CN114492022A - Road condition sensing data processing method, device, equipment, program and storage medium - Google Patents
Road condition sensing data processing method, device, equipment, program and storage medium Download PDFInfo
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- CN114492022A CN114492022A CN202210081361.8A CN202210081361A CN114492022A CN 114492022 A CN114492022 A CN 114492022A CN 202210081361 A CN202210081361 A CN 202210081361A CN 114492022 A CN114492022 A CN 114492022A
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- G16Y40/00—IoT characterised by the purpose of the information processing
- G16Y40/60—Positioning; Navigation
Abstract
The invention provides a road condition sensing data processing method, a road condition sensing data processing device, electronic equipment and a storage medium, wherein the method comprises the following steps: carrying out data cleaning processing on the original road condition sensing data through the cloud server to obtain target road condition sensing data; sending the target road condition sensing data to a road test communication unit through the cloud server; the road test communication unit sends the target road condition sensing data to a vehicle end communication unit; the vehicle-end communication unit converts the target road condition sensing data into target road condition twinning data and sends the target road condition twinning data to the automatic driving simulation engine, so that different automatic driving algorithms can be detected by the automatic driving simulation engine through the target road condition twinning data, a traffic simulation scene is more consistent with an actual road scene, and meanwhile, the simulation effect can be effectively improved through the road condition twinning data, and the real-time performance of the traffic simulation scene is higher.
Description
Technical Field
The present invention relates to data simulation, and in particular, to a method and an apparatus for processing road condition sensing data, an electronic device, a computer program product, and a storage medium.
Background
With the development of computer technology and traffic technology, traffic simulation is becoming an important tool in traffic engineering and other related fields. The traffic simulation refers to the study of traffic behaviors by using simulation technology, and is a technology for monitoring and describing the change of traffic motion along with time and space.
In the related art, the driving process of the vehicle under the set path can be simulated by using simulation software, but various influence factors are likely to occur in actual travel, so that the vehicle cannot finish a normal travel according to the set path, for example, a traffic accident occurs on the set path, a part of road sections on the set path are closed, and the like, so that the accuracy rate is low during traffic simulation, and the detection of an automatic driving algorithm in a traffic simulation state is not facilitated.
Disclosure of Invention
In view of this, embodiments of the present invention provide a road condition sensing data processing method, apparatus, electronic device, computer program product, and storage medium, which can convert target road condition sensing data into target road condition twin data and send the target road condition twin data to an automatic driving simulation engine, so that different automatic driving algorithms can be detected by the automatic driving simulation engine through the target road condition twin data, and thus, the construction sources of simulation scene contents are enriched, so that a traffic simulation scene is more consistent with an actual road scene, and meanwhile, a simulation effect can be effectively improved through the road condition twin data, so that the real-time performance of the traffic simulation scene is stronger.
The technical scheme of the embodiment of the invention is realized as follows:
the embodiment of the invention provides a road condition sensing data processing method, which comprises the following steps:
acquiring original road condition sensing data and sending the original road condition sensing data to a cloud server;
carrying out data cleaning processing on the original road condition sensing data through the cloud server to obtain target road condition sensing data;
sending the target road condition sensing data to a road test communication unit through the cloud server;
when the vehicle-end communication unit enters the communication range of the road test communication unit, the road test communication unit sends the target road condition sensing data to the vehicle-end communication unit;
and the vehicle-end communication unit converts the target road condition sensing data into target road condition twinning data and sends the target road condition twinning data to an automatic driving simulation engine so as to realize detection of different automatic driving algorithms through the automatic driving simulation engine through the target road condition twinning data.
The embodiment of the present invention further provides a traffic sensing data processing device, where the traffic sensing data processing device includes:
in the above scheme, the information processing module is configured to obtain a division standard of a target road, and determine road segment information matched with a drive test sensor based on the division standard of the target road;
the information processing module is used for monitoring the conditions in the corresponding road sections by the road test sensor according to the road section information to obtain the original road condition sensing data;
and the information processing module is used for sending the original road condition sensing data to different subjects of a message queue of the cloud server by the road test sensor according to the road section information.
In the above scheme, the information processing module is configured to perform data deduplication processing on the original road condition sensing data, and delete duplicate road condition sensing data and illegal road condition sensing data in the original road condition sensing data;
the information processing module is used for determining a noise threshold value matched with the original road condition sensing data;
and based on the noise threshold, carrying out noise cleaning processing on the original road condition sensing data to obtain the target road condition sensing data.
In the above scheme, the information processing module is configured to process the target road condition sensing data through a road condition event recognition algorithm to obtain first target road condition sensing data matched with a target road condition event;
the information processing module is used for sending the first target road condition sensing data to a simulation scene database so as to store the first target road condition sensing data matched with the target road condition event;
and the information processing module is used for calling the first target road condition sensing data through the simulation scene database when the target road condition event is detected by triggering an automatic driving algorithm.
In the above scheme, the information processing module is configured to extract a vehicle flow direction in a road segment from the target road condition sensing data;
the information processing module is used for triggering a vehicle driving direction detection algorithm and detecting the vehicle flow direction and the driving direction of a target vehicle in the road section;
the information processing module is used for determining that the target road condition event is a reverse driving event when the fact that the vehicle flow direction is inconsistent with the driving direction of the target vehicle in the road section is detected;
and the information processing module is used for recording the first target road condition sensing data matched with the reverse driving event.
In the above scheme, the information processing module is configured to obtain a road condition event recognition algorithm uploaded by a target object;
the information processing module is used for determining a traffic participation object matched with the target road condition twin data, wherein the traffic participation object comprises at least one of the following items: automotive, non-automotive, and pedestrian;
the information processing module is used for determining road information matched with the target road condition twin data and roadside signboard information;
the information processing module is used for processing the target road condition sensing data by using the road information, the road side signboard information and the traffic participant through the road condition event recognition algorithm, and determining that the target road condition event is a traffic regulation violation event;
and the information processing module is used for recording the second target road condition sensing data matched with the traffic regulation violation event.
