CN111563313A - Driving event simulation reproduction method, system, equipment and storage medium - Google Patents
Driving event simulation reproduction method, system, equipment and storage medium Download PDFInfo
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Abstract
The invention relates to a driving event simulation reproduction method, a system, equipment and a storage medium, wherein the driving event simulation reproduction method comprises the following steps: acquiring a driving event data set and vehicle parameters; preprocessing the acquired driving event data set, and constructing a vehicle dynamics model according to vehicle parameters; the method comprises the steps of obtaining driving environment information, classifying the driving environment information, and extracting a plurality of driving event characteristic scenes; constructing a driving simulation virtual environment, and establishing a driving simulation scene based on the extracted driving event characteristic scene; and sending the driving simulation scene and the vehicle dynamics model to a driving simulation system so that the driving simulation system simulates and reproduces the driving environment of the vehicle in the driving process, and after acquiring the simulated driving behavior data of the target vehicle, the driving simulation system acquires the motion feedback of the target vehicle based on the driving environment and displays the motion feedback visually, so that the on-site road traffic environment of the traffic accident is reproduced completely, and the highly customized driving simulation scene development is realized.
Description
Technical Field
The present invention relates to the field of driving simulation technology and traffic incident (accident) reproduction technology, and more particularly, to a driving incident simulation reproduction method, system, device, and storage medium.
Background
1. The first related art is as follows: and (3) driving simulation technology.
The driving simulation technology is proved to be applicable to research on traffic safety and vehicle safety as a virtual reality technology, and compared with the related technology based on the real road traffic environment, such as natural driving behavior research and the like, the driving simulation technology can ensure the safety of the research environment, can carry out repeated research on a specific traffic scene, and has better economy.
The existing technical defects are as follows: firstly, the model is generally not developed on the basis of traffic accidents or driving dangerous events occurring in the real traffic environment, and the model construction from the characteristic research of multi-sample traffic accidents or driving dangerous events to a typical dangerous driving simulation scene cannot be realized; secondly, most of driving simulators with the function of customizing the complete vehicle level dynamic model are car dynamic model simulators, the functions of simulating the dynamics of the truck are not provided, and the simulation of the influence of the liquid shaking in the tank body on the motion characteristics of the truck in the driving process of the tank truck can not be realized.
The second related art is: simulation technique for accident reproduction
The simulation software for accident reproduction (such as pc-crash) mainly utilizes the data collected in accident field to make accident vehicle reversely push the whole collision process from the end position after collision so as to make accident cause analysis, such as collision speed analysis and collision angle analysis, etc.
The third related technology: vehicle dynamics simulation technology
Vehicle dynamics simulation software (such as carsim, truck, etc.) can realize vehicle dynamics simulation at the whole vehicle level, but the vehicle dynamics simulation software can only perform simple road traffic environment modeling, and cannot perform highly customized driving simulation scene development based on the real road traffic environment.
Disclosure of Invention
In order to solve the technical problems, the invention aims to provide a driving event simulation reproduction method, a system, equipment and a storage medium, wherein dangerous driving events and typical characteristics thereof occurring in the driving process of a vehicle are extracted as a driving event data set on the basis of vehicle driving data collected in the real road traffic environment, then clustering analysis is carried out through driving environment information, and a driving simulation scene is established; meanwhile, a vehicle dynamics model is built according to vehicle parameters, particularly for a tank truck, a tractor and a trailer, when the vehicle dynamics model is built, the characteristics of displacement of the mass center of the vehicle, longitudinal impact force, lateral shaking and the like caused by shaking of liquid in a tank body in the driving process of a non-full-load tank truck are extracted, and the tank truck dynamics model is built through vehicle dynamics simulation software; and respectively importing the driving simulation scene of the constructed typical dangerous driving scene and the tank truck dynamic model into a driving simulation visual scene environment generation system and a vehicle dynamic simulation system of the driving simulation system, and establishing a dangerous scene simulation and reproduction system which is based on a driving simulation technology, real road traffic environment vehicle driving data and has the typical vehicle dynamic characteristics of the tank truck.
