629 results about "Cruise control" patented technology

The invention relates to the technical field of vehicle cruise control, and discloses a neural network driven vehicle adaptive cruise control method. Real-time driving data are collected through a multi-modal sensor, spatial-temporal feature fusion is carried out through a multi-layer convolutional neural network to generate dynamic environment sensing data, and a pre-trained adaptive decision model is input to obtain driving strategy parameters. And constructing a mixed integer programming model on the basis, globally planning a cruise path by adopting an incremental branch and bound algorithm integrating a dynamic relaxation threshold and a heuristic pruning strategy, and outputting optimal cruise trajectory data. A hierarchical control framework comprising a planning layer, a coordination layer and an execution layer is constructed, the planning layer generates a global trajectory sequence, the coordination layer dynamically corrects a local trajectory, and the execution layer achieves vehicle longitudinal acceleration and transverse steering angle tracking based on a robust sliding mode control algorithm and outputs a vehicle control instruction to complete self-adaptive cruise control. And the cruise control performance, safety and stability of the vehicle in a complex environment are improved.

The present application relates to the technical field of autonomous driving functions, and in particular to a control method and device integrating predictive cruise and lane changing decision-making. The method comprises: receiving the accelerations, speeds and positions of a controlled autonomous driving vehicle and surrounding traffic vehicles at a current moment so as to construct an IDM microscopic following model to predict surrounding traffic vehicle states in a preset future long time domain; on the basis of the surrounding traffic vehicle states in the preset future long time domain, constructing an optimization cost function, so as to plan a lane keeping strategy or lane changing strategy; on the basis of the lane keeping strategy or lane changing strategy, using a quintic polynomial to solve for a reference path; on the basis of the reference path, establishing an optimal control problem cost function for continuous intersection predictive cruise control, so as to solve for the optimal cruise speed within a traveling lane; and sending the reference path and the optimal cruise speed within the traveling lane to the controlled autonomous driving vehicle for control. Thus, the problems that existing lane changing decision-making only considers longitudinal motion and fails to pay attention to a development trend of the surrounding environment, possible dangers and the like are solved.

The invention discloses an intelligent automobile cooperative cruise safety control method under Dos attacks and physical faults, and relates to automobile intelligent safety and automatic driving. A hierarchical control framework is adopted and comprises an observer layer and a tracking layer. The method comprises the following steps: establishing a vehicle longitudinal dynamics model and a DoS attack model for DoS attack in a V2X communication network and the problems of sensor and actuator faults and parameter isomerism of a vehicle; a completely distributed self-adaptive preset time observer based on event triggering is designed for each following vehicle in the observer layer, and rapid and accurate estimation of the state of the pilot vehicle is achieved; the method comprises the following steps: constructing an augmentation system at a tracking layer, designing a distributed intermediate observer, carrying out online estimation and compensation on faults of a sensor and an actuator, designing a distributed active fault-tolerant controller based on a fault estimation value and a pilot vehicle state estimation value, and calculating a wheel driving torque to realize safe cruise control. Multiple threats of coexistence of network attacks and physical faults are effectively handled, and the stability and safety of the cooperative cruise system are ensured.

The invention relates to the technical field of underwater desilting robot cruise control, in particular to an underwater desilting robot intelligent cruise control method based on environmental perception, and the method comprises the steps: determining a track deviation distance by measuring the position distance of an underwater desilting robot between each moment and all moments within a preset duration before; and determining a second gain adjustment coefficient based on the variation trend of the track deviation distance at all moments within a preset time period before the current moment, and determining a gain adjustment coefficient in combination with the first gain adjustment coefficient so as to optimize the gain coefficient of the sliding mode controller and control the attitude of the underwater dredging robot. According to the method, the problem of hysteresis course errors of the underwater dredging robot caused by fixed gain in traditional sliding mode control is solved, gain adaptive optimization is realized by dynamically fusing multi-source trend data, and the dredging efficiency of the underwater dredging robot is improved.

