CN116734892B

CN116734892B - Method, device, equipment and medium for processing driving data

Info

Publication number: CN116734892B
Application number: CN202311025437.6A
Authority: CN
Inventors: 王友辰; 李欣; 刘畅
Original assignee: Tencent Technology Shenzhen Co Ltd
Current assignee: Tencent Technology Shenzhen Co Ltd
Priority date: 2023-08-15
Filing date: 2023-08-15
Publication date: 2023-11-03
Anticipated expiration: 2043-08-15
Also published as: CN116734892A

Abstract

The application discloses a processing method, a device, equipment and a medium of driving data, which can be applied to the map field and the automatic driving field, and the method of the application can comprise the following steps: acquiring a target path to be driven of a simulation object; the simulated object is provided with a corresponding navigation object, and the navigation object moves along with the running of the simulated object; acquiring a target running mode set for a simulation object, and driving the simulation object to run on a target path according to the target running mode; in the running process of the simulation object, generating simulation positioning information of a navigation object corresponding to the simulation object; the simulation positioning information is used for simulating a simulation test of navigating the simulation object by adopting the navigation object in the target driving mode. By adopting the application, the efficiency of acquiring the positioning information (such as the simulation positioning information) can be improved, and the cost of acquiring the positioning information can be reduced.

Description

Method, device, equipment and medium for processing driving data

Technical Field

The present application relates to the field of data processing technologies, and in particular, to a method, an apparatus, a device, and a medium for processing running data.

Background

During the running of a vehicle, it is often necessary to position the vehicle for navigation. Before the vehicle is positioned and navigated in the actual application scene, a large amount of positioning information of the vehicle in the driving process needs to be acquired, so that the related work of navigation test is performed on the vehicle based on the large amount of positioning information.

In the existing application, the positioning information of the vehicle is collected in the actual running process of the vehicle, and the navigation test is carried out on the vehicle by using the positioning information later, but the efficiency of collecting the positioning information of the vehicle in the mode is very low, and the positioning information of the vehicle needs to be collected in the actual running process of the vehicle, so that the cost of collecting the positioning information of the vehicle is very high.

Disclosure of Invention

The application provides a processing method, a device, equipment and a medium of driving data, which can improve the efficiency of acquiring positioning information (such as simulation positioning information) and reduce the cost of acquiring the positioning information.

In one aspect, the present application provides a method for processing driving data, including:

acquiring a target path to be driven of a simulation object; the simulated object is provided with a corresponding navigation object, and the navigation object moves along with the running of the simulated object;

Acquiring a target running mode set for a simulation object, and driving the simulation object to run on a target path according to the target running mode;

in the running process of the simulation object, generating simulation positioning information of a navigation object corresponding to the simulation object; the simulation positioning information is used for simulating a simulation test of navigating the simulation object by adopting the navigation object in the target driving mode.

Optionally, acquiring a target path to be travelled by the simulation object includes:

acquiring a starting driving position and a stopping driving position set by an analog object;

generating at least one candidate path of the simulation object on the high-precision map based on the starting driving position and the ending driving position; each candidate path is a different path from the starting running position to the ending running position;

selecting a target path from at least one candidate path;

the simulation positioning information is used for simulating a simulation test of navigation of the simulation object on the high-precision map by adopting the navigation object in the target driving mode.

In one aspect, the present application provides a processing device for driving data, including:

the acquisition module is used for acquiring a target path to be driven by the simulation object; the simulated object is provided with a corresponding navigation object, and the navigation object moves along with the running of the simulated object;

The driving module is used for acquiring a target running mode set by the simulation object and driving the simulation object to run on a target path according to the target running mode;

the generation module is used for generating simulation positioning information of the navigation object corresponding to the simulation object in the driving process of the simulation object; the simulation positioning information is used for simulating a simulation test of navigating the simulation object by adopting the navigation object in the target driving mode.

Optionally, the driving module drives the simulated object to travel on the target path according to the target travel mode, including:

calculating a running parameter of the simulation object at a time point indicated by the target time interval based on the target running mode according to the target time interval;

driving the simulation object to run according to the corresponding running parameters at the time point indicated by the target time interval; the simulation object is used for running according to the running parameters of any time point in a period from any time point indicated by the target time interval to the next time point of the any time point;

wherein the driving parameters at any time point comprise at least one of the following: the driving speed of the simulation object at any time point, the driving acceleration of the simulation object at any time point and the driving track indication information of the simulation object at any time point.

Optionally, the time points indicated by the target time interval include an i-1 th time point and an i-th time point, i is a positive integer, and the time interval between the i-1 th time point and the i-th time point is the target time interval;

the driving module calculates a driving parameter of the simulation object at a time point indicated by the target time interval based on the target driving mode according to the target time interval, and the driving module comprises the following steps:

acquiring a driving parameter of a simulation object at an i-1 time point; the travel parameter at the i-1 th time point is determined based on the target travel mode and the initial travel parameter set to the simulation object;

based on the target travel pattern and the travel parameters at the i-1 th time point, the travel parameters of the simulation object at the i-1 th time point are calculated.

Optionally, the target driving mode includes: a speed range mode, a speed change mode, a driving lane change mode and a driving lane preference mode during driving;

the driving module calculates the driving parameter mode of the simulation object at the ith time point based on the target driving mode and the driving parameter at the ith-1 time point, and the driving module comprises the following steps:

calculating the running speed of the simulation object at the ith time point based on the running speed and the running acceleration of the simulation object at the ith-1 time point;

Determining the running acceleration of the simulation object at the ith time point based on the speed range mode, the speed change mode and the running speed of the simulation object at the ith time point;

determining driving lane indicating information of the simulation object at the ith time point based on the driving lane changing mode, the driving lane preference mode and the driving lane indicating information of the simulation object at the ith-1 time point;

the travel speed, the travel acceleration, and the travel lane indication information of the simulation object at the i-th time point are determined as the travel parameter at the i-th time point.

Optionally, the driving module determines a manner of driving acceleration of the simulation object at the ith time point based on the speed range mode, the speed variation mode and the driving speed of the simulation object at the ith time point, including:

acquiring a target running speed associated with a speed range mode; the running speed of the simulation object fluctuates in the adjacent range of the target running speed;

acquiring a target acceleration and a target speed change proportion associated with a speed change mode; the target acceleration is used for determining the change range of the running acceleration of the simulation object, and the target speed change proportion is used for determining the adjacent range of the running speed fluctuation of the simulation object;

Acquiring a speed difference value of the target running speed and the running speed of the simulation object at the ith time point, and taking a product value of an absolute value of the speed difference value and a target speed change proportion as an acceleration adjustment value;

based on the target acceleration and the acceleration adjustment value, the running acceleration of the simulation object at the i-th point in time is determined.

