893 results about "Braking distance" patented technology

Various systems and methods are presented regarding utilizing technology onboard a first vehicle to reduce probability of a second vehicle being further involved in a traffic accident occurring between the first vehicle and a third vehicle. The first vehicle can transmit a notification to the second vehicle, wherein the notification can provide details regarding the collision, collision location, vehicles involved, etc. The second vehicle, operating autonomously, can self-adjust operation to avoid being involved in the accident, e.g., the first vehicle and third vehicle are in a rear-end collision, which the second vehicle can navigate to avoid. The second vehicle can, for example, self-determine whether a safe braking distance can be achieved, navigation into an adjacent lane, warn other vehicles of the collision. Accordingly, autonomous vehicles can reduce probability of pile-up collisions occurring.

The embodiment of the invention provides a rotor control method of a magnetic drive conveying system and related equipment. The method comprises the steps that planning operation data of a target rotor and the operation distance between the target rotor and a previous rotor are obtained; obtaining a reference adjustment speed; the minimum braking distance of the target rotor is calculated based on the reference adjusting speed, the reference adjusting speed is updated based on the distance difference value between the safe reference distance and the minimum braking distance, an updated reference adjusting speed is obtained, the updated reference adjusting speed serves as a new reference adjusting speed to conduct minimum braking distance calculation, and the minimum braking distance of the target rotor is obtained. Taking the reference adjustment speed as the maximum safe operation speed until the distance difference value does not exceed the preset distance difference value; and updating the planned operation data of the target rotor based on the maximum safe operation speed, and performing operation control on the target rotor according to the updated planned operation data, thereby effectively improving the operation safety of the rotor in the magnetic drive conveying system on the magnetic suspension conveying track.

The invention belongs to the field of road vehicle control systems, and relates to a method for predicting the risk of collision between an electric bicycle and a vehicle based on the multi-modal behavior of the electric bicycle, which utilizes physical modeling and takes the influence of the braking distance and the transverse and longitudinal stability of the electric bicycle on the vehicle as a basic risk; automobile risks caused by the environment are further considered, and multi-dimensional environment risk assessment modeling is carried out by integrating four dimensions of dynamic distance-speed, adjacent vehicle types, traffic flow density and weather conditions (precipitation, temperature, wind speed and visibility); the risk of electric bicycle operation behaviors (acceleration change and steering angle and frequency) to the automobile is combined; the complex relation between the environment change and the whole vehicle risk is captured in real time by using the environment sensitivity coefficient, and finally a set of comprehensive, accurate and real-time multi-dimensional comprehensive risk assessment method is provided for the vehicle for the multi-mode riding behavior of the electric bicycle, so that the collision risk in the complex traffic flow environment is reduced.

The invention provides an intelligent vehicle lane changing trajectory planning method based on model predictive control, which comprises the following steps: firstly, sensing environment information in real time, calculating an emergency braking distance and an expected safety distance, and deciding behaviors of an intelligent vehicle; secondly, on the basis that a vehicle point quality model serves as a prediction model, an improved artificial potential field method and a model are combined to predict, control and plan a lane changing track, and the current optimal lane changing reference track selected from the sine lane changing reference track cluster is included; and finally, tracking the trajectory by adopting a trajectory tracking controller based on model predictive control. The improved artificial potential field method is adopted to fully adapt to the position, speed and acceleration changes of surrounding obstacle vehicles, the dynamic obstacle avoidance effect is remarkable, and the lane changing safety of the intelligent vehicle is guaranteed; the situations of following the front vehicle, canceling lane change and the like are also considered, and the adaptive scene is wider.

An apparatus for measuring the stopping distance of a working machine is provided. The working machine includes a user interface, at least one processor, and at least one memory including a computer program code. The at least one memory and the computer code are configured to, with the at least one processor, cause the apparatus at least to: receive at least one speed parameter based on at least one user input on the user interface, receive at least one speed information value from a controller or the engine control unit of the working machine, send at least one command to the controller or the engine control unit to at least stop the working machine when the received speed information value is equal to the at least one speed parameter, and calculate the stopping distance of the working machine. A method and a system are also disclosed.

