218 results about "Driving simulation" patented technology

The invention provides an airspace simulation deduction method and system based on digital twinning, and belongs to the technical field of airspace simulation, and the method comprises the steps: integrating geographic bottom plate data and airspace element data, carrying out the meshing based on an airspace grid engine, and constructing an airspace digital twinning model; receiving at least one flight plan, and mapping the flight plan to the airspace digital twin model to generate a corresponding simulation aircraft entity; based on a preset simulation engine, driving the simulation aircraft entity to perform flight simulation in the airspace digital twin model, and calculating a simulation flight situation; in the simulation process, airspace conflict detection and early warning are carried out based on the simulation flight situation and the airspace digital twin model; and outputting a simulation deduction result, performing three-dimensional visual output on the simulation flight situation data and the early warning information, and generating an analysis report including conflict statistics and airspace evaluation. The airspace resource allocation is optimized, the flight safety is improved, and intelligent and efficient management is realized.

The invention belongs to the technical field of analog simulation, and particularly relates to an intelligent simulation system with an autonomous decision-making capability, which comprises simulation management used for task scene initialization, system parameter configuration and simulation process control and operation. The display system is used for 2D / 3D visual display and playback of simulation results; the model implementation system is connected with the simulation management and display system and is used for implementing a target model and a flight mode model according to configuration parameters; the intelligent target generation system is used for automatically generating a maneuvering combination strategy, a task load control strategy and a radar control strategy according to the simulation situation information generated by the model implementation system, and feeding back the maneuvering combination strategy, the task load control strategy and the radar control strategy to the model implementation system to drive simulation deduction; wherein the system can execute a plurality of simulation modes including large sample space random task simulation, task simulation without autonomous capability level and task simulation with certain autonomous capability level according to simulation types set by the simulation management and display system.

The invention relates to an automatic driving test scene simulation generalization generation method and system based on knowledge distillation. The method comprises the following steps: acquiring real trajectory data, constructing a scene-level multi-agent trajectory generation framework based on a denoising diffusion probability model, and generating diversified and vivid agent trajectories through an iterative denoising process so as to realize modeling of multi-agent interaction behaviors in a complex traffic environment; a mixed knowledge self-distillation framework is further proposed, multi-level knowledge of a teacher model is migrated in a student model, and task loss and distillation loss are dynamically balanced in combination with a simulated annealing strategy, so that the cross-scene adaptability and generation stability of the model are improved; simulation verification shows that the generated intelligent agent track can effectively reduce the collision event rate and the retrograde event rate, and interaction coordination and traffic rule constraints are ensured. According to the system, the authenticity, diversity and cross-scene adaptive capacity of an automatic driving simulation scene can be improved.

The invention relates to the technical field of automatic driving simulation, in particular to a performance evaluation method, system and device of an automatic driving simulation platform and a medium, and the method comprises the steps: constructing a simulation environment and a simulation vehicle equipped with a sensor, an actuator and a vehicle-mounted calculation unit simulation model; establishing a multi-dimensional platform evaluation system covering security, efficiency, response time and data processing capability, defining a specific sub-index, an evaluation method and a target data item needing to be collected for each dimension, and setting a comprehensive evaluation rule; running a closed-loop simulation test in the simulation platform, and synchronously collecting all target data; calculating evaluation results of the sub-indexes one by one based on the collected data; and judging whether the overall performance of the platform reaches the standard according to comprehensive evaluation rules. According to the invention, systematization, standardization and quantitative evaluation of the performance of the automatic driving simulation platform are realized, the reliability and comparability of a test result are improved, and an effective basis is provided for optimization of the simulation platform.