According to one aspect of the present invention, there is provided a driving event simulation reproducing method, comprising the steps of:
acquiring a driving event data set and vehicle parameters;
preprocessing the acquired driving event data set, and constructing a tank truck vehicle dynamic model according to vehicle parameters;
the method comprises the steps of obtaining driving environment information, classifying the driving environment information, and extracting a plurality of driving event characteristic scenes;
constructing a driving simulation virtual environment, and establishing a driving simulation scene based on the extracted driving event characteristic scene;
and sending the driving simulation scene and the vehicle dynamics model to a driving simulation system so that the driving simulation system can simulate and reproduce the driving environment in the driving process of the vehicle, and after acquiring the simulated driving behavior data of the target vehicle, the driving simulation system acquires the motion feedback of the target vehicle based on the driving environment and displays the motion feedback in a visualized manner.
Further, the driving event data set includes, but is not limited to, the following data: text data, and video image data inside and outside the target vehicle before and after the occurrence time of the driving event;
and/or
The vehicle parameters include: the external dimension, the specific power, the rated power, the preparation quality, the rated load quality, the front suspension/the rear suspension, the axle load, the axle distance, the tire specification, the engine model, the engine discharge capacity, the tank body transportation medium type, the tank body cabin number, the external dimension of the tank car and the interface shape of the tank body;
and/or
The driving environment information comprises time, weather and objects when a driving event occurs, speed, longitudinal acceleration and transverse acceleration of a target vehicle and a related vehicle in the period of the occurrence of the driving event and corresponding driving behavior data of a driver;
and/or
The vehicle dynamics model achieves a motion characteristic of the vehicle.
Further, the obtained driving event data set is preprocessed, and the preprocessing comprises the following steps:
classifying video image data and text data in the driving event data set;
visually displaying the video image data so that a worker can add an image label to the video image data through an editing window;
and converting the text data into a recognizable data format and matching the data with corresponding video image data.
Further, the image tag comprises time, weather, road environment, relative position of the target vehicle and the associated vehicle and motion characteristics of the associated vehicle when the event occurs;
the text data includes a traveling speed, a longitudinal acceleration, a lateral acceleration, and a driving behavior data of the corresponding driver during the period of occurrence of the traveling event of the target vehicle.
Further, the method comprises the step of enabling the vehicle dynamic model to reach the motion characteristic of the vehicle through calibration.
According to another aspect of the present invention, there is provided a driving event simulation reproducing system including:
the data acquisition module is configured for acquiring a driving event data set and vehicle parameters;
the data preprocessing module is configured for preprocessing the acquired driving event data set;
the vehicle dynamics model modeling module is configured for constructing a tank truck vehicle dynamics model according to vehicle parameters;
the event characteristic extraction module is configured for acquiring driving environment information, classifying the driving environment information and extracting a plurality of driving event characteristic scenes;
the driving simulation scene modeling module is configured for constructing a driving simulation virtual environment and establishing a driving simulation scene based on the extracted driving event characteristic scene;
and the driving simulation scene reproduction module is configured to send the driving simulation scene and the vehicle dynamics model to the driving simulation system, so that the driving simulation system can acquire the simulated driving behavior data of the target vehicle, simulate and reproduce the driving environment in the driving process of the vehicle, and acquire the motion feedback of the target vehicle based on the driving environment and visually display the motion feedback.
Further, the data preprocessing module comprises:
the data classification unit is configured for classifying the video image data and the text data in the driving event data set;
the data editing window unit is configured for visually displaying the video image data so that a worker can add an image tag to the video image data through an editing window, wherein the image tag comprises time, weather, road environment, relative positions of a target vehicle and an associated vehicle and motion characteristics of the associated vehicle when a driving event occurs;
and the data re-extraction unit is configured for converting the text data into a recognizable data format and matching the data with the corresponding video image data, wherein the text data comprises the running speed, the longitudinal acceleration and the transverse acceleration of the target vehicle and the corresponding driving behavior data of the driver in the running event occurrence period.
Further, the vehicle dynamics model modeling module is also configured to enable the vehicle dynamics model to reach the motion characteristic of the vehicle through calibration.