The invention discloses an intelligent networked automobile AEB system based on an improved TTC model and a control strategy of the intelligent networked automobile AEB system. The control strategy comprises the following steps that S1, a data acquisition module acquires sensor data in real time and transmits the sensor data to a safe automobile distance judgment module; s2, calculating collision time Tttc by a safe vehicle distance judgment module; s3, calculating a dynamic safe distance Dego by a safe vehicle distance judgment module; s4, the safe vehicle distance judgment module calculates the braking distance which should be reserved in the vehicle driving process; s5, a safe vehicle distance judgment module calculates graded braking threshold values Ti, Tj and Ts; s6, a safe vehicle distance judgment module judges whether a collision risk exists or not according to the improved TTC trigger logic; s7, if the risk threshold is triggered, entering a grading early warning control module, and outputting corresponding strategies under different risks according to risk grades; the method solves the problems that a dynamic safety distance is lacked and a graded braking threshold value is statically set, and is suitable for more complex scenes with different vehicle speeds, road conditions and driving environments.

The invention discloses a converter body mounting and positioning system and method based on a buggy ladle, and belongs to the technical field of converter mounting and positioning. According to the converter body mounting and positioning system, the position detection device is used for detecting whether position deviation exists on the two sides of the converter body or not in the in-place conveying process and detecting the alignment condition of the converter body and bolt mounting holes in a converter support; when the converter body has installation position deviation, the steel rail on the corresponding side is clamped through the speed reduction clamping device; when the converter body reaches the braking distance, the steel rails on the two sides are clamped at the same time, and simultaneous speed reduction of the single side or the two sides of the buggy ladle is achieved; and after the converter body is in place, the steel rail is clamped and locked through the brake locking device, so that parking brake of the buggy ladle is realized. In the conveying process of the converter, through accurate control and auxiliary braking of the buggy ladle, high-precision automatic in-position of the converter body can be achieved, and the installation efficiency and the installation precision are improved.

The invention provides an electronic control hydraulic braking optimization method for a new energy light passenger car, which comprises the following steps of: monitoring the position of a brake pedal through a high-precision sensor, correcting a signal in combination with vehicle speed and load information, identifying the braking intention of a driver, calculating the required braking force, and recovering energy by braking through a motor. The regenerative braking power is dynamically adjusted according to the braking force requirement, smooth transition to hydraulic braking is achieved when necessary, the braking response time is shortened through the rapid pressure building technology and optimization design, the braking distance is reduced, and the braking strategy is intelligently adjusted according to different road conditions, for example, motor braking is reduced on a wet and slippery road surface to avoid slipping; and motor braking is added on the long downhill road section to reduce the risk of heat attenuation, and the dual purposes of improving the braking performance and efficiently utilizing energy are achieved.

The invention discloses an automatic emergency braking control method and device based on a black spot technology and a vehicle. When the vehicle enters a black spot area, the vehicle obtains an optimal active braking parameter to correct the active braking parameter of the vehicle, and automatic emergency braking is executed based on the corrected active braking parameter; the method for obtaining the optimal active braking parameters comprises the following steps: dynamically delimiting a black spot area according to multi-dimensional data when emergency braking of each vehicle is triggered; obtaining the multi-dimensional data in the black spot area; and obtaining the optimal active braking parameters based on the vehicle speed, deceleration fluctuation, braking distance, vehicle weight and environment information during emergency braking. And the optimal active braking parameter when emergency braking is triggered in the black spot area is obtained. According to the method, the black spot technology is combined, the black spot area is established, ADAS program upgrading is conducted on the vehicle entering the black spot area, the vehicle can better adapt to the vehicle condition and the road condition in the area, the active braking curve is optimized, the comfort degree is improved, the situation that braking is not stopped after the automatic emergency braking function is triggered is reduced, and safety is improved.

