44 results about "Road roughness" patented technology

The invention is suitable for the technical field of vehicle dynamics modeling and control, and provides a preview active suspension stiffness control method based on road surface grading and MAP mapping, and the method comprises the steps: collecting a road image through a vehicle-mounted visual sensor, dividing regions, and recognizing the road surface unevenness grade of each region through a convolutional neural network; obtaining the vehicle speed; and according to the current pavement grade and the vehicle speed, a vehicle speed-pavement grade-rigidity mapping MAP table generated in advance is inquired, and the target suspension rigidity is rapidly obtained and adjusted. According to the invention, the dependence on a high-precision sensor and a high-computing-power processor is reduced, and low-cost and fast-response rigidity optimization control of the preview active suspension is realized.

The invention discloses a vehicle air suspension height compensation method, device and equipment and a storage medium. Firstly, the driving state of a target vehicle, the road surface unevenness and the current heights (including the heights of the right front air bag, the left front air bag, the right rear air bag and the left rear air bag) of four air bags can be obtained. The average height of the front axle is then calculated from the heights of the right front and left front airbags, and the compensated height of the front axle is determined in conjunction with the target airbag height. Then, the right front air bag and the left front air bag are adjusted according to the compensated height, and balance of the front axle is ensured. And for the rear axle, the driving state of the vehicle, the road surface unevenness, the target height of the air bags and the current height of the right rear air bag and the current height of the left rear air bag are considered, and then corresponding height compensation is conducted on the two air bags of the rear axle. When the vehicle runs on different road shoulders, height compensation control between the air bags can be achieved, so that the heights of the four air bags are effectively coordinated, it is ensured that the vehicle body is kept balanced, and then driving safety and comfort are improved.

The utility model relates to road detection technical field especially, it relates to a road flatness intelligent detection device, including main control circuit, multichannel capacitance sensor array, electromagnetic shield casing, the multichannel capacitance sensor array is by the multiple capacitive proximity sensor that is arranged in matrix, is fixed in detection device bottom, the multichannel capacitance sensor array adopts differential type measurement structure, and is equipped with the isolation drive ring between adjacent capacitive proximity sensor, the signal conditioning circuit is connected between the multichannel capacitance sensor array and main control circuit, the inertia measurement unit is connected to main control circuit, the electromagnetic shield casing covers the device, adopts the layered shielding structure, contains at least one conducting layer and a layer electromagnetic shield layer, and is connected through multipoint earthing between layers, the utility model can adopt multichannel capacitance sensor array and realize high accuracy, non -contact type measurement, and through the electromagnetic shield design, temperature compensation and attitude change compensation of the target ensure measurement stability.

The application discloses a kind of based on multi-angle weighting correction's road surface flatness measurement method and system, it is related to data measurement technical field, method includes: obtaining to be measured section and measurement route, obtain laser sensor, the elevation data of measurement point in measurement route is collected;Obtain initial weight coefficient, obtain the reflection intensity of laser sensor, according to the reflection intensity of the laser sensor corresponding to measurement point the correction coefficient of the laser sensor corresponding to measurement point is obtained;According to the correction coefficient of the laser sensor corresponding to measurement point and initial weight coefficient, the target weight coefficient of the laser sensor corresponding to measurement point is obtained;According to the target weight coefficient of the laser sensor corresponding to measurement point and elevation data, the target elevation data corresponding to measurement point is obtained, according to the target elevation data of measurement point in measurement route, the road surface flatness of to be measured section is obtained.The application has the advantages of dynamic self-adaptability, weighted fusion and tolerance expansion optimization.

The present invention relates to the technical field of road pavement slabs, and to a road pavement slab. The road pavement slab comprises a pavement slab body. Connecting rod members are evenly arranged and spaced apart in the pavement slab body. The connecting rod members are variable-diameter rods; a thin end of each variable-diameter rod is a solid rod, and a thick end thereof is provided with a deep connecting hole. The solid rod at the thin end of one connecting rod member can be in fit connection with the deep connecting hole at the thick end of the another connecting rod member. The connecting rod members are embedded in the pavement slab body, the thin ends extend from one end surface of the pavement slab body, and the end portions of the thick ends are flush with the opposite end surface of the pavement slab body. The advantages of the present invention are: low cost and a high pavement speed are achieved; a paved road has high flatness and good stability, is not prone to damage and is suitable for a vehicle to pass through; and the road pavement slab is particular suitable for rapid pavement in rural areas to improve road conditions.

