2529 results about "Navigation system" patented technology

The invention discloses an AR navigation system and method based on a visual language model, and the method comprises the steps: firstly carrying out video data collection, and constructing a memory database; secondly, querying a navigation target most related to a natural language request of a user in the constructed memory database to obtain a current AR equipment pose and a target pose; and then solving the shortest path from the current pose to the target pose by using the current AR equipment pose and the target pose according to the point cloud map, and optimizing the path direction to finally obtain an optimized path. And finally, guiding a user to move along the planned path through view superposition path indication and voice prompt in AR equipment by utilizing the optimized path, and updating the point cloud map and the memory database. According to the invention, high-precision real-time positioning and sparse point cloud map construction can be realized only by camera input in indoor and outdoor complex environments with low GPS precision, accurate navigation is carried out, and the flexibility and intelligent level of navigation are improved.

The invention discloses a multi-modal information fusion odometer construction method for star catalogue positioning, and relates to the technical field of star catalogue patroller positioning. The method comprises the following steps: carrying out space joint calibration on a monocular camera, a laser radar and an inertial measurement unit, reconstructing a laser radar point cloud by using a timestamp of a camera image, and realizing time synchronization of the camera image and the laser radar point cloud; establishing an IMU pre-integration error model; and performing motion compensation distortion removal on the laser point cloud by using an IMU pre-integration result, and extracting geometric features of the distorted laser point cloud based on a neighbor region smoothness calculation method of a fixed measurement distance. By researching a multimodal information fusion odometer method, the accumulative error of motion measurement is reduced, the positioning precision and stability are improved, technical support is provided for design and development of a star catalogue navigation system, and the problems that a single-modal star catalogue positioning method is weak in environment adaptive capacity and poor in algorithm generalization are solved.

The invention relates to the technical field of autonomous navigation and robot environment perception, and discloses a multi-source sensor fused adaptive navigation system, which comprises a multi-source sensor space-time synchronization module, a quantum particle filtering positioning estimation module, a space-time element learning controller module, a cross-modal quantum fusion module and an adaptive navigation control module. Multi-source data space-time alignment is realized through Lie group SE (3) calibration and dynamic time warping; the positioning robustness of particle filtering is improved based on quantum state coding and annealing optimization; dynamically distributing a fusion weight and injecting a physical constraint by utilizing a meta-learning network; feature level fusion of laser radar, vision and inertial data is realized by means of a quantum entanglement mechanism; and constructing closed-loop adaptive navigation by combining model predictive control and quantum purity trigger feedback. According to the method, the navigation reliability problem caused by misalignment of multi-modal sensor data fusion, divergence of state estimation and insufficient cross-modal relevance in a dynamic environment is solved.

The invention relates to the technical field of unmanned aerial vehicle navigation and control, and discloses an unmanned aerial vehicle indoor and outdoor seamless navigation method fusing Beidou and visual positioning. Comprising the following steps: S1, synchronously acquiring original observation data of a Beidou satellite navigation system of an unmanned aerial vehicle, an image sequence acquired by a visual sensor and inertial data of an inertial measurement unit; s2, processing the original observation data of the Beidou satellite navigation system to obtain the position of the unmanned aerial vehicle, according to the unmanned aerial vehicle indoor and outdoor seamless navigation method and system fusing Beidou and visual positioning, through a self-adaptive fusion filter module, the fusion weight of the unmanned aerial vehicle and visual positioning is dynamically adjusted according to the Beidou signal quality; smooth transition of indoor and outdoor navigation main sources is achieved, pose jump is effectively avoided, a tight coupling depth fusion algorithm is adopted, the precision and robustness of the system are improved, the continuous and stable flight capacity of the unmanned aerial vehicle in complex indoor and outdoor environments is ensured, and the application scene is expanded.