According to another aspect of the present invention, there is provided an apparatus comprising:
one or more processors;
a memory for storing one or more programs,
the one or more programs, when executed by the one or more processors, cause the one or more processors to perform the method of any of the above.
According to another aspect of the invention, there is provided a computer readable storage medium storing a computer program which, when executed by a processor, implements a method as defined in any one of the above.
Compared with the prior art, the invention has the following beneficial effects:
1. the driving event simulation reproduction method disclosed by the invention is used for establishing a driving simulation scene on the basis of a vehicle driving event data set acquired in a real road traffic environment, and completing model construction of multi-sample traffic accidents or driving dangerous events by combining construction of a vehicle dynamics model and realization of the vehicle dynamics model in a driving simulation system, so that complete reproduction of a field road traffic environment where a traffic accident occurs is realized, and highly customized driving simulation scene development is realized.
2. The driving event simulation and reproduction system disclosed by the invention is simple in composition, a driving simulation scene is established on the basis of a vehicle driving event data set acquired in a real road traffic environment through mutual cooperation of various composition modules and units, the model construction of characteristics of a multi-sample traffic accident or driving danger event is completed by combining the construction of a vehicle dynamics model and the realization of the vehicle dynamics model in the driving simulation system, the complete reproduction of a field road traffic environment in which the traffic accident occurs is realized, and the development of a highly customized driving simulation scene is realized.
3. The device and the computer readable storage medium storing the computer program of the embodiment of the invention establish a driving simulation scene based on a vehicle driving event data set collected in a real road traffic environment, and complete the model construction of multi-sample traffic accidents or driving danger event characteristics by combining the construction of a vehicle dynamics model and the realization of the vehicle dynamics model in a driving simulation system, thereby realizing the complete reproduction of the field road traffic environment of the traffic accidents and realizing the development of a highly customized driving simulation scene.
Drawings
FIG. 1 is a flowchart of a driving event simulation reproducing method according to an embodiment;
FIG. 2 is a reference diagram of an integrally packaged driving event data set;
FIG. 3 is one of the reference graphs of the decoded driving event data set;
FIG. 4 is a second reference map of the decoded driving event data set;
FIG. 5 is a third reference image of the decoded driving event data set;
FIG. 6 is one of the schematic diagrams of an image tag;
FIG. 7 is a second schematic diagram of an image tag;
FIG. 8 is a diagram illustrating the result of encoding video image data;
FIG. 9 is a schematic diagram of text data extraction;
FIG. 10 is a diagram illustrating the result of matching text data with image encoding result data; (ii) a
FIG. 11 is a schematic diagram of selecting a clustering index and normalizing;
FIG. 12 is a second schematic diagram of selecting a clustering index and performing normalization;
FIG. 13 is a third schematic diagram of selecting clustering indexes and normalizing;
FIG. 14 is a schematic diagram of a clustering result of rear-end driving events;
FIG. 15 is a diagram illustrating a statistical characterization of clustering indicators;
FIG. 16 is a second schematic diagram of statistical characteristics of clustering indexes;
FIG. 17 is a third schematic diagram of statistical characteristics of clustering indexes;
FIG. 18 is a schematic diagram of clustering results;
FIG. 19 is one of schematic diagrams of constructing a driving simulation virtual environment;
FIG. 20 is a second schematic view of a virtual environment for driving simulation;
FIG. 21 is a third schematic view of a virtual environment for constructing a driving simulation;
FIG. 22 is a schematic view of a driving simulation scene;
FIG. 23 is a second schematic view illustrating a driving simulation driving scenario;
FIG. 24 is a third schematic view of a driving scene for constructing a driving simulation;
FIG. 25 is a fourth schematic view illustrating a driving simulation driving scene;
FIG. 26 is one of driving simulation driving scenarios;
FIG. 27 is a second driving simulation scenario;
FIG. 28 is a third driving simulation scenario;
FIG. 29 is one of another driving simulation driving scenario;
FIG. 30 is a second driving simulation driving scenario;
FIG. 31 is a third driving simulation scenario;
FIG. 32 is one of schematic diagrams of a vehicle dynamics model construction;
FIG. 33 is a second schematic diagram of a vehicle dynamics model;
FIG. 34 is a third schematic diagram of a vehicle dynamics model.