Optionally, the speed change mode is associated with a first acceleration and a second acceleration, the first acceleration is smaller than the target value, the second acceleration is larger than the target value, the first acceleration corresponds to a first speed change proportion, and the second acceleration corresponds to a second speed change proportion; the method for acquiring the target acceleration and the target speed change proportion related to the speed change mode by the driving module comprises the following steps:

acquiring speed change instruction information of a time point when the running speed of the simulation object is equal to the target running speed; the ith time point is any time point when the running speed of the simulation object changes from the initial running speed to the target running speed or after the running speed changes to the target running speed;

if the speed change indication information indicates that the simulation object needs to run at a reduced speed, the first acceleration is taken as a target acceleration, and the first speed change proportion is taken as a target speed change proportion;

If the speed change instruction information indicates that the simulation object needs to accelerate, the second acceleration is taken as a target acceleration, and the second speed change proportion is taken as a target speed change proportion.

Optionally, the mode of obtaining the speed change indication information of the simulation object by the driving module includes:

generating a first random number within a target numerical range; the target value range comprises a first value sub-range and a second value sub-range;

if the value of the first random number is in the first value sub-range, determining that the speed change indication information is information for indicating that the simulation object needs to run at a reduced speed;

if the value of the first random number is within the second value sub-range, the speed change instruction information is determined to be information for indicating that the simulation object needs to accelerate running.

Optionally, the driving module determines a driving acceleration mode of the simulation object at the ith time point based on the target acceleration and the acceleration adjustment value, including:

if the target acceleration is the first acceleration and the ith time point is a time point before the running speed of the simulation object is reduced from the target running speed to the first running speed, determining the sum of the first acceleration and the acceleration adjustment value as the running acceleration of the simulation object at the ith time point; the first running speed is equal to the difference between the target running speed and a first ratio, wherein the first ratio is the ratio of the absolute value of the first acceleration to the change proportion of the target speed;

If the target acceleration is the first acceleration and the ith time point is a time point when the running speed of the simulation object is reduced from the target running speed to the first running speed or after the first running speed, determining the acceleration adjustment value as the running acceleration of the simulation object at the ith time point;

if the target acceleration is the second acceleration and the ith time point is the time point before the running speed of the simulation object is increased from the target running speed to the second running speed, determining the difference value between the second acceleration and the acceleration adjustment value as the running acceleration of the simulation object at the ith time point; the second running speed is equal to the sum of the value of the target running speed and a second ratio, and the second ratio is the ratio of the value of the second acceleration to the change ratio of the target speed;

if the target acceleration is the second acceleration and the i-th time point is a time point when the traveling speed of the simulation object increases from the target traveling speed to the second traveling speed or after the second traveling speed, the opposite number of the acceleration adjustment values is determined as the traveling acceleration of the simulation object at the i-th time point.

Optionally, the driving module determines a manner of driving lane indication information of the simulation object at the ith time point based on the driving lane change mode, the driving lane preference mode and the driving lane indication information of the simulation object at the ith time point, and the driving module includes:

If the driving channel indication information of the ith-1 time point indicates that the simulation object does not have the lane change at the ith-1 time point, determining a target driving channel which the simulation object needs to drive at the ith time point based on the driving channel change mode and the driving channel preference mode;

if the driving lane indication information of the i-1 time point indicates that the simulation object is in a continuous lane changing state in the target period and the i time point does not belong to the time point in the target period, determining a target driving lane on which the simulation object needs to drive at the i time point based on the driving lane change mode and the driving lane preference mode;

if the target driving lane is inconsistent with the driving lane where the simulation object is located at the ith-1 time point, determining that driving lane indication information at the ith time point comprises indication information of a lane to be changed and the target driving lane;

if the target driving lane is consistent with the driving lane where the simulation object is located at the ith-1 time point, determining that the driving lane indication information at the ith time point is the indication information without changing lanes.

Optionally, the device is further configured to:

if the driving lane indication information of the ith-1 time point indicates that the simulation object is in the continuous lane change state in the target period and the ith time point belongs to the time point in the target period, determining that the driving lane indication information of the ith time point is the indication information of the simulation object in the continuous lane change state in the target period;

Wherein the i-1 th time point belongs to a time point within the target period.

Optionally, the simulation object has at least one travelable travel path at the ith point in time; the driving module determines a mode of a target driving lane on which the simulation object needs to travel at an i-th time point based on the driving lane change mode and the driving lane preference mode, and the driving module comprises:

determining a driving lane where the simulation object is located at the i-1 time point as a current driving lane;

acquiring a numerical value sub-range corresponding to a current driving lane in at least one driving lane in a target numerical value range based on the driving lane change mode;

based on the driving lane preference mode, acquiring corresponding numerical value sub-ranges of all driving lanes except the current driving lane in at least one driving lane in a target numerical value range respectively;

generating a third random number within the target numerical range;

and determining the driving lane corresponding to the numerical value sub-range where the numerical value of the third random number in at least one driving lane is positioned as a target driving lane.

Optionally, any time point indicated by the target time interval is a target time point; the generation module generates the simulation positioning information of the navigation object in the driving process of the simulation object, and comprises the following steps:

Acquiring an initial driving position of a target path;

calculating the simulated running position of the simulated object at the target time point based on the starting running position and the running parameters of each time point before the target time point;

and generating simulation positioning information based on the simulation running position.

Optionally, the generating module generates the mode of the simulated positioning information based on the simulated driving position, including:

performing satellite signal conversion processing on the simulated driving position to generate a simulated satellite signal of the simulated object at a target time point;

acquiring a reference satellite signal of a satellite base station, performing differential processing on the simulated satellite signal and the reference satellite signal, and generating a differential satellite signal of a simulation object at a target time point;

determining the simulated satellite signals and the differential satellite signals of the simulated object at the target time point as the simulated satellite signals and the differential satellite signals of the navigation object at the target time point;

the simulated positioning information comprises simulated satellite signals and differential satellite signals of the navigation object at the target time point.

Optionally, the generating module calculates a mode of simulating the driving position of the simulated object at the target time point based on the driving parameters of each time point before the target time point indicated by the starting driving position and the target time interval, including:

Calculating a target running position of the simulation object at the target time point based on the starting running position and running parameters of each time point before the target time point indicated by the target time interval;

and (5) carrying out noise adding processing on the target running position to obtain the simulated running position.

Optionally, the target driving location comprises a plurality of location components; the generating module performs noise adding processing on the target driving position to obtain a mode of simulating the driving position, and the method comprises the following steps:

acquiring Gaussian noise distribution respectively associated with each position component of a target driving position;

in Gaussian noise distribution associated with each position component, sampling the added Gaussian noise of each position component;

and (3) adopting the Gaussian noise added to each position component to add noise to each position component respectively, and obtaining the simulated driving position.

if the simulation object is not in the lane change state at the target time point, determining the default angular velocity and the running acceleration of the simulation object at the target time point as target sensing signals of the simulation object at the target time point;

If the simulation object is in the lane change state at the target time point, determining the running angular velocity of the simulation object based on the lane change track of the simulation object at the target time point, and determining the running angular velocity and the running acceleration of the simulation object at the target time point as target sensing signals of the simulation object at the target time point;

generating a simulated sensing signal of the navigation object at a target time point based on the target sensing signal; the simulated positioning information comprises a simulated sensing signal.