The invention belongs to the field of automatic driving, and particularly relates to a multi-scene fusion automatic driving analog simulation test method and system, and the method comprises the steps: obtaining multi-source heterogeneous driving data, carrying out the preprocessing and fusion of the multi-source heterogeneous driving data, and obtaining standardized scene data; based on the standardized scene data, constructing a basic simulation scene by adopting a photo-level real-time rendering technology, and optimizing and constructing the basic simulation scene into a three-dimensional scene model by adopting a 3D Gaussian splashing technology; based on a preset scene generation rule and through a 4D space-time modeling algorithm, performing expansion and variation on the three-dimensional scene model, and automatically generating a multi-dimensional test scene set; executing a simulation test corresponding to the multi-dimensional test scene set, and collecting test result data of the automatic driving system; and establishing a scene optimization and algorithm iteration closed-loop mechanism based on the test result data, and dynamically optimizing the multi-dimensional test scene set and the automatic driving system algorithm.

Techniques are discussed herein for generating and evaluating driving simulations based on synthetic scenarios. Simulated objects may be controlled based on parameters determining the attributes and behaviors of the objects, and scenarios may be synthetically modified by changing the parameters for a simulated object. For a driving scenario with a synthetic simulated object, a simulation system may analyze driving log data to determine a probability or prevalence associated with the driving scenario. In various examples, the simulation system may determine marginal density estimates for individual attributes of the simulated object, as well as a cumulative distribution function modeling the dependence between the attributes. The joint probability distribution determined for the synthetic simulated object can be used for evaluating the efficacy of the simulation and the performance of the simulated vehicle controllers.

The invention relates to the technical field of industrial detection, and discloses a lithium niobate metasurface defect intelligent identification method based on reactive ion beam etching, which systematically solves the problem of scarcity of experimental data through physical driving simulation and a physics-based rendering algorithm, and provides large-scale field specific training data for a deep learning model. The bidirectional coupling simulation model generates defect morphology prediction data conforming to an etching dynamics law based on real process parameters and material parameters, the prediction data is converted into a synthetic image with real microscopic image statistical characteristics by a physical rendering algorithm, and the quality and consistency of the synthetic data are ensured by an automatic labeling and statistical verification process. According to the method, the number of samples of the ternary association database is multiplied, and extreme process conditions and rare defect modes which are difficult to obtain through experimental collection are covered.

The invention relates to the technical field of automatic driving, and discloses a vehicle driving scene generation method based on an automatic driving simulation environment, and a track generation method, system and equipment, and the vehicle driving scene generation method comprises the steps: determining a dense depth map according to a real vehicle driving scene image and a sparse radar point cloud corresponding to the real vehicle driving scene image; generating a dense three-dimensional point cloud under the global coordinate system according to the dense depth map; and generating a future observation image of the vehicle driving scene based on the dense three-dimensional point cloud. According to the scheme, the vehicle driving simulation scene which is stable in geometric structure and good in picture consistency can be generated in the vehicle automatic driving closed-loop simulation process, and the consistency and controllability of driving scene generation are improved.

The invention discloses an automatic driving test and evaluation method and device based on a large language model, and solves the problems that the pertinence of a test scene is insufficient, the result understanding depends on manpower, the evaluation interpretation is weak and the like in a traditional method. By means of semantic analysis, logical reasoning and domain knowledge support of a large language model and in combination with an automatic driving test domain knowledge graph, generation of a structured test portrait of a tested system, construction of a test demand list, generation of a semantic test scene description file, interpretable test result attribution, multi-dimensional comprehensive evaluation and report output are completed in sequence. And a test portrait is updated through report feedback to form a closed loop. The method is suitable for function verification and performance evaluation of an automatic driving simulation test, can also be used for post-processing analysis of real vehicle test data, realizes automation of a whole test process and interpretability of an evaluation result, and improves test precision and efficiency.

The invention relates to a multi-vehicle automatic driving simulation system and method supporting DORA middleware, and belongs to the technical field of automatic driving. The system comprises a simulation platform and a domain controller group. The simulation platform comprises a multi-vehicle Dora-bridge, traffic scene simulation software and vehicle dynamics simulation software, the multi-vehicle Dora-bridge receives multi-vehicle state data, sensor data and vehicle cooperative control information generated by the traffic scene simulation software, and the multi-vehicle Dora-bridge publishes the multi-vehicle state data, the sensor data and the vehicle cooperative control information in the form of a DORA topic for each domain controller to subscribe; meanwhile, control instructions issued by the domain controllers in the form of DORA topics are received and issued to the vehicle dynamics simulation software. The domain controller group comprises a plurality of domain controllers, each domain controller corresponds to one automatic driving vehicle, and software of the domain controller group consists of a plurality of DORA function nodes to realize an automatic driving function. According to the invention, an effective solution is provided for simulation of the multi-vehicle automatic driving system based on the DORA middleware, the development efficiency is improved, and the development cost is reduced.