In the above scheme, the information processing module is configured to determine a data format corresponding to the automatic driving simulation engine;
the information processing module is used for converting the target road condition sensing data into target road condition twinning data by the vehicle-end communication unit based on the data format;
the information processing module is used for sending the target road condition twin data to a target automatic driving simulation engine;
and the information processing module is used for storing the identification information of the target automatic driving simulation engine in a cloud server.
In the above scheme, the information processing module is configured to create a virtual driving environment according to the target road condition twin data and the test scene information, and acquire a target simulated vehicle in the virtual driving environment;
the information processing module is used for carrying out running prediction on the target simulated vehicle at the simulated vehicle position through the automatic driving model at the simulated vehicle position on the simulated running track to obtain predicted running data, wherein the predicted running data has running control authority aiming at the target simulated vehicle so as to change the running track of the target simulated vehicle.
In the above solution, the information processing module is configured to trigger a location service process matched with the target object identifier;
the information processing module is used for determining the position detection information of the target object by carrying out position detection processing on the target road condition twin data through the position service process;
the information processing module is used for recording the position detection information and converting the position detection information into a data format matched with the position service process to form the position service information;
the information processing module is used for acquiring timestamp information corresponding to the position service information and constructing a geographic position real-time database in the virtual driving environment by using the position service information and the timestamp information.
In the above scheme, the information processing module is configured to obtain, in the virtual driving environment, map data matched with positioning information of a target simulated vehicle through a geographic position real-time database;
the information processing module is used for carrying out data analysis processing on the map data to obtain road parameters corresponding to the vehicle;
wherein the road parameter corresponding to the vehicle is at least one of the following:
the number of lanes of the position of the target simulation vehicle, the road attribute information of the position of the target simulation vehicle and the road monitoring information of the position of the target simulation vehicle;
and the information processing module is used for displaying the road parameters in the navigation information presented in the map client and presenting the road parameters to different target objects in the virtual driving environment through the instant messaging client.
In the above scheme, the information processing module is configured to obtain real-time location information of the target simulation vehicle when corresponding navigation information is presented in the map client;
the information processing module is used for sending the real-time position information of the target simulation vehicle to a cloud server network and recording a traveling route matched with the target simulation vehicle through the cloud server network;
the information processing module is used for carrying out real-time position pushing on the instant messaging client sides carried by different target simulation vehicles through the cloud server network so as to realize that the different target simulation vehicles obtain the real-time position information of the corresponding target simulation vehicles through the instant messaging client sides.
An embodiment of the present invention further provides an electronic device, where the electronic device includes:
a memory for storing executable instructions;
and the processor is used for realizing the preorder road condition sensing data processing method when the executable instructions stored in the memory are operated.
The embodiment of the invention also provides a computer-readable storage medium, which stores executable instructions, and is characterized in that the executable instructions are executed by the processor to realize the preorder road condition sensing data processing method.
The embodiment of the invention has the following beneficial effects:
according to the technical scheme provided by the invention, the original road condition sensing data is obtained and sent to the cloud server; carrying out data cleaning processing on the original road condition sensing data through the cloud server to obtain target road condition sensing data; sending the target road condition sensing data to a road test communication unit through the cloud server; when the vehicle-end communication unit enters the communication range of the road test communication unit, the road test communication unit sends the target road condition sensing data to the vehicle-end communication unit; the vehicle-end communication unit converts the target road condition sensing data into target road condition twinning data and sends the target road condition twinning data to the automatic driving simulation engine, so that different automatic driving algorithms can be detected through the target road condition twinning data by the automatic driving simulation engine, the construction sources of simulation scene contents are enriched, a traffic simulation scene is more consistent with an actual road scene, meanwhile, the simulation effect can be effectively improved through the road condition twinning data, and the real-time performance of the traffic simulation scene is higher.
Drawings
Fig. 1 is a schematic view of a use environment for processing road condition sensing data according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of an electronic device according to an embodiment of the present invention;
fig. 3 is a schematic view of an optional flow of the road condition sensing data processing method according to the embodiment of the present invention;
fig. 4 is a schematic view of an optional flow of the road condition sensing data processing method according to the embodiment of the present invention;
fig. 5 is a schematic view of an optional flow of the road condition sensing data processing method according to the embodiment of the present invention;
fig. 6 is a schematic view of an optional flow of the road condition sensing data processing method according to the embodiment of the present invention;
FIG. 7 is a schematic diagram illustrating a twin target road condition data configuration process according to an embodiment of the present invention;
FIG. 8 is a schematic diagram illustrating a twin target road condition data configuration process according to an embodiment of the present invention;
FIG. 9 is a schematic diagram of a simulation effect of twin data of the target road condition according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail with reference to the accompanying drawings, the described embodiments should not be construed as limiting the present invention, and all other embodiments obtained by a person of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.
In the following description, reference is made to "some embodiments" which describe a subset of all possible embodiments, but it is understood that "some embodiments" may be the same subset or different subsets of all possible embodiments, and may be combined with each other without conflict.
Before further detailed description of the embodiments of the present invention, terms and expressions mentioned in the embodiments of the present invention are explained, and the terms and expressions mentioned in the embodiments of the present invention are applied to the following explanations.
1) In response to the condition or state on which the performed operation depends, one or more of the performed operations may be in real-time or may have a set delay when the dependent condition or state is satisfied; there is no restriction on the order of execution of the operations performed unless otherwise specified.
2) And position sharing, wherein each conversation member entering the position sharing function can observe respective position information on a map in real time.
3) Digital twinning: the technology is a general term for mapping physical states in the real world into the virtual world through devices such as sensors, and for feeding back and influencing corresponding entities in the real world through some interactive operations in the virtual world.
4) Open loop simulation: the output of the tested algorithm of the main vehicle in the simulation scene does not influence the behavior of the main vehicle in the scene, only the output state (such as different planning tracks and the like) sent by the test algorithm can be seen, the method is generally used for replaying the drive test data, and the behaviors of the obstacle vehicle and the main vehicle are consistent with those in the replay data.
5) Closed loop simulation: the output of the tested algorithm (planned trajectory, etc.) in the simulation scene may affect the positioning of the tested subject in the scene in real time, and surrounding obstacles may interact based on the behavior of the tested subject, such as evasion, overtaking, etc.
