2911 results about "Steering angle" patented technology

The invention discloses a vehicle-mounted Beidou positioning deviation self-calibration system fused with inertial navigation information, and relates to the technical field of navigation and positioning. The method is used for solving the problems of positioning deviation accumulation and signal failure in a complex environment. The system realizes space-time alignment of inertial navigation and Beidou observation data through timestamp interpolation and coordinate system conversion, and constructs a multi-source synchronous data stream. A difference value between an inertial navigation calculation speed and a Beidou Doppler speed is analyzed based on a vehicle incomplete constraint model, and a weight factor is generated in combination with a confidence threshold to suppress abnormal observation. A geometric matching error is calculated through a high-precision lane map curvature and a vehicle steering angle, and candidate tracks are screened to generate transverse calibration parameters. The noise covariance is dynamically adjusted through a tight coupling filtering algorithm, the mode is switched to a lane constraint calibration mode when a Beidou signal is interrupted, inertial navigation errors are compensated through error boundary constraint, and stable output is achieved. Multi-source data deep fusion and adaptive robust calibration are realized, and system robustness and positioning continuity are improved.

The invention belongs to the technical field of path planning, and discloses an unmanned driving dynamic path planning method and system based on multi-source data fusion, and the method comprises the steps: collecting an ice and snow pavement friction coefficient, a curve curvature and an obstacle point cloud, constructing a sensor confidence coefficient matrix, generating a fused semantic map, and constructing a dynamic environment semantic model. Outputting a real-time friction coefficient field and a risk thermodynamic map layer; the roadside unit broadcasts coordinates of opposite vehicles in a blind area of a curve to a vehicle end, constructs an ice and snow pavement offset crowdsourcing map, and generates a global-local fusion topology; fusing the real-time friction coefficient field and the global-local fusion topology to generate a smooth trajectory set, and further generating a risk optimal path instruction set; a steering angle and torque instruction is decomposed, positioning drift is compensated in real time, and a normal mode for updating the vehicle positioning state and a degradation mode when the millimeter wave radar fails are constructed; and generating execution logs and health state vectors, and aggregating the execution logs and the health state vectors of multiple vehicles to form closed-loop iterative update.

The invention belongs to the technical field of intelligent driving, and particularly relates to an intelligent driving method and system with a body, and the method comprises the steps: fusing the V2X data of a vehicle-mounted laser radar, a millimeter wave radar and a road side unit, and obtaining the vehicle driving information; constructing a centimeter-level dynamic environment model by adopting a space-time alignment algorithm, and realizing multi-source data space-time synchronization and obstacle real-time prediction; designing a hierarchical reward function including security, efficiency and comfort rewards based on a user risk cognition mechanism, and generating an end-to-end reinforcement learning decision in combination with a Transform architecture; optimizing the dynamic environment model through reinforcement learning decision; inputting vehicle driving information into the optimized centimeter-level dynamic environment model, and predicting obstacles and vehicle tracks in a vehicle driving path; an MPC-Hybrid feedforward-feedback control system is constructed, a feedforward module is adopted to calculate a front wheel turning angle and acceleration parameters according to obstacles in a vehicle driving path and a vehicle track, and a feedback module is adopted to optimize transverse and longitudinal errors; controlling the driving direction of the vehicle according to the front wheel turning angle and the acceleration parameter transverse and longitudinal errors; according to the invention, through deep fusion of vehicle-road collaborative perception and reinforcement learning decision, the reliability and adaptability of the automatic driving system are significantly improved.

The invention discloses an electric forklift multi-mode driving switching method and system based on multivariable cooperation, and relates to the technical field of industrial vehicle intelligent control. The method is used for solving the problems of one-sided working condition sensing, switching oscillation and safety fault tolerance deficiency in multi-mode driving. The method comprises the following steps: firstly, generating a dynamically weighted working condition feature vector through multi-source sensing data fusion, and quantifying a stability risk, an energy consumption constraint and a power demand; secondly, based on a stability risk trigger steering safety envelope, arbitrating a multi-mode priority and correcting a torque upper limit in combination with a fuzzy rule to form an anti-conflict execution sequence; then, torque distribution and a steering angle acceleration instruction are optimized in a rolling mode in the safe envelope boundary, center-of-gravity shift is synchronously restrained, the track precision is improved, and energy consumption is reduced; finally, the control authority is transferred adaptively according to the operation intensity of a driver, when the decision is abnormal, the load-ramp rule base is degraded, an instruction is transferred through an S-shaped curve, and a torque balancing strategy is executed at the high position of a pallet fork to maintain stable.

