12 results about "Self driving" patented technology

The technology provides an interior camera sensing system for self-driving vehicles. The sensor system includes image sensors and infrared illuminators to see the vehicle's cabin and storage areas in all ambient lighting conditions. The system can monitor the vehicle for safety purposes, to detect the cleanliness of the cabin and storage areas, as well as to detect whether packages or other objects have been inadvertently left in the vehicle. The cameras are arranged to focus on selected regions in the vehicle cabin and the system carries out certain actions in response to information evaluated for those regions. The interior space is divided into multiple zones assigned different coverage priorities. Regardless of vehicle size or configuration, certain actions are performed according to various ride checklists and the imagery detected by the interior cameras. The checklists include pre-ride, mid-ride, and post-ride checklists.

A quantum method that uses the Mz quantum circuit that receives a given single chaotic value to generate strong quantum key stream of three keys. The method includes encrypting a quantum plain color image; applying set of CNOT gates between qubits of a quantum image and qubits of a quantum key to obtain a quantum encrypted image; generating a new quantum key, applying additional set of CNOT gates between the qubits the quantum color image, and the corresponding qubits of the quantum key as target qubits; performing a quantum plain scrambling (QPS) operation; and applying set of CNOT gates; and obtaining, by the quantum circuit, a quantum ciphered image.

Provided are an information processing method, an information processing apparatus, and a program that can increase a diversity of learning data for configurations or techniques of unspecified devices. The information processing method includes: obtaining sensor data obtained by a sensor installed in a vehicle, and at least one type of traveling data of the vehicle; associating the sensor data and the at least one type of traveling data with each other; determining a degree of difference of the at least one type of traveling data from the at least one type of one or more traveling data associated with one or more sensor data; and selecting the sensor data as learning data according to the degree of difference.

A method and device for amending a reference path associated with a vehicle are disclosed. The method includes: (i) acquiring road segment data and reference path data, the reference path data having a plurality of anchor points defining the reference path along the road segment, (ii) using the road segment data and the reference path data to determine a safe deviation interval for each one of the plurality of anchor points, a given safe deviation interval for a given anchor point being indicative of an acceptable deviation of the vehicle from the reference path; and (iii) using the safe deviation intervals to determine an amended path for the vehicle instead of the reference path, such that by following the amended path the vehicle falls within the constraints of the road segment.

Systems and methods for autonomous driving which calculates path trajectories by incorporating latencies of vehicle components and calculations so that when the vehicle is in an autonomous driving mode and using a trajectory to calculate a designated path, the latencies of each vehicle component can be taken into account to provide a more accurate vehicle path.

The present disclosure provides a method and an apparatus for planning an automatic parking path, a medium and a device and belongs to the field of self driving technologies. The method includes: extracting perception information within a predetermined parking space including a target vehicle place, which is perceived by a vehicle; based on the perception information, identifying a ground sideline of the target parking place, a road sideline and an actual obstacle contour line; cropping the ground sideline and the road sideline intersecting with the ground sideline and taking remaining ground sideline and road sideline as corresponding boundaries of an available parking space of the target parking place; and, performing collision detection based on the corresponding boundaries of the available parking space and the actual obstacle contour line, and based on a result of the collision detection, performing vehicle trajectory planning to obtain an automatic parking planning path.

Techniques described in this application are directed to determining safe path navigation of an autonomous personal mobility device, including a self-driving electric scooter, using sensors and / or data from other sources. The autonomous personal mobility device is configured to generate maps and transform the maps into tile segments that can be shared with other autonomous personal mobility devices. Techniques further include receiving a request for an autonomous personal mobility device at a location, and enabling the autonomous personal mobility device to self-drive to the location.

