580results about "External condition output parameters" patented technology

A system for processing multi-modal data representing an environment to generate scene graphs of the environment is described. The system can obtain sensor data associated with a vehicle operating in the environment. In examples, the system can determine a set of features from the sensor data, including one or more objects and one or more agents present in the environment, and can generate a scene graph that represents the poses and velocities of these objects and agents relative to the environment. In some examples, based on generating the scene graph, the system can generate a knowledge graph by encoding the relationships among the identified objects and agents. In some examples, the system can generate a control signal, using attributes that represent the states of objects and agents in the knowledge graph, and provide this control signal to the vehicle in order to adjust or cause the operation of the vehicle.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

Various systems and methods are presented regarding utilizing technology onboard a vehicle to mitigate the effects of communication signals being deleteriously affected / lost when operational surroundings cause occlusion / loss of receipt of positioning / location signals at the vehicle. The vehicle can be operating non-autonomously, partially autonomously, or autonomously. To supplement the lost / occluded signals position information of other systems proximate to the vehicle can be obtained / utilized. The other systems can include another vehicle, a mobile device, an internet, and suchlike. Also, onboard devices can be utilized to determine the location, such as an onboard camera system providing information regarding street signs, building facades, and suchlike.

According to certain aspects, a computer-implemented method for operating an autonomous or semi-autonomous vehicle may be provided. With the customer's permission, an identity of a vehicle operator may be identified and a vehicle operator profile may be retrieved. Operating data regarding autonomous operation features operating the vehicle may be received from vehicle-mounted sensors. When a request to disable an autonomous feature is received, a risk level for the autonomous feature is determined and compared with a driver behavior setting for the autonomous feature stored in the vehicle operator profile. Based upon the risk level comparison, the autonomous vehicle retains control of vehicle or the autonomous feature is disengaged depending upon which is the safer driver- the autonomous vehicle or the vehicle human occupant. As a result, unsafe disengagement of self-driving functionality for autonomous vehicles may be alleviated. Insurance discounts may be provided for autonomous vehicles having this safety functionality.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

A multi-vehicle control system (MVCS) for control of a multi-vehicle system having independently powered and steered lead and trailer vehicles connected by a slidable length sensing tow bar system. The MVCS includes a controller configured to receive throttle, brake, and steering signals from the lead vehicle, receive signals from the tow bar system indicating an extension length of the tow bar system, a front angle deviation of the lead vehicle, and a rear angle deviation of the trailer vehicle. The controller is further configured to determine, based on the received signals, a trailer vehicle acceleration / deceleration output and a trailer vehicle steering output, determine a driving scenario of the multi-vehicle system, and operate the multi-vehicle system based on the determined driving scenario and the determined trailer vehicle acceleration / deceleration output and trailer vehicle steering output.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

A road surface evaluation apparatus includes an electronic control unit having a microprocessor and a memory. The microprocessor is configured to perform acquiring driving information of each of a plurality of vehicles, including position information of the plurality of vehicles while driving and acceleration information indicating acceleration of the plurality of vehicles and map information including road information; evaluating the road roughness based on the acquired acceleration information of the plurality of vehicles; and outputting information on the evaluated road surface roughness in association with the acquired road information.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

A method for detecting and mitigating tailgating behavior in vehicle environment is disclosed. The method includes receiving real-time data from sensors integrated into a vehicle. The real-time data comprises information related to the surroundings of the vehicle. The method comprises analyzing the real-time data based on using Artificial Intelligence (AI) models extracted from a memory, to detect patterns and behaviors of the vehicle. The method includes identifying tailgating behavior based on the patterns and behaviors of the vehicle. The method includes validating accuracy of the identified tailgating behavior using the AI models. The method includes generating an alert to a user of the vehicle based on the validation of the accuracy of the identified tailgating behavior. The method comprises enabling an autonomous control system integrated with the vehicle to adjust speed and lane positioning of the vehicle based on the alert.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