The invention relates to the technical field of vehicle suspensions, and provides a suspension damping compensation method and system and related equipment. The suspension damping compensation method comprises the following steps: monitoring driving state parameters of a vehicle in response to the condition that the total mileage of the vehicle meets a mileage threshold value; in response to the driving state parameters, representing that the vehicle is in a steady-state working condition, detecting road surface roughness and an output electric signal of an electric control shock absorber in a suspension; responding to the condition that the current output electric signal meets the compensation condition corresponding to the current road surface roughness, and obtaining a current compensation current value corresponding to the current mileage value of the vehicle according to the mapping relation between the mileage value and the compensation current value; and according to the current compensation current value, damping output of the electric control shock absorber is compensated. According to the suspension damping compensation method, damping compensation of the electric control shock absorber of the suspension is achieved in a low-cost, anti-false-triggering, high-precision and high-reliability mode, the damping performance of the electric control shock absorber and the cushioning function of the suspension are effectively maintained, and comfort, controllability and safety of the whole vehicle are guaranteed.

This invention relates to the field of roadbed strength, specifically to a method for detecting the strength of highway roadbeds based on a semi-empirical modified curve. This invention records the pressure and displacement during impact using sensors on a falling weight deflectometer, calculates the vertical displacement of the road surface, selects a Beckman beam deflectometer and a test vehicle, installs the Beckman beam deflectometer between the two rear wheels of the test vehicle, corrects the test vehicle parameters, calculates the deflection value, corrects the diameter of the left and right tires of the test vehicle to 22.35 cm, and corrects the ground pressure of the left and right tires of the test vehicle to 0.75 MPa. The vertical displacement and deflection values ​​measured in steps (2) and (3) are recorded and compared with the national highway roadbed strength standard, thereby achieving rapid detection of roadbed strength without damaging the road structure. Furthermore, the test vehicle can be used to detect and evaluate the road smoothness of the selected road.

The present application relates to the technical field of vehicle steering control, and particularly relates to a rack force fusion estimation method for different working conditions of steer-by-wire based on fuzzy control, which comprises the following steps: collecting road roughness, judging whether it is not less than a first threshold value, if yes, measuring a first rack force based on a rack force estimator of a vehicle-tire model, otherwise collecting an actual vehicle speed; judging whether the vehicle speed is less than a second threshold value, if yes, measuring a second rack force based on a rack force estimator of a steering system model, otherwise judging whether the vehicle speed is less than a third threshold value, if yes, measuring the first rack force, otherwise measuring a front wheel steering angle of the vehicle, and judging whether it is not greater than a fourth threshold value, if yes, measuring the first rack force, otherwise measuring the second rack force; adopting fuzzy control when the first and second rack forces are converted, so as to realize smooth connection of the rack force estimation value under different working conditions. Thus, the problem that the applicability of the rack force estimator under bumping road, different vehicle speeds and steering angles is not fully studied in the steer-by-wire system is solved.

The invention discloses a road flatness detection device and method for highway construction, and relates to the technical field of road detection.The road flatness detection device comprises a detection vehicle body, and a cleaning frame is fixedly installed on the outer wall of one side of the detection vehicle body; through the arrangement of a mounting frame, a moving block, a mounting box, a detection roller, a detection block, a displacement sensor, a detection camera, a first spraying box, a second spraying box, an electromagnetic valve, a marking nozzle and an information processor, when the detection roller makes contact with a protruding road surface, the detection roller moves upwards and drives the detection block to move upwards at the same time; the height of a protruding road surface is detected through the displacement sensor, crack information of the road surface is collected in cooperation with the detection camera, data processing is carried out through the information processor, spraying marking is carried out on the protruding road surface and the road surface with cracks, and pits and protrusions of the road surface are rapidly detected and marked. And follow-up workers can conveniently maintain the road surface, uneven and cracked road sections can be clearly found, and the working efficiency is improved.