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.

Disclosed is a corner module apparatus for a vehicle. The corner module includes a driving unit that provides drive power to a wheel of the vehicle, a braking unit that interferes with rotation of the wheel to generate braking power, and a suspension unit connected to the driving unit. The suspension unit absorbs shock transferred from a road surface. The corner module also includes a steering unit connected to the suspension unit and rotated about a steering axis inclined with respect to the wheel. The steering unit adjusts a steering angle of the wheel.

The invention discloses a cooperative steering control method considering man-machine mutual reliability, and aims to solve the problem of man-machine conflict in an existing man-machine co-driving system. The invention relates to the field of intelligent driving. The system specifically comprises an expected path module, a man-machine steering conflict evaluation module, a driver experience evaluation module, a weight distribution module, a non-cooperative game module and a man-machine co-driving vehicle. The expected path module generates an expected path between the driver and the controller; the man-machine steering conflict evaluation module outputs the trust degree of the driver to the controller based on the steering action of the driver, the vehicle state and the expected path of the driver and the controller; the driver experience evaluation module outputs the driver trust degree of the controller based on the vehicle state; the weight distribution module is used for outputting a driver control weight; and the non-cooperative game module outputs an optimal turning angle in combination with the expected path of the driver and the controller and the control weight of the driver, and controls the man-machine co-driving vehicle to complete the cooperative steering action.

A vehicle-mounted GNSS positioning method based on multi-motion model interaction includes: establishing a position-constant velocity (PCV) model and a position-constant steering angular velocity (PCSAV) model for two attitudes of a carrier (i.e., linear motion and turning motion) respectively to obtain a state estimation vector and a state transition matrix of the carrier of the PCV model and the PCSAV model at a previous moment, introducing an interacting multiple model (INM), establishing a heuristic position-velocity filtering (HPV)-IMM model based on the IMM model to achieve an information filtering interaction between the PCV model and the PCSAV model, and obtaining a state estimation vector and an error covariance matrix of the carrier at a current moment, so as to obtain a position and velocity of the carrier at the current moment. The present disclosure solves the problem of low accuracy of a traditional single kinematic model in multi-motion attitude vehicle positioning.

The invention relates to the technical field of automobile electric control, in particular to a new energy automobile electric control steering control method and system, and the method comprises the steps: obtaining and preprocessing a four-wheel vibration data sequence, carrying out the segmentation and consistency evaluation of the vibration data sequence of each wheel, and selecting a current data sequence in an optimal segment to calculate a road condition influence coefficient. And matching the current data sequence with the historical vibration data sequence, calculating the similarity to determine the influence weight, adjusting the influence coefficient in combination with the steering angle change rate of the historical vibration data sequence, inputting the adjusted pavement condition influence coefficient into the ECU, dynamically adjusting the steering auxiliary torque, and realizing accurate steering control. According to the method, the optimal segment is selected through segment processing and consistency evaluation to accurately reflect the current road condition, the steering auxiliary torque is dynamically adjusted in combination with historical vibration data sequence matching and the steering angle change rate, and the driving safety and comfort are improved.

The present application relates to the technical field of vehicles, and provides a vehicle control method and apparatus, an electronic device, and a medium. The method comprises: on the basis of the transverse motion state quantity and the longitudinal motion state quantity of a first vehicle, solving for a tracking control problem for tracking a planning path and a planning speed, so as to obtain a first wheel steering angle control quantity and an expected acceleration of the first vehicle, wherein the first wheel is a front wheel or a rear wheel, the planning path comprises a reference value of the transverse motion state quantity of the vehicle at a series of time points in the future, and the planning speed comprises a reference value of the longitudinal motion state quantity of the vehicle at a series of time points in the future; obtaining the acceleration control quantity of the first vehicle on the basis of the expected acceleration of the first vehicle and the actual acceleration thereof; and controlling the first vehicle on the basis of the first wheel steering angle control quantity and the acceleration control quantity of the first vehicle. In the present application, vehicle control is carried out in a transverse and longitudinal combined tracking control mode, so that the speed tracking accuracy can be improved as much as possible while the path tracking accuracy is ensured.