The invention relates to the technical field of robot navigation, and discloses a safety inspection robot multi-mode navigation system fused with subconscious learning. The system obtains a visual image, a depth distance, an inertial measurement unit and other multi-dimensional perception data of an inspection environment, performs environment feature extraction to generate an environment semantic topological graph, and constructs a dynamic navigation cost map and a preliminary navigation path according to the environment semantic topological graph. During path execution, the system detects abnormal navigation behaviors in real time, extracts the features of the abnormal navigation behaviors and obtains a first correction coefficient. And the system judges whether the implicit environment semantic identifier is identified, and if the implicit environment semantic identifier is identified, the corresponding path key node is taken as a semantic navigation reference point, a final navigation path is generated through fusion, and a time stamp is recorded. And if the time stamp exceeds the preset tolerance, extracting a corresponding second correction coefficient. And the system combines the basic navigation performance evaluation value, the first correction coefficient and the second correction coefficient to output a multi-modal navigation decision result.

The invention discloses an intelligent navigation system of a sweeping robot, which relates to the technical field of household intelligent equipment and comprises a multi-source sensor array, a dynamic environment modeling module, a path planning engine, a multi-mode positioning module, an autonomous decision controller, a cloud collaborative optimization unit and a fault degradation processing module. Omnibearing environment perception is provided through a multi-source sensor array, data are fused in real time through a dynamic environment modeling module, a grid map is updated in an incremental mode, obstacle semantic information is marked, an improved A * algorithm and a dynamic window method are fused through a path planning engine, and an optimized path giving consideration to global efficiency and local dynamic obstacle avoidance is generated. The multi-modal positioning module fuses SLAM resolving and IMU data through tight coupling to achieve centimeter-level high-precision and high-robustness positioning, and the autonomous decision controller intelligently and dynamically adjusts the cleaning priority, the advancing speed and the exception handling strategy according to the path, environment state and pose information, so that the cleaning behavior better meets the requirement.

The invention discloses a method for judging an RTK abnormal value in an automatic driving integrated navigation system, and relates to the technical field of automatic driving high-precision integrated navigation, and the method comprises the steps: collecting RTK observation data, inertial measurement unit data, a wheel speed pulse signal and LiDAR point cloud data, carrying out timestamp alignment and coordinate system unification, and generating a fusion data value; calculating a carrier-to-noise ratio weight signal quality index of the satellite through the fused data value, and generating a signal quality report; and combining the signal quality report, the current satellite geometric accuracy factor and the vehicle motion acceleration, calculating a residual threshold, constructing a coriolis force compensated double-integral prediction model by using inertial measurement unit data, and predicting the position of the vehicle at the current moment. According to the method, multi-dimensional features such as satellite signal quality, vehicle motion state and residual analysis are fused through multi-source decision, and the anomaly detection capability of complex scenes such as urban canyons is effectively improved.

The invention discloses an OVER-NAV vision-language combined navigation system and method, and belongs to the technical field of intelligent navigation.The system comprises a navigation server, a user handheld terminal and a navigation terminal.The navigation server comprises a vision module, a language obtaining module, a vision map module, a semantic map module and a multi-modal feature cross-modal interaction module; the core of the system is that a multi-modal feature cross-modal interaction module comprises a topology-aware heterogeneous modal representation unified framework, a differential geometry inspired dynamic attention guidance mechanism and a heterogeneous knowledge integration and collaborative optimization framework, and deep fusion of three modals of visual information, a language instruction and a semantic map is realized; according to the method, the navigation accuracy is remarkably improved, the natural language instruction understanding accuracy reaches 92%, the high recognition accuracy is still kept in illumination changing and noisy environments, and the method is particularly suitable for complex shopping mall environments, outdoor-indoor seamless transition navigation and other scenes.