The invention discloses a commercial vehicle team cruise control method and system, computer equipment and a storage medium, and relates to the technical field of automatic driving and vehicle infrastructure cooperative control, and the method comprises the steps: carrying out the vehicle role interaction of a team vehicle according to a cooperative relation and a vehicle role interaction logic; establishing a surrounding environment potential field model, and describing an interaction relationship between vehicles inside and outside the motorcade; calculating the longitudinal and transverse potential fields of the vehicles of the fleet, and controlling the distance between the vehicles and the safe distance; a model prediction controller for team cruise is constructed by considering the target speed and the environmental influence; and the safety, speed and control constraints of vehicle movement are set, and the driving performance is optimized. The stability of formation control is enhanced, the formation requirements of complex scenes are met, the real-time dynamic control capability is improved, and the formation energy efficiency is optimized.

A control system for a vehicle is provided, the control system comprising one or more controllers, the control system configured to receive an acceleration or deceleration demand signal from an automatic cruise control system, and request modification of one or more parameters of the vehicle suspension system in response to the received acceleration or deceleration demand signal. In this way, the vehicle suspension system may be modified in preparation for an acceleration or deceleration of the vehicle, to inhibit or at least reduce the occupants of the vehicle experiencing an undesirable pitching movement of the vehicle during the course of the change in speed of the vehicle.

The invention relates to the technical field of automatic driving trajectory planning control, in particular to an optimal inter-vehicle time interval control method for cooperative cruise of a truck under a communication delay condition. According to the method, a layered control framework of truck cooperative cruise control is designed, and a vehicle safety inter-vehicle time interval model, a communication delay model and a queue collision safety model are constructed; the inter-vehicle time interval, the communication delay coefficient and the safety coefficient are quantified into space particles, optimization is carried out based on a particle swarm algorithm, and the optimal inter-vehicle time interval on the basis of guaranteeing the queue safety and the fuel economy is obtained; designing a longitudinal model predictive control (MPC) expected acceleration decision controller of truck cooperative cruise by considering multi-target constraints of safety and fuel economy in a vehicle following process to obtain an expected acceleration; and a load change-considered feedforward and active-disturbance-rejection control brake driving error compensation model is established, so that the anti-jamming capability of the model is enhanced, and the actual acceleration of the queue truck accurately follows the expected acceleration under the load change condition.

The present disclosure generally relates to managing cruise control settings. A cruise control indicator is displayed at a location that corresponds to a cruise control speed concurrently with a textual indication of the cruise control speed. In response to receiving an input to change the cruise control speed, the cruise control indicator and the textual indication of the cruise control speed move along at least a portion of the path corresponding to speed.

The invention discloses an unmanned ship automatic cruise control system and a control method thereof, and particularly relates to the field of unmanned ship automatic cruise, and the unmanned ship automatic cruise control system comprises a cruise area division module, a cruise data acquisition module, a cruise data analysis module and a control module. According to the method, a self-adaptive control system is constructed through a four-dimensional linkage mechanism of the course deviation correction value, the environmental disturbance force, the control efficiency index and the path tracking deviation rate, a water flow and wind power square term modeling and steerage coefficient dynamic conversion mechanism is adopted, the transient disturbance suppression effect is remarkably improved, and the control efficiency is improved. By monitoring the nonlinear relation between the product of the accelerator and the rudder angle and the attitude of the ship body in real time, dynamically constraining the output of the actuator, avoiding attitude instability and ensuring the safety under the four-level sea condition, the system improves the course correction weight at the end point stage and starts waypoint preview and smoothing coefficient adjustment at the long leg based on the conjoint analysis of the deviation ratio threshold and the residual distance, and the ship body attitude is optimized. And the full-voyage tracking precision is optimized.

The invention relates to a vehicle cruise control method and device, vehicle-mounted computing equipment and a vehicle, relates to the technical field of intelligent driving, and can improve the driving safety and stability of the vehicle under ice and snow weather conditions. The method comprises the following steps: predicting a future road surface state of a driving road surface of a vehicle according to meteorological data and road surface state information; under the condition that the future road surface state is the ice and snow road surface state, actual friction information of the driving road surface is obtained; determining a target driving state of the vehicle according to the actual friction information and a vehicle cruise condition, controlling the driving of the vehicle according to the target driving state, and obtaining an actual driving state in the driving process; and according to the actual driving state and a braking compensation strategy corresponding to the ice and snow pavement state, braking control information is determined, and driving of the vehicle is adjusted according to the braking control information.