The utility model discloses engineering road construction detection equipment which comprises a mounting frame and first universal wheels, a first vertical plate and a second vertical plate are fixed to the top of the mounting frame, a mounting plate is fixed between the first vertical plate and the second vertical plate, a sliding groove is formed in the mounting plate in a penetrating mode, and a mounting block in sliding fit with the sliding groove is arranged on the mounting plate; the mounting block and the first vertical plate are jointly provided with a detection assembly. The detection assembly comprises a vertical rod which is arranged on the installation block in a penetrating mode and is in sliding fit with the installation block, a top plate fixed to the upper end of the vertical rod, a baffle fixed to the top of the top plate, a spring which is arranged on the vertical rod in a sleeving mode and is fixed between the bottom of the top plate and the top of the installation block, and a first infrared distance measuring sensor fixed to a first vertical plate. Second universal wheels are arranged at the lower ends of the vertical rods, the bottoms of the second universal wheels are flush with the bottoms of the first universal wheels, and a displayer, a controller and an alarm which are electrically connected with the first infrared distance measuring sensor are fixed to the first vertical plate. According to the invention, the road flatness can be conveniently detected.

The application is suitable for the field of bridge multi-order frequency identification method, and provides a bridge multi-order frequency indirect identification method based on vehicle-road-bridge information decoupling, which comprises the following steps: step S1: based on vehicle-bridge coupling dynamics equation, the coupling relationship among vehicle, road and bridge is established; step S2: by using dimensionless parameters, the road roughness information in the coupling system is completely eliminated from the difference between the front and rear wheel responses of the double-axle vehicle, and the vehicle and bridge information are separated; step S3: finally, according to the size of the driving speed, different subspace identification algorithms are selected to indirectly obtain the multi-order frequency of the bridge from the vehicle response. The technical problems of the adverse effect of road roughness in the process of indirectly identifying the bridge frequency through the vehicle response and the limitation of the vehicle driving speed are solved.

The invention discloses a method for testing a dry ground adhesion coefficient of an automobile tire. The method comprises the following steps: determining a test speed range; the tractor runs in the test road section at the first output power, and the surface temperature of tires and the speed of the tractor are detected; calculating a dynamic adhesive force coefficient, correcting the dynamic adhesive force coefficient, and recording the corrected dynamic adhesive force coefficient as a standard dynamic adhesive force coefficient; determining a correction coefficient; acquiring the surface roughness of the road surface on the driving path of the to-be-tested tire on the trailer, and the longitudinal force and the transverse force borne by the trailer; and calculating the standard dynamic adhesion coefficient of the tire to be tested, and correcting the standard dynamic adhesion coefficient by using the correction coefficient to obtain the dry ground adhesion coefficient of the tire. According to the method, the corresponding relation between the real-time roughness and the correction coefficient is established, the adhesive force deviation caused by pavement roughness changes is compensated in a targeted mode, and the high-precision requirements of tire basic performance evaluation and road safety monitoring can be met.

The invention relates to the technical field of suspensions, and discloses an active self-adaptive control method for a damping suspension, which comprises the following steps: acquiring parameters of a road to be driven and parameters of the suspension in the driving process, judging whether the damping force needs to be adjusted according to the acquired road flatness and the parameters of the suspension in the driving process, and if yes, judging whether the damping force needs to be adjusted; if adjustment is judged, an adjustment coefficient is obtained through fuzzy PID control based on particle swarm optimization optimization according to the road flatness and the ramp coefficient, the damping force is adjusted through the adjustment coefficient, and a damping force adjustment value is obtained; the damping force adjustment value is corrected according to the suspension performance evaluation index, if it is judged that correction is needed, a correction coefficient is obtained according to the evaluation index based on fuzzy PID control after particle swarm optimization, the damping force adjustment value is corrected according to the correction coefficient, and a damping force final value is obtained; and storing the to-be-driven road parameter, the vehicle driving parameter, the adjustment coefficient, the damping force adjustment value, the correction coefficient and the damping force final value. The active self-adaptive adjustment of the suspension is realized, and the driving smoothness and stability are improved.

This utility model provides a traffic road smoothness detection device, including a mounting frame; a mounting groove is provided at the top of the mounting frame, through which a control module passes, and a display is also installed in the mounting groove, electrically connected to the control module; an infrared detector is also provided on one side of the mounting frame, electrically connected to the control module; multiple sets of mounting parts and multiple sets of clips and slots are evenly arranged inside the mounting frame, and a connecting frame is rotatably provided in each of the multiple sets of mounting parts; distance sensors are installed in each of the multiple sets of clips and slots, and the multiple sets of distance sensors are connected to the control module through connectors; an assembly is also connected to the connecting frame, and a positioning rod is rotatably provided at the top of the assembly; a positioning plate is also provided inside the mounting frame, and the positioning plate has through holes corresponding to the clips and slots, with the positioning rod passing through the through holes. The device connects the infrared detector and multiple sets of distance sensors to the control module, and the two work together to detect smoothness, rut depth, crack width, etc., thereby improving detection accuracy and efficiency.