Optionally, the navigation object is in a first reference coordinate system, and the simulation object is in a second reference coordinate system;

the generation module generates a simulated sensing signal of the navigation object at a target time point based on the target sensing signal, and comprises the following steps:

acquiring a coordinate system conversion parameter between a first reference coordinate system and a second reference coordinate system;

and mapping the target sensing signal from the second reference coordinate system to the first reference coordinate system based on the coordinate system conversion parameters to obtain the simulation sensing signal of the navigation object at the target time point.

Optionally, the method for acquiring the target path to be driven by the simulation object by the acquisition module includes:

selecting a target path from at least one candidate path;

In one aspect the application provides a computer device comprising a memory and a processor, the memory storing a computer program which, when executed by the processor, causes the processor to perform the method of one aspect of the application.

An aspect of the application provides a computer readable storage medium storing a computer program which, when executed by a processor, causes the processor to perform the method of the above aspect.

According to one aspect of the present application, there is provided a computer program product comprising a computer program stored in a computer readable storage medium. The processor of the computer device reads the computer program from the computer-readable storage medium, and the processor executes the computer program to cause the computer device to execute the method provided in various optional manners of the above aspect and the like.

The application can acquire the target path to be driven by the simulation object; the simulated object is provided with a corresponding navigation object, and the navigation object moves along with the running of the simulated object; the target running mode set by the simulation object can be obtained, and the simulation object is driven to run on the target path according to the target running mode; and, in the course of driving of the simulation object, can produce the simulation positioning information of the correspondent navigation object of the simulation object; the simulation positioning information is used for simulating a simulation test of navigating the simulation object by adopting the navigation object in the target driving mode. Therefore, the method provided by the application can flexibly set the corresponding running mode (such as the target running mode) of the simulated object (the simulated running object), and can drive the simulated object to run on the target path according to the set target running mode, and as the navigation object can move along with the running of the simulated object, the simulation positioning information (namely the simulated positioning information) of the navigation object can be quickly and conveniently generated in the running process of the simulated object, so that the efficiency of acquiring the information (such as the positioning information) of the navigation object for positioning and navigation of the running object is improved, and then the simulation positioning information can simulate the simulation test of navigation of the simulated object by adopting the navigation object; in addition, the application can acquire the simulated positioning information of the navigation object in the simulated running process of the simulated object without acquiring the positioning information of the real running object in the running process, thereby reducing the cost of acquiring the positioning and navigation information of the navigation object on the running object.

Drawings

In order to more clearly illustrate the application or the technical solutions of the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it being obvious that the drawings in the description below are only some embodiments of the application, and that other drawings can be obtained from them without inventive effort for a person skilled in the art.

Fig. 1 is a schematic diagram of a network architecture according to the present application;

FIG. 2 is a schematic view of a scenario in which a simulated object is driven in a simulated manner;

FIG. 3 is a schematic flow chart of a method for processing driving data according to the present application;

FIG. 4 is a schematic diagram of an interface for a path setup provided by the present application;

FIG. 5 is a schematic flow chart of a driving method of a simulation object provided by the application;

FIG. 6 is a schematic view of a scenario in which a time point is determined according to the present application;

FIG. 7 is a schematic view of another scenario in which a simulated object is simulated for traveling according to the present application;

FIG. 8 is a schematic view of a scenario in which a simulated object is driven in a simulated manner according to the present application;

FIG. 9 is a schematic view of a scenario in which a simulated object is driven in a simulated manner according to the present application;

FIG. 10 is a flow chart of a method for generating simulated positioning information provided by the present application;

FIG. 11 is a schematic view of a scenario for generating a simulated driving location provided by the present application;

FIG. 12 is a flow chart of another method for generating simulated positioning information provided by the present application;

FIG. 13 is a schematic view of a scenario for generating simulated positioning information provided by the present application;

fig. 14 is a schematic structural view of a processing device for driving data according to the present application;

fig. 15 is a schematic structural diagram of a computer device according to the present application.

Detailed Description

The following description of the embodiments of the present application will be made more apparent and fully hereinafter with reference to the accompanying drawings, in which some, but not all embodiments of the application are shown. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.

Artificial intelligence (Artificial Intelligence, AI) is the theory, method, technique and application system that uses a digital computer or a machine controlled by a digital computer to simulate, extend and extend human intelligence, sense the environment, acquire knowledge and use the knowledge to obtain optimal results. In other words, artificial intelligence is an integrated technology of computer science that attempts to understand the essence of intelligence and to produce a new intelligent machine that can react in a similar way to human intelligence. Artificial intelligence, i.e. research on design principles and implementation methods of various intelligent machines, enables the machines to have functions of sensing, reasoning and decision.

The artificial intelligence technology is a comprehensive subject, and relates to the technology with wide fields, namely the technology with a hardware level and the technology with a software level. Artificial intelligence infrastructure technologies generally include, for example, sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing technologies, pre-training model technologies, operation/interaction systems, mechatronics, and the like. The pre-training model is also called a large model and a basic model, and can be widely applied to all large-direction downstream tasks of artificial intelligence after fine adjustment. The artificial intelligence software technology mainly comprises a computer vision technology, a voice processing technology, a natural language processing technology, machine learning/deep learning and other directions.

With research and advancement of artificial intelligence technology, research and application of artificial intelligence technology is being developed in various fields, such as common smart home, smart wearable devices, virtual assistants, smart speakers, smart marketing, unmanned, autopilot, unmanned, digital twin, virtual man, robot, artificial Intelligence Generated Content (AIGC), conversational interactions, smart medical, smart customer service, game AI, etc., and it is believed that with the development of technology, artificial intelligence technology will be applied in more fields and with increasing importance value.

The application relates to an automatic driving technology in artificial intelligence. The automatic driving technology refers to that the vehicle realizes self-driving under the condition of no driver operation. Typically including high-precision maps, environmental awareness, computer vision, behavioral decision-making, path planning, motion control, and the like. The automatic driving comprises various development paths such as single car intelligence, car-road coordination, networking cloud control and the like. The automatic driving technology has wide application prospect, and the current field is the field of logistics, public transportation, taxis and intelligent transportation, and is further developed in the future.

In the present application, the simulated object (i.e. the simulated driving object) can automatically drive on the corresponding path according to the set driving mode, and the description of the corresponding embodiment of fig. 3 can be seen specifically.

Firstly, it should be noted that all data (such as related data of a driving path, a driving mode, driving parameters and the like of a simulation object) collected by the present application are collected under the condition that the object (such as a user, an organization or an enterprise) to which the data belongs agrees and authorizes, and the collection, the use and the processing of the related data need to comply with related laws and regulations and standards of related countries and regions.

Here, the related art concept related to the present application will be described.

GPS: the global positioning system (Global Positioning System, GPS), a high-precision radio navigation positioning system based on satellites, provides accurate geographic location, vehicle speed and accurate time information anywhere in the world and near earth space.

RTK: real-time kinematic carrier phase difference technology is a difference method for processing the observed quantity of carrier phases of two measuring stations in Real time, and the carrier phases acquired by a reference station (which can be called a reference) are sent to a user receiver (such as a navigation object) to calculate the difference and calculate the coordinates.

