7301results about "Driver input parameters" patented technology

A system and method for electric vehicle operational optimization is disclosed. The system comprises a memory storing processor-executable instructions and a processor, communicably coupled with the memory. The system obtains input data and predict health and performance parameters. The system generates computer simulated instances which emulate a behavior and a performance of the electric vehicle. The system, further, validates the health and the performance parameters by simulating the computer simulated instances in a virtual environment. The system determines a behavior status, a performance status and a health status of the electric vehicle. Thereafter, the system determines abnormality associated with the electric vehicle, followed by determining action for rectifying the abnormality. Consequently, the system controls an operation by performing the determined action at the electric vehicle.

A management server system may obtain data associated with a vehicle. The management server system may obtain the data from a plurality of data sources associated with the vehicle. The data may include a plurality of subsets of data that each correspond to correspond to a particular driver assignment category. Each subset of data may identify a particular persona as a driver of a vehicle. The management server system may determine a driver of the vehicle based on each subset of data and a hierarchical plurality of driver assignment categories. Based on the determination of the driver of the vehicle, the management server system can dynamically map the driver to a particular event. The management server system may generate a user interface identifying the driver and the event.

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.

This application discloses a method, system, and related equipment for intelligent energy management of new energy vehicles. Based on the vehicle's starting and ending points, at least one candidate energy-saving path is determined. The predicted energy consumption of the vehicle along at least one candidate energy-saving path is lower than that of other paths. The total energy consumption is predicted based on road condition information and energy consumption impact information for each path. In response to the selection of at least one candidate energy-saving path, a preset travel route is determined. The preset travel route includes multiple road segments, and the total energy consumption includes the energy consumption of each road segment. With the goal of minimizing fuel consumption along the preset travel route, the engine's operating state is controlled based on the initial state of charge (SOC) of the power battery in each road segment, the energy consumption of the road segment, and the vehicle's actual overall demand, ensuring the engine operates within its high-efficiency range. Using this application can reduce fuel consumption for users and improve the driving experience.

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.

The present disclosure relates to transportation and related methods and systems including software-defined vehicles, vehicle operating states, an identity management system, an intelligent digital twin system that creates, manages, and provides digital twins for transportation systems using sensor and other data, and the integration of a transportation system with an AI convergence system of systems, providing a multi-layered system for intelligent automation and data-driven decision making across operational aspects of a transportation system.

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 charging system can include a housing. The housing can include a controller. The housing also can include a power source configured to power the controller. The charging system also can include a wireless charger configured to transfer energy to the power source. The wireless charger can include a first indicator. The first indicator can be configured to provide a first non-flashing visual output at a first brightness level and indicative of a first charging status of the power source. The first indicator also can be configured to provide a second non-flashing visual output at a second brightness level indicative of a second charging status of the power source. Other embodiments are disclosed.

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 charging system can include a housing. The housing can include an inner surface. The housing also can include an internal power source. The housing further can include a component configured to draw energy from the internal power source. The charging system also can include a removable charging source. The removable charging source can be removably coupled to the housing. The removable charging source can include first and second registration structures at different locations of a perimeter of a portion of the removable charging source. The first and second registration structures can align the inner surface of the housing with the removable charging source. Other embodiments are disclosed.

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.

The invention discloses a driver state sensing system based on physiological indexes and external behavior analysis, which relates to the technical field of vehicle active safety control, and comprises a sensor group integrated in a driver contact or close area and a vehicle control part and used for collecting physiological signals and behavior characteristic signals of a driver in real time, the physiological signals at least comprise heart rate and skin electric signals, and the behavior characteristic signals at least comprise eyelid movement, head posture and steering wheel operation signals. According to the driver state sensing system, the comprehensiveness and accuracy of driver state sensing are remarkably improved by integrating physiological indexes and external behavior analysis, the limitation of single signal judgment is effectively overcome through a multi-source signal fusion mechanism, the reliability of state evaluation is ensured, and the advanced signal preprocessing technology adopted by the system is high in reliability. The data anti-interference capability is enhanced, the feature extraction precision is improved, and the robustness of the model is enhanced.