6) An Intelligent Transportation System, also known as Intelligent Transportation System, is a comprehensive Transportation System that effectively and comprehensively applies advanced scientific technologies (information technology, computer technology, data communication technology, sensor technology, electronic control technology, automatic control theory, operational research, artificial intelligence, etc.) to Transportation, service control and vehicle manufacturing, and strengthens the connection among vehicles, roads and users, thereby ensuring safety, improving efficiency, improving environment and saving energy.
7) An intelligent vehicle-road cooperative system, which is called a vehicle-road cooperative system for short, is a development direction of an Intelligent Transportation System (ITS). The vehicle-road cooperative system adopts the advanced wireless communication, new generation internet and other technologies, implements vehicle-vehicle and vehicle-road dynamic real-time information interaction in all directions, develops vehicle active safety control and road cooperative management on the basis of full-time dynamic traffic information acquisition and fusion, fully realizes effective cooperation of human and vehicle roads, ensures traffic safety, improves traffic efficiency, and thus forms a safe, efficient and environment-friendly road traffic system.
8) Traffic Simulation (Traffic Simulation): the traffic simulation refers to the study of traffic behaviors by using simulation technology, and is a technology for monitoring and describing the change of traffic motion along with time and space. It contains stochastic properties, can be microscopic or macroscopic, and involves mathematical models that describe the real-time motion of the transportation system over a period of time. According to the difference of the traffic simulation model in description degree of the research object, the traffic simulation model can be divided into microscopic simulation, mesoscopic simulation and macroscopic simulation, wherein the microscopic simulation has the highest detail description degree on elements and behaviors of a traffic system, for example, the traffic simulation model describes the traffic flow by taking a single vehicle as a basic unit, and the microscopic behaviors of the vehicle such as car following, overtaking, lane change and the like on a road can be truly reflected; for example, the description of the traffic flow by the mesoscopic traffic simulation model is often a queue formed by a plurality of vehicles, can describe the inflow and outflow behaviors of the queue at road sections and nodes, and can also approximately describe behaviors of vehicles such as lane change in a simple manner; for example, traffic flow can be described by some concentrated macroscopic models of flow, speed, density relation, etc., but not by detailed behaviors of road conditions events while vehicles are driving.
9) A Mini Program (Program) is a Program developed based on a front-end-oriented Language (e.g., JavaScript) and implementing a service in a hypertext Markup Language (HTML) page, and software downloaded by a client (e.g., a browser or any client embedded in a browser core) via a network (e.g., the internet) and interpreted and executed in a browser environment of the client saves steps installed in the client. For example, the small program in the terminal is awakened through a voice instruction, so that the small program for realizing various services such as air ticket purchase, task processing and making, data display and the like can be downloaded and run in the social network client. By the small program of the vehicle-mounted terminal, the running state information of the target simulation vehicle can be displayed in the virtual running environment, and the navigation information of the target simulation vehicle can also be displayed, so that the use experience which is completely the same as that of the real driving environment is obtained.
Before introducing the road condition sensing data processing method provided by the application, firstly, a process of generating simulation information by using road data is introduced in the related technology, the traditional automatic driving simulation software can provide a virtual test scene for an algorithm operated on an automatic driving automobile, the performance of each index of the algorithm operation is evaluated by operating the algorithm in a test environment similar to that of an actual road and generating detailed index evaluation, and a simulation engine provides a high-precision map, a manually set or AI intelligent traffic flow vehicle, a 3D rendering picture based on physical vehicle dynamics and photo-level image quality, an algorithm scheduling and communication system similar to that of an actual vehicle and the like in the virtual environment, so that a virtual test environment as real as possible is provided for the automatic driving algorithm.
However, the sources of the simulation scenes are only 2, 1), the simulation scenes are artificially set for each barrier (vehicle, person and the like) appearing in the scenes in a scene editor, wherein the behavior of the AI-based traffic flow vehicle is generally controlled by a parameter-based vehicle behavior algorithm obtained by offline machine learning and other algorithms on roadside traffic conditions acquired from a specific area and a specific time period, and the method has the disadvantages that the traffic flow algorithm can only be used for restoring the behavior of real vehicles as much as possible, the scene library is rich in dependence on the function of a scene editing tool and the skill and proficiency of scene editing personnel, and the efficiency of scene construction is low; 2) the method has the defects that recorded data cannot interact with a detected algorithm in the scene in real time, so that the behavior of the detected algorithm is inconsistent with the behavior of a main vehicle during the drive test at that time, the scene possibly fails, the recorded data are generally used for open-loop simulation, and meanwhile, the collection of the drive test data seriously depends on the number of the automatic drive test vehicles, the efficiency is low, and the collection of large-scale data is not facilitated.
In order to solve the problems, the application provides a road condition sensing data processing method which can convert target road condition sensing data into target road condition twinning data and send the target road condition twinning data to an automatic driving simulation engine, so that different automatic driving algorithms can be detected by the automatic driving simulation engine through the target road condition twinning data, the construction sources of simulation scene contents are enriched, a traffic simulation scene is more consistent with an actual road scene, meanwhile, the simulation effect can be effectively improved through the road condition twinning data, and the real-time performance of the traffic simulation scene is stronger.
Fig. 1 is a schematic view of a usage scenario of the road condition sensing data processing method according to an embodiment of the present invention, referring to fig. 1, a road test sensor 10-1 performs data acquisition, a vehicle-mounted terminal 10-2 is provided with a client capable of performing a road condition sensing data processing function, and the client may be installed in a vehicle-mounted communication unit (optionally, other terminals, such as a mobile phone or a vehicle-mounted navigation device), where the terminal may be an intelligent device such as a mobile phone or a vehicle-mounted intelligent system. The road condition sensing data processing method provided by the invention can serve clients (packaged in a vehicle-mounted terminal or different mobile electronic devices) with available types as cloud services, and the specific use scene is not specifically limited in the application, wherein the road condition sensing data processing method is provided for enterprise clients as the cloud services to help the enterprise clients to test algorithms of different automatic driving simulation engines.