The invention discloses a long-distance rail identification and obstacle detection method and system, and the method comprises the steps: combining a long-focus optical system with an ultra-high-speed industrial camera at a hardware level, and building a high-collection-frame-rate and long-distance optical detection system; on the software level, a region of interest for obstacle detection is delimited according to recognition and visual segmentation of left and right rail lines of a rail, advanced visual tasks such as a rail obstacle intrusion detection algorithm based on target detection are executed, and finally high-frame-rate recognition and detection of long-distance rails and rail obstacles are achieved. According to the invention, a Schmidt-Cassegrain optical system with a focal length of 2000mm is used, and an ultra-high-speed industrial camera with a resolution of 1920 * 1080 and 3000 frames per second is combined to build a long-distance high-frame-rate optical detection platform which is erected on a driving position of a train to detect railway conditions within a range of 6km in real time; serious accidents caused by overlong braking distance due to high-speed running of the train can be prevented. Compared with a traditional train driver eye observation and laser radar-based scanning imaging mode, a farther detection distance, better detection and recognition robustness and a higher frame rate can be realized through the long-distance optical observation platform and the rear-end real-time detection system.

The invention relates to an electric drive semitrailer grading AEB control decision-making method considering road surface factors, and the method comprises the following steps: S1, enabling a vehicle to obtain front vehicle information and road surface information through a sensor, a high-precision map and other ways, calculating a correction adhesion coefficient through combining with the state of the vehicle, and determining the maximum gradient limit; s2, outputting a maximum braking deceleration correction factor through fuzzy control by taking the correction adhesion coefficient and the gradient as input; s3, according to the advantages and disadvantages of the road surface working conditions and the maximum braking deceleration correction factor, the maximum braking deceleration is calculated according to the working conditions; s4, calculating a safe braking distance and collision time according to the current state of the vehicle and the speed and distance of the front vehicle; and S5, the collision time is used for early warning decision making, the safety braking distance is used for emergency braking decision making, the corrected maximum braking deceleration serves as a full-force braking target value, and graded AEB control is achieved. According to the method, road surface factors are fully considered, vehicle safety can be guaranteed under different attachment conditions and slope road surfaces, and the braking stability is remarkably improved.

The invention discloses a vehicle, a control method and device thereof and an AEB controller, and relates to the technical field of vehicle control. According to the method, the center-of-gravity position of the vehicle can be obtained, and the braking acceleration of the AEB system of the vehicle can be flexibly adjusted based on the center-of-gravity position. The adjusted braking acceleration is the maximum braking acceleration that enables the yaw stability degree of the vehicle to be greater than a degree threshold value when braking is performed at the center-of-gravity position. Moreover, under the condition that the distance between the vehicle and the target obstacle in front of the vehicle is smaller than the safe braking distance, the method can control the vehicle to brake according to the adjusted braking acceleration. Therefore, according to the method provided by the invention, the gravity center position of the vehicle can be considered during braking, so that high yaw stability of the vehicle during braking can be ensured by adopting the braking acceleration adjusted based on the gravity center position for braking, and the safety of the vehicle during braking is improved.

The invention discloses an AGV safety control method for intelligent warehousing, and relates to the technical field of intelligent warehousing, and the method comprises the following steps: constructing a global three-dimensional load distribution diagram of an automatic guided vehicle in real time through the fusion of a laser radar and an inertial measurement unit, and outputting a mass distribution matrix; based on the mass distribution matrix, millimeter wave Doppler tomography is superposed, the barycentric coordinates are dynamically corrected, and a corrected mass distribution matrix is obtained; and inputting the corrected mass distribution matrix into a braking dynamic prediction engine, and generating a prediction curve of an adaptive braking distance and braking response time in combination with online inversion estimation of a ground friction coefficient. Through the digital twin simulation and micro-pulse pre-braking strategy, the risk of inertial collision and cargo overturning is effectively reduced, a storage scheduling system is controlled in parallel, path reconstruction and driving priority dynamic adjustment are achieved, and global safety and efficient scheduling of intelligent storage are guaranteed.