The technology provides an interior camera sensing system for self-driving vehicles. The sensor system includes image sensors and infrared illuminators to see the vehicle's cabin and storage areas in all ambient lighting conditions. The system can monitor the vehicle for safety purposes, to detect the cleanliness of the cabin and storage areas, as well as to detect whether packages or other objects have been inadvertently left in the vehicle. The cameras are arranged to focus on selected regions in the vehicle cabin and the system carries out certain actions in response to information evaluated for those regions. The interior space is divided into multiple zones assigned different coverage priorities. Regardless of vehicle size or configuration, certain actions are performed according to various ride checklists and the imagery detected by the interior cameras. The checklists include pre-ride, mid-ride, and post-ride checklists.

Described herein are techniques for facilitating communications between vehicles within a platoon while minimizing latency. In some embodiments, such techniques may be performed by a lead vehicle and may comprise obtaining, from one or more sensors, sensor information pertaining to an environment in which the lead vehicle is located and generating, from the sensor information, driving instructions to be executed by a platoon of vehicles. The techniques may further comprise identifying, within the platoon of vehicles, a plurality of separate groups of vehicles and transmitting the generated driving instructions to a platooning platform via a long-range communication channel such that the driving instructions are relayed to each of the plurality of separate groups of vehicles. The techniques may further comprise transmitting the generated driving instructions to at least one additional vehicle of the platoon of vehicles via a short-range communication channel.

The present invention relates to hybrid self-driving ground vehicle (100) for autonomous navigation In one embodiment, the hybrid self-driving ground vehicle (100) comprises a mobility platform (102) configured to actuate movement of the vehicle, an odometry sensor system (104) configured to continuously estimate translational and rotational motion of the mobility platform, a visual sensing system (106) comprising plurality of two-dimensional camera configured to acquire image data of an environment, an obstacle detection system (108) configured to detect dynamic and static obstacles, one or more processors (110, 112) operatively coupled to the odometry sensor system, the visual sensing system, and the obstacle detection system, wherein the one or more processors configured to: select between an Automated Guided Vehicle (AGV) operational mode and an Autonomous Mobile Robot (AMR) operational mode, continuously localize the vehicle using the odometry sensor system, intermittently perform environment mapping at selected keyframes by processing image data from the two-dimensional cameras to generate and update a two-dimensional navigation-oriented representation of the environment and autonomously navigate the vehicle within the environment while maintaining positional accuracy through intermittent calibration.

The invention discloses a method, device and equipment for determining the transverse distance of a target vehicle and a medium, and belongs to the field of automatic driving, and the method comprises the steps: obtaining the target driving parameters of the target vehicle and obtaining the driving parameters of the vehicle when the target vehicle exists in front of a road on which the vehicle travels; performing risk assessment according to the target driving parameter and the self-driving parameter to obtain an assessment result; if the assessment result is that the collision risk exists, the transverse distance of the target vehicle is determined based on the target driving parameters and the driving parameters of the vehicle, and the transverse distance is the distance between the vehicle body edge of the target vehicle and the left and right channel sidelines of the road. According to the method, the transverse distance detection is triggered only when the two vehicles have the collision risk, frequent calculation of non-threat targets is avoided, calculation power resource occupation is reduced, the resource utilization rate is improved, response delay of the vehicle control end due to frequent data input can be avoided, unnecessary forced movement is reduced, and the driving smoothness is improved.

A signal transmission method and an apparatus can be used in the field of autonomous driving, intelligent driving, or self driving. In embodiments of this application, a total available frequency band of a detection apparatus includes N frequency bands with same bandwidths, the N frequency bands respectively correspond to N orientation ranges, and N is an integer greater than 1. When the detection apparatus transmits a signal, a first available frequency band of the signal is determined based on an orientation of the detection apparatus, the signal is transmitted on the first available frequency band, and the first available frequency band is one of the N frequency bands. In this way, detection apparatuses in different orientation ranges use different frequency bands to transmit signals. In this way, selection of a transmission frequency band of a detection apparatus can be standardized, and interference between detection apparatuses can be reduced.