The invention relates to a vehicle emergency steering auxiliary method, device and equipment and a storage medium. The main technical scheme comprises the steps of obtaining target object information in front of a current vehicle, and determining whether a collision risk exists or not according to the target object information; when it is determined that the collision risk exists, environment data information around the vehicle is obtained; according to the environment data information, obtaining general obstacle information and drivable area information; obtaining optimal reference path information and steering angle information according to the general obstacle information and the drivable area information; and according to the optimal reference path information and the steering angle information, the vehicle is controlled to conduct emergency steering auxiliary operation. According to the method, after the existence of the collision risk is determined, the general obstacle information and the drivable area information are obtained based on the environment data information around the vehicle, and then the optimal reference path information and the steering angle information are obtained, so that the vehicle is controlled to perform emergency steering assistance operation, and the purposes of ensuring the use safety of a driver and the vehicle and improving the driving safety are achieved. And the collision risk is reduced.

The invention discloses a 12-axis PCB drilling machine AGV path planning system with an intelligent obstacle avoidance function, and relates to the technical field of path planning, a first machine learning model of an AGV chassis steering angle and a first machine learning model of a mechanical arm shaft joint angle are obtained through training according to historical AGV operation parameters and simulated workshop operation parameters; identifying ground flatness compensation, vibration compensation, gravity center shift compensation and light influence compensation according to the real-time workshop parameters, determining a proportionality coefficient by using an optimal sequence diagram method, and further determining a second machine learning model; and a control instruction for AGV chassis steering and mechanical arm joint movement is generated based on the second machine learning model. Through multi-source data fusion, a dynamic compensation mechanism and machine learning optimization, the accuracy, the obstacle avoidance capability and the system robustness of path planning are improved, and efficient and safe execution of a PCB drilling task is ensured.

The invention discloses a man-machine dynamic cooperative steering control method integrating reinforcement learning and a game theory, and aims to optimize dynamic weight distribution of a driver and a controller so as to guarantee driving safety and path tracking precision of a man-machine co-driving vehicle. The invention relates to the field of intelligent driving. The system comprises an expected path module, a reinforcement learning module, a non-cooperative game module and a man-machine co-driving vehicle module. The expected path module is used for generating an expected path sequence of the driver and the controller and an expected path at the current moment; the reinforcement learning module receives the expected path at the current moment, the vehicle dynamic information and the optimal rotation angle of the driver and the controller, and training is carried out to generate a driver control weight; and the non-cooperative game module combines the driver control weight, the expected path sequence of the driver and the controller and the state information of the vehicle, optimizes the optimal steering angle of the driver and the controller through the non-cooperative game, and realizes the cooperative steering control of the man-machine co-driving vehicle.

The invention relates to the technical field of automobile active obstacle avoidance, and provides an electric automobile obstacle avoidance control method and system, and the method comprises the steps: obtaining obstacle data, and generating a vector model of an obstacle; projecting the obstacle to the relative motion direction of the current vehicle based on the vector model, and judging whether scraping and collision occur relative to the operation parameters of the current vehicle; when the scraping and collision probability exceeds a preset risk value, generating an obstacle avoidance control instruction deviating from obstacle projection; wherein the obstacle avoidance control instruction comprises a steering angle automatic response instruction of the current vehicle under the current path curvature and a self-feedback torque enhancement instruction based on road surface friction. Through vector model projection and relative motion direction analysis, dynamic evaluation of obstacle collision probability and cooperative control of steering angle automatic response and torque enhancement, path correction and power output are considered, different road conditions (such as ice and snow / wet and slippery road surfaces) are automatically adapted, and active intervention is performed before a preset risk threshold value is triggered.

The invention relates to the technical field of vehicle stability control and fault-tolerant control, and discloses a steer-by-wire vehicle stability control method under actuator faults and input hysteresis, a terminal and a medium. The method comprises the following steps: establishing a kinetic model of a steer-by-wire vehicle, and constructing a front wheel subsystem kinetic model in a steer-by-wire system by comprehensively considering an actuator fault, input hysteresis and a state constraint condition; according to the steering angle instruction of the driver and the ideal vehicle model, the expected yaw velocity and the expected sideslip angle of the vehicle are obtained through calculation; designing an upper-layer stability controller of the front wheel subsystem; generating a desired front wheel steering angle for the front wheel subsystem; and a lower-layer steering angle tracking controller of the front wheel steering system is designed, the front wheel steering angle tracking performance of the steer-by-wire system under the working conditions of actuator faults and input hysteresis is ensured, and the actual front wheel steering angle of the vehicle approaches the expected front wheel steering angle. According to the invention, the steer-by-wire system can still maintain the stability of the vehicle under the conditions of actuator fault and input hysteresis.