The invention belongs to the technical field of braking force control, and particularly relates to a braking force control method which comprises the following steps: S01, vehicle state and environment detection; s02, making a braking force distribution strategy; s03, brake operation is executed; and S04, evaluating and optimizing the braking effect. According to the braking force control method, through the braking effect evaluation and optimization steps, the difference between the actual braking distance and the expected braking distance is evaluated, various information in the braking process is collected and analyzed, the information provides data support for continuously optimizing the braking force control strategy, the braking distance can be further shortened, the braking efficiency is improved, and the braking force control method is suitable for being popularized and applied. Meanwhile, key factors influencing the braking effect can be identified and the influence degree of the key factors on the braking performance can be quantified through application of a data analysis and modeling technology, subsequent further optimization is facilitated, and shaking and noise in the braking process are reduced by accurately controlling braking force distribution and utilization of friction force between tires and the ground.

The invention discloses an auxiliary driving method and device and intelligent driving equipment, and the method comprises the steps: obtaining weather information which indicates the weather type and / or road surface type of the current environment of the intelligent driving equipment; wherein the first weather type comprises one or more of a weather type for limiting visibility of a driver, a weather type for limiting sensing capability of a sensing system, or a weather type for increasing a braking distance of the intelligent driving equipment, and the first road surface type comprises a road surface type for increasing the braking distance of the intelligent driving equipment; according to the first environment information, a prompt device of the intelligent driving equipment is controlled to prompt a driving suggestion, and the driving suggestion comprises a driving strategy corresponding to the first environment information. The method can be applied to vehicles such as intelligent vehicles and new energy vehicles, and when severe weather influencing driving safety is detected, the vehicle user can be prompted about related information in time, so that the influence of the severe weather on driving is reduced.

The invention discloses a braking control optimization method and system combined with vehicle multi-state perception, and belongs to the technical field of vehicle intelligent control, and the method comprises five steps of multi-source data acquisition, data preprocessing, multi-state risk modeling, multi-target braking force distribution and braking control optimization. Based on a tire dynamic model and a semantic physical double-source weighting mechanism, generating high-precision vehicle multi-state sensing feature data; a multi-state risk modeling method based on path prediction and a physical constraint model is combined with a dynamic risk weight adjustment mechanism to calculate a comprehensive target deceleration; a multi-objective optimization function including the braking distance, the stability and the tire reliability is constructed, and four-wheel braking force distribution and coaxial cooperative control are carried out; and pressure control is executed according to the optimization result, and brake control optimization is achieved. According to the method, real-time self-adaptive adjustment of the brake control strategy can be achieved under the complex environment and multiple working conditions, and the safety, stability and response precision of braking are improved.

The invention belongs to the technical field of urban rail train operation protection, and discloses a remote obstacle detection method based on image and radar fusion. According to the invention, the scene and scheme of urban rail train obstacle detection are analyzed; determining the distance requirement of the urban rail train for detecting the obstacle and the obstacle size requirement matched with the distance; key data required by obstacle detection and constraint conditions of the urban rail train running speed are analyzed; determining the highest running speed of the train during obstacle detection by using data acquired by a laser radar, an IMU (Inertial Measurement Unit) and a camera and detection; according to the highest running speed, train braking response time and the longest braking distance are analyzed; due to the fact that a laser radar sensor has distance limitation, an image estimation target distance algorithm and an image and radar fusion algorithm are determined; according to a fusion algorithm, detection of obstacles which are 200 m away from the front of the train and are larger than 1.5 m in height is compensated, and the requirement for long-distance obstacle detection in a train operation scene is met.