The present disclosure discloses an anthropomorphic lane-changing control method and system based on driving risk quantification, and a vehicle. The method includes: determining whether a main vehicle has a lane-changing intention based on motion statuses of the main vehicle and a front vehicle in a current lane; if there is a lane-changing intention, generating an anthropomorphic lane-changing trajectory that satisfies safety constraints and reachability constraints; based on a motion status of a traffic participant that causes a risk to the main vehicle, calculating an overall risk level and determining whether the anthropomorphic lane-changing trajectory satisfies risk constraints; and if the risk constraints are not satisfied, regenerating an anthropomorphic lane-changing trajectory; or if the risk constraints are satisfied, performing tracking control based on a preview-following theory. In the present disclosure, a lane-changing intention is described and identified based on actually measured data, to generate an anthropomorphic lane-changing trajectory.

A vision language model (VLM) may be used to evaluate signs that designate restricted or toll lanes, determine whether it is permissible (and / or the cost) to merge into a restricted or toll lane, and / or determine when to merge out of a restricted or toll lane based on the cost. Frames from one or more (e.g., front-facing) camera(s) may be evaluated for applicable signs (e.g., using a sign recognition DNN or a VLM). If detected, the (e.g., cropped) image of the sign may be provided as input to a VLM with a textual prompt instructing the VLM to determine whether to drive in the restricted or toll lane (e.g., whether it can be taken within budget) and / or what the cost would be. The generated response may be provided to an ADAS to trigger an initiation of a merge left or right or a determination to stay in the current lane.

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 “one-pedal rocking mode” for extricating an electric vehicle from a stuck condition is implemented by: receiving, via a human-machine interface (HMI) of the electric vehicle, an indication of a user selection to activate the one-pedal rocking mode; operating the electric vehicle in the one-pedal rocking mode responsive to detecting movement of an accelerator pedal of the electric vehicle; controlling at least one electric motor of the electric vehicle to: (i) apply a forward torque to corresponding drive wheels when the accelerator pedal is in a first pedal position that exceeds a forward threshold, (ii) apply a reverse torque to the corresponding drive wheels when the accelerator pedal is in a second pedal position that is less than or equal to the forward threshold; and exiting the one-pedal rocking mode by switching operations of the electric vehicle to a second operating mode responsive to detecting an exit condition.

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.

The invention discloses a new energy automobile hybrid power system cooperative control device and method.The new energy automobile hybrid power system cooperative control device comprises a multi-source data collection module, a cooperative control center and an execution unit, and the multi-source data collection module transmits collected information data to the cooperative control center; the cooperative control center comprises a data fusion unit, an energy management module, a heat management module and a cooperative decision-making unit, the data fusion unit receives data information of the multi-source data acquisition module, carries out fusion processing, and transmits the data information to the energy management module and the heat management module; the energy management module and the heat management module output a control strategy to the collaborative decision-making unit, and the collaborative decision-making unit judges a correction strategy and then sends a control instruction to the execution unit. The method has the advantages that cooperative control of energy management and heat management is achieved, various dimension data of road conditions, driving behaviors, power states and heat source states are fused, the problem of system unbalance caused by single module optimization is solved, and dynamic cooperation of energy management and heat management is achieved.

The invention discloses an emergency takeover triggering method and system based on environment perception and driver state recognition, and relates to the technical field of emergency takeover, and the method comprises the following steps: obtaining environment perception data and driver state data, and carrying out the risk grade evaluation; judging whether to initiate a takeover request according to the risk level; if a takeover request is sent, instruction consistency detection is carried out based on game modeling, a driver and an automatic driving system are abstracted into two agents, and operation intentions of the two agents are inferred respectively; if the detection results are inconsistent, entering a conflict strategy processing flow, evaluating the advantages and disadvantages of the strategies of the two conflict parties according to the driver state confidence and the environmental risk level, and outputting a game reasoning result; the problems of lack of consistency judgment, high calculation complexity and difficulty in real-time response in the prior art are solved.

The invention discloses a chassis coordination control method and system based on tire side deviation state evaluation, and relates to the technical field of four-wheel steering four-wheel drive vehicle dynamics control. The method comprises the steps that an expected front wheel rotation angle is determined based on an expected steering wheel rotation angle input by a driver, and a front wheel rotation angle is determined; further determining a feed-forward front wheel steering angle, a feed-forward rear wheel steering angle and an additional yaw moment based on feed-forward control and feedback control, determining a first tire slip angle and a second tire slip angle based on a road adhesion coefficient, and further determining a wheel torque control weight, a feedback front wheel steering angle control weight and a feedback rear wheel steering angle control weight; and further determining a driving yaw moment, a feedback front wheel steering angle and a feedback rear wheel steering angle, determining a total longitudinal force based on an expected longitudinal acceleration input by a driver, and performing four-wheel torque distribution based on the total longitudinal force and the driving yaw moment to obtain a four-wheel driving torque. The driving stability of the vehicle under the limiting working condition can be improved.