Disclosed are an inertial baseline integrated navigation method, and a product, a medium, a device and an autonomous underwater vehicle, relating to the field of navigation. The method comprises: in an initial stage of the starting of an inertial baseline integrated navigation system, an SINS using a USBL to assist with initial alignment and obtaining initial attitude information (1); when the inertial baseline integrated navigation system enters a formal navigation operating state, the SINS performing pure inertial navigation solving on the basis of the initial attitude information, so as to obtain navigation parameter calculation values including errors (2), wherein the navigation parameter calculation values comprise the attitude, velocity and position; on the basis of the navigation parameter calculation values including the errors, constructing a navigation state error model based on a Lie group (3); on the basis of a Huber function, constructing a generalized maximum likelihood estimation model (4); according to the navigation state error model based on a Lie group and the generalized maximum likelihood estimation model, establishing an integrated navigation robust Kalman filtering algorithm (5); on the basis of the integrated navigation robust Kalman filtering algorithm, performing filtering estimation on the inertial baseline integrated navigation system, so as to obtain a state estimation value (6); and on the basis of the state estimation value, performing feedback updating on navigation parameters, and on the basis of the updated navigation parameters, performing navigation. The method can improve the integrated filtering precision and positioning and orientation precision.

The invention discloses a satellite navigation positioning method and device and a storage medium. The positioning method comprises the steps that observation parameters collected by a mobile terminal in a preset epoch are obtained, the observation parameters comprise GNSS parameters and inertial navigation correlation parameters, and the GNSS parameters comprise GNSS prior parameters and GNSS posterior parameters; the observation parameters are input into a preset positioning precision evaluation model, a precision evaluation value is obtained, and the positioning precision evaluation model is obtained based on training of historical observation parameters collected by multiple epochs; determining whether the positioning information represented by the current observation parameter is accurate based on the precision evaluation value; when it is determined that the positioning information is inaccurate, a positioning result is determined based on a floating point solution of integer ambiguity; and when the positioning information is determined to be accurate, determining a positioning result based on the fixed solution of the integer ambiguity. The method has the technical effect of improving the positioning precision and the positioning reliability of the global satellite navigation system.

The invention relates to the technical field of orchard automatic navigation deviation correction, in particular to an automatic navigation deviation correction system for an orchard track power platform. Comprising a chassis, a vehicle control unit, a navigation system vehicle-mounted computer, a laser radar, a navigation control box, a navigation antenna, a steering motor, a differential planetary mechanism, a rotating speed sensor, an edge architecture control box, a driving wheel assembly, a servo valve and a steering pump. The mode that the whole vehicle controller regulates and controls the servo valve to conduct deviation rectification is adopted, the deviation rectification response speed is high, the control precision is high, the high-speed operation working condition of the orchard power platform can be adapted, and the operation efficiency is improved; the swash plate plunger steering pump is adopted to drive the steering motor, the driving power is small, the heat balance stability is good, and the cost is low; the differential steering mechanism is adopted as a deviation rectifying executing mechanism, the transmission efficiency of the power platform is not affected, the steering line type is controllable, steering is stable, the overcorrection phenomenon is effectively avoided, the automatic navigation operation precision is effectively improved, and the automatic navigation deviation rectifying stability of the orchard power platform is improved.

In one implementation, a method for navigating a host vehicle relative to a road segment includes receiving a captured image representative of at least a portion of the road segment; receiving a planned drivable path representation based on one or more map sections associated with the road segment, wherein the drivable path is determined for navigating the host vehicle; generating an overlaid representation of the captured image with the planned drivable path; providing the overlaid representation to a trained network, wherein the trained network is configured to receive the overlaid representation as input and provide, based on the combination of the captured image and the planned drivable path, an output that includes an indication of whether the host vehicle drivable path represents a valid path along the road segment; and causing a navigation system of the host vehicle to determine a navigational change for the host vehicle based on the indication of whether the host vehicle drivable path represents a valid path along the road segment.

To eliminate the influence of station position fluctuations in a satellite navigation system. [Solution] In satellite navigation systems, including the US GPS and Japan's Quasi-Zenith Satellite System, when multiple reference stations are installed to form a wide-area differential correction system (WADGPS), previously, position errors caused by fluctuations in station position would remain in the position information calculated by the user receiver.However, by adding a correction amount to the correction information provided by WADGPS in advance to cancel this, the position errors caused by fluctuations in station position at the user station can be reduced without changing the calculation processing content at the WADGPS user station, thereby improving the accuracy of the position information calculated by the user station.