The invention discloses a lane selection and lane change control method based on lane level road flatness information. The method is executed when a vehicle intelligent driving or auxiliary driving system is started and a vehicle runs on a one-way multi-lane road. The system obtains lane-level positioning results regularly or irregularly, collects data, evaluates the road flatness of a current driving lane, and uploads the road flatness to a map provider. The system also regularly or irregularly queries and controls the vehicle to keep or change to the optimal lane for driving according to the road flatness information of each traffic lane of the current road provided by the map provider. Meanwhile, the system receives a voice lane change instruction sent by a driver based on visual observation and / or somatosensory perception of road flatness, and controls the vehicle to execute lane change. And when the vehicle changes the lane due to the reason that the vehicle does not drive out of the road, evaluating the road flatness of the lane after lane change, comparing the road flatness with the original lane before lane change, and controlling the vehicle to turn back to the original lane if the lane change is poor.

The utility model discloses a road flatness detection sensing device, which relates to the technical field of road flatness detection and comprises a movable seat and a protective assembly, a fixed seat is mounted at the rear end of the upper surface of the movable seat, a pushing handrail is arranged on the upper surface of the fixed seat, and the protective assembly is arranged on the surface of the movable seat. And the protection assembly comprises a fixed frame, limiting sliding grooves, limiting sliding blocks, a protection sliding cover, a protection box, a protection cover, a heat dissipation opening, a heat dissipation cavity and a dustproof net, the fixed frame is arranged on the lower side of the movable seat, the limiting sliding grooves are formed in the surfaces of the two sides of the fixed frame, and the limiting sliding blocks are slidably connected to the inner sides of the limiting sliding grooves. According to the road flatness detection sensing device, the detection sensing mechanism can be protected by the device through the protection assembly, the detection mechanism can be prevented from being damaged, garbage can be pushed away by the device through the baffle assembly in the pushing process, and the influence of garbage, stones and the like on the ground on a detection result is avoided.

Method comprising: Receiving a variety of sensor data at a road roughness algorithm, determining, via the road roughness algorithm, that the wheel data exceeds a wheel threshold and a severity level exceeds the wheel threshold, executing a wheel flag, determining, based on the wheel flag, that the ride height data exceeds a ride height threshold, executing a ride height flag, determining, based on the wheel flag and the ride height flag, that a wheel pushdown time exceeds a time threshold, identifying, via the road roughness algorithm, an IMU change exceeding an IMU threshold, executing, based on the IMU change exceeding the IMU threshold, an IMU flag, adjusting, based on the IMU flag, parameters of the road roughness algorithm, and combining the wheel flag, the ride height flag, and the IMU flags to define a road anomaly.

The utility model discloses a road flatness detection device which comprises a fixing rod assembly, a laser flatness detector and a camera shooting assembly are installed on the fixing rod assembly, the laser flatness detector comprises a first fixing sleeve, the first fixing sleeve is fixedly connected with the fixing rod assembly through a second puller screw, and the camera shooting assembly is fixedly connected with the fixing rod assembly through a second puller screw. The camera shooting assembly comprises a second fixing sleeve, the second fixing sleeve is fixedly connected with the fixing rod assembly through a third jacking screw, the fixing rod assembly comprises a main rod, and auxiliary rods are arranged at the two ends of the main rod. A plurality of groups of laser flatness detectors form a laser detection system, a plurality of groups of camera shooting assemblies form a camera shooting system, the whole detection device is directly connected with a vehicle, a person drives the vehicle to run on a road, the detection device synchronously moves along with the vehicle, and the road flatness is detected in the running process. The total length of the fixing rod assembly can be correspondingly adjusted according to the road width.