IMU: inertial Measurement Unit inertial sensors, sensors that can be used to detect and measure the acceleration and rotational movement (e.g., angular velocity) of a traveling object.

High-precision map: a map with high accuracy, which can contain map elements such as road shape, road sign, traffic sign and obstacle, can be accurate to centimeter level.

Referring to fig. 1, fig. 1 is a schematic structural diagram of a network architecture according to the present application. As shown in fig. 1, the network architecture may include a server 200 and a cluster of terminal devices, which may include one or more terminal devices, the number of which will not be limited here. As shown in fig. 1, the plurality of terminal devices may specifically include a terminal device 1, a terminal device 2, a terminal device 3, …, a terminal device n; as shown in fig. 1, the terminal device 2, the terminal devices 3, …, and the terminal device n may be connected to the server 200 through a network, so that each terminal device may interact with the server 200 through the network connection.

The server 200 shown in fig. 1 may be an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, or a cloud server providing cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDNs, basic cloud computing services such as big data and artificial intelligence platforms, and the like. The terminal device may be: intelligent terminals such as intelligent mobile phones, tablet computers, notebook computers, desktop computers, intelligent televisions, vehicle-mounted terminals and the like. A specific description of an embodiment of the present application will be made below taking communication between the terminal device 1 and the server 200 as an example.

Referring to fig. 2, fig. 2 is a schematic view of a scene of a simulated running of a simulated object according to the present application. The above-described terminal device 1 may be a user device of a user, and the user may set a target path to be traveled to an analog object (may be an analog vehicle here) in the terminal device 1, and may set a corresponding traveling mode (i.e., a target traveling mode) to the analog object.

Optionally, the generating process of the target path may include: the user may set a start travel position and an end travel position for the simulation object in the terminal device 1, and further, the terminal device 1 may transmit the start travel position and the end travel position to the server 200, and one or more candidate routes may be planned by the server 200 based on the start travel position and the end travel position.

The server 200 may return the planned one or more candidate paths to the terminal device 1, and the terminal device 1 may perform visual display on the one or more candidate paths, so that a user may select a target path to be driven by the simulation object from the one or more candidate paths.

Further, the terminal device 1 may resend the selected target path to the server 200, and the server 200 may drive the simulated object to travel on the target path according to the set target travel mode, where the simulated object further has a corresponding navigation object (for example, the navigation object may be a simulated navigation device for navigating the simulated object), and the navigation object moves along with the travel of the simulated object, so that during the travel of the simulated object, the server 200 may generate simulated positioning information of the navigation object, where the simulated positioning information may be used to position the simulated object, and therefore, it may be understood that the simulated positioning information may be applied to a test scenario in which the simulated object is navigated and positioned by using the navigation object.

The method provided by the application does not need to consume a large amount of manpower and material resources in a real scene to acquire the positioning information of the navigation equipment in the running process of the real running object, and the simulation positioning information of the navigation object can be quickly generated by correspondingly running the simulation object according to a set mode (such as a mode indicated by a target running mode), so that the cost for acquiring the positioning information of the navigation object is greatly reduced, and the convenience for acquiring the positioning information of the navigation object is improved.

Referring to fig. 3, fig. 3 is a flow chart of a processing method of driving data according to the present application. The execution body in the embodiment of the present application may be a processing device (hereinafter may be simply referred to as a processing device) of running data, where the processing device may be one computer device or a cluster of computer devices formed by a plurality of computer devices, and the computer device may be a server, a terminal device, or other devices, which is not limited to this. As shown in fig. 3, the method may include:

step S101, a target path to be driven by a simulation object is obtained; the simulated object is provided with a corresponding navigation object, and the navigation object moves along with the running of the simulated object.

Alternatively, the simulated object may be a simulated (e.g., virtual) travel object, i.e., the simulated object may be a simulated travel-enabled object. The simulation object may be any drivable object such as a simulated vehicle.

The processing device may obtain a path to be travelled by the simulated object, which may be referred to as a target path. Alternatively, the target path may be a path on a high-definition map, and the target path may be a default path set in advance. Alternatively, the target path may be a path set by the user himself; for example, the processing device may provide a visual path setup interface that enables a user to set a path (e.g., a target path) to be traveled by the simulated object on the path setup interface, which may be described as follows.

The processing device may acquire a start travel position set by the simulation object, that is, a position at which the simulation object starts traveling, and an end travel position, that is, a position at which the simulation object ends traveling. The start travel position and the end travel position may be entered by a user on a path setup interface.

Further, the processing apparatus may generate (i.e., plan) at least one candidate route for the simulation object on the high-precision map based on the start travel position and the end travel position, each candidate route being a route traveling from the start travel position to the end travel position, and different candidate routes may be different routes from the start travel position to the end travel position. For example, the processing device may invoke a route planning service to generate one or more candidate paths for the simulated object on a high-definition map.

The path setting interface may include (e.g., display) a high-precision map, so that the planned at least one candidate path may be visually displayed in the high-precision map, so as to be viewed and selected by a user, and support the user to select the target path to be driven by the simulated object from the planned at least one candidate path on the path setting interface.

Alternatively, after the initial driving position and the final driving position of the simulation object are given, the processing device may also automatically select a target path to be driven by the simulation object from at least one planned candidate path, for example, a candidate path with the largest mileage may be selected as the target path, or a candidate path with the largest road change (for example, a change of a ramp converging into a main road, a change of multiple lanes into fewer lanes (for example, a change of three lanes into two lanes or a single lane), a change of fewer lanes into multiple lanes, or the like) may be selected as the target path by the processing device, or a candidate path with a curved road comparison may also be selected as the target path, and specifically, the method may be preset according to an actual application scenario.

The target path to be driven by the simulation object may be a path determined in a map (such as a high-precision map) in any feasible manner, and specifically how to set the target path or which path the target path is may be determined according to an actual application scenario, which is not limited.

Referring to fig. 4, fig. 4 is an interface schematic diagram of a path setting according to the present application. The interface shown in fig. 4 may be a path setting interface on which a user can set a start travel position (i.e., start point coordinates herein) and an end travel position (i.e., end point coordinates herein).

Furthermore, 3 routes (which can be understood as 3 candidate routes) can be planned by invoking the route planning service, and the length and the time of use of each route can be calculated in advance. Further, the support user selects one of the 3 routes as the target route, and the target route may be an SD route (may also be referred to as an SD track) which may be a road-level planned route (i.e., a travel path which may not include a specific travel of the simulation object), and the SD track may include each section of road on which the simulation object is to travel, that is, the target route may be configured of a plurality of sections of roads. The selected target path may be displayed in a map of the path setting interface shown in fig. 4, and the start travel position of the target path may be a "start" word in the map, and the end travel position of the target path may be a "end" word in the map.

The above-mentioned simulation object may also have a corresponding navigation object, which may also be a simulation object, which may be a simulation object for navigating the simulation object, which may follow the simulation object for movement, e.g. the navigation object may move synchronously following the travel of the simulation object during the travel of the simulation object.

For example, the navigation object may be a simulated object placed inside the simulated object. By way of example, the navigation object may be a simulated navigation device, such as a simulated user terminal that may be used for driving navigation, or a simulated vehicle-mounted terminal that may be used for driving navigation, etc.