The invention discloses a predictive cruise control method and device, a storage medium and a vehicle, and the method comprises the steps: obtaining the traffic environment information of a road where the vehicle is located, and carrying out the road reconstruction of the road according to the traffic environment information, and obtaining at least one road section; determining the driving feature classification of the target driver according to the driving feature data of the vehicle driven by the target driver; determining influence coefficients corresponding to different influence indexes in a cruise control algorithm based on driving feature classification; the minimum cost of a cruise control algorithm is determined based on the preset vehicle speed range, the gear range and the influence coefficients corresponding to the different influence indexes; and determining a target vehicle speed and a target gear of each road section based on the minimum cost, and performing predictive cruise control on the vehicle based on the target vehicle speed and the target gear. According to the method, predictive cruise control of the fuel oil heavy commercial vehicle in a high-speed scene can be achieved, and the purposes of reducing fuel oil consumption, relieving driving fatigue of a driver and improving driving experience are achieved.

The present application provides a vehicle cruise control method and system, a medium, an electronic device, and in-vehicle infotainment. The vehicle cruise control method comprises: calculating a speed deviation on the basis of a preset speed of a vehicle and an ego-vehicle speed; on the basis of a speed deviation range where the speed deviation is located, selecting variable control parameters, and performing segmented control on a requested acceleration, wherein the speed deviation range is a range obtained by division on the basis of the magnitude of speed deviation, and includes a negative large deviation zone, a negative small deviation zone, a positive small deviation zone, and a positive large deviation zone; and calculating a PID control quantity of vehicle cruise control on the basis of the variable control parameters and the speed deviation. The present application can improve the control precision of cruise control, and reduce the speed fluctuation generated in the control process.

The invention discloses a vehicle cruise control method and system based on traffic prediction, and relates to the technical field of vehicle intelligent control. The method comprises the following steps: preprocessing vehicle state data and driving environment data by utilizing edge calculation; performing information fusion and mapping on the preprocessed data by using a cloud control platform to obtain a road traffic condition simulation result, and generating an optimal vehicle driving strategy according to the road traffic condition simulation result by using reinforcement learning; a hierarchical control strategy is constructed by considering traffic constraints and economic vehicle speed factors, and the vehicle is dynamically regulated and controlled; and the real-time driving state of the vehicle is fed back to the cloud control platform, and parameter optimization is carried out on the optimal driving strategy of the vehicle. According to the invention, traffic information is efficiently mined and fused by using the powerful information processing and fusion capability of the cloud control platform, predictive cruise control of the vehicle is realized in combination with a vehicle control optimization algorithm, and the energy-saving effect and the driving efficiency of the vehicle in a complex traffic environment are improved.

A method for selecting a following target when changing lanes during adaptive cruise control, comprising: receiving signals for detecting front objects in the own lane and the adjacent lane that are located in front of the own vehicle and judging whether the respective front objects are vehicles; detecting whether a lane change of the own vehicle is occurring by determining the degree of lateral deviation of the own vehicle from the own lane;Detecting the distance between the front objects of the own vehicle in the own lane and the adjacent lane into which the own vehicle will change lanes and the own vehicle, as well as the coincidence rate between the own trajectory and the front objects of the own vehicle in the own lane when the own vehicle changes lanes, and selecting a front object in the own lane or the adjacent lane as a provisional follow-up target; if it is determined that the provisional follow-up target is a vehicle, determining the provisional follow-up target as the final follow-up target;Repeating the above steps at fixed time intervals until the host vehicle has completely changed lanes into the adjacent lane. A system for selecting a follow-up destination when changing lanes during adaptive cruise control, comprising a sensor, a processor, and an adaptive cruise control module, the processor configured to execute the method described above.

The invention discloses a car following control method and a related product. According to the scheme, multi-source data are acquired, and the multi-source data are fused to obtain a fusion result; based on the fusion result, performing multi-modal trajectory prediction on the driving behavior of the preceding vehicle to obtain a prediction result of the driving behavior of the preceding vehicle; the multi-modal trajectory prediction comprises longitudinal motion prediction and transverse motion prediction; quantifying a car following risk by using a multi-dimensional risk index to obtain a risk level; constructing a multi-target cost function based on the fusion result, the front vehicle driving behavior prediction result and a control vector, and solving the multi-target cost function by using a preset constraint condition to obtain an initial control parameter of the vehicle; and on the basis of the risk level, initial control parameters of the vehicle are adjusted, and target control parameters of the vehicle are obtained. Compared with the problem of response lag in adaptive cruise control in the prior art, the adaptive cruise control method has obvious advantages.