In some embodiments of the present invention, the drive test unit RSU may perform data broadcasting; the road side sensor mainly comprises a high-definition camera, a laser radar and a millimeter wave radar. The high-definition camera can detect the positions and the speeds of vehicles and pedestrians in a visual angle range in real time, and count the real-time traffic flow of a road surface and the like; the millimeter wave radar can acquire information such as the type, position and speed of a vehicle, the position and speed of a pedestrian and the like; the laser radar can be used for detecting the congestion queuing state of vehicles, the positions and the types of the vehicles, wrong driving directions, visibility (fog), people, animals and the like. The raw data obtained by the sensors are sent to an edge calculation unit for data fusion. After acquiring the original road condition sensing data, sending the original road condition sensing data to a cloud server; carrying out data cleaning processing on the original road condition sensing data through the cloud server to obtain target road condition sensing data; sending the target road condition sensing data to a road test communication unit through the cloud server; when the vehicle-end communication unit enters the communication range of the road test communication unit, the road test communication unit sends the target road condition sensing data to the vehicle-end communication unit; the vehicle-end communication unit converts the target road condition sensing data into target road condition twinning data and sends the target road condition twinning data to the automatic driving simulation engine, so that different automatic driving algorithms are detected by the automatic driving simulation engine through the target road condition twinning data, a traffic simulation scene is more consistent with an actual road scene, and meanwhile, the simulation effect can be effectively improved through the road condition twinning data, and the real-time performance of the traffic simulation scene is higher.
As will be described in detail below, the road condition sensing data processing device according to the embodiment of the present invention may be implemented in various forms, such as a dedicated terminal with image processing and data calculating functions, or an internet of vehicles device with image processing and data processing functions, for example, the road condition sensing data processing device in fig. 1. Fig. 2 is a schematic structural diagram of the road condition sensing data processing device according to an embodiment of the present invention, and it can be understood that fig. 2 only shows an exemplary structure of the road condition sensing data processing device, and not a whole structure, and a part of the structure or the whole structure shown in fig. 2 may be implemented as required.
The road condition sensing data processing device provided by the embodiment of the invention comprises: at least one processor 201, memory 202, user interface 203, and at least one network interface 204. The various components of the traffic sensing data processing device are coupled together by a bus system 205. It will be appreciated that the bus system 205 is used to enable communications among the components of the connection. The bus system 205 includes a power bus, a control bus, and a status signal bus in addition to a data bus. For clarity of illustration, however, the various buses are labeled as bus system 205 in fig. 2.
The user interface 203 may include, among other things, a display, a keyboard, a mouse, a trackball, a click wheel, a key, a button, a touch pad, or a touch screen.
It will be appreciated that the memory 202 can be either volatile memory or nonvolatile memory, and can include both volatile and nonvolatile memory. The memory 202 in embodiments of the present invention is capable of storing data to support operation of the terminal (e.g., 10-1). Examples of such data include: any computer program, such as an operating system and application programs, for operating on a terminal (e.g., 10-1). The operating system includes various system programs, such as a framework layer, a core library layer, a driver layer, and the like, and is used for implementing various basic services and processing hardware-based tasks. The application program may include various application programs.
In some embodiments, the traffic sensing data processing device provided in the embodiments of the present invention may be implemented by a combination of software and hardware, and for example, the traffic sensing data processing device provided in the embodiments of the present invention may be a processor in the form of a hardware decoding processor, which is programmed to execute the traffic sensing data processing method provided in the embodiments of the present invention. For example, a processor in the form of a hardware decoding processor may employ one or more Application Specific Integrated Circuits (ASICs), DSPs, Programmable Logic Devices (PLDs), Complex Programmable Logic Devices (CPLDs), Field Programmable Gate Arrays (FPGAs), or other electronic components.
As an example that the road condition sensing data processing device provided by the embodiment of the present invention is implemented by combining software and hardware, the road condition sensing data processing device provided by the embodiment of the present invention may be directly embodied as a combination of software modules executed by the processor 201, the software modules may be located in a storage medium, the storage medium is located in the memory 202, the processor 201 reads executable instructions included in the software modules in the memory 202, and the road condition sensing data processing method provided by the embodiment of the present invention is completed by combining necessary hardware (for example, including the processor 201 and other components connected to the bus 205).
By way of example, the Processor 201 may be an integrated circuit chip having Signal processing capabilities, such as a general purpose Processor, a Digital Signal Processor (DSP), or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or the like, wherein the general purpose Processor may be a microprocessor or any conventional Processor, or the like.
As an example of the road condition sensing data processing apparatus provided in the embodiment of the present invention implemented by hardware, the apparatus provided in the embodiment of the present invention may be implemented by directly using the processor 201 in the form of a hardware decoding processor, for example, the apparatus may be implemented by one or more Application Specific Integrated Circuits (ASICs), DSPs, Programmable Logic Devices (PLDs), Complex Programmable Logic Devices (CPLDs), Field Programmable Gate Arrays (FPGAs), or other electronic components to implement the road condition sensing data processing method provided in the embodiment of the present invention.
The memory 202 in the embodiment of the present invention is used for storing various types of data to support the operation of the traffic sensing data processing device. Examples of such data include: any executable instructions for operating on the traffic sensing data processing device, such as executable instructions, may be included in the program for implementing the method for processing traffic sensing data according to the embodiment of the present invention.
In other embodiments, the traffic sensing data processing device provided in the embodiments of the present invention may be implemented in a software manner, and fig. 2 shows the traffic sensing data processing device 2020 stored in the memory 202, which may be software in the form of a program, a plug-in, and the like, and includes a series of modules, and as an example of the program stored in the memory 202, the traffic sensing data processing device 2020 may include the following software modules: an information transmission module 2081 and an information processing module 2082. When the software modules in the road condition sensing data processing device 2020 are read into the RAM by the processor 201 and executed, the functions of the software modules in the road condition sensing data processing device 2020 are described as follows:
the information transmission module 2081 is configured to acquire original road condition sensing data and send the original road condition sensing data to a cloud server.
The information processing module 2082 is configured to perform data cleaning processing on the original road condition sensing data through the cloud server to obtain target road condition sensing data.