The invention discloses a combined navigation method and system of an unmanned surface vehicle. The method comprises the following steps: forming a GNSS (Global Navigation Satellite System) / INS (Inertial Navigation System) integrated navigation system by using a GNSS (Global Navigation Satellite System) and a strapdown inertial navigation system (INS), and establishing a mathematical model of a GNSS / INS integrated navigation system filter; the mathematical model comprises a state equation and a measurement equation; establishing a mathematical model of the influence of the GNSS auxiliary information on the GNSS positioning precision so as to preliminarily adjust the measurement noise in the measurement equation; through an improved Sage-Husa adaptive filtering algorithm, adaptive estimation is carried out on the preliminarily adjusted measurement noise, and a measurement noise estimation final value is obtained; and according to the motion characteristics of the unmanned surface vehicle, adding motion constraint conditions to the measurement equation. The GNSS auxiliary information mathematical model based on multivariate function fitting is established, the influence of the external environment on the positioning precision is objectively reflected, the measurement noise in the filter is dynamically adjusted, and the positioning precision of the integrated navigation system under the interference condition is remarkably improved.

The invention relates to the technical field of automatic driving, and discloses a dense semantic map navigation system based on multi-sensor fusion and factor graph optimization, which comprises a sensor module, an environment mapping module, a real-time positioning module, a detection and classification module and a path planning control module, a complete technical architecture from environment mapping, real-time positioning, obstacle detection and tracking, trajectory prediction, global path planning and local path planning is covered, and high-precision environment mapping, real-time positioning, obstacle detection and avoidance and path planning are realized by using various sensors such as a laser radar, an IMU (Inertial Measurement Unit) and a binocular camera and a sensing data fusion technology. In combination with deep learning and an optimization algorithm, high-precision autonomous navigation of the unmanned vehicle in a complex dynamic environment is realized, and the robustness and safety of path planning are improved.

The invention discloses a power distribution network fault positioning method and device based on a satellite time service inverter, and belongs to the technical field of power system fault diagnosis, and the method comprises the steps: obtaining a time service signal of a satellite navigation system, decoding the time service signal to generate a unified space-time reference, distributing the unified space-time reference to a plurality of inverter nodes in a power distribution network, and forming a cooperative measurement network; a coding sequence current signal is injected into a power distribution network line through a master control inverter node; synchronously acquiring response voltage traveling wave data by each inverter node, performing cross-correlation analysis on the response voltage traveling wave data and the coded sequence current signal, and extracting propagation time delay of each inverter node; and correcting the reference line wave velocity by using the current line parameters and the current meteorological data, and calculating fault point position data in combination with propagation time delay. According to the method, an inverter cooperative measurement network is constructed by using satellite time service, a coding sequence current signal is actively injected, and a real-time wave velocity is corrected by combining an intelligent model, so that rapid, accurate and high-reliability positioning of a power distribution network fault can be realized.

The invention belongs to the technical field of unmanned aerial vehicles, and provides an omni-directional vision positioning system and method and an unmanned aerial vehicle, the omni-directional vision positioning system is installed on a fuselage of the unmanned aerial vehicle, and the omni-directional vision positioning system comprises an image acquisition device used for acquiring a real-time scene image in an omni-directional range in the flight process of the unmanned aerial vehicle; the inertial measurement sensor is connected with the image acquisition equipment and is used for synchronously acquiring motion state data of the unmanned aerial vehicle; the navigation system is connected with the image acquisition equipment and the inertial measurement sensor and is configured to execute at least one of distortion correction processing and feature extraction processing on the real-time scene image to obtain a processed image; and according to the motion state data and the processed image, determining current pose information of the unmanned aerial vehicle in a space coordinate system constructed by taking a take-off point of the unmanned aerial vehicle as an original point. The positioning precision and robustness of the unmanned aerial vehicle in a complex environment are improved, and the requirement of high-precision autonomous flight is met.