The invention discloses a commercial vehicle cruise control method and system giving consideration to physiological strain and energy conservation. The method comprises the following steps that a human body physiological strain index is constructed, a vehicle oil consumption and energy conservation index is constructed, an optimal cruise speed planning model is established, and the vehicle oil consumption and energy conservation index and passing time are comprehensively considered to form an overall reward function; a reinforcement learning algorithm is introduced for solving, and the optimal cruise speed within the predicted duration is obtained; constructing a vehicle-seat-human body system longitudinal and vertical coupling dynamic model, and calculating a human body physiological strain index under the optimal cruise speed; vehicle state constraints and optimal cruise speed sequence tracking constraints are coded as control constraints, and a longitudinal model prediction control strategy is formed based on a human body physiological strain index, a vehicle fuel consumption energy-saving index and tracking deviation; and a pitching regulation and control mechanism is added to realize vertical ceiling hybrid control, and the vehicle suspension is regulated and controlled. The vehicle cruising performance can be improved, and collaborative optimization of human body physiological strain and vehicle energy saving is achieved.

The invention discloses a thermal power generating unit transition peak regulation intelligent cruise control method based on an intelligent control algorithm, and relates to the technical field of intelligent control algorithms, and the method comprises the steps: constructing a distributed sensor network through deploying distributed sensors at all key positions of a thermal power generating unit, and obtaining the operation parameters of the thermal power generating unit in real time; external data are introduced and integrated, and short-term load demand prediction is generated according to an intelligent control algorithm; constructing a dynamic optimization function by combining a power grid dispatching instruction and a load prediction result and by taking the minimum coal consumption, the shortest peak regulation response time and the minimum equipment life loss as targets; adopting a hybrid algorithm of model predictive control and reinforcement learning to obtain an optimal control instruction; the control instruction is transmitted to a boiler combustion system and a steam turbine speed regulating system, and the fuel amount, the water supply amount and the valve opening degree are regulated; and dynamically adjusting model parameters and fuzzy rule weights of model prediction control through reinforcement learning to realize adaptive control of the thermal power generating unit.

An unmanned aerial vehicle autonomous electric power facility inspection method based on three-dimensional semantic driving relates to the technical field of unmanned aerial vehicle cruise control, and comprises the following steps: constructing a three-dimensional semantic representation containing key components under a unified world coordinate system, and generating a three-dimensional semantic point cloud with component category labels in real time in combination with airborne visual perception; and the inspection requirements in the operation and maintenance regulation are analyzed into an ordered component-level task sequence, and on the basis, the unmanned aerial vehicle autonomously plans an observation pose and a local flight path according to the three-dimensional semantic distribution of the target component, so that the adaptive approaching and coverage of the key component are realized. According to the invention, operation and maintenance semantics can be precisely followed, fine-grained sensing of key parts is realized, an inspection path is enabled to be close to a concern point, environment adaptability is realized, the inspection efficiency is effectively improved, the cost is reduced, and the problems that current electric power facility unmanned aerial vehicle inspection depends on a preset mode, the operation and maintenance semantics are difficult to meet, and key part sensing and adaptability are lacked are solved. And the inspection tour effect is not good enough.

Provided is a driver assistance system (DAS) including: a storage configured to store driver tendency data including an amount of decrease in acceleration when a vehicle approaches a specific section, in a state in which an adaptive cruise control (ACC) of the vehicle is deactivated; and a controller including at least one processor configured to process the driver tendency data, wherein the controller is configured to, upon the vehicle re-entering the specific section during travel of the vehicle with the ACC, control the vehicle to perform one of acceleration control and deceleration control based on the driver tendency data.

A road driving optimization method and system having a vehicle sensor configured to collect external sensor data, vehicle status data, and communication data; a control module configured to analyze the collected data to detect a trigger event, a state of the target vehicle, an achievable speed range, and an instantaneous traction; a decoupling estimator module configured to analyze the trigger event, a state of the target vehicle, an achievable speed range, and the personalized driver profile to determine a maximum free flow distance and an arrival speed at the free flow distance; a machine learning model configured to predict a speed profile of the host vehicle during approaching the trigger event based on the determined free flow distance, the determined arrival speed at the determined free flow distance, and the instantaneous traction; and a cruise control system configured to implement the predicted speed profile.