Detailed Description
In order to better understand the technical scheme of the invention, the invention is further explained by combining the specific embodiment and the attached drawings of the specification.
The first embodiment is as follows:
the embodiment provides a driving event simulation reproduction method, as shown in fig. 1, including the following steps:
and S1, acquiring the driving event data set and the vehicle parameters.
The driving event data set includes, but is not limited to, the following data: text data, and video image data inside and outside the target vehicle before and after the occurrence time of the driving event;
the text data comprises the running speed, the longitudinal acceleration and the transverse acceleration of the target vehicle and corresponding driving behavior data of the driver in the running event occurrence period; as shown in fig. 2, the data sample is the whole encapsulated data output by the data acquisition device; the data samples shown in fig. 3-5 are decoded data output by the data acquisition device, and the data shown in fig. 3-5 is more friendly than the data shown in fig. 2, and requires less data extraction work.
The vehicle parameters include: the external dimension, the specific power, the rated power, the preparation quality, the rated load quality, the front suspension/the rear suspension, the axle load, the axle distance, the tire specification, the engine model, the engine discharge capacity, the tank body transportation medium type, the tank body cabin number, the external dimension of the tank car and the interface shape of the tank body;
s2, preprocessing the acquired driving event data set, and constructing a vehicle dynamics model according to vehicle parameters; the method specifically comprises the following steps:
s2-1, classifying the video image data and the text data in the driving event data set;
s2-2, visually displaying the video image data to enable a worker to add image labels to the video image data through the editing window, wherein the image labels comprise time when a driving event occurs, weather, road environment, relative positions of a target vehicle and an associated vehicle, and motion characteristics (such as acceleration, deceleration and lane change) of the associated vehicle; as shown in fig. 6-7, alternatively, a data encoding table of image tags may be made for increasing efficiency, and the video image data encoding result is shown in fig. 8;
s2-3, converting the text data into a recognizable data format and matching the data format with the corresponding video image data, continuously extracting the text data, wherein the extraction result is shown in figure 9, and the matching result is shown in figure 10, and is matched with the corresponding video image data coding result shown in figure 8.
S2-4, according to vehicle parameters and motion characteristics of a vehicle, constructing a vehicle dynamics model by using a Trucksim whole vehicle dynamics software, and if necessary, enabling the vehicle dynamics model to reach the motion characteristics of the vehicle through calibration, and when modeling a tractor, a trailer or a tank truck, constructing the whole vehicle dynamics model by using the Trucksim whole vehicle dynamics simulation modeling software according to the acquired data of the tractor and the trailer and the characteristics of mass center displacement, longitudinal impact force, lateral shaking and the like of the vehicle caused by the shaking of liquid in a tank body (as shown in figures 32-34); compared with a common trailer, the tank truck has poorer side-tipping stability, and the dynamic Trucksim model of the tank truck can be calibrated by using a double-shift-line simulation working condition and combining the acquired driving event data set or the real vehicle test data.
S3, acquiring driving environment information, classifying the driving environment information, and extracting a plurality of driving event characteristic scenes; taking rear-end driving events as an example, in the classification of driving environment information, firstly, a clustering index is selected according to the type of the driving events and is subjected to standardization processing (fig. 11-13 are the clustering index selected by the rear-end driving events and the standardization processing), then, the Euclidean distance of the standardized value of each event data clustering index is calculated, each driving event is clustered by adopting the shortest distance method (fig. 14 is a schematic diagram of the clustering result of the rear-end driving events, the clustering result is roughly divided into 10 types (see the table head of fig. 15) after clustering, the 1 st type contains 974 data, the 2 nd type contains 56 data, the 3 rd type contains 31 data, the 4 th-10 th type has less data, and 16 types in total, therefore, when the classification statistics is carried out (fig. 15-17), the classification statistics results of the 4 th-10 types are combined, the effective data finally used for constructing the driving simulation scene are the 1 st type, the 2 nd type and the 3 rd type. ) (ii) a And finally, carrying out classified statistics on the driving events according to the clustering result, calculating the statistical characteristics of the driving events in each category on each clustering index (as shown in fig. 15-17), and displaying that the average speed of the target vehicle is 39.9km/h in fig. 18, which is a characteristic scene of the rear-end driving event of the 1 st category obtained according to the clustering result (in the figure, a red vehicle is a target vehicle, and a blue vehicle is a related vehicle).