The application discloses a kind of vehicle-mounted laser IRI detection methods based on acceleration vibration compensation, it is related to road flatness detection technical field, including obtaining the road elevation survey data of laser range finder collected in the process of vehicle driving, the vehicle vibration acceleration data of acceleration sensor collected and the vehicle mileage data of encoder collected, and according to the time sequence of collection road elevation survey data, vehicle vibration acceleration data and vehicle mileage data are time-synchronized and arranged to generate time series detection data.In the application, by uniform time marking and time-synchronized and arranged processing to road elevation survey data, vehicle vibration acceleration data and vehicle mileage data, the three types of data form a one-to-one correspondence under the same time axis, so as to establish a complete time series detection data structure, provide a unified data basis for subsequent vibration compensation calculation, improve the overall consistency and continuity of data processing process.

A method comprising receiving a plurality of sensor data at a road roughness algorithm, determining, via the road roughness algorithm, that wheel data exceeds a wheel threshold and a severity level exceeds a wheel threshold, executing a wheel flag, determining, based on the wheel flag, that a ride height data exceeds a ride height threshold, executing a ride height flag, determining, based on the wheel flag and the ride height flag, that a duration of a wheel jerk of the wheel data exceeds a time threshold, identifying, via the road roughness algorithm, that a change in an IMU exceeds an IMU threshold, executing an IMU flag based on the change in the IMU exceeding the IMU threshold, adjusting a parameter of the road roughness algorithm based on the IMU flag, and fusing the wheel flag, the ride height flag, and the IMU flag to define a road anomaly.

The present disclosure provides a system and method for road roughness measurement. A vehicle having a plurality of road noise cancellation sensors captures vibration data as it travels along a road. The vehicle checks whether a set of operating conditions of the vehicle are satisfied. If the set of operating conditions is satisfied, the vehicle determines a portion of the vibration data captured during a time range in which the set of operating conditions is satisfied. The vehicle may then use the portion of the vibration data to extract feature data of the one or more features. The vehicle then uses feature data associated with the one or more features to determine a roughness indicator for the road on which the vehicle is currently traveling. The road roughness indicator measurements may be used to trigger further analysis of the vibration data to determine other parameters of the vehicle.

The application discloses a road detection device and a detection process, which comprise a supporting and moving assembly and a detection assembly, characterized in that the detection assembly comprises a sliding block, the sliding block is fixedly connected with an electric push rod 1, the push rod of the electric push rod 1 penetrates through the sliding block, the push rod of the electric push rod 1 is fixedly connected with a circular tube, the circular tube is fixedly connected with symmetrical supporting rods, one of the supporting rods is fixedly connected with an L-shaped rod, the L-shaped rod is fixedly connected with a vertical plate 2, and the circular tube is provided with a spring 1 and a round head rod. The application relates to the field of detection equipment, in particular to a road detection device and a detection process. The application aims to provide a road detection device and a detection process, and the road flatness detection is facilitated.

A method including receiving, at a road roughness algorithm, a plurality of sensor data, determining, via the road roughness algorithm, the wheel data exceeds a wheel threshold and a severity level exceeding the wheel threshold, executing a wheel flag, determining, based on the wheel flag, the ride height data exceeds a ride height threshold, executing a ride height flag, determining, based on the wheel flag and the ride height flag, a time duration of a wheel jerk of the wheel data exceeds a time threshold, identifying, via the road roughness algorithm, a change in IMU that exceed an IMU threshold, executing, based on the change in the IMU exceeding the IMU threshold, an IMU flag, adjusting, based on the IMU flag, parameters of the road roughness algorithm, and fusing the wheel flag, the ride height flag, and the IMU flag to define a road anomaly.

The invention relates to a parameter design method and device of an active ISD suspension, and belongs to the technical field of vehicle suspension control, and the parameter design method of the active ISD suspension comprises the following steps: based on the sprung mass, the unsprung mass, the tire equivalent spring stiffness, the running speed and the road surface unevenness coefficient of a target vehicle, calculating the parameter of the active ISD suspension; a vehicle dynamics model of the active ISD suspension system and an MPC controller frame of the active ISD suspension system are constructed; and determining a damping coefficient, a spring stiffness coefficient and an inertia coefficient of each three-element unit based on a GA algorithm and a vehicle dynamics model, and determining an input weight and an output weight of the active ISD suspension system based on the determined damping coefficient, spring stiffness coefficient and inertia coefficient of each three-element unit, the MPC controller frame and the RL model. According to the method, the vehicle performance is ensured while the active ISD suspension parameter design efficiency is improved.