The invention relates to the technical field of flight control, in particular to a hybrid control FPV unmanned aerial vehicle flight control system and method. The method comprises the following steps: acquiring triaxial angular velocity data of the unmanned aerial vehicle in real time by using an inertial navigation system, eliminating high-frequency noise and performing zero offset calibration; constructing a corresponding linear extended state observer to adjust a gain parameter in real time based on an absolute value of an observation error, and filtering tiny noise disturbance through a dead zone function to realize high-precision estimation of the system state and total disturbance of the unmanned aerial vehicle so as to obtain an error and an error change rate; and designing a self-adaptive PID control law to dynamically adjust PID control quantities corresponding to proportion, integral and differential gains, carrying out dynamic weighted stacking according to a flight mode, generating a three-axis control quantity, carrying out flight control on the FPV unmanned aerial vehicle, and meanwhile, realizing real-time visual verification of a control effect corresponding to the flight control. According to the invention, high-precision and high-robustness attitude control can be realized.

The invention discloses an improved Kalman filtering ocean current estimation method based on inertial information and DVL speed. The method comprises the following steps: S1, system initialization and data acquisition; s2, performing inertial navigation system (INS) resolving, namely performing mechanical arrangement resolving based on IMU data; s3, constructing a fusion filtering state model and an observation model; s4, adaptive Kalman filtering iteration estimation: after discretizing the state equation and the observation equation, executing filtering iteration according to a period; and S5, state feedback correction and ocean current output. According to the improved Kalman filtering ocean current estimation method based on inertial information and DVL speed, a fusion framework of an augmented state model and adaptive Kalman filtering is constructed, and high-precision ocean current estimation and navigation correction are realized through five key processes.

The invention belongs to the technical field of ablation puncture navigation, and particularly relates to an ablation puncture surgery navigation system under AI visual guidance. Through cooperative work of the phase monitoring module, the channel construction module, the needle moving control module, the displacement prediction module and the feedback control module, an intelligent surgical navigation system is constructed, breathing phase information and multi-modal medical image data of a patient can be obtained in real time, and therefore a safe and optimized needle moving path is accurately planned, and the operation accuracy is improved. Meanwhile, through real-time monitoring and quantitative evaluation of parameters such as tissue deformation and pressure distribution in the needle moving process, potential operation risks can be found and corrected in time, smooth operation is ensured, in addition, the system can dynamically adjust the needle moving path and the puncture angle according to the real-time breathing state of a patient, and the operation safety is improved. The accuracy and the safety of the operation are further improved, so that intelligent management and personalized treatment in the ablation puncture operation process are realized.

The invention relates to the technical field of blind guiding robot interactive navigation, and particularly discloses a blind guiding robot interactive navigation system combining vision, inertial navigation and voice, which is characterized in that environmental vision, movement and voice data are synchronously acquired through a multi-modal perception data acquisition module, and are analyzed through a situation-user joint state feature extraction module; a user potential intention deduction module is combined to predict a user intention and generate a self-adaptive guide strategy; a self-adaptive guiding path optimization module adjusts a navigation path according to a strategy to ensure safety and high efficiency; finally, the situational multi-mode interaction instruction output module provides voice and tactile feedback, and interaction experience and navigation autonomy are enhanced. According to the method, the travel problem of the visually impaired person in a complex environment is solved, the individuation, context perception capability and safety of blind guiding are improved, and more natural and efficient navigation assistance is brought to the visually impaired person.