The invention relates to a vehicle dynamics simulation method and system based on a recurrent neural network and a medium. The method comprises the steps that control quantity time sequence data and state quantity time sequence data of a real vehicle are collected; constructing a time sequence window as the input of a recurrent neural network based on the control quantity time sequence data and the state quantity time sequence data; processing the time sequence window through the recurrent neural network, and outputting a longitudinal acceleration predicted value and a yaw velocity predicted value at the next moment; and inputting the longitudinal acceleration predicted value and the yaw velocity predicted value into a kinematics model, and calculating to obtain velocity, course angle and displacement information at the next moment so as to form a hybrid dynamics closed loop combining neural network deduction and kinematics integration. According to the invention, model training can be carried out based on the real vehicle data to cover wider working condition scenes, so that the dynamic characteristics of the real vehicle can be better aligned, and the requirements of automatic driving simulation on diversified scenes are met.

The invention relates to the technical field of road condition simulation driving simulation, in particular to a vehicle driving simulation system and method suitable for a road condition simulation test, and the method comprises the steps: obtaining various instruction signal amplitudes for simulating the operation behavior of a driver and the inclination angle data of a six-degree-of-freedom motion platform; extracting inclination angle high-frequency and low-frequency sets, and obtaining high-frequency motion inhibition degrees of all acquisition periods; calculating a motion gain characteristic value of each instruction signal, obtaining a scaling characteristic value of each instruction signal in combination with the high-frequency motion suppression degree, and adjusting a time-varying proportionality coefficient of each instruction signal in a classical washout algorithm; and the target extension amount of each electric cylinder of the six-degree-of-freedom motion platform is obtained by utilizing a classic washout algorithm and combining a six-degree-of-freedom motion platform pose inverse solution algorithm, and the pose of the six-degree-of-freedom motion platform is controlled. According to the invention, the vehicle driving simulation precision can be improved.

The present disclosure relates to a map processing method and device in a simulation system and electronic equipment, and belongs to the technical field of map processing. The map processing method in the simulation system comprises: acquiring a map in at least one format; processing the map according to a rasterized map format to obtain a target map; the rasterized map format comprises a topology layer and a geometry layer; the topology layer comprises a logical structure of a road, and the road comprises a plurality of lanes; the geometry layer comprises a geometry shape description of the plurality of lanes; and the target map is imported into an automatic driving simulation system for automatic driving simulation task processing. The present disclosure can realize fast import and lightweight operation of a third-party map.

This invention discloses a method and apparatus for evaluating the mechanical properties of high-voltage wiring harnesses. The method includes: constructing a rigid-flexible coupling model of the entire vehicle, comprising a rigid body model of the vehicle and a flexible cable model of the high-voltage wiring harness within the vehicle; performing a driving simulation on the rigid-flexible coupling model of the entire vehicle under target operating conditions to obtain a first motion simulation result of the high-voltage wiring harness, and then determining a first mechanical property evaluation result based on this result; performing a stress simulation on the flexible cable model based on the first motion simulation result to obtain a second motion simulation result for each fixed clip node; and performing a mechanical property simulation on each fixed clip node based on the second motion simulation result to obtain the corresponding second mechanical property evaluation result. This invention solves the technical problem that related technologies, which use a decentralized and static approach, cannot accurately evaluate the mechanical properties of high-voltage wiring harnesses, thus hindering the accurate analysis of failure modes of high-voltage wiring harnesses during long-term service.