The information processing module 2082 is configured to send the target road condition sensing data to a road test communication unit through the cloud server.
The information processing module 2082 is configured to, when the vehicle-end communication unit enters the communication range of the drive test communication unit, send the target road condition sensing data to the vehicle-end communication unit by the drive test communication unit.
The information processing module 2082 is configured to convert the target road condition sensing data into target road condition twin data by the vehicle-end communication unit, and send the target road condition twin data to an automatic driving simulation engine, so as to implement detection of different automatic driving algorithms by the automatic driving simulation engine through the target road condition twin data.
According to the electronic device shown in fig. 2, in one aspect of the present application, the present application further provides a computer program product or a computer program comprising computer instructions stored in a computer readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes different embodiments and combinations of embodiments provided in various alternative implementations of the road condition sensing data processing method.
Continuing to explain the road condition sensing data processing method provided by the embodiment of the present invention with reference to the road condition sensing data processing device shown in fig. 2, fig. 3 is an optional schematic flow diagram of the road condition sensing data processing method provided by the embodiment of the present invention, and it can be understood that the road condition sensing data processing method shown in fig. 3 can be applied to a traffic simulation system for detecting different automatic driving simulation engines or different automatic driving algorithms through twin target road conditions, wherein the steps shown in fig. 3 can be executed by the road condition sensing data processing system, and the road condition sensing data processing system includes: the system comprises a cloud server, a vehicle-end communication unit and a drive test communication unit. The following is a description of the steps shown in fig. 3.
Step 301: the road condition sensing data processing device acquires original road condition sensing data and sends the original road condition sensing data to the cloud server.
In some embodiments of the present invention, the obtaining of the original traffic sensing data and the sending of the original traffic sensing data to the cloud server may be implemented in the following manner:
acquiring a division standard of a target road, and determining road section information matched with a drive test sensor based on the division standard of the target road; the road test sensor monitors the conditions in the corresponding road section according to the road section information to obtain the original road condition sensing data; and the road test sensor sends the original road condition sensing data to different subjects of a message queue of the cloud server according to the road section information. The road side measuring sensor can detect various traffic participant information (such as pedestrian states, non-motor vehicle states, road states, passing vehicle states, traffic flow and the like) at the intersection, and can also acquire other road side units and management center cloud platform data. When the used cloud server is an edge cloud server (or a server cluster), the road test sensor monitors the conditions in the corresponding road section according to the road section information, the original road condition sensing data is obtained and then can be transmitted to the edge cloud server, and the real-time state of the current intersection is obtained after algorithm processing and fusion processing are carried out through the edge cloud server. The states comprise pedestrian collision risks, vehicle collision risks, traffic jam conditions, road dangers (accumulated water, icing and pothole pavements), traffic signal lamp states and the like, and therefore real-time monitoring of road condition sensing data in corresponding road sections is achieved.
Step 302: and the road condition sensing data processing device carries out data cleaning processing on the original road condition sensing data through the cloud server to obtain target road condition sensing data.
Referring to fig. 4, fig. 4 is a schematic view of an optional flow chart of the road condition sensing data processing method according to the embodiment of the present invention, which specifically includes the following steps:
step 401: and the road condition sensing data processing device performs data deduplication processing on the original road condition sensing data and deletes repeated road condition sensing data and illegal road condition sensing data in the original road condition sensing data.
Each RSU information is a real-time dynamically updated data table, and the sensing data in the road section is monitored, so that repeated and illegal road condition sensing data can be collected, and the data processing pressure of the cloud server can be reduced by deleting the repeated road condition sensing data and the illegal road condition sensing data in the original road condition sensing data, so that the processing speed of the road condition sensing data is higher.
Step 402: the road condition sensing data processing device determines a noise threshold value matched with the original road condition sensing data.
Step 403: and the road condition sensing data processing device carries out noise cleaning processing on the original road condition sensing data based on the noise threshold value to obtain the target road condition sensing data.
The original road condition sensing data collected by the road test sensor is subjected to data cleaning processing in the cloud server to obtain target road condition sensing data, and therefore the road test unit can only transmit the target road condition sensing data when communicating with the vehicle-end communication unit, the defect that data processing is slow in the prior art due to the fact that the road test unit is used for processing the road condition sensing data is avoided.
Step 303: and the road condition sensing data processing device sends the target road condition sensing data to a road test communication unit through the cloud server.
Step 304: and when the vehicle-end communication unit enters the communication range of the road test communication unit, the road test communication unit sends the target road condition sensing data to the vehicle-end communication unit.
Step 305: the vehicle-end communication unit of the road condition sensing data processing device converts the target road condition sensing data into target road condition twinning data and sends the target road condition twinning data to the automatic driving simulation engine, so that different automatic driving algorithms can be detected by the automatic driving simulation engine through the target road condition twinning data.
In some embodiments of the present invention, the vehicle-end communication unit converts the target traffic sensing data into target traffic twin data, and sends the target traffic twin data to the automatic driving simulation engine, which may be implemented in the following manner:
determining a data format corresponding to the automatic driving simulation engine; the vehicle-end communication unit converts the target road condition sensing data into target road condition twin data based on the data format; sending the target road condition twin data to a target automatic driving simulation engine; and storing the identification information of the target automatic driving simulation engine in a cloud server. Therefore, the cloud server can record basic information of the target road condition twin data acquired by the automatic driving simulation engine, charges an operator of the automatic driving simulation engine according to the data volume and the data duration of the transmitted target road condition twin data, and meanwhile, the provided target road condition twin data can adapt to different types of automatic driving simulation engines so as to achieve the effect of expanding the adaptation range of the target road condition twin data.
In some embodiments of the present invention, referring to fig. 5, fig. 5 is a schematic flow chart of an alternative traffic sensing data processing method provided in the embodiments of the present invention, which specifically includes the following steps:
step 501: and the road condition sensing data processing device processes the target road condition sensing data through a road condition event recognition algorithm to obtain first target road condition sensing data matched with the target road condition event.