Step S102, a target running mode set for the simulation object is obtained, and the simulation object is driven to run on a target path according to the target running mode.

Alternatively, the processing device may also acquire a driving mode set by the analog object, and the driving mode set by the analog object may be referred to as a target driving mode, and the target driving mode may be used to indicate a manner in which the mode object is required to drive, which will be described in detail below.

Wherein the target travel pattern set by the simulation object may include at least one of the following patterns set by the simulation object: a speed range pattern during travel, a speed change pattern during travel, a lane change pattern during travel, and a lane preference pattern during travel.

The speed change mode set by the simulation object can be used for indicating the fluctuation range of the driving speed of the simulation object in the driving process; the speed change mode set by the simulation object can be used for indicating the change condition of the running acceleration (also simply referred to as acceleration) of the simulation object in the running process; the driving lane change mode set by the simulation object can be used for indicating the change condition of the driving lane of the simulation object in the driving process (namely the change condition of the driving lane, such as the change condition of the driving lane); the lane preference mode set by the simulated object may be used to indicate on which lane (e.g., left lane, center lane, or right lane) the simulated object is required to travel more (or with a greater probability).

Illustratively, in one possible embodiment, the present application may provide a plurality of speed range modes, a plurality of speed change modes, a plurality of lane change modes, and a plurality of lane preference modes for selection by a user.

Illustratively, the plurality of selectable speed range modes may include, but are not limited to: a low-speed running mode (e.g., running in a low-speed range), a medium-speed running mode (e.g., running in a medium-speed range), and a high-speed running mode (e.g., running in a high-speed range). The speed range mode set to the simulation object in the target running mode may be any one selected among the plurality of speed range modes.

The initial running speed may be set for the simulation object, where the initial running speed is a speed when the simulation object starts running from a starting running position of the target path, and may be equal to 0 or greater than 0, where the initial running speed is greater than 0 and may be used to simulate a scene where navigation positioning is started only in the middle of running the vehicle, and where the initial running speed is equal to 0 and may be used to simulate a scene where navigation positioning is started when the vehicle starts running.

Alternatively, each of the speed range modes may be associated with a running speed, and the running speed of the simulation object may be increased or decreased (for example, may be initially increased or decreased with a fixed acceleration) from the initial running speed at which the running speed of the simulation object is initially set to the running speed associated with the speed range mode, and then the running speed of the simulation object may be fluctuated within a vicinity of the running speed associated with the speed range mode set by the simulation object or may be kept to run at a constant speed according to a speed change mode set by the simulation object described below. The magnitude of the travel speeds associated with the different speed range modes may be different.

For example, the mode of low-speed running may be referred to as a first speed range mode, the mode of medium-speed running may be referred to as a second speed range mode, and the mode of high-speed running may be referred to as a third speed range mode; the first speed range mode may be associated with a smaller travel speed (which may be referred to as a first travel speed), the second speed range mode may be associated with a medium magnitude travel speed (which may be referred to as a second travel speed), and the third speed range mode may be associated with a larger travel speed (which may be referred to as a third travel speed).

The first running speed, the second running speed and the third running speed may be fixed speeds set in advance, the first running speed may be smaller than the second running speed, and the second running speed may be smaller than the third running speed.

In this case, the travel speed associated with the speed range mode set by the simulation object in the target travel mode may be referred to as a target travel speed, that is, the travel speed of the simulation object may fluctuate within a vicinity of the target travel speed.

Illustratively, the plurality of selectable speed change modes may include, but are not limited to: the mode of keeping the vehicle speed (i.e. keeping a fixed running speed unchanged, and running at a constant speed), the mode of slightly accelerating and decelerating (e.g. the range of acceleration fluctuation can be smaller), the mode of normally accelerating and decelerating (e.g. the range of acceleration fluctuation is middle), and the mode of greatly accelerating and decelerating (e.g. the range of acceleration fluctuation can be larger). The speed change pattern set to the simulation object in the target running pattern may be any one selected from the plurality of speed change patterns.

Each speed change pattern may be associated with two respective running accelerations (which may be simply referred to as accelerations). One of the two running accelerations may be smaller than a target value, the other running acceleration may be larger than the target value, and the target value may be equal to 0, that is, one running acceleration is smaller than 0 (negative value), one running acceleration is larger than 0 (positive value), the running acceleration larger than 0 is used for accelerating the simulated object, and the running acceleration smaller than 0 is used for decelerating the simulated object.

And, each of the two traveling accelerations may correspond to a respective speed change ratio, wherein the traveling acceleration associated with the vehicle speed change pattern set by the simulation object may be used to determine a change range of the traveling acceleration of the simulation object during traveling, and the speed change ratio corresponding to the traveling acceleration associated with the vehicle speed change pattern set by the simulation object may be used to determine a range in which the traveling speed of the simulation object fluctuates in the vicinity (i.e., in the vicinity) of the target traveling speed (i.e., in the vicinity of the target traveling speed).

Alternatively, the absolute values of the two running accelerations associated with the slight acceleration and deceleration modes may be smaller, the absolute values of the two running accelerations associated with the normal acceleration and deceleration modes may be medium, and the absolute values of the two running accelerations associated with the great acceleration and deceleration modes may be larger; the absolute values of the two running accelerations associated with the mode of slight acceleration and deceleration may be smaller than the absolute values of the two running accelerations associated with the mode of normal acceleration and deceleration, and the absolute values of the two running accelerations associated with the mode of normal acceleration and deceleration may be smaller than the absolute values of the two running accelerations associated with the mode of normal substantial deceleration.

The two accelerations associated with the speed change pattern set to the simulation object in the target running pattern may be referred to as a first acceleration and a second acceleration, respectively, the first acceleration may be smaller than the target value, the second acceleration may be larger than the target value, the speed change ratio associated with the first acceleration may be referred to as a first speed change ratio, and the speed change ratio associated with the second acceleration may be referred to as a second speed change ratio. Subsequently, one acceleration may be selected from the first acceleration and the second acceleration as a target acceleration, and the running acceleration of the simulated object in the running process may be determined by the target acceleration, and this specific process may be described in the following related embodiment of fig. 5; the target acceleration may be referred to as a target acceleration associated with a speed change pattern set to the simulation object, and a speed change ratio corresponding to the target acceleration may be referred to as a target speed change ratio.

By way of example, the plurality of selectable lane change modes may include, but are not limited to: a mode of constant lane change (i.e., a mode of keeping running on one running lane without lane change), a mode of slight lane change (which may be understood as a smaller lane change probability), a mode of normal lane change (which may be understood as a medium lane change probability), a mode of frequent lane change (which may be understood as a larger lane change probability). The lane change pattern set to the simulation target in the target running pattern may be any one selected from the plurality of lane change patterns.

If the simulation object is set in the lane-changing mode, a flow for judging whether the simulation object needs lane change or not is not needed in the driving process of the simulation object.