The application discloses a micro-grid digital sand table system based on real statistical law scene data generation, relates to the related field of micro-grid simulation and optimal control technology, and comprises an artificial configuration layer, which is used for receiving micro-grid static parameters configured by a user; a scene automatic generation layer, which is used for automatically generating dynamic meteorological, load and electricity price time sequence data for driving simulation based on historical statistical law; a physical simulation layer, which is used for calculating real-time power, energy state and operation cost of the micro-grid according to the generated data; an equal power mapping calibration module, which is used for collecting measured data of the physical world, comparing and correcting model parameters with the output of the physical simulation layer, so that the digital sand table satisfies the equal power characteristic; and a high-speed control interface, which is used for interacting with external control algorithms in terms of state information and control instructions. The problems of strong dependence on scene data, insufficient scene coverage, missing simulation fidelity and equal power characteristic and lack of large-scale training data support of the existing micro-grid simulation method are solved.

The invention provides an automatic driving simulation agent method, and the method comprises the steps: obtaining bag data; screening a to-be-controlled vehicle as a target agent based on the bag packet data; main vehicle track change features, target agent state features, interaction relation features of the main vehicle and the target agent and environment constraint features of the target agent are calculated respectively; performing feature fusion on the main vehicle track change feature, the state feature of the target agent, the interaction relationship feature of the main vehicle and the target agent and the environmental constraint feature of the agent; and making a driving decision based on a feature fusion result. By means of the method, the simulation scene better fits the actual interaction situation.

The invention relates to the technical field of road condition simulation, in particular to a high-speed multi-scene vehicle-road cooperative driving simulation system, which comprises a scene simulation and data acquisition module, a vehicle-road cooperative driving simulation module, a vehicle-road cooperative driving simulation module and a vehicle-road cooperative driving simulation module, wherein the scene simulation and data acquisition module is used for acquiring point cloud data around a simulated vehicle in real time through a virtual simulation scene; the noise analysis module is used for analyzing local and global outlier characteristics of all point cloud data in each voxel and calculating the noise interference prominence of each point cloud data; the point cloud filtering module is used for identifying and eliminating abnormal point clouds based on noise interference prominence; voxel filtering processing is carried out on the remaining point cloud data; and the vehicle-road collaborative module is used for updating the three-dimensional point cloud map of the simulated vehicle by using the filtered point cloud data so as to realize a vehicle-road collaborative simulation test. The invention aims to improve the filtering processing effect of the voxel filtering algorithm on the point cloud data, so that the quality of updating the three-dimensional point cloud map in real time is ensured.

The application relates to a multi-scene emergency disposal decision system in traffic safety management. The system comprises a dynamic decision library module, an accident perception positioning module, an intelligent decision matching module and a multi-department linkage scheduling module. The system can analyze historical accident cases through structuring, build a knowledge graph and a simulation model, generate a dynamic fusion decision knowledge base, obtain multi-source heterogeneous perception data in real time, perform abnormal analysis and directional analysis, generate structured accident confirmation information, retrieve matching cases and strategy packages in the knowledge base, generate and optimize disposal schemes, distribute the deconstructed disposal tasks to emergency departments, monitor the execution process in real time, generate a disposal complete data package and update the knowledge base. The method can significantly improve the efficiency and accuracy of emergency disposal in traffic safety management by building a dynamic fusion decision knowledge base and combining real-time data-driven simulation optimization, and can enhance multi-scene adaptability and multi-department collaboration ability.

The invention discloses an interactive simulation cockpit, and relates to the technical field of driving simulation. The problems of insufficient immersion, single interaction dimension, simulation scene solidification and the like existing in existing simulation driving are solved. The interaction module is integrated in the cabin body, the electric sliding rail is arranged on the inner wall of the bottom of the cabin body, the seat is fixed to the inner wall of the electric sliding rail through bolts, and the display screen, the pedal, the operation table and the steering wheel are arranged in front of the seat. The interaction module comprises a biological characteristic acquisition module used for acquiring physiological state data of a driver in real time, a force interaction unit used for the driver to directly simulate driving, and an environment simulation restoration module used for providing a simulation scene. According to the invention, a'human-vehicle-environment 'deep closed-loop interactive simulation cockpit is realized, a one-way output mode of an existing simulator is broken through, the state of a driver can be sensed in real time, and the simulation driving content and feedback intensity are dynamically adjusted, so that the authenticity and effectiveness of training are greatly improved.