In some embodiments of the present invention, the target traffic sensing data is processed by a traffic event recognition algorithm to obtain a first target traffic sensing data matched with a target traffic event, and the method can be implemented as follows:
extracting the vehicle flow direction in the road section from the target road condition sensing data; triggering a vehicle driving direction detection algorithm, and detecting the vehicle flow direction and the driving direction of a target vehicle in the road section; when the fact that the vehicle flow direction is inconsistent with the driving direction of the target vehicle in the road section is detected, determining that the target road condition event is a reverse driving event; and recording the first target road condition sensing data matched with the reverse driving event. When the vehicle flow direction and the lane passing condition are detected, the vehicle flow direction of the target lane is east-west, and the vehicle flow direction of the adjacent lane corresponding to the target lane is west-east, so that the vehicle flow directions of the two lanes are opposite lanes, and whether the reverse driving occurs can be detected by detecting the consistency of the vehicle flow direction and the driving direction of the target vehicle in the road section.
Step 502: and the road condition sensing data processing device sends the first target road condition sensing data to a simulation scene database so as to store the first target road condition sensing data matched with the target road condition event.
Step 503: and when the road condition sensing data processing device triggers an automatic driving algorithm to detect the target road condition event, calling the first target road condition sensing data through the simulation scene database.
In some embodiments of the present invention, the traffic condition event recognition algorithm uploaded by the user can be tested by the traffic condition sensing data processing method provided by the present application, specifically, the target traffic twin data provided by the present application can test any type of traffic condition event recognition algorithm to obtain the traffic condition event recognition algorithm uploaded by the target object; determining traffic participation objects matched with the target traffic twin data, wherein the traffic participation objects comprise at least one of the following: automotive, non-automotive, and pedestrian; determining road information and roadside signboard information which are matched with the target road condition twin data; processing the target road condition twin data by the road information, the road side signboard information and the traffic participating object through the road condition event recognition algorithm, and determining that the target road condition event is a traffic regulation violation event; and recording second target road condition sensing data matched with the traffic regulation violation event. Therefore, after the target road condition twin data is processed and the target road condition event is determined to be a traffic regulation violation event, second target road condition sensing data matched with the traffic regulation violation event is recorded, and the second target road condition sensing data can be sent to the cloud server to be stored so as to be called again in more scenes and generate a virtual driving environment for testing.
In some embodiments of the present invention, a specific algorithm uploaded by a target object determines whether a current road condition sends a road condition event with a simulation value, and the specific identification algorithm supports loading of determination rule index configurations suitable for different areas, such as different criteria for line pressing, overspeed, low speed, and the like, and finally, after the specific road condition event occurs, a corresponding tag can be printed and a scene conversion service is asynchronously triggered, and data of a period of time before the occurrence time of the current event is converted into a scene format that can be identified by a simulation system and stored in a simulation scene database, wherein the specific identification algorithm in this embodiment is an independent module and supports different users to upload their own identification algorithms, and only needs to access through a specified programming interface API. For example, one possible implementation flow is as follows:
1. loading a corresponding rule configuration file according to configuration and initializing when the identification algorithm is started; 2. loading high-precision map data of the relevant area; 3. continuously receiving preprocessed real-time traffic road condition data through an interface, wherein the preprocessed real-time traffic road condition data comprises recognized traffic participants such as vehicles, pedestrians and bicycles, intersection traffic light signals and the like, and calculating whether each vehicle violates rules configured in a rule configuration file, such as line pressing, overspeed and the like, by combining road information (lane lines and road signs), roadside signboard information and the like stored in high-precision map data; 4. and if the event of the traffic participant violating the configuration rule is found, asynchronously calling a scene conversion service through an interface, transmitting a timestamp, parameters related to a vehicle ID, an event label and the like, and generating corresponding simulation scene data.
In some embodiments of the invention, a virtual driving environment may be created according to the target road condition twin data and the test scenario information, and a target simulated vehicle may be acquired in the virtual driving environment; and at the position of the simulated vehicle on the simulated driving track, performing driving prediction on the target simulated vehicle at the position of the simulated vehicle through the automatic driving model to obtain predicted driving data, wherein the predicted driving data has driving control authority aiming at the target simulated vehicle so as to change the driving track of the target simulated vehicle. Further, when creating a virtual driving environment according to the target road condition twin data and the test scenario information, various types of virtual roads may be created using the target road condition twin data, for example: the virtual road type is an intersection type, and an intersection road belonging to the intersection type can be created. After the target virtual road is created, virtual vehicles (including a tested target simulation vehicle and a non-tested obstacle vehicle) can be created in the target virtual road, pedestrians can be created, vehicle behavior parameters can be created for the non-tested obstacle vehicle (for example, the vehicle behavior parameters of the obstacle vehicle are predicted and planned through a certain automatic driving model, and the obstacle vehicle is controlled to autonomously run in a virtual running environment); meanwhile, pedestrian behavior parameters may also be set for the pedestrian (e.g., by setting a target object behavior parameter (e.g., a walking direction, a walking speed, etc.) for the obstacle target object, so that the obstacle target object may autonomously walk in the virtual driving environment using the preset invariant target object behavior parameter).
In some embodiments of the present invention, in a real driving environment, the vehicle-mounted terminal may navigate through a small program of the instant messaging client and provide a location service process to meet the use requirements of different users, so that the same service may be provided when performing traffic simulation through the target road condition twin data, and specifically, the location service process matching the target object identifier may be triggered; through the position service process, position detection processing is carried out on the twin data of the target road condition, and position detection information of the target object is determined; recording the position detection information, and converting the position detection information into a data format matched with the position service process to form the position service information; obtaining timestamp information corresponding to the location service information, and constructing a geographic location real-time database in the virtual driving environment by using the location service information and the timestamp information. Therefore, when traffic simulation is carried out through the target road condition twin data, the target object can obtain the use experience which is completely the same as that in actual driving.
In order to better explain the processing process of the road condition sensing data processing method provided by the present application, the following describes the use environment of the road condition sensing data processing method provided by the present application by taking twin data of a target road condition as an example, and referring to the use scenario diagram of fig. 1, the road condition sensing data processing method provided by the present invention can serve clients (packaged in a vehicle-mounted terminal or packaged in different mobile electronic devices) in a cloud service form, and the present application is not particularly limited in a specific use scenario, wherein the present application is provided as a cloud service to enterprise clients to help the enterprise clients to detect different automatic driving algorithms.