Systems, methods, and apparatus related to sensor data processing for a vehicle to improve operation when sunlight or other bright light enters a sensor of the vehicle. In one approach, adjustable filtering is configured for a sensor of a vehicle. In one example, an optical filter is positioned on the path of light that reaches an image sensor of a camera. For example, the filtering improves ability to stay in adaptive cruise control when driving into direct sunlight at sunset. The optical filters can have controllable properties such as polarization. In one example, a controller of the vehicle is configured to automatically adjust the properties of the optical filter to improve image quality to improve object recognition. In another example, a camera is configured with composite vision that uses sensors in different radiation spectrums (e.g., visible light, and infrared light). The composite vision can provide enhanced vision capability for an autonomous vehicle that is driving in the direction of the sun.

Collective action by multiple vehicles traversing a vehicle transportation network is used to improve operation of vehicles and utilization of the vehicle transportation network. Sensor data for multiple monitored vehicles traveling in a common direction along a road in a vehicle transportation network is received and used as input to a traffic estimation model to determine an estimated congestion for the road in the common direction. A cruise control setting for each of several controlled vehicles, at least some of the controlled vehicles traveling behind the monitored vehicles in the common direction, is determined from the estimated congestion. The cruise control setting is transmitted to the controlled vehicles to modify operation of the controlled vehicles using respective cruise control systems of the controlled vehicles.

The invention relates to a vehicle adaptive cruise control method and device and a controller. The method comprises the steps that under the condition that a vehicle is in a vehicle self-adaptive cruise control mode, real-time sensing data of the vehicle and a planned driving track of the vehicle are acquired; utilizing the real-time sensing data and the planned driving track to obtain predicted energy consumption information of the vehicle for the planned driving track; acquiring endurance influence information of the vehicle according to the predicted energy consumption information; determining a target acceleration of the vehicle based on the endurance influence information of the vehicle and the dynamic driving performance optimization information of the vehicle, and generating a vehicle control instruction based on the target acceleration; the vehicle control instruction is used for indicating the vehicle to perform adaptive cruise control according to the vehicle control instruction. By adopting the method, the self-adaptive cruise control of the vehicle can be carried out in combination with the endurance influence of energy consumption instead of only focusing on safety, comfort and efficiency targets, and the precision of the self-adaptive cruise control of the vehicle can be improved through the mode.

While operating a host vehicle in a lane of a road, a target vehicle operating in the lane in front of the host vehicle is represented with a virtual vehicle. Upon receiving, from an infrastructure element, operation data describing vehicle operation for the road, acceleration of the target vehicle is predicted based on the operation data. An adjustment to a speed for the virtual vehicle is determined based on the acceleration. The virtual vehicle is updated based on the adjustment to the speed. Upon determining that the virtual vehicle is between the target vehicle and the host vehicle, the host vehicle is operated based on the virtual vehicle.

The invention discloses a fixed wing type cross-domain aircraft capable of realizing self-adaptive load replacement, belongs to the technical field of cross-domain aircrafts, and is used for a water-air double-domain operation cross-domain aircraft. Comprising an aircraft body, a main wing, an aileron, a tail assembly, a vertical take-off and landing support, a vertical take-off and landing rotor wing, a fixed wing propeller, an underwater propeller, a load replacement device and a control module. The control module comprises a decision making system, a telemetering communication system, a state sensing system, an underwater water surface load replacement system, a water surface four-rotor vertical take-off and landing control system, an air fixed-wing cruise control system and an underwater vehicle control system. According to the fixed wing type cross-domain aircraft, through collaborative innovation of a multi-mode power system and self-adaptive buoyancy control, the dynamic characteristic adaptation problem in cross-domain navigation is solved, and the fixed wing type cross-domain aircraft has the vertical take-off and landing capacity, the air cruising capacity and the underwater maneuvering capacity.