S4, constructing a driving simulation virtual environment, and establishing a driving simulation scene based on the extracted driving event characteristic scene, wherein the driving environment information comprises time, weather and objects when the driving event occurs, speed, longitudinal acceleration and transverse acceleration of the target vehicle and the associated vehicle in the driving event occurrence time period and corresponding driving behavior data of the driver; in particular, the method comprises the following steps of,
and constructing a driving simulation virtual environment by using UC-winRoad software, and establishing a driving simulation scene based on the extracted driving event characteristic scene. In the modeling of the driving simulation scene, firstly, UC-winRoad software is used for constructing a driving simulation virtual environment (as shown in figures 19 to 21), and then the driving simulation scene is constructed according to the statistical characteristics of the driving events obtained by clustering. For example: obtaining a cluster analysis result of rear-end driving events according to the graphs of 15-17, wherein the statistical characteristics of the 1 st type rear-end driving event actually comprise two types of driving scenes, one type is the rear-end driving event on a road section, the associated vehicle is positioned right in front of the vehicle, the driving speed is about 40km/h, and the vehicle is suddenly braked; the second type is a rear-end driving event at an intersection. Therefore, the two types of driving simulation driving scenes are respectively constructed for the type 1 rear-end driving event (as shown in fig. 22 to 25), and the finally obtained type 1 rear-end driving event section driving simulation driving scene and the intersection driving simulation driving scene are shown in fig. 26-28 and fig. 29-31 (the reasons for the occurrence of the driving event are all sudden braking of the front vehicle).
And S5, sending the driving simulation scene and the vehicle dynamics model to a driving simulation system, so that the driving simulation system can obtain the simulated driving behavior data of the target vehicle, simulate and reproduce the driving environment in the driving process of the vehicle, and obtain the motion feedback of the target vehicle based on the driving environment and visually display the motion feedback, wherein the driving simulation system has a vehicle dynamics self-defining function.
The method comprises the steps of establishing a driving simulation scene based on a vehicle driving event data set collected in a real road traffic environment, completing model construction of multi-sample traffic accidents or driving dangerous events by combining construction of a vehicle dynamics model and realization of the vehicle dynamics model in a driving simulation system, realizing complete reproduction of a site road traffic environment of traffic accidents, and realizing development of a highly customized driving simulation scene.
The present embodiment provides a driving event simulation and reproduction system for any of the above driving event simulation and reproduction methods, including:
the data acquisition module is configured for acquiring a driving event data set and vehicle parameters; the driving event data set includes, but is not limited to, the following data: video image data and text data inside and outside the target vehicle before and after the occurrence moment of the driving event; the vehicle parameters include: the external dimension, the specific power, the rated power, the preparation quality, the rated load quality, the front suspension/the rear suspension, the axle load, the axle distance, the tire specification, the engine model, the engine discharge capacity, the tank body transportation medium type, the tank body cabin number, the external dimension of the tank car and the interface shape of the tank body;
the data preprocessing module is configured to preprocess the acquired driving event data set, and comprises:
the data classification unit is configured for classifying the video image data and the text data in the driving event data set;
the data editing window unit is configured for visually displaying the video image data so that a worker can add an image tag to the video image data through an editing window, wherein the image tag comprises time, weather, road environment, relative positions of a target vehicle and an associated vehicle and motion characteristics of the associated vehicle when an event occurs;
and the data re-extraction unit is configured for converting the text data into a recognizable data format and matching the data with the corresponding video image data, wherein the text data comprises the running speed, the longitudinal acceleration and the transverse acceleration of the target vehicle and the corresponding driving behavior data of the driver in the running event occurrence period.
And the vehicle dynamics model modeling module is configured for constructing a tank truck vehicle dynamics model according to vehicle parameters, and enabling the vehicle dynamics model to reach the motion characteristics of the vehicle through calibration when necessary.