Techniques are described herein for evaluating and tuning parameters for controlling the behavior of an autonomous vehicle in or near intersections controlled by traffic signals. A planning component of an autonomous vehicle may use a set of traffic signal parameters to compute trajectory costs for the vehicle associated with traversing an intersection controlled by a traffic signal in a non-permissible state (e.g., a red light). A parameter tuning system may execute driving simulations using the planning component and a candidate set of parameters to control the behavior of a simulation vehicle within a training data set of traffic signal intersections. The parameter tuning system may determine performance metrics based on the behaviors of the simulated vehicle and may execute a search algorithm to determine modified (e.g., optimal) parameter sets for controlling vehicles during real-world driving scenarios having intersections controlled by traffic signals.

Provided is an information processing system comprising: a storage means that stores, in a database, a first feature amount which is information relating to a vehicle driving simulation, the first feature amount being linked to a first text generated on the basis of simulation data; an actual data acquisition means that acquires a second feature amount which is information relating to actual driving of the vehicle; an identification means that identifies, from the database, the first feature amount in the simulation data relating to actual data, on the basis of the second feature amount; and an analysis means that analyzes the actual data on the basis of the first text linked to the identified first feature amount.

The invention discloses a steering limiting device of a driving simulator, a steering gear box and a steering limiting method, and belongs to the technical field of driving simulation. The steering limiting device of the driving simulator comprises a steering shaft, and a calibration magnet is fixedly arranged at the center of the lower end face of the steering shaft; the bearing is sleeved and fixed on the steering shaft; the limiting disc sleeves and is fixed on the steering shaft, and a left limiting part and a right limiting part are arranged on the limiting disc; the supporting cover is fixed to the lower end of the bearing, the limiting disc is located in the supporting cover, and a probe hole and a limiting hole are formed in the supporting cover; the angle sensor is fixed on the supporting cover and corresponds to the position of the detection hole; and the telescopic limiting mechanism is fixed to the supporting cover, the telescopic end of the telescopic limiting mechanism can extend to penetrate through the limiting hole to be in limiting fit with the left limiting part or the right limiting part, and the angle sensor is electrically connected with the telescopic limiting mechanism. Compared with an existing steering limiting device, the overall size of the steering limiting device is greatly reduced, and the space occupied by the steering limiting device in a steering gear box is remarkably reduced.

The invention provides a method and a system for predicting uncertainty of driver perception time in an insufficient trust scene, and relates to the technical field of intelligent transportation, and the method comprises the steps: constructing a driving simulation scene library, executing a main task and a secondary task, collecting the insufficient trust level and the task load of a driver under the task takeover failure, and obtaining a driving simulation scene database; carrying out trust-load relation calculation by combining the trust base line and the corresponding load base line; and establishing a load-attention distribution relationship, calculating to obtain perception time based on the trust-load relationship, and outputting a comprehensive evaluation report according to the perception time. According to the method and the device, the technical problems of insufficient quantitative prediction of driver perception time, unexplainable model and incapability of outputting uncertain distribution in a scene with insufficient trust in the prior art can be solved; the technical effects of improving the driver perception efficiency evaluation accuracy, enhancing the risk response capability description comprehensiveness and improving the man-machine co-driving safety guarantee level are achieved.

Provided is a traffic simulation for controlling a motion of an object, such as a vehicle, a pedestrian moving on a road or a pavement, in a driving simulation, an autonomous driving simulation, or the like. A traffic simulation method according to an embodiment of the present disclosure includes the steps of: importing a new moving object into a simulation environment of a simulator; retrieving data of a moving path and a start point of the moving object which is created based on a function, among pre-stored data; calculating 3D coordinates regarding a position of the moving object; moving the moving object along the moving path in the simulation environment, based on the calculated 3D coordinates; and calculating a next position of the moving object.

