM signals. Each of these different sets of signals may include an encoded identifier that uniquely identifies each respective signal set of the different sets of signals. Each of these signal sets may include several pulses of a particular frequency with a same relative phase relationship followed by pulses that have a different phase relationship. These changes in phase may be used to encode the unique identifiers into the different sets of transmitted EM energy and these identifiers may be used by a sensing apparatus to associate specific received sets of EM energy with specific sets of transmitted EM energy.

A target vehicle speed generating device basically includes a determination unit and a correction unit. The determination unit determines whether or not a sudden change point is present in the target vehicle speed contained in the corrects the target vehicle speed so as to eliminate the sudden change point upon determining that the sudden change point is present by the determination unit. The sudden change point corresponds to a point at which acceleration changes in excess of a predetermined condition.

There is provided a method and control system for limiting a driver acceleration request of a vehicle. The vehicle comprises a controller arrangement that receives a driver acceleration request and determines whether the driver acceleration request is below an acceleration threshold. If so, it initiates a limiting protocol and dependent on the distance between a preceding vehicle and the host vehicle limits the acceleration of the vehicle in comparison to the driver acceleration request. The invention further relates to a vehicle comprising such as control system.

Vehicles can include systems and apparatus for performing signal processing on sensor data from radar(s) and LiDAR(s) located on the vehicles. A method includes obtaining and filtering radar point cloud data of an area in an environment in which a vehicle is operating on a road to obtain filtered radar point cloud data; obtaining a light detection and ranging point cloud data of at least some of the area, where the light detection and ranging point cloud data include information about a bounding box that surrounds an object on the road; determining a set of radar point cloud data that are associated with the bounding box that surrounds the object; and causing the vehicle to operate based on one or more characteristics of the object determined from the set of radar point cloud data.

An object detection device includes a first sensor, a second sensor, a calculation range selector and an estimator. The first sensor outputs a radio frequency (RF) signal, receives a reflected RF signal reflected from an object, and obtains a first measurement value for the object based on a received reflected RF signal. The second sensor obtains a second measurement value for the object by sensing a physical characteristic from the object. The physical characteristic sensed by the second sensor is different from a characteristic of the object measured as the first measurement value obtained by the first sensor. The calculation range selector sets a first reference range based on the second measurement value. The first reference range represents a range of execution of a first calculation for detecting a position of the object using a first algorithm. The estimator performs the first calculation only on the first reference range using the first measurement value, and generates a first result value as a result of performing the first calculation. The first result value represents the position of the object.