The invention discloses an automatic driving vehicle control method and device and an automatic driving vehicle, and belongs to the field of automatic driving. The control method comprises the following steps: after acquiring vehicle information and a non-driving track of a target vehicle and acquiring road information and system delay time, firstly determining a target obstacle based on the size of the vehicle and the non-driving track, and calculating a relative distance based on motion information of the target obstacle; the minimum braking distance of the target vehicle is calculated based on the road information, the system delay time and the vehicle speed, when the relative distance is smaller than or equal to the minimum braking distance, it is indicated that the collision risk exists, and therefore the target vehicle needs to be controlled according to a preset control strategy. According to the scheme, the minimum braking distance is calculated from multiple dimensions, when to conduct braking control can be accurately judged in combination with the relative distance, and driving safety of the automatic driving vehicle in complex environments such as mines can be ensured.

The invention relates to the technical field of rail transit detection, in particular to an inspection control system for a rail transit line, which comprises an inspection robot, an intelligent safety helmet and a server, and is characterized in that the server comprises a task distribution module used for acquiring an inspection task and issuing the inspection task to the inspection robot and the intelligent safety helmet; the inspection robot performs automatic inspection according to the inspection task; the positioning module is used for acquiring real-time position information of the inspection robot when the inspection robot executes the inspection task through a first positioning device, and drawing and sorting according to the real-time position information to obtain a trajectory; the detection module is used for detecting the track, and if the track is abnormal, corresponding position information is recorded and loaded to the track line; if the foreign matter exists on the track, parking and notifying the intelligent safety helmet before the braking distance threshold value is reached; and the intelligent auxiliary module is used for providing assistance. The problem that a single inspection mode has limitation is solved, inspection is more comprehensive, and the inspection efficiency of the working track is improved.

The embodiment of the invention relates to a reversing obstacle avoidance method and system for remote driving of a loader and a medium, and belongs to the technical field of intelligent remote driving of loaders, and the obstacle avoidance method comprises the steps that feature extraction is conducted on ultrasonic radar data and millimeter wave radar data, and feature information is obtained; inputting the feature information into a deep neural network to obtain an obstacle type; calculating to obtain the moving path and speed of the obstacle; predicting a first predicted position of the obstacle after the first time interval; on the basis of the current position of the obstacle and the current position of the loader, the transverse distance and the longitudinal distance between the obstacle and the loader in the two-dimensional direction are obtained; the corresponding braking distance is obtained based on the speed of the loader and the speed of the obstacle, and the braking signal is output under the condition that the transverse distance is smaller than the first threshold value and the longitudinal distance is smaller than or equal to the braking distance, so that the control accuracy of the reversing obstacle avoidance process can be improved, sudden braking is avoided, and the use feeling and safety are improved.

The invention relates to the technical field of traffic safety evaluation, and discloses a regional traffic safety operation evaluation index algorithm, which comprises the following steps of: 1, data collection: collecting brake data of vehicles in a region through a vehicle traveling data recorder and other vehicle data collection equipment; according to the regional traffic safety operation evaluation index algorithm, braking data, including multi-dimensional information such as vehicle identification, braking time, braking position, braking speed, braking distance and braking type, of vehicles in a region are collected through a vehicle traveling data recorder and other vehicle data acquisition equipment, and the data are collected and utilized to obtain the evaluation index of the regional traffic safety operation. Therefore, traffic safety evaluation is no longer limited to traditional traffic accident statistical data, but dynamic behavior information of the vehicle in the driving process can be deeply excavated, for example, by analyzing the braking speed and the braking distance, the braking performance and the safety risk of the vehicle under different road conditions can be more accurately evaluated.

The invention discloses an energy management system and method based on distributed braking and a vehicle, and belongs to the technical field of electric vehicles. The sensor array unit is used for collecting the vehicle acceleration, the wheel rotating speed, the wheel vertical load and the road friction coefficient; a wheel vertical load and a road friction coefficient are obtained through a wheel control unit, and the real-time maximum braking force is calculated; the vehicle acceleration, the real-time maximum braking force and the wheel rotating speed are obtained through a central control unit, the vehicle required braking force is calculated according to the vehicle acceleration and the vehicle mass, and according to the real-time maximum braking force, the distribution coefficient is dynamically adjusted, and the vehicle required braking force is distributed to all wheels; according to the wheel rotating speed, the energy recovery efficiency and the regenerative braking torque are combined, and the energy recovery power is determined. Under emergency braking or complex road conditions, the stability of the vehicle can be better maintained, the braking distance can be better shortened, and the problem that an existing electric vehicle cannot deal with road emergency situations to conduct stable braking and energy recovery is solved.