The invention provides a 3D SR simulation system based on a vehicle-mounted SOME / IP, computer equipment and a method, and relates to the technical field of driving simulation. A data configuration module, a data generation module, a data analysis module and a 3D SR simulation module are constructed. The data configuration module is used for defining a specific vehicle type data specification, and configuring an SOME / IP data structure when a development project demand is changed; the data generation module instantiates an operation object corresponding to the data specification into a structured program object, and generates an SOME / IP binary data stream; and the data analysis module performs deserialization and analysis on the SOME / IP binary data stream according to a specific vehicle model data specification, generates simulation data conforming to the SOME / IP protocol specification, inputs the simulation data to the 3D SR simulation module for scene simulation test, and migrates a real vehicle test environment to a laboratory, so that dependence on a real vehicle road test is avoided, the development period is shortened, and the development test efficiency is improved.

The invention discloses an automatic driving scene multi-view video generation method and system based on space-time consistency constraint. According to the method, in a diffusion model generation process, three attention mechanisms are integrated: based on cross-view-angle deformable cross attention of a camera pose, geometric consistency among different view angles is realized; on the basis of cross-frame cross attention of optical flow prior, motion coherence between adjacent frames is ensured; and on the basis of the global time sequence consistency constraint of cross attention, the reasonability of long sequence generation is ensured. According to the method, the problems of geometric distortion and time sequence breakage in multi-view video generation are effectively solved, high-quality dynamic scene videos with consistent time and space can be generated, and efficient data support is provided for automatic driving simulation.

Techniques are described herein for converting driving logs to driving simulations and for analysis and improvement of said conversion. A driving log relating to a driving scenario may be received and a feature may be determined. A driving simulation of the driving simulation may be generated based on the driving log, and a value may be determined that indicates an ability of a system generating the simulation to represent the feature. The value may be stored. The driving simulation may also be stored.

To provide a driving simulation system that can accurately reproduce driving conditions. [Solution] The driving reproduction device 10, as a driving reproduction system, is equipped with at least one processing unit, a CPU 10a, and reproduces the driver's driving in the vehicle 1. The CPU 10a performs the following: acquires driving characteristic data of driving scenes in which predetermined characteristics appear in the driver's driving, and reproduces the driver's driving by autonomous driving control of the vehicle, in a manner in which adjustments have been made based on the driving characteristic data so that the predetermined characteristics can be properly perceived by the driver who performed the driving.

The invention belongs to the technical field of automatic driving simulation, discloses a human-driven vehicle lane changing behavior simulation model, method and system, and aims to solve the problems that'pseudo-interaction 'interference exists in human-driven vehicle lane changing modeling, global'latest lane changing point' pressure conflicts with local vehicle dynamic response, and a traditional model is low in nonlinear heterogeneous behavior description precision. An LA-Transform lane changing behavior simulation model is designed, and the LA-Transform lane changing behavior simulation model is constructed through a collaborative architecture network of input embedding and feature preprocessing optimization, short-time dynamic feature extraction and integration of a long and short-term memory network, sparse optimization of a self-adaptive sparse attention mechanism and encoder-decoder global integration. The method is specially used for high-precision simulation of the lane changing behavior of people driving vehicles in the confluence area. Data used for model training are all from a CitySim public data set Freeway C scene, and experimental verification shows that the model can generate a track conforming to real driver lane changing characteristics.

This application discloses a torque distribution method, a torque distribution device, and a vehicle, belonging to the field of vehicle technology. The torque distribution method includes: acquiring the vehicle's current total required torque and current vehicle speed; based on the current total required torque and current vehicle speed, searching in a torque distribution ratio mapping relationship to obtain the vehicle's target torque distribution ratio; and, if it is determined that the vehicle's allowable driving power consumption is less than a target power consumption threshold, distributing torque to the vehicle according to the target torque distribution ratio; wherein, the torque distribution ratio mapping relationship is used to characterize the correspondence between total required torque, vehicle speed, and a first torque distribution ratio, the first torque distribution ratio being obtained through driving simulation based on the vehicle's total required torque and vehicle speed, resulting in the torque distribution ratio that minimizes the vehicle's total drive loss. This method can achieve more economical torque distribution, effectively reduce the vehicle's system energy consumption, and help increase driving range.