An apparatus of a first vehicle includes a processor configured to detect a fault associated with a second vehicle. The processor is configured to obtain sensor data associated with a sensing region of the second vehicle. The processor is configured to provide an output, based on the sensor data, for controlling the second vehicle to traverse a vehicle transportation network

Example embodiments relate to self-supervisory and automatic response techniques and systems. A computing system may use sensor data from an autonomous vehicle sensor to detect an object in the environment of the vehicle as the vehicle navigates a path. The computing system may then determine a detection distance between the object and the sensor responsive to detecting the object. The computing system may then perform a comparison between the detection distance and a baseline detection distance that depends on one or more prior detections of given objects that are in the same classification group as the object. The computing system may then adjust a control strategy for the vehicle based on the comparison.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

According to an embodiment, disclosed is a system comprising, a sensor and a processor; wherein the processor storing instructions in a non-transitory memory that, when executed, cause the processor to detect, via the sensor of a host vehicle, a target vehicle; capture, via the sensor, a first region comprising a first characteristic of the target vehicle; analyze, the first region using an image processing module; determine, an identity of the target vehicle; capture, via the sensor, a second region comprising a second characteristic of the target vehicle; analyze, the second region using the image processing module; and determine, a safety feature that is enabled in the target vehicle.

The disclosure relates to a motor vehicle, to a driver assistance system, and to a method for operating the driver assistance system. A relevant slipstream region of a further motor vehicle driving in a predetermined surrounding region of the motor vehicle is detected. A current slipstream efficiency is ascertained based on whether the motor vehicle is driving in the slipstream region and, if so, based on which of the slipstream partial regions of the slipstream region the motor vehicle is driving in. An overall aerodynamic efficiency is ascertained based on a current driving speed of the motor vehicle and the current slipstream efficiency. An individual overall aerodynamic efficiency potential that characterizes an overall aerodynamic efficiency that will be achieved by the motor vehicle when same drives in the slipstream region of the further motor vehicle is assigned to the further motor vehicle based on the driving speed and slipstream region.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

A method or system for adaptive vehicle spacing, including determining a current state of a vehicle based on sensor data captured by sensors of the vehicle; for each possible action in a set of possible actions: predicting, based on the current vehicle state a first zone future safety value corresponding to a first safety zone of the vehicle; and selecting, based on the first zone future safety values for each of the possible actions in the set, a vehicle action.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

Systems and methods are provided for learning a driving behavior during a cut-in cut-out event or other triggering event to create a profile that adjusts operation of the adaptive cruise control (ACC) component of the vehicle to mimic the preferences of the driver. The profile may be based on data collected during a previous cut-in cut-out event or other triggering event. The data may be transmitted to an adaptive cruise control system that uses the data as input to a machine learning model. Output of the machine learning model may update the profile for the driver that operates the vehicle in ACC during the cut-in cut-out event. When the vehicle is operating in ACC and an event is within a threshold value of the cut-in cut-out event occurs at a later time, the vehicle may apply rules defined in the profile.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

Techniques are provided which may be implemented using various methods and / or apparatuses in a vehicle to utilize vehicle external sensor data, vehicle internal sensor data, vehicle capabilities and external CV2X input to determine, send, receive and utilize data elements to determine inter-vehicle spacing, intersection priority, lane change behavior and spacing and other autonomous vehicle behavior.

A computer implemented method is provided. The method, comprises: receiving from an autonomous vehicle sensor data, wherein the sensor data is indicative of an environment in which the vehicle is currently located or was previously located. The method further comprises receiving or determining additional data associated with at least one of: the sensor data, the vehicle, or the environment, wherein the additional data is different from the sensor data. The method further comprises displaying, on a display, an output comprising a representation of the sensor data. The method further comprises determining, based at least in part on the additional data, a reliability metric, the reliability metric being indicative of how reliable the sensor data is at representing the environment in which the vehicle is located at a current time. The method further comprises causing the output on the display to be based at least in part on the reliability metric.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.