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.

The invention discloses a vehicle driving assistance system and method based on AR glasses. The system comprises an environment sensing module, a driver state monitoring module, a danger early warning and avoiding module, an automatic driving and auxiliary driving module, a driving simulation and training module, an abnormal behavior recognition module, a road information and navigation module and a health and emergency response module. The environment perception module is used for solving the problem of poor sight in extreme weather and road perception in a complex environment; by means of sensors such as the laser radar and the camera, road obstacles, pedestrians and vehicles can be accurately recognized, highlighted marking in the AR visual field is achieved, accidents caused by sight blind areas or distraction are reduced, indexes such as the blinking frequency and the head posture of a driver can be monitored, immediate reminding is conducted when fatigue or distraction is found, and parking and resting are forcibly suggested when necessary; and when the driver does not respond in time, the system can automatically brake or adjust the direction to avoid collision.

The invention relates to the technical field of electric vehicle control, in particular to an AI-based electric vehicle intelligent starting and acceleration control method and system. The method comprises the following steps: acquiring a driving log of a vehicle owner, performing intelligent vehicle optimization after starting, and constructing an intelligent starting mode selection strategy; physiological state data of a driver are obtained, state change evolution analysis is carried out, and a personalized driving portrait is constructed; holographic state sensing and vehicle virtual simulation are carried out, and a vehicle synchronous digital simulation model is constructed; radar feedback sensing information and a real-time monitoring image in front of a vehicle are collected, traffic situation prediction and vehicle scene prediction and perception are carried out, and a vehicle scene prediction and perception model is constructed. According to the method, the driving starting mode of the vehicle is intelligently selected, vehicle owner requirements and environment available power constraints are matched, and vehicle acceleration efficiency maximization and safety optimization are achieved.

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.

The invention relates to the technical field of risk assessment, in particular to a safe driving assessment method and system based on Beidou navigation. The method comprises the following steps: acquiring corresponding real-time position, speed and driving track data in a vehicle driving process through a Beidou navigation module, and acquiring vehicle state data and environment sensing data to obtain a vehicle multi-dimensional driving state data set; performing vehicle space-time and driving operation feature analysis and driving road matching analysis on the vehicle multi-dimensional driving state data set to obtain vehicle driving road attribute matching data; and carrying out vehicle driving risk estimation and vehicle safety over-rate evaluation based on the vehicle driving road attribute matching data, carrying out safety comparison verification evaluation, generating vehicle personalized driving improvement suggestions, and pushing the vehicle personalized driving improvement suggestions to the vehicle-mounted terminal to execute corresponding vehicle safe driving behavior improvement operation. According to the invention, real-time monitoring, accurate evaluation and active safety intervention of vehicle driving behaviors can be realized.

Embodiments herein provide a system and methods for parking a vehicle that considers the location of adjacent vehicles and determines parking maneuvers to allow easy access to the vehicle. The parking maneuvers are determined based on the space needed for each passenger to open their door and to safely exit or enter the vehicle. The vehicle may be positioned in a parking spot next to an adjacent vehicle. The system self-drives the vehicle when executing the parking maneuvers and sensors are used to determine the position of the vehicle in relation to the adjacent vehicle. The vehicle may be positioned such that passengers can safely exit the vehicle while in the parking spot. Once the passengers exit and are safely away, the vehicle is maneuvered within the parking spot to a position that does not impede access to the adjacent vehicle.

A method to prevent intoxicated operation is described. The method includes providing instructions to a vehicle user to position a vehicle user body portion posture in a predefined alignment. The method further includes obtaining the vehicle user body portion posture from a first vehicle detector, and determining whether the vehicle user body portion posture is in the predefined alignment. The method includes activating a plurality of vehicle visual indicators to illuminate in a predefined manner when the vehicle user body portion posture is in the predefined alignment. The method further includes providing instructions to the vehicle user to move vehicle user eyes to track the plurality of vehicle visual indicators, and obtaining a vehicle user eye movement from a second vehicle detector. The method further includes determining whether the vehicle user eye movement meets a predetermined condition, and actuating a control action accordingly.

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.