The embodiment of the invention provides a vehicle aerodynamic resistance control method and device, a vehicle and a storage medium, the vehicle comprises air supply equipment and an empennage which are arranged at the tail, and the method comprises the steps that the vehicle speed and the tail static pressure of the vehicle are obtained, and the braking state of the vehicle is determined; judging whether the vehicle meets an aerodynamic resistance reduction condition or not according to the vehicle speed and the tail static pressure of the vehicle; according to the vehicle speed and the vehicle braking state, whether the vehicle meets the aerodynamic resistance increasing condition or not is judged; if the vehicle meets the aerodynamic resistance reduction control condition, air supply equipment and an empennage of the vehicle are adjusted to reduce the aerodynamic resistance of the vehicle; if the vehicle meets the control condition for increasing the aerodynamic resistance, the aerodynamic resistance of the vehicle is increased, so that the aerodynamic resistance of the vehicle can be controlled in real time by controlling the air supply equipment and the empennage mounted at the tail part of the vehicle, and the aerodynamic resistance is reduced when the vehicle runs at a high speed so as to improve the endurance; and when the vehicle is braked, the pneumatic resistance is increased to shorten the braking distance.

The invention discloses a comfortable braking control method and device and a storage medium, and relates to the technical field of comfortable braking, and the method comprises the steps that when a vehicle is braked, and the current vehicle speed, the current braking deceleration and the expected braking strength meet preset comfortable braking conditions, a comfortable braking function is started; the comfortable braking function comprises a plurality of control cycles, and in each control cycle, the sum of the downward movement amount of the front suspension and the upward movement amount of the rear suspension is equal to the downward movement amount of the rear vehicle body by adjusting the braking torque of the vehicle and the rigidity of each suspension. By adjusting the braking torque of the vehicle and the rigidity of each suspension, the sum of the downward movement amount of the front suspension and the upward movement amount of the rear suspension is determined to be equal to the downward movement amount of the rear vehicle body, so that the movement posture of the vehicle body is changed from pitching to vertical parallel movement when the vehicle is braked, and the braking comfort is improved while the braking distance is not increased.

The invention relates to the technical field of vehicle braking, in particular to a comfortable parking control method and device, a medium and a product. The comfortable parking control method comprises the steps that whether activation conditions are met or not is judged according to current vehicle state information and braking requirements; when the activation condition is met, the voltage buildup unit target is larger than the braking requirement; and the breakover current of the front axle pressure increasing valve IV1 is adjusted to be smaller than the breakover current of the rear axle pressure increasing valve IV2. By adjusting the braking force of the first wheel end and the braking force of the second wheel end, the effect of reducing pitching can be achieved, and comfortable braking experience is provided for a driver. The front axle pressure increasing valve IV1 of the front axle can be controlled by increasing the target of the pressure building unit, low front axle pressure and high rear axle pressure are achieved, the situation that the braking intention of a driver is directly reduced is avoided, and the influence of the function on the pedal feeling is weakened. Compared with the intention of a driver, the front axle pressure is reduced, but the rear axle pressure is increased, the overall deceleration influence is small, and the influence on the braking distance is weakened.