The event characteristic extraction module is configured for acquiring driving environment information, classifying the driving environment information and extracting a plurality of driving event characteristic scenes; the driving environment information comprises time, weather and object when a driving event occurs, speed, longitudinal acceleration and transverse acceleration of the target vehicle and the associated vehicle in the period of the occurrence of the driving event and corresponding driving behavior data of the driver
The driving simulation scene modeling module is configured for constructing a driving simulation virtual environment and establishing a driving simulation scene based on the extracted driving event characteristic scene;
the driving simulation system is provided with a motion platform, a motion platform controller and a driving simulation cabin, the motion platform controller is respectively connected with a driving simulation system server and the motion platform and controls the motion platform to vibrate, and the driving simulation cabin is fixed on the motion platform.
It should be understood that the modules or units described in the driving event simulation reproduction system correspond to the steps described in the driving event simulation reproduction method. Thus, the operations and features described above for the method are also applicable to the subsystems of the driving event simulation and reproduction system and the units included therein, and are not described herein again.
As another aspect, the present embodiment also provides an apparatus adapted to implement the embodiments of the present application, the apparatus including a computer system including a Central Processing Unit (CPU) that can perform various appropriate actions and processes according to a corresponding program stored in a Read Only Memory (ROM) for executing the respective steps described in the above driving event simulation reproduction method or a corresponding program loaded from a storage section into a Random Access Memory (RAM) for executing the respective steps described in the above driving event simulation reproduction method. In the RAM, various programs and data necessary for system operation are also stored. The CPU, ROM, and RAM are connected to each other via a bus. An input/output (I/O) interface is also connected to the bus.
The following components are connected to the I/O interface: an input section including a keyboard, a mouse, and the like; an output section including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage section including a hard disk and the like; and a communication section including a network interface card such as a LAN card, a modem, or the like. The communication section performs communication processing via a network such as the internet. The drive is also connected to the I/O interface as needed. A removable medium such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive as necessary, so that a computer program read out therefrom is mounted into the storage section as necessary.
In particular, according to an embodiment of the present disclosure, the processes described by the respective steps described in the driving event simulation reproduction method described above may be implemented as a computer software program. For example, embodiments of the present disclosure include a computer program product comprising a computer program tangibly embodied on a machine-readable medium, the computer program comprising program code for performing the driving event simulation reproduction method described above. In such an embodiment, the computer program may be downloaded and installed from a network via the communication section, and/or installed from a removable medium.
The flowcharts in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the flowchart illustrations, and combinations of blocks in the flowchart illustrations, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or by combinations of special purpose hardware and computer instructions.
The units or modules described in the embodiments of the present application may be implemented by software or hardware. The described units or modules may also be provided in a processor. The names of these units or modules do not in some cases constitute a limitation of the unit or module itself.
As another aspect, the present embodiment also provides a computer-readable storage medium, which may be the computer-readable storage medium included in the system in the foregoing embodiment; or it may be a separate computer readable storage medium not incorporated into the device. The computer-readable storage medium stores one or more programs for use by one or more processors in executing the flowcharts of the driving event simulation reproduction method described in the present application.
The above description is only a preferred embodiment of the application and is illustrative of the principles of the technology employed. It will be appreciated by a person skilled in the art that the scope of the invention as referred to in the present application is not limited to the embodiments with a specific combination of the above-mentioned features, but also covers other embodiments with any combination of the above-mentioned features or their equivalents without departing from the inventive concept. For example, the features described above have similar functions to (but are not limited to) those disclosed in this application.
Claims (10)
1. A driving event simulation reproduction method is characterized by comprising the following steps:
acquiring a driving event data set and vehicle parameters;
preprocessing the acquired driving event data set, and constructing a vehicle dynamics model according to vehicle parameters;
the method comprises the steps of obtaining driving environment information, classifying the driving environment information, and extracting a plurality of driving event characteristic scenes;
constructing a driving simulation virtual environment, and establishing a driving simulation scene based on the extracted driving event characteristic scene;
and sending the driving simulation scene and the vehicle dynamics model to a driving simulation system so that the driving simulation system can simulate and reproduce the driving environment in the driving process of the vehicle, and after acquiring the simulated driving behavior data of the target vehicle, the driving simulation system acquires the motion feedback of the target vehicle based on the driving environment and displays the motion feedback in a visualized manner.