A parking method and apparatus, and a vehicle. The method comprises: acquiring a position where a vehicle is located and information of a target parking space; planning a parking path on the basis of the position and the information of the target parking space, wherein the parking path comprises paths traveled in an opposite-direction steering mode and in a same-direction steering mode, in the opposite-direction steering mode, the direction of a front wheel steering angle and the direction of a rear wheel steering angle of the vehicle are opposite, and in the same-direction steering mode, the direction of the front wheel steering angle and the direction of the rear wheel steering angle are identical; and controlling the vehicle to be parked in the target parking space from a first position on the basis of a first parking path.

The method is mainly applied to the technical field of automobile engineering. The invention discloses a driving turning anti-collision control method and device, a vehicle and a medium, and the method comprises the steps: responding to a steering instruction of the vehicle, and generating a local coordinate system taking the current position of the vehicle as an original point; determining predicted position coordinates of the vehicle in the local coordinate system based on the steering angle and the driving speed of the vehicle; when the obstacle is detected, determining the obstacle coordinate of the obstacle in the local coordinate system; determining a collision risk value of the vehicle and the obstacle based on the predicted position coordinate and the obstacle coordinate; and when the collision risk value is larger than a preset safety threshold value, a braking instruction is sent to the vehicle so as to control the vehicle to brake. According to the method, the static or low-speed moving obstacle can be effectively identified in a complex turning scene, and a braking measure is taken in time, so that the active safety of the vehicle in the turning process is improved, and the collision risk is reduced.

The invention discloses an automatic driving path planning method based on multi-sensor fusion, and relates to the technical field of automatic driving, and the method comprises the steps: collecting environment, vehicle and positioning data through multi-source sensors, such as a laser radar and a camera; mapping a vehicle body coordinate system through coordinate conversion, and carrying out downsampling, correction enhancement and denoising preprocessing on data; extracting multi-sensor features, and distributing weights by means of a cross-modal attention mechanism to complete multi-modal fusion; recognizing obstacles and passable areas, and predicting a 5s track of a dynamic obstacle; 5-8 initial paths are generated based on the coordinate system and dynamic constraints; constructing a multi-objective function to screen an optimal path; and finally, a steering angle and an acceleration instruction are calculated through model prediction control, and accurate path tracking is realized. The sensing robustness is improved through multi-sensor fusion, the dynamic weight adjustment adapts to the complex environment, the emergency obstacle avoidance mechanism is quick in response, and the automatic driving reliability and the scene adaptability are integrally enhanced.

The invention discloses a multi-signal fusion yaw velocity credibility calculation method and electronic equipment. The method includes calculating a first yaw velocity based on a vehicle model; calculating a second yaw velocity based on the lateral acceleration; calculating a third yaw velocity based on the geometric constraint of the wheel speed difference; determining whether a credibility updating condition is satisfied; and if yes, determining the credibility of the actually measured yaw velocity of the sensor according to the first yaw velocity, the second yaw velocity, the third yaw velocity and the actually measured yaw velocity of the sensor. Multi-dimensional signals such as the wheel speed, the steering angle and the acceleration are fused, and fault tolerance is improved. And through threshold screening and weighted fusion, noise and sudden change interference are suppressed. And front wheel calculation can be switched when a rear wheel breaks down, so that the system continuity is guaranteed.

The invention discloses an unmanned agricultural machine path tracking preset performance control method and system, and the method comprises the steps: collecting the pose information of an unmanned agricultural machine, building an unmanned agricultural machine path tracking error kinematic model, and designing a finite time preset performance function based on the unmanned agricultural machine path tracking error kinematic model. The constraint is converted through nonlinear mapping; based on the Lyapunov stability theory, adopting a backstepping method to recursively design an actual control law, and according to the actual control law, performing inverse transformation on the input of the unmanned agricultural machine tracking control system in the error kinematics model of the unmanned agricultural machine tracking control system to obtain the front wheel steering angle of the unmanned agricultural machine. According to the method, convergence is completed within finite time, and transient control performance and steady control performance of a path tracking control system are considered.