Alternatively, each lane change pattern may be associated with two sub-ranges of values within a target range of values (which may be a preset range, such as a (0) range), which are not overlapping within the target range of values, one sub-range of values may be used to determine that the simulated object is required to change lanes, and one sub-range of values may be used to determine that the simulated object is not required to change lanes.

The two numerical sub-ranges associated with the driving lane change pattern set by the simulation object may be referred to as a third numerical sub-range for determining that the simulation object needs lane change and a fourth numerical sub-range for determining that the simulation object does not need lane change. If the mode of slight lane change is set for the analog object, the fourth numerical value sub-range may be greater than the third numerical value sub-range; if the simulation object is set in a normal lane-changing mode, the fourth numerical value sub-range may be equal (equal in size, unequal in value) to the third numerical value sub-range; if a frequently changing pattern is set for the simulation object, the fourth numerical subrange may be smaller than the third numerical subrange.

Illustratively, the plurality of selectable travel path preference modes may include, but are not limited to: a mode biased to travel on the left (e.g., a mode biased to travel on the left lane may be understood as having a greater probability of traveling on the left (e.g., changing lanes to the left), a mode biased to travel on the middle (e.g., a mode biased to travel on the middle lane may be understood as having a greater probability of traveling on the middle (e.g., changing lanes to the middle)), a mode biased to travel on the right (e.g., a mode biased to travel on the right lane may be understood as having a greater probability of traveling on the right (e.g., changing lanes to the right)), and a mode biased to travel on the right (e.g., to the right) may be understood as having a greater probability of traveling on the right than on the left and middle). The lane preference mode set to the simulation object in the target travel mode may be any one selected from the plurality of lane preference modes.

Alternatively, the processing apparatus may further provide a setting interface (may be referred to as a mode setting interface) for a travel mode of the simulation object, and the speed range mode, the speed change mode, the travel lane change mode, and/or the travel lane preference mode set by the simulation object in the above-described target travel mode may be set by the user in the mode setting interface. Or, the target driving mode may be set by default, and how the target driving mode is specifically set may be determined according to the actual application scenario, which is not limited.

Further, if the speed change pattern set to the simulation object is a pattern for maintaining the vehicle speed (i.e., a pattern for traveling at a constant speed), the traveling acceleration of the simulation object does not need to be generated during the traveling of the simulation object, and the traveling acceleration of the simulation object may be always 0 after the traveling speed of the simulation object is increased or decreased from the initial traveling speed to the target traveling speed.

Through the above-described process, a target travel pattern set to the simulation object, which may be set in real time or in advance by the user or the processing apparatus, may be acquired.

The processing device may drive the simulation object to travel on the target path in accordance with the target travel mode set as described above. The process of driving the simulation object to travel on the target path according to the set target travel mode can be further described in the following corresponding embodiment of fig. 7.

Step S103, in the driving process of the simulation object, generating simulation positioning information of a navigation object corresponding to the simulation object; the simulation positioning information is used for simulating a simulation test of navigating the simulation object by adopting the navigation object in the target driving mode.

Optionally, in the process that the simulated object runs on the target path according to the target running mode, the navigation object moves synchronously along with the running of the simulated object, in the process that the navigation object moves along with the running of the simulated object (also can be understood as the running of the simulated object), the processing device can generate simulation positioning information of the navigation object, the simulation positioning information can be used for simulating the simulation test of the navigation of the simulated object by adopting the navigation object in the target running mode, for example, the simulation positioning information can be used for testing the positioning and navigation effects (such as accurate positioning) of the simulated object by adopting the navigation object in the running process of the simulated object.

Because the target path of the simulated object can be a path on a high-precision map, the generated simulated positioning information can be used for simulating the test of high-precision positioning navigation of the simulated object on the high-precision map by adopting the navigation object in the target driving mode. The specific process of generating the simulated positioning information may also be referred to as the related description in the corresponding embodiments of fig. 8 and 9 described below.

The above-described method of the present application provides a simulation system for acquiring positioning information of a traveling object, which is built in the real world (because it is a real map (such as a real high-definition map) that is used), and which simulates the driving behavior of a user in a very fine manner (such as the driving behavior of the user simulated by a set target traveling pattern), so that the acquired simulated positioning information is truly reliable.

In addition, the simulation system provided by the application is light and easy to use, and the simulation system supports a user to quickly set a corresponding running path (such as a target path) and a running mode (such as a target running mode) of the simulation object, so that the user can conveniently use the simulation system to quickly acquire the simulation positioning information of the simulation object.

Referring to fig. 5, fig. 5 is a flow chart of a driving method of a simulation object provided by the present application. As shown in fig. 5, the method may include:

step S201, calculating a driving parameter of the simulation object at a time point indicated by the target time interval based on the target driving mode according to the target time interval.

Alternatively, the simulated positioning information may contain a GPS signal simulated by the simulated object, and thus the driving parameter of the simulated object may be acquired according to the frequency of the acquired GPS signal, i.e., the target time interval may be determined according to the frequency of the acquired GPS signal.

For example, assuming that the frequency of the GPS signal is 1Hz, indicating that the GPS signal needs to be acquired every 1 second, the target time interval may be 1 second.

Thus, it can be understood that the time point indicated by the target time interval may be a time point taken according to the target time interval, the 1 st time point indicated by the target time interval may be a time point when the simulation object starts to travel from the starting travel position, and the 2 nd time point indicated by the target time interval may be a time point (e.g., a time point 1 second after the 1 st time point) of the target time interval after the 1 st time point, that is, a time interval between the 1 st time point and the 2 nd time point is the target time interval; similarly, the 3 rd time point indicated by the target time interval may be a time point of the target time interval after the 2 nd time point (for example, a time point of 1 second after the 2 nd time point), the time interval between the 2 nd time point and the 3 rd time point is also the target time interval, and so on, each time point indicated by the target time interval may be obtained until the simulation object is driven to the end of the driving position.

Wherein the 2 nd time point may be referred to as the next time point to the 1 st time point, and the 3 rd time point may be referred to as the next time point to the 2 nd time point; conversely, the 1 st time point may be referred to as the last time point of the 2 nd time point, and the 2 nd time point may be referred to as the last time point of the 3 rd time point; and so on.

Therefore, the processing device may calculate, according to the target time interval and based on the target running mode, running parameters of the simulation object at each time point indicated by the target time interval (may be simply referred to as running parameters of each time point), and during continuous running of the simulation object on the target path, for each time point indicated by the target time interval, a corresponding running parameter may be calculated. It is to be understood that unless specifically stated below, the described time points may refer to the time points indicated by the target time interval.

Referring to fig. 6, fig. 6 is a schematic view of a scenario for determining a time point according to the present application. As shown in fig. 6, the time points indicated by the target time interval may include a 1 st time point, a 2 nd time point, a 3 rd time point, a 4 th time point … here, and the 1 st time point may be a time point at which the simulation object starts traveling from the start traveling position.

The time interval between adjacent two time points may be a target time interval, and the time interval between the 1 st time point and the 2 nd time point, the time interval between the 2 nd time point and the 3 rd time point, and the time interval between the 3 rd time point and the 3 rd time point may be target time intervals.