In some embodiments of the present invention, referring to fig. 6, fig. 6 is a schematic flow chart of an optional method for processing road condition sensing data according to an embodiment of the present invention, which specifically includes the following steps:
step 601: and acquiring original road condition sensing data, and sending the original road condition sensing data to a cloud server.
Step 602: and carrying out data cleaning processing on the original road condition sensing data through the cloud server to obtain target road condition sensing data.
Step 603: and sending the target road condition sensing data to a road test communication unit through the cloud server.
Step 604: the road test communication unit sends the target road condition sensing data to a vehicle end communication unit;
step 605: and the vehicle-end communication unit converts the target road condition sensing data into target road condition twin data and sends the target road condition twin data to an automatic driving simulation engine.
Referring to fig. 7, fig. 7 is a schematic diagram of a target road condition twin data configuration process in an embodiment of the present invention, wherein a traffic simulation system may configure corresponding twin data access modules according to different conditions of simulation requirements, and in addition, corresponding detection units may need to be configured when detecting states of pedestrian collision risk, vehicle collision risk, traffic congestion condition, road hazard (ponding, icing, pothole pavement), and traffic signal lights, for example, using corresponding communication hardware as a basis under specific road side conditions.
Referring to fig. 8, fig. 8 is a schematic diagram of a configuration process of twin target road conditions data in an embodiment of the present invention, where the ditw _ data _ port module may be configured to convert real-time twin target road conditions data into an obstacle message format that can be identified in a simulation system, so as to provide for Planning and calculation by an autonomous driving host vehicle algorithm Planning, and the ditw _ data _ port module replaces an AI-based traffic flow algorithm module in a simulation scene in the related art, and reflects real traffic conditions of a current road side in real time.
Step 606: the automatic driving simulation engine constructs a traffic simulation environment based on the target road condition twin data and tests an automatic driving algorithm.
Referring to fig. 9, fig. 9 is a schematic diagram of a simulation effect of target road condition twin data in the embodiment of the present invention, where traffic simulation may be performed on traveling vehicles in a simulated road network based on the target road condition twin data, the target vehicles may travel in the simulated road network according to the target road condition twin data, based on dynamic traveling influences between the target vehicles and historical vehicles, the traveling vehicles in the simulated road network may travel to corresponding destinations steadily, and the target road condition twin data may be obtained based on traveling processes of the traveling vehicles in the simulated road network. The target road condition twin data can be used for rendering and displaying, so that the real-time simulated traffic road condition can be displayed in a visual mode. The urban traffic manager can make traffic decision, control and plan based on the visual simulated traffic road condition. For example, when a road congestion is found, a traffic guidance screen is set on a congested road section and the traffic guidance screen is increased. The traffic control measures are used for relieving road congestion, and drivers can test different types of automatic driving algorithms through simulated traffic road conditions of the target road condition twin data.
The invention has the following beneficial technical effects:
the method comprises the steps of acquiring original road condition sensing data and sending the original road condition sensing data to a cloud server; performing data cleaning processing on the original road condition sensing data through the cloud server to obtain target road condition sensing data; sending the target road condition sensing data to a road test communication unit through the cloud server; when the vehicle-end communication unit enters the communication range of the road test communication unit, the road test communication unit sends the target road condition sensing data to the vehicle-end communication unit; the vehicle-end communication unit converts the target road condition sensing data into target road condition twinning data and sends the target road condition twinning data to the automatic driving simulation engine, so that different automatic driving algorithms can be detected through the target road condition twinning data by the automatic driving simulation engine, the construction sources of simulation scene contents are enriched, a traffic simulation scene is more consistent with an actual road scene, meanwhile, the simulation effect can be effectively improved through the road condition twinning data, and the real-time performance of the traffic simulation scene is higher.
The above description is intended to be illustrative only, and should not be taken as limiting the scope of the invention, which is intended to include all such modifications, equivalents, and improvements as fall within the true spirit and scope of the invention.
Claims (15)
1. A road condition sensing data processing method is characterized by comprising the following steps:
acquiring original road condition sensing data and sending the original road condition sensing data to a cloud server;
carrying out data cleaning processing on the original road condition sensing data through the cloud server to obtain target road condition sensing data;
sending the target road condition sensing data to a road test communication unit through the cloud server;
when the vehicle-end communication unit enters the communication range of the road test communication unit, the road test communication unit sends the target road condition sensing data to the vehicle-end communication unit;
and the vehicle-end communication unit converts the target road condition sensing data into target road condition twinning data and sends the target road condition twinning data to an automatic driving simulation engine so as to realize detection of different automatic driving algorithms through the automatic driving simulation engine through the target road condition twinning data.
2. The method according to claim 1, wherein the obtaining the raw traffic sensing data and sending the raw traffic sensing data to a cloud server comprises:
acquiring a division standard of a target road, and determining road section information matched with a drive test sensor based on the division standard of the target road;
the road test sensor monitors the conditions in the corresponding road section according to the road section information to obtain the original road condition sensing data;
and the road test sensor sends the original road condition sensing data to different subjects of a message queue of the cloud server according to the road section information.
3. The method according to claim 1, wherein the obtaining of the target road condition sensing data by performing data cleaning processing on the original road condition sensing data through the cloud server comprises:
carrying out data duplication elimination processing on the original road condition sensing data, and deleting repeated road condition sensing data and illegal road condition sensing data in the original road condition sensing data;
determining a noise threshold value matched with the original road condition sensing data;
and based on the noise threshold, carrying out noise cleaning processing on the original road condition sensing data to obtain the target road condition sensing data.
4. The method of claim 1, further comprising:
processing the target road condition sensing data through a road condition event recognition algorithm to obtain first target road condition sensing data matched with the target road condition event;
sending the first target road condition sensing data to a simulation scene database to store the first target road condition sensing data matched with the target road condition event;
and when the automatic driving algorithm is triggered to detect the target road condition event, calling the first target road condition sensing data through the simulation scene database.