The invention discloses an agricultural machinery high-precision automatic driving intelligent control system, which belongs to the technical field of agricultural machinery vehicle automatic driving and comprises a data acquisition module, a path planning module, a control module and an instruction execution module. The data acquisition module is used for acquiring a dynamic data set in real time and transmitting the dynamic data set to the path planning module, and the path planning module is used for receiving and analyzing the dynamic data set and generating an optimal path; the control module is used for synchronously receiving the optimal path, the real-time vehicle body posture dynamic data and the environment change data and generating a control instruction set; the instruction execution module receives the control instruction set, synchronously adjusts the steering angle and the running speed of the agricultural machine, generates actual execution parameters and feeds back the actual execution parameters to the control module. Through arrangement of the control module, the data acquisition module, the path planning module and the instruction execution module, the collision hidden danger caused by insufficient environmental adaptability of a traditional fixed track algorithm is solved.

The invention relates to an unmanned tractor operation path tracking and machine tool cooperative control system and method, and the system obtains the position and posture of a tractor, machine tool operation parameters and topographic information in real time through fusing the data of multi-source sensors, such as GNSS positioning and laser radar topographic perception. A multi-objective optimization function including a path tracking error, an operation precision error and a ground vibration excitation amount is constructed, and a particle swarm-genetic algorithm (PSO-GA) hybrid optimization algorithm is introduced for result optimization, so that cooperative control of tractor unit operation parameters such as a steering angle, a vehicle speed and a machine tool hydraulic parameter is realized. According to the method, in the operation of the unmanned tractor in the hilly terrain, the path tracking error is effectively reduced, the operation uniformity is improved, the influence of terrain factors on the operation is reduced, and the operation efficiency and the equipment durability under complex working conditions are remarkably improved.

The present disclosure relates to a computer-implemented method for determining a real time steering angle (58) for a railway bogie (1) and to a control device (40) which is configured to perform the method, the method comprising: deter-mining by a sensor assembly at least one lateral real time sensor signal (38), which is characteristic for a lateral position of a tread of at least one wheel of the railway bogie (1) with respect to a railway track, determining, by means of a positioning algorithm (47), a real time position and / or orientation of the railway bogie (1) with respect to the railway track (31), using the received at least one lateral real time sensor signal (38) and determining the real time steering angle (58) for steering of the railway bogie (1), using the determined real time position and / or orientation of the railway bogie (1).

The invention discloses an intelligent automobile double-event trigger control method aiming at double communication networks. The method comprises the following steps: initializing; establishing intelligence to judge whether an SC event triggering condition and a CA event triggering condition are met or not; solving a front wheel steering angle control instruction; and performing intelligent automobile double-event trigger control. According to the invention, a double-event trigger condition is designed to determine whether a state signal of an intelligent automobile path tracking type 1 fuzzy model is updated to a type 1 fuzzy time-lag controller or not and determine whether a front wheel steering angle control instruction calculated by the type 1 fuzzy time-lag controller is updated to an actuator module or not; communication resources of double communication networks are effectively saved; the method has the capability of efficiently avoiding the problem of communication congestion, can save a lot of communication resources, and improves the reliability of the intelligent automobile in the path tracking control process. The fuzzy time-delay controller is designed to calculate a front wheel steering angle control instruction, and the reliability of path tracking control of the intelligent automobile is ensured.

The invention belongs to the field of distributed driving automobile control, and discloses a distributed driving automobile path tracking and stability control optimization method and related equipment, and the method comprises the steps: firstly building a tire cornering stiffness dynamic range through multi-source sensing data, and reducing the influence of nonlinear characteristics on a model; then, through a dynamic output feedback model prediction control algorithm, an estimation state sequence and an error boundary of a vehicle side slip angle are calculated online, an optimal control gain is matched in real time based on a two-dimensional table, a combined control quantity of a four-wheel steering angle and an additional yawing moment is formed, and parameter uncertainty caused by vehicle speed change is effectively compensated; and finally, torque distribution is carried out by adopting a quadratic programming algorithm and taking tire utilization rate minimization as a target. According to the method, the vehicle path tracking precision and the transverse stability under the complex working condition are improved, meanwhile, the tire saturation risk is reduced, the tire utilization rate is reduced, the transverse tracking error is reduced, and unified optimization of safety and controllability in the automatic driving process is achieved.