Systems and methods for vehicle suspension control. An example method includes obtaining a road roughness map associated with a geographic area in which the vehicle is located, the road roughness map reflecting road condition metrics for road segments that form roads included in the geographic area. Based on the road roughness map, it is determined that a threshold percentage of road segments along an upcoming threshold distance of a navigable route exceed a threshold road condition metric. Suspension of the vehicle is adjusted, with the suspension being adjusted to reduce the effects of road roughness.

The invention discloses a road field flatness investigation monitoring method and system, and relates to the technical field of road flatness monitoring, and the method comprises the steps: integrating a support vector machine model at an edge calculation node, carrying out the quantitative prediction analysis through employing an IRI value, an RMS value and a crack score as input features, and obtaining a preliminary road surface flatness monitoring result; the method comprises the steps of obtaining environment parameters corresponding to a current monitored road and historical road surface flatness data, constructing a multivariable compensation function, dynamically correcting a preliminary flatness monitoring result, obtaining a final road surface flatness monitoring result, generating a road surface monitoring report based on the final road surface flatness monitoring result, and uploading the road surface monitoring report to a cloud server for real-time monitoring. According to the road flatness monitoring method disclosed by the invention, the precision and efficiency of road flatness monitoring are improved, and meanwhile, the strong capabilities of road management level and maintenance efficiency are shown.

The application provides a bridge parallel steel wire pull cable corrosion fatigue residual life prediction method, and relates to the technical field of bridge safety evaluation, comprising: obtaining first information and second information; establishing a random traffic flow model based on the first information; performing cable force time history analysis considering vehicle-bridge dynamic response based on the second information and preset bridge road roughness, and obtaining the response time history of the bridge system; processing the response time history based on the rain flow counting method to obtain all stress amplitudes of the bridge and corresponding cycle times; based on all the stress amplitudes and corresponding cycle times, the time increment method is used to calculate the corrosion fatigue duration of the bridge parallel steel wire pull cable, and the fatigue life of the bridge parallel steel wire pull cable is output. The application is used for evaluating the residual life of the pull cable changing with the external environment during the service period, the evaluation model can be dynamically updated combined with the actual inspection results, and the effective combination of the theoretical model and the measured data is realized.

Systems and methods for vehicle suspension control. An example method includes obtaining a road roughness map associated with a geographic area in which the vehicle is located, the road roughness map reflecting road condition metrics for road segments that form roads included in the geographic area. Based on the road roughness map, it is determined that a threshold percentage of road segments along an upcoming threshold distance of a navigable route exceed a threshold road condition metric. Suspension of the vehicle is adjusted, with the suspension being adjusted to reduce the effects of road roughness.

The application discloses a kind of test methods of the dry adhesion coefficient of automobile tire, comprising: determining test speed range;Towing vehicle travels in test section with first output power, the surface temperature of tire and the speed of towing vehicle are detected;Calculate dynamic adhesion coefficient, correct dynamic adhesion coefficient, and the corrected dynamic adhesion coefficient is recorded as standard dynamic adhesion coefficient;Determine correction coefficient;Obtain the surface roughness of the road on the driving path of the tire to be tested on trailer, the longitudinal force and lateral force received by trailer;Calculate the standard dynamic adhesion coefficient of the tire to be tested, and the standard dynamic adhesion coefficient is corrected using correction coefficient to obtain the dry adhesion coefficient of tire.The application establishes the corresponding relationship between real-time roughness and correction coefficient, compensates the adhesion deviation caused by the change of road roughness, and can meet the high-precision demand of tire basic performance evaluation and road safety monitoring.

The application discloses a bridge vehicle-induced vibration prediction method based on a modal expansion and a residual CNN-LSTM network. According to the modal expansion method, the input vehicle parameters and road roughness are reconstructed into fixed-dimension features, and the concerned vehicle-induced vibration is analyzed and predicted by means of the multi-scale feature extraction and time sequence dependence extraction capacity of the residual convolution-long short-term memory network, so that the prediction precision of the vehicle-induced vibration is improved. The application generates training set samples by using a test design method and a numerical simulation method, so that the prediction precision and generalization ability of the obtained network model are ensured under the premise of controlling the number of training samples. The application has the beneficial effect of overcoming the time-consuming problem of traditional vehicle-bridge coupled vibration analysis, can quickly and reliably predict and analyze the vehicle-induced vibration of a target bridge according to vehicle parameters and road roughness, and is suitable for long-term safety evaluation of highway bridges under the action of random vehicle flow.