The invention relates to an information fusion method and device of a multi-source navigation system, computer equipment and a computer program product. The method comprises the following steps: constructing a preset number of sub-models according to sensor systems in the multi-source navigation system, taking the product of the expected credibility and the real-time credibility of the performance of each sensor system as the comprehensive credibility of each sensor system, and determining a state transition probability matrix of the sub-models according to the comprehensive credibility; state prediction updating and measurement updating are carried out on each sub-model, and a system error state and a system state covariance are calculated; and calculating a predicted posterior probability of each sub-model, determining an interactive weight between the sub-models according to the predicted posterior probability and the state transition probability matrix, and correcting and updating the system error state and the system state covariance according to the interactive weight to obtain a final system error state and a final system state covariance. By adopting the method, the robustness of information fusion can be effectively improved.

Embodiments relate to a method and apparatus for determining lane level localization of a vehicle with global coordinates. An automotive vehicle includes a vehicle navigation system, a database comprising standard-definition map data corresponding to road level latitude and longitude coordinates for a plurality of roadway features, at least one image sensor, and a processor in communication with the vehicle navigation system, the database, and the at least one image sensor. The processor is configured to determine an initial location of the vehicle, estimate a current location of the vehicle based on a dead reckoning process, detect, based on image data from the at least one image sensor, a lateral position of the vehicle within a lane of a road, and update the current location of the vehicle based on a difference between the estimated current location and the lateral position of the vehicle within the lane.

The invention relates to three-dimensional traffic navigation, in particular to a three-dimensional traffic navigation system based on space-time grid coding, which comprises a low-altitude path planning module for planning an optimal flight path for an aircraft in a low-altitude airspace based on a four-dimensional space-time grid coding model and adjusting the path in real time in combination with dynamic environmental factors; the airspace conflict detection module is used for carrying out conflict detection on aircrafts in a low-altitude airspace, judging whether conflicts exist or not and finding potential conflicts in time; the path collaborative planning module is used for carrying out collaborative path planning on the multiple aircrafts with conflicts in the low-altitude airspace and solving the problem of conflicts among the multiple aircrafts; the cross-modal traffic coordination module is used for integrating ground and low-altitude traffic systems, realizing seamless connection and efficient coordination of an optimal ground path and an optimal flight path, and providing an integrated three-dimensional traffic navigation scheme; the method can overcome the defects that in the prior art, path planning efficiency is low, airspace conflicts are difficult to accurately detect, and a cross-modal traffic cooperation mechanism is lacked.

The invention provides a heterogeneous animal robot collaborative navigation system based on a large language model, which comprises a centralized control center, and is provided with a visual perception conversion module and an instruction generation module. The visual perception conversion module extracts semantic information by using a visual large model SAM, generates a bird's-eye view (BEV) representation in combination with a space-time attention mechanism, constructs a global semantic map through a semantic segmentation decoder, and converts the global semantic map into natural language description by means of a BLIP-2 model. The instruction generation module inputs visual description, navigation information, historical tracks and human expert instructions as cues into the large language model, outputs a navigation thinking chain including task allocation and instruction selection, and includes four intermediate steps of state prediction, filtering, action prediction and instruction output. According to the system, through a centralized control structure and a cooperative sensing control method, the sensing, cooperation and communication capabilities of the heterogeneous animal robot are improved, and efficient navigation and decision execution of the heterogeneous animal robot in a complex environment are ensured.

The invention belongs to the technical field of underwater positioning navigation, and relates to an integrated navigation system and method based on robust adaptive Kalman filtering, and the system comprises a strapdown inertial navigation system, a Doppler velocimeter, a depth sensor and a data processing module; the method comprises the following steps: constructing a state space model based on an integrated navigation system, and estimating system noise parameters on line in real time by introducing a Sage-Husa adaptive filtering mechanism; performing sequential processing on the multi-dimensional measurement information by adopting a sequential measurement and variance limitation method, and setting upper and lower limits of scalar measurement noise variance; an IGGIII criterion is introduced, and gross errors of measurement information are detected through a residual filter; according to the method, noise and outlier interference can be suppressed in a complex underwater environment, and the positioning precision, robustness and stability of a navigation system are improved.