The utility model discloses a field cultivation platform, which belongs to the technical field of cultivation equipment and comprises a work platform, a steering support mechanism and the like, and a cross beam of the work platform is a steel pipe and is fixedly connected with a beam frame and an end plate; the steering supporting mechanism comprises a rotating drum, an upper seat body, a lower seat body, a swing arm and a wheel set; through cooperative control of the first telescopic cylinder, the second telescopic cylinder and the third telescopic cylinder, the functions of height adjustment, flexible steering and off-ground steering assisting are achieved; an end plate is provided with an adjusting hole to adjust the terrain clearance of the platform, the stability is enhanced through the swing arm structure design, and the second telescopic cylinder expands the steering angle of the wheel set through a folding arm structure; the beam is of a sealed structure to form a hydraulic oil cavity, space is saved, and maintenance frequency is low. The farmland cultivation platform is flexible in steering, suitable for farmland operation in complex terrains and capable of efficiently completing tasks such as cultivation and transition, and adaptability and operation efficiency are greatly improved.

The invention provides a vehicle control method, electronic equipment and a storage medium, and the method comprises the steps: controlling the driving torque of wheels according to the actual slip rate and the target slip rate of the wheels under the condition that a low-load starting stability control function of a vehicle is activated, a first deviation between the target slip rate and the actual slip rate is maintained in a first set range; and according to the actual yaw velocity and the target yaw velocity of the vehicle, the rear wheel rotation angle is controlled, so that a second deviation between the target yaw velocity and the actual yaw velocity is maintained within a second set range. According to the technical scheme, the acceleration performance of the vehicle under the low-load starting working condition is effectively improved, the steering wheel correction amplitude and frequency of a driver are effectively reduced, the control confidence of the driver is enhanced, and the driving control experience is improved.

The invention relates to an intelligent vehicle taillight system, a control method thereof and a vehicle, the intelligent vehicle taillight system comprises a data acquisition module used for acquiring vehicle dynamic operation parameters and external environment information, the vehicle dynamic operation parameters comprise at least one of brake pedal stroke, steering angle, vehicle speed and automatic driving state data, and the external environment information is used for acquiring the external environment information; the external environment information comprises at least one of a rear vehicle distance and a pedestrian position; the intelligent control module is connected with the data acquisition module and is used for generating current working condition information of the vehicle based on the vehicle dynamic operation parameters and the external environment information; and the tail lamp is connected with the intelligent control module and performs corresponding display and projection operation according to the current working condition information. According to the invention, the driving safety can be improved.

The invention discloses an automobile driving state blind area monitoring method and a rearview mirror, and relates to the technical field of blind area monitoring. Comprising the following steps of information collection, specifically, sensors and cameras are installed on wheels of an automobile, a steering wheel steering column, an automobile chassis and a steering system respectively, driving state data of the automobile speed, the steering wheel angle, the automobile acceleration and the steering angle and image data around the automobile are collected in real time, and real-time automobile information data are obtained; according to the system, driving state data such as the vehicle speed, the steering wheel angle, the vehicle acceleration and the steering angle are combined, the blind area around the vehicle is monitored in real time through the sensor and the camera, and when the vehicle steers, the blind area monitoring range is adjusted in real time to adapt to the driving direction change; the rearview mirror can display blind area images in real time, the blind area alertness of a driver can be greatly improved, and the traffic accident risk caused by the blind area is effectively reduced.

The embodiment of the invention provides a vehicle steering control method, a controller, a vehicle, a medium and a program product, and the method comprises the steps: obtaining a steering wheel rotation angle and a vehicle longitudinal speed of the vehicle when the vehicle is controlled to steer; according to the steering wheel angle and the vehicle longitudinal speed, target steering control parameters are determined, and control is conducted according to the target steering control parameters; actual steering control parameters of the vehicle are obtained; according to the target steering control parameter and the actual steering control parameter, fast terminal sliding mode control is carried out, and yawing moment and a rear wheel steering angle are generated; according to the yawing moment and the steering angle of the rear wheels, the two first wheels are controlled, and the control stability of the vehicle can be improved through the embodiment of the invention.