Patent classifications
G05D1/0077
Driver re-engagement system
In a network of autonomous or semi-autonomous vehicles, an alert may be triggered when one of the vehicles switches from autonomous to manual mode. The alert may be communicated to nearby autonomous vehicles so that drivers of those vehicles may become aware of a potentially unpredictable manual driver nearby. Drivers of autonomous vehicles who may have become disengaged (e.g., sleeping, reading, talking, etc.) during autonomous driving may become re-engaged upon noticing the alert. A re-engaged driver may choose to switch his/her own vehicle from autonomous to manual mode in order to appropriately react to an unpredictable nearby manual driver. In additional or alternative embodiments, the alert may be triggered or intensified when indications of impairment of a nearby driver or malfunction of a nearby vehicle are detected.
Harvesting Machine, Obstacle Determination Program, Recording Medium on Which Obstacle Determination Program is Recorded, Obstacle Determination Method, Agricultural Work Machine, Control Program, Recording Medium on Which Control Program is Recorded, and Control Method
A harvesting machine includes: a machine main body 1; a harvesting unit 15 that is provided forward of the machine main body 1 and is capable of swinging upward and downward relative to the machine main body 1; a height detection unit that is capable of detecting a height position H at which the harvesting unit 15 is located; and an obstacle detection unit that is capable of detecting an obstacle that is located forward thereof in a travel direction. The obstacle detection unit includes: a first sensor 21 and a second sensor 22 that are provided at different positions in a vertical direction, and output detection information regarding a detection area that is located forward thereof in the travel direction; a selection unit that selects at least either the detection information from the first sensor 21 or the detection information from the second sensor 22 based on the height position H of the harvesting unit 15; and a determination unit that determines the obstacle based on the detection information selected by the selection unit.
VEHICLE TRAVELING REMOTE CONTROL SYSTEM
In a vehicle traveling remote control system, vehicles and a remote control apparatus communicate with each other to repeatedly transmit, from the remote control apparatus to each vehicle, a remote control value to be used to control traveling of each vehicle. The vehicle traveling remote control system includes the remote control apparatus and a traveling control unit. The remote control apparatus includes a remote control value generating unit that repeatedly generates the remote control value for traveling control of each vehicle. The traveling control unit is provided in each vehicle and executes the traveling control based on the remote control value repeatedly received from the remote control apparatus. The remote control apparatus generates, using the remote control value generating unit, the remote control value in accordance with a priority or a target response cycle that are changed depending on a traveling environment of each vehicle.
Secure system that includes driving related systems
A system that may include multiple driving related systems that are configured to perform driving related operations; a selection module; multiple fault collection and management units that are configured to monitor statuses of the multiple driving related systems and to report, to the selection module, at least one out of (a) an occurrence of at least one critical fault, (b) an absence of at least one critical fault, (c) an occurrence of at least one non-critical fault, and (d) an absence of at least one non-critical fault; and wherein the selection module is configured to respond to the report by performing at least one out of: (i) reset at least one entity out of the multiple fault collection and management units and the multiple driving related systems; and (ii) select data outputted from a driving related systems.
Apparatus and method for controlling vehicle based on redundant architecture
The present disclosure relates to an apparatus and a method for controlling a vehicle, and more particularly to a vehicle control apparatus having a redundant architecture. A vehicle control apparatus according to one embodiment of the present disclosure includes: a receiver, configured to receive sensing information from a vehicle sensor; a first electronic controller, configured to generate a first vehicle control command based on the received sensing information; a monitor, configured to monitor whether the first electronic controller is out of order; and a second electronic controller, configured to generate a second vehicle control command based on the received sensing information if the first electronic controller is out of order.
Heterogeneous processing in unmanned vehicles
A system-on-module (SOM) for controlling an unmanned vehicle (UV) is provided. The SOM comprises a circuit board, a first processing system in operative communication with the circuit board, and a second processing system in operative communication with the circuit board. The first processing system includes one or more first processing units and a volatile programmable logic array. The first processing system is configured to execute a first process for the UV. The second processing system includes one or more second processing units and a non-volatile programmable logic array. The second processing system is configured to monitor execution of the first process by the first processing system.
Regression-based line detection for autonomous driving machines
In various examples, systems and methods are disclosed that preserve rich spatial information from an input resolution of a machine learning model to regress on lines in an input image. The machine learning model may be trained to predict, in deployment, distances for each pixel of the input image at an input resolution to a line pixel determined to correspond to a line in the input image. The machine learning model may further be trained to predict angles and label classes of the line. An embedding algorithm may be used to train the machine learning model to predict clusters of line pixels that each correspond to a respective line in the input image. In deployment, the predictions of the machine learning model may be used as an aid for understanding the surrounding environment—e.g., for updating a world model—in a variety of autonomous machine applications.
Vehicle control system and control method
A vehicle control system includes first and second traveling control units for performing traveling control of controlling driving, braking, and/or steering of a vehicle without depending on a driving operation of a driver. In a case in which control instructions concerning the same actuator conflict between the first traveling control unit and the second traveling control unit, the first traveling control unit arbitrate the control instructions.
Autonomous vehicle with independent auxiliary control units
An autonomous vehicle which includes multiple independent control systems that provide redundancy as to specific and critical safety situations which may be encountered when the autonomous vehicle is in operation.
Obstacle detecting method, apparatus, device and computer storage medium
An obstacle detecting method, apparatus, device and computer storage medium are proposed. The method includes: obtaining data acquired by a plurality of sensors installed on a vehicle at the same time; combining the data acquired at the same time to obtain a data set corresponding to the time; and performing obstacle detection based on the data set to obtain obstacle information. The technical solution may reduce financial costs and enrich information amount of the data, and may simplify the obstacle detecting steps, and avoid the problem about failure to fuse data in different formats, and thereby further improve the vehicle's travel safety.