2. The driving event simulation reproduction method according to claim 1,
the driving event data set includes, but is not limited to, the following data: text data, and video image data inside and outside the target vehicle before and after the occurrence time of the driving event;
and/or
The vehicle parameters include: the external dimension, the specific power, the rated power, the preparation quality, the rated load quality, the front suspension/the rear suspension, the axle load, the axle distance, the tire specification, the engine model, the engine discharge capacity, the tank body transportation medium type, the tank body cabin number, the external dimension of the tank car and the interface shape of the tank body;
and/or
The driving environment information comprises time, weather and objects when a driving event occurs, speed, longitudinal acceleration and transverse acceleration of the target vehicle and the associated vehicle in the period of the occurrence of the driving event, and corresponding driving behavior data of the driver.
3. A driving event simulation reproduction method according to claim 1, wherein the preprocessing of the acquired driving event data set comprises:
classifying video image data and text data in the driving event data set;
visually displaying the video image data so that a worker can add an image label to the video image data through an editing window;
and converting the text data into a recognizable data format and matching the data with corresponding video image data.
4. A driving event simulation reproduction method according to claim 3, wherein the image tag includes time when the driving event occurs, weather, road environment, relative position of the target vehicle and the associated vehicle, and motion characteristics of the associated vehicle;
the text data includes a traveling speed, a longitudinal acceleration, a lateral acceleration, and a driving behavior data of the corresponding driver during the period of occurrence of the traveling event of the target vehicle.
5. The driving event simulation reproduction method according to claim 1, further comprising: and the vehicle dynamic model is calibrated to reach the motion characteristic of the vehicle.
6. A driving event simulation reproduction system, comprising:
the data acquisition module is configured for acquiring a driving event data set and vehicle parameters;
the data preprocessing module is configured for preprocessing the acquired driving event data set;
the vehicle dynamics model modeling module is configured for constructing a tank truck vehicle dynamics model according to vehicle parameters;
the event characteristic extraction module is configured for acquiring driving environment information, classifying the driving environment information and extracting a plurality of driving event characteristic scenes;
the driving simulation scene modeling module is configured for constructing a driving simulation virtual environment and establishing a driving simulation scene based on the extracted driving event characteristic scene;
and the driving simulation scene reproduction module is configured to send the driving simulation scene and the vehicle dynamics model to the driving simulation system so that the driving simulation system simulates and reproduces the driving environment of the vehicle in the driving process, and the driving simulation system acquires the motion feedback of the target vehicle based on the driving environment and visually displays the motion feedback after acquiring the simulated driving behavior data of the target vehicle.
7. A driving event simulation reproduction system according to claim 6, wherein the data preprocessing module comprises:
the data classification unit is configured for classifying the video image data and the text data in the driving event data set;
the data editing window unit is configured for visually displaying the video image data so that a worker can add an image tag to the video image data through an editing window, wherein the image tag comprises time, weather, road environment, relative positions of a target vehicle and an associated vehicle and motion characteristics of the associated vehicle when a driving event occurs;
and the data re-extraction unit is configured for converting the text data into a recognizable data format and matching the data with the corresponding video image data, wherein the text data comprises the running speed, the longitudinal acceleration and the transverse acceleration of the target vehicle and the corresponding driving behavior data of the driver in the running event occurrence period.
8. A driving event simulation reproduction system according to claim 6, wherein the vehicle dynamics model modelling module is further configured to arrive at the vehicle dynamics model by calibration at a vehicle motion characteristic.
9. An apparatus, characterized in that the apparatus comprises:
one or more processors;
a memory for storing one or more programs,
the one or more programs, when executed by the one or more processors, cause the one or more processors to perform the method recited in any of claims 1-5.
10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1-5.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN112560170A (en) * | 2020-11-30 | 2021-03-26 | 中国汽车工程研究院股份有限公司 | Traffic accident analysis method based on driving simulator dynamics analysis |
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