And, in the time interval between the two time points, the simulation object can travel according to the travel parameter of the previous time point. As here, in the period 1, the simulation object may travel at the travel speed at the 1 st time point, in the period 2, the simulation object may travel at the travel speed at the 2 nd time point, in the period 3, the simulation object may travel at the travel speed at the 3 rd time point, and so on.

Alternatively, the driving parameter at any point of time indicated by the target time interval may include at least one of: the running speed (i.e., the running speed, in kilometers per second) of the simulation object at any one point in time, the running acceleration (i.e., the running acceleration) of the simulation object at any one point in time, and the running track indication information of the simulation object at any one point in time.

The driving lane indication information at any time point is used for indicating whether the simulation object needs to start lane change at any time point or whether the simulation object is in a lane change state at any time point.

For example, a lane change time may be set, and assuming that it takes 4 seconds to set a lane change, the lane indication information at each time point within the 4 seconds may be used to indicate that the simulation object is in a lane change state (e.g., a continuous lane change state).

It is understood that the running parameter at the 1 st time point may be an initial running parameter (may be set by a user or may also be set by the processing device) set (may include a set initial running speed, an initial running acceleration, and initial running track indicating information), and the running parameter at each time point after the 1 st time point may be calculated based on the running parameter at the previous time point at each time point in combination with the upper target running mode, which may be described in detail as follows.

For example, in one possible embodiment, the present application may first change the simulated object from the initial running speed to (first change to) the target running speed (i.e., the running speed associated with the speed range mode set by the simulated object) at the fixed initial running speed according to the fixed initial running acceleration, and then let the simulated object change the running speed and the running acceleration according to the speed change mode.

In the present application, the initial travel lane instruction information is usually used to instruct the simulation object not to change lanes or to be in a lane change state, and therefore, the travel acceleration and the travel lane instruction information in the travel parameters at each time point before the simulation object changes from the initial travel speed to the target travel speed (the target travel speed may not be included) may be the initial travel acceleration and the initial travel lane instruction information in the initial travel parameters; the running speed of the simulation object in the running parameter at each time point before the initial running speed is changed to the target running speed may be a running speed after the initial running speed is changed and updated based on the initial running acceleration and the time interval between each time point and the 1 st time point.

On this basis, the time points indicated by the target time interval may include an i-1 th time point and an i-th time point, i is a positive integer, the i-1 th time point is the last time point of the i-th time point, i.e., the time interval between the i-1 th time point and the i-th time point is the target time interval. The i-th time point may be a time point when the simulation object changes from the initial travel speed to the target travel speed or any time point after changing to the target travel speed. The following describes in detail how the travel parameter at the i-th time point is calculated.

The processing device may acquire the running parameters of the simulation object at the i-1 th time point, the running parameters at the i-1 th time point may be obtained based on the target running mode and the initial running parameters set for the simulation object, and if the i-1 st time point is the last time point of the time point when the simulation object is changed from the initial running speed to the target running speed, the running speed in the running parameters at the i-1 th time point may be obtained by substituting the initial running speed, the initial acceleration, and the time interval between the i-1 st time point and the 1 st time point into the speed model (the speed model may be expressed as a formula) After calculation, the initial driving speed can be substituted into the formula>Substituting the initial acceleration into a in the formula, substituting the time interval between the i-1 time point and the 1 st time point into t in the formula, where v can represent the calculated travel speed at the i-1 time point. The travel acceleration and the travel lane indication information in the travel parameter at the i-1 th time point may be the initial travel acceleration and the initial travel lane indication information.

If the i-1 th time point is a time point when the simulation object changes from the initial running speed to the target running speed or any time point after the change to the target running speed, the principle of calculating the running parameter at the i-1 th time point is the same as the principle of calculating the running parameter at the i-1 th time point described below.

The processing apparatus may calculate the travel parameter of the simulation object at the i-th time point by the set target travel pattern and the travel parameter of the simulation object at the i-1-th time point, as described below.

First, the processing apparatus may calculate the traveling speed of the simulation object at the i-1 th time point by simulating the traveling speed and the traveling acceleration of the object at the i-1 th time point: the processing device may substitute the i-1 th travel speed, the travel acceleration, and the time interval between the i-1 th and i-th time points (i.e., the target time interval) into the speed model, so as to calculate the travel speed of the simulation object at the i-th time point. The travel speed of the simulation object at the ith time point can be calculated in advance when the travel parameter of the simulation object at the ith-1 time point is calculated.

Next, the processing apparatus may also determine the traveling acceleration of the simulation object at the i-th time point by the speed range pattern, the speed change pattern, and the traveling speed of the simulation object at the i-1-th time point set by the simulation object, as described below.

The processing device may acquire the above-described target travel speed associated with the speed range mode set by the simulation object, the travel speed of the simulation object fluctuating within a vicinity of the target travel speed.

The processing device may further acquire the above-described target acceleration and target speed change ratio associated with the speed change pattern set by the analog object, and the process may include, for example: the two accelerations associated with the speed change pattern set by the simulation object may include the first acceleration less than 0 for decelerating the simulation object and the second acceleration greater than 0 for accelerating the simulation object; the first acceleration corresponds to a first speed change ratio, the second acceleration corresponds to a second speed change ratio, and the first speed change ratio and the second speed change ratio may be the same or different.

Thus, the processing apparatus can acquire the shift instruction information of the simulation object when the running speed of the simulation object is the target running speed (i.e., may be any time when the running speed is changed from the initial running speed to the target running speed), that is, if the simulation object does not always keep the target running speed constant running after the running speed reaches the target running speed, the shift instruction information of the simulation object at the time when the running speed of the simulation object reaches the target running speed (i.e., is equal to) may be acquired, which may be used to instruct whether the simulation object needs to start the deceleration running or the acceleration running at the time point when the running speed is equal to the target running speed.

If the shift instruction information is used to instruct the simulation object to perform the deceleration traveling at a time point when the traveling speed is equal to the target traveling speed, the first acceleration may be set as the target acceleration, and the first speed change ratio corresponding to the first acceleration may be set as the target speed change ratio.

In contrast, if the shift instruction information is used to instruct the simulation object that the acceleration running is required at a time point when the running speed is equal to the target running speed, the second acceleration may be set as the target acceleration, and the second speed change ratio corresponding to the second acceleration may be set as the target speed change ratio.

The manner of obtaining the above-mentioned speed change indication information may include, but is not limited to: the processing device may generate a random number for determining whether the simulation object is to be run at an acceleration or a deceleration within the target value range, the random number may be referred to as a first random number, and the value of the first random number may be random within the target value range, i.e., the probability that the value of the generated first random number is each value within the target value range is the same.

The target value range may be set by itself in advance, for example, the target value range may be a range of (0, 1).

Therefore, if the value of the first random value is within the first value sub-range, it may be determined that the shift instruction information of the simulation object may be information indicating that the simulation object needs to perform the deceleration running; if the value of the second random value is within the second numerical sub-range, it may be determined that the shift instruction information of the simulation target may be information indicating that the simulation target needs to perform acceleration running.