The invention relates to the technical field of automobiles, and particularly provides a heavy-duty automobile cruise control method, system and device and a storage medium, and the method comprises the steps: obtaining real-time road condition information and vehicle operation data through the fusion of a vehicle-mounted sensor and a driving assistance map; predicting a future vehicle weight, and predicting a future road adhesion coefficient based on the vehicle operation data and the historical road adhesion coefficient data; constructing a state variable based on the real-time road condition information, the vehicle operation data and the road adhesion coefficient, and defining a control variable; establishing a cost function including a safety item, a fuel saving item and a stability item, and setting constraint conditions of a vehicle state variable and a control variable; based on a dynamic programming algorithm, solving a minimum value of a cost function under the condition of satisfying constraint conditions, and obtaining an optimal control variable sequence; and according to the optimal control variable sequence, the gear, the driving torque and the braking torque of the vehicle are adjusted. Through multi-source information fusion and layered dynamic planning, the cruise control performance of the heavy-duty car is remarkably improved.

The present application relates to a braking method for an adaptive cruise control system (ACC), the method comprising: receiving an engine drag torque limit value of the vehicle; performing a correction of the engine drag torque limit value according to the vehicle's longitudinal speed and the actual torque value of the vehicle's engine; and determining, according to the corrected engine drag torque limit value, whether braking is performed via the vehicle stability control system (ESP). The present application further relates to a computer program product, a computer-readable storage medium, and a domain controller.

The invention relates to the technical field of deep peak regulation of thermal power generating units, in particular to a thermal power generating unit peak regulation load intelligent cruise control method based on big data analysis, and aims to solve the problems that in the prior art, the output of a thermal power generating unit cannot be adaptively adjusted based on real-time monitoring, the optimal action cannot be selected according to real-time data, and the power consumption is low. And the stability, economy and operation efficiency of the power grid are reduced. According to the method, a peak regulation control strategy is optimized by using a reinforcement learning algorithm, the output of the thermal power generating unit is adaptively adjusted based on real-time monitoring, a reward function is designed by comprehensively considering the frequency stability, the output constraint, the economy and the unit state, the system safety and economy are balanced, the learning efficiency is improved through experience playback of the DQN algorithm and a target network mechanism, and the method is suitable for popularization and application. Rapid convergence and continuous optimization are achieved, after training, the system selects the optimal action according to real-time data, and the stability, economical efficiency and operation efficiency of a power grid are remarkably improved.

A method for predictive cruise control of a vehicle includes: specifying a cruise speed and an optimal cruise requirement; according to the road condition information of the road section ahead and the current driving dynamic condition, limited by the driving dynamic parameters, of the vehicle, the possible speed track of the vehicle on the road section ahead is determined, and the road condition information comprises gradient information, curvature information and speed limiting information; an optimal speed trajectory is selected from the possible speed trajectories, and the optimal speed trajectory corresponds to the speed trajectory with the minimum comprehensive cost under the condition that the optimal cruise requirement is met; the optimal speed trajectory is used as a target vehicle speed trajectory for predictive cruise control of the vehicle. According to the method, the optimal cruise speed and engine torque requirements can be comprehensively planned in combination with various road condition information, so that the optimal cruise requirements of at least saving energy consumption and / or saving time and / or avoiding excessive and overweight use of a service brake are met. An apparatus for predictive cruise control of a vehicle, an electronic device for predictive cruise control of a vehicle, a vehicle, and a computer readable medium are also disclosed.

The invention provides an adaptive cruise system adjusting method, a vehicle and a storage medium, the method is applied to the field of automatic driving, and the method comprises the following steps: determining a target control factor of an adaptive cruise system based on an attention parameter of a driver of the vehicle and an initial control factor of the adaptive cruise system of the vehicle, the target control factor is used for adjusting a control parameter of the adaptive cruise system, and the attention parameter is used for evaluating the concentration degree of the driver driving the vehicle; determining a target control parameter of the adaptive cruise system based on the target control factor and an initial control parameter of the adaptive cruise system; and driving control is conducted on the vehicle through the self-adaptive cruise control system according to the target control parameters. According to the method, the control factor of the self-adaptive cruise system can be dynamically adjusted according to the real-time state of the driver, and the vehicle is controlled in real time according to the control factor, so that the vehicle is controlled to run safely under the condition that the driver is in a distraction state, and the probability of accidents of the vehicle is reduced.