The invention relates to the technical field of forklift control, and discloses a control system and a control method of a standing plate type pallet truck. A pressure state signal of a hydraulic oil way is obtained through a pressure switch, a load state is judged, and a power mode is selected through a mode selection switch; and the controller controls the forklift to run according to the set acceleration running curve or brake according to the braking running curve according to different vehicle running states. The pressure switch is used for recognizing the light-load and heavy-load working conditions of the vehicle, the maximum speed of the light load of the vehicle is increased according to different load conditions and different power modes, the braking distance of the vehicle under different loads and the running stability of the vehicle are ensured, and the service life of the vehicle is prolonged. Therefore, the working efficiency of the vehicle is improved, the purposes of smooth driving and safe and smooth braking of the vehicle are achieved, and various control requirements of a user on high efficiency, safety, comfort and the like of the vehicle under different working conditions are met.

The invention discloses a multi-train cooperative tracking control method under relative braking protection constraint. The method comprises the following steps: constructing an optimization model; cooperative tracking control; the step of constructing the optimization model specifically comprises train dynamic model establishment, train operation constraint and optimization control problem; the cooperative tracking control specifically comprises model reconstruction based on an augmented Lagrangian method, solution by adopting a trust region method, and design of a multi-train cooperative tracking control algorithm under relative braking protection constraint. According to the solution algorithm based on the trust region method, efficient solution of the multi-train cooperative tracking control strategy under the relative braking distance is achieved. The cooperative control strategy designed by the invention is solved through a trust region method, so that the control force of the high-speed train can be adjusted at each decision moment. By means of the adjustment, the actual train distance can be rapidly converged to the expected train distance, and the efficiency and safety of train operation are guaranteed.

The invention relates to the technical field of vehicle safety, and discloses an intelligent safety early warning and emergency braking linkage device for an electric motorcycle. According to the device, the driving state and the surrounding environment of the motorcycle are monitored in real time by integrating various sensors, the relative distance between the motorcycle and an obstacle, the braking distance and the acceleration change rate can be accurately calculated, so that timely early warning of potential dangers is achieved, when abnormal conditions are detected, safety early warning signals can be rapidly sent out, and the safety of the motorcycle is guaranteed. The anti-lock braking system has the advantages that the anti-lock braking system is linked with the anti-lock braking system, emergency braking is automatically executed, the response time of a rider in emergency is effectively shortened, the risk of misjudgment is effectively reduced, the user feedback module provides real-time state information and safety suggestions for the rider through a networking data screen, the safety awareness and the coping capacity of the rider are further enhanced, and the safety of the rider is improved. According to the device, the active safety protection level of the motorcycle is improved, the accident rate can be reduced, and a safer travel environment is created for a rider.

The invention provides a vehicle control method and related equipment. The vehicle control method comprises the steps that driving environment parameters, driving state parameters and historical characteristic parameters of a current vehicle are obtained; performing data processing on the driving environment parameters, the driving state parameters and the historical characteristic parameters to obtain target data; predicting a target distance of the current vehicle according to the target data, wherein the target distance comprises at least one of a vehicle following distance and a braking distance; and controlling the current vehicle to run according to the target distance. According to the invention, the determination precision of the following distance and the braking distance of the vehicle is improved.

The invention belongs to the field of wind power equipment transportation, and provides a wind power large piece transportation path intelligent planning system and method based on deep learning, and the method comprises the steps: obtaining terrain DEM data in a wind power plant range, and converting the terrain DEM data into three-dimensional vector data and three-dimensional vertex coordinates; receiving the three-dimensional vertex coordinates, constructing a road network topological structure representation based on a homotopy theory, extracting microscopic local features and a macroscopic global structure of a road network through a multi-level graph neural network, and realizing dynamic representation and updating of the road network based on manifold learning; receiving the road network topological structure representation and the road network features, and generating a vehicle dynamics constraint condition and a road section geometric difficulty coefficient by comprehensively considering the maximum climbing angle, the maximum turning angle, the maximum speed and the braking distance of the vehicle; and receiving the road network dynamic representation, the vehicle dynamics constraint condition and the road section geometric difficulty coefficient, and generating an optimal transportation path with balanced safety, time efficiency and transportation cost by adopting a multi-target reinforcement learning algorithm.