The invention relates to an unmanned aerial vehicle autonomous path navigation system based on multi-modal fusion and adaptive optimization and an algorithm thereof. The system comprises a multi-modal sensor module, a data fusion processing module, an adaptive algorithm processing module and a flight control module. The method comprises the following steps: step 1, data acquisition; step 2, data fusion; step 3, algorithm processing; and 4, controlling the flight of the unmanned aerial vehicle. The method has the advantages that multiple sensors such as a visual camera, a laser radar and a millimeter wave radar are integrated through deep fusion of multi-modal sensors, a fusion algorithm based on deep learning and a Transform architecture is adopted, weights are automatically distributed through an attention mechanism, deep data fusion is achieved, and the accuracy and accuracy of data fusion are improved. Compared with a single sensor or a simple data fusion mode, the problem that the single sensor is easily interfered by the environment is effectively solved, and the obstacle recognition accuracy and the environment modeling precision are greatly improved under the complex environments of low illumination, strong smoke, electromagnetic interference and the like.

The invention relates to the technical field of medical navigation, in particular to an augmented reality blood vessel fusion navigation system for transcatheter occlusion, which comprises a real-time image acquisition module, a blood vessel three-dimensional model construction module, an image enhancement module, a navigation module and a fusion module, and is characterized in that the image acquisition module is connected with an ultrasonic catheter to acquire a blood vessel three-dimensional image. The model construction module creates a three-dimensional blood vessel model based on the images, the image enhancement module enhances the blood vessel image through spatial adaptive transformation, key point recognition, region adaptive segmentation and edge feature extraction, and the navigation module determines the position of the tip of the catheter by using the three-dimensional blood vessel model and the enhanced image. The fusion module fuses the enhanced image and the blood vessel model to generate fusion display data, and the AR equipment displays the blood vessel three-dimensional model at the tip position of the catheter in an overlapping manner based on the tip position of the catheter and the fusion data, so that the visualization effect of a complex blood vessel structure is remarkably improved, and an accurate space reference is provided for catheter navigation.

The invention relates to the technical field of automatic driving vehicle control, in particular to a drive-by-wire chassis whole vehicle test device and method, which considers the delay compensation of a vehicle steering actuator and comprises an upper computer, a real-time controller, a drive-by-wire chassis vehicle, a combined navigation system and a USB-CAN (Universal Serial Bus-Controller Area Network) acquisition module. The method comprises the following steps that a vehicle in-loop system is built on a rack, and the delay characteristic of a steering actuator is identified through step and sine mixed excitation signals; establishing a vehicle trajectory tracking error model containing delay compensation based on an identification result; deploying a delay compensation model in a real vehicle environment, and verifying trajectory tracking performance; comparing the transverse error and the course angle error before and after compensation, and evaluating the compensation effect. The invention provides a drive-by-wire chassis whole vehicle test device and method integrating delay identification, model injection and real vehicle verification, and an engineering scheme is provided for dynamic rapid calibration and algorithm migration of an automatic driving drive-by-wire chassis actuator.

The invention discloses a scenarized vehicle-mounted advertisement recommendation system for intelligent traffic, and relates to the technical field of intelligent traffic, and the system comprises a data collection module which collects a direction deviation angle, a speed matching degree and a path following rate in real time through a vehicle sensor and a navigation system, and obtains original behavior data; the feature extraction module is used for processing the original behavior data by adopting a time sequence analysis method, extracting dynamic features of steering frequency, pause time difference and signal acquisition frequency, and determining a behavior signal sequence; the correlation analysis module is used for calculating a correlation coefficient according to the matching degree of the behavior signal sequence and the navigation setting information on the aspects of time synchronism and environmental interference factors to obtain a correlation feature vector; according to the intelligent traffic-oriented scenarized vehicle-mounted advertisement recommendation system, through combination of multi-level behavior analysis and a recommendation algorithm, the pertinence of advertisement pushing and the user acceptability are remarkably improved, and an efficient advertisement putting effect is realized.