5. The method as claimed in claim 4, wherein the processing the target traffic sensing data by the traffic event recognition algorithm to obtain a first target traffic sensing data matched with the target traffic event comprises:
extracting the vehicle flow direction in the road section from the target road condition sensing data;
triggering a vehicle driving direction detection algorithm, and detecting the vehicle flow direction and the driving direction of a target vehicle in the road section;
when the fact that the vehicle flow direction is inconsistent with the driving direction of the target vehicle in the road section is detected, determining that the target road condition event is a reverse driving event;
and recording the first target road condition sensing data matched with the reverse driving event.
6. The method of claim 4, further comprising:
acquiring a road condition event recognition algorithm uploaded by a target object;
determining traffic participation objects matched with the target traffic twin data, wherein the traffic participation objects comprise at least one of the following: automotive, non-automotive, and pedestrian;
determining road information and roadside signboard information which are matched with the target road condition twin data;
processing the target traffic twin data by the road information, the roadside signboard information and the traffic participation object through the traffic event recognition algorithm, and determining that the target traffic event is a traffic regulation violation event;
and recording second target road condition sensing data matched with the traffic regulation violation event.
7. The method as claimed in claim 1, wherein the vehicle-end communication unit converts the target traffic sensing data into target traffic twin data and transmits the target traffic twin data to an automatic driving simulation engine, comprising:
determining a data format corresponding to the automatic driving simulation engine;
the vehicle-end communication unit converts the target road condition sensing data into target road condition twin data based on the data format;
sending the target road condition twin data to a target automatic driving simulation engine;
and storing the identification information of the target automatic driving simulation engine in a cloud server.
8. The method of claim 1, further comprising:
creating a virtual driving environment according to the target road condition twin data and the test scene information, and acquiring a target simulation vehicle in the virtual driving environment;
and at the position of the simulated vehicle on the simulated driving track, performing driving prediction on the target simulated vehicle at the position of the simulated vehicle through the automatic driving model to obtain predicted driving data, wherein the predicted driving data has driving control authority aiming at the target simulated vehicle so as to change the driving track of the target simulated vehicle.
9. The method of claim 8, wherein the method comprises:
triggering a position service process matched with the target object identification;
determining the position detection information of the target object by carrying out position detection processing on the target road condition twin data through the position service process;
recording the position detection information, and converting the position detection information into a data format matched with the position service process to form the position service information;
obtaining timestamp information corresponding to the location service information, and constructing a geographic location real-time database in the virtual driving environment by using the location service information and the timestamp information.
10. The method of claim 8, wherein the method comprises:
in the virtual driving environment, map data matched with the positioning information of the target simulation vehicle is obtained through a geographic position real-time database;
carrying out data analysis processing on the map data to obtain road parameters corresponding to the vehicle;
wherein the road parameter corresponding to the vehicle is at least one of the following:
the number of lanes of the position of the target simulation vehicle, the road attribute information of the position of the target simulation vehicle and the road monitoring information of the position of the target simulation vehicle;
and displaying the road parameters in navigation information presented in a map client, and presenting the road parameters to different target objects in the virtual driving environment through an instant messaging client.
11. The method of claim 10, further comprising:
when the corresponding navigation information is presented in the map client, acquiring real-time position information of the target simulation vehicle;
sending the real-time position information of the target simulation vehicle to a cloud server network, and recording a traveling route matched with the target simulation vehicle through the cloud server network;
and carrying out real-time position pushing on the instant messaging client sides carried by different target simulation vehicles through the cloud server network so as to realize that the different target simulation vehicles obtain the real-time position information of the corresponding target simulation vehicles through the instant messaging client sides.
12. A road condition sensing data processing device, characterized in that, the road condition sensing data processing device includes:
the information transmission module is used for acquiring original road condition sensing data and sending the original road condition sensing data to the cloud server;
the information processing module is used for carrying out data cleaning processing on the original road condition sensing data through the cloud server to obtain target road condition sensing data;
the information processing module is used for sending the target road condition sensing data to a road test communication unit through the cloud server;
the information processing module is used for sending the target road condition sensing data to the vehicle-end communication unit by the road test communication unit when the vehicle-end communication unit enters the communication range of the road test communication unit;
the information processing module is used for converting the target road condition sensing data into target road condition twin data by the vehicle-end communication unit and sending the target road condition twin data to the automatic driving simulation engine so as to realize detection of different automatic driving algorithms through the target road condition twin data by the automatic driving simulation engine.
13. A computer program product comprising a computer program or instructions, wherein the computer program or instructions, when executed by a processor, implement the road condition sensing data processing method according to any one of claims 1 to 11.
14. An electronic device, characterized in that the electronic device comprises:
a memory for storing executable instructions;
a processor, configured to execute the executable instructions stored in the memory, and implement the road condition sensing data processing method according to any one of claims 1 to 11.
15. A computer-readable storage medium storing executable instructions, wherein the executable instructions when executed by a processor implement the road condition sensing data processing method according to any one of claims 1 to 11.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115391477A (en) * | 2022-10-31 | 2022-11-25 | 智道网联科技(北京)有限公司 | Data processing method and device, electronic equipment and storage medium |
| CN115862183A (en) * | 2023-02-28 | 2023-03-28 | 禾多科技（北京）有限公司 | Sensor characteristic engineering information construction method, device, equipment and computer medium |
| WO2024051387A1 (en) * | 2022-09-06 | 2024-03-14 | 腾讯科技（深圳）有限公司 | Data processing method and apparatus, device and computer-readable storage medium |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2024051387A1 (en) * | 2022-09-06 | 2024-03-14 | 腾讯科技（深圳）有限公司 | Data processing method and apparatus, device and computer-readable storage medium |
| CN115391477A (en) * | 2022-10-31 | 2022-11-25 | 智道网联科技(北京)有限公司 | Data processing method and device, electronic equipment and storage medium |
| CN115862183A (en) * | 2023-02-28 | 2023-03-28 | 禾多科技（北京）有限公司 | Sensor characteristic engineering information construction method, device, equipment and computer medium |
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