Alternatively, in general, the time point when the traveling speed of the simulation object is equal to the target traveling speed may be set such that the probability of performing acceleration traveling and the probability of performing deceleration traveling are equal, the sum of the probability of performing acceleration traveling and the probability of performing deceleration traveling may be 1, the probability of performing acceleration traveling may be understood as a ratio of the first numerical value sub-range to the target numerical value sub-range, the probability of performing deceleration traveling may be understood as a ratio of the second numerical value sub-range to the target numerical value sub-range, and thus the first numerical value sub-range may be a half range of the target numerical value range, and the second numerical value sub-range may be a range of the other half of the target numerical value range. If the first numerical sub-range can be a numerical range of (0, 0.5), the second numerical range can be a numerical range of (0.5, 1).

In some possible embodiments, the probability of performing acceleration running and the probability of performing deceleration running may be different at a time point when the running speed of the simulation object is equal to the target running speed, and may be determined according to an actual application scenario without limitation.

Further, the processing device may calculate the driving acceleration of the simulation object at the i-th time point by the obtained target driving speed, the target acceleration, the driving speed of the simulation object at the i-1-th time point, and the target speed change ratio, and the process may include:

the processing device may acquire a difference (may be referred to as a speed difference) between the target running speed and the running speed of the simulation object at the i-th point in time, and may calculate a product value between an absolute value of the speed difference and the target speed change ratio, which may be referred to as an acceleration adjustment value (which is a positive value, i.e., a positive number).

It is understood that the value of the acceleration adjustment value is less than or equal to the absolute value of the target acceleration. Next, the processing device may calculate the running acceleration of the simulation object at the i-th point in time by the target acceleration and the acceleration adjustment value: if the target acceleration is the first acceleration and the i-th time point is a time point before the traveling speed of the simulation object is reduced (first reduced) from the target traveling speed to the first traveling speed, the sum of the first acceleration (negative value) and the acceleration adjustment value (positive value) may be regarded as the traveling acceleration (negative value) of the simulation object at the i-th time point.

The first running speed may be equal to a difference between the target running speed and a first ratio, which may refer to a ratio between an absolute value of the first acceleration and a target speed variation ratio. Since if the i-th time point is a time point when the traveling speed of the simulation object is equal to the target traveling speed, the difference between the target traveling speed and the traveling speed of the simulation object at the i-th time point is 0, and at this time, the traveling acceleration of the simulation object at the i-th time point may be the target acceleration (i.e., the first acceleration).

Further, if the target acceleration is the first acceleration and the i-th time point is a time point when the traveling speed of the simulation object is reduced (first reduced) from the target traveling speed to the first traveling speed or after the first traveling speed, the acceleration adjustment value may be directly regarded as the traveling acceleration (positive value) of the simulation object at the i-th time point. The first travel speed is smaller than the target travel speed, and it is understood that when the travel speed of the simulation object gradually decreases from the target travel speed toward the first travel speed, the absolute value of the travel acceleration of the simulation object gradually decreases toward 0. Therefore, the range in which the traveling speed of the simulation object fluctuates within the range of less than or equal to the target traveling speed is the range from the first traveling speed to the target traveling speed.

Further, it is understood that, if the i-th time point is a time point when the traveling speed of the simulation object decreases to the first traveling speed, the difference between the target traveling speed and the traveling speed of the simulation object at the i-th time point may be a difference obtained by subtracting the first traveling speed from the target traveling speed, and since the first traveling speed is equal to a difference between the target traveling speed and the first ratio, the difference obtained by subtracting the first traveling speed from the target traveling speed is the first ratio, which is in turn equal to a ratio obtained by dividing the absolute value of the first acceleration by the target speed change ratio, and therefore, a product value of the difference (equal to the first ratio) of the target traveling speed from the first traveling speed multiplied by the target speed change ratio is equal to the absolute value of the first acceleration, that is, the acceleration adjustment value is equal to the absolute value of the first acceleration at this time, that is, and the traveling acceleration of the simulation object at i-time points is equal to the absolute value of the target acceleration. With this, after the running speed of the simulation object is reduced to the first running speed, the acceleration running can be started by taking the absolute value of the target acceleration as the running acceleration, and the whole acceleration or deceleration judgment process is circulated again until the target running speed is accelerated, so that the current gear shift instruction information is acquired again.

Through the above process, if the running speed of the simulation object reaches the target running speed, if the running is required to be decelerated, the running acceleration of the simulation object may gradually change from the target acceleration to 0 (i.e. from rapid deceleration to slow deceleration until the speed tends to be non-deceleration) in the process that the running speed of the simulation object is reduced to the first running speed, and after the running speed of the simulation object is reduced to the first running speed, the running acceleration of the simulation object may gradually change from the absolute value (positive acceleration) of the target acceleration to 0 (i.e. from rapid acceleration to slow acceleration until the speed tends to be non-acceleration), until the running speed reaches the target running speed again, and the current speed change instruction information is acquired again.

Similarly, if the target acceleration is the second acceleration and the i-th time point is a time point before the traveling speed of the simulation object increases (first increases) from the target traveling speed to the second traveling speed, the difference obtained by subtracting the acceleration adjustment value (positive value) from the second acceleration (positive value) may be regarded as the traveling acceleration (positive value) of the simulation object at the i-th time point.

The second running speed may be equal to a sum of the target running speed and a second ratio, where the second ratio may be a ratio obtained by comparing a value of the second acceleration with a target speed variation ratio. Since if the i-th time point is a time point when the traveling speed of the simulation object is equal to the target traveling speed, the difference between the target traveling speed and the traveling speed of the simulation object at the i-th time point is 0, and at this time, the traveling acceleration of the simulation object at the i-th time point may be the target acceleration (i.e., the second acceleration).

Further, if the target acceleration is the second acceleration and the i-th time point is a time point when the traveling speed of the simulation object increases from the target traveling speed to (first to) the second traveling speed or after increasing to the second traveling speed, the opposite number (negative value, that is, negative number) of the acceleration adjustment value may be regarded as the traveling acceleration (negative value) of the simulation object at the i-th time point. The second running speed is greater than the target running speed, and it is understood that when the running speed of the simulation object gradually increases from the target running speed toward the second running speed, the running acceleration of the simulation object gradually decreases toward 0. Therefore, the range in which the traveling speed of the simulation object fluctuates in the range greater than or equal to the target traveling speed is the range from the target traveling speed to the second traveling speed.

It will be appreciated that, if the i-th time point is a time point when the running speed of the simulation object increases to the second running speed, the difference between the target running speed and the running speed of the simulation object at the i-th time point may be a difference obtained by subtracting the target running speed from the second running speed (i.e., an absolute value of the speed difference), and since the second running speed is equal to a sum of the target running speed and the second ratio, the difference obtained by subtracting the target running speed from the second running speed is a second ratio which is equal to a ratio obtained by dividing the value of the second acceleration by the target speed change ratio, and therefore, a product of the difference (equal to the first ratio) of the second running speed and the target speed change ratio is equal to the value of the second acceleration, that is, a counter of the acceleration adjustment value is equal to a counter of the second acceleration at this time, that is, and the running acceleration of the simulation object at i-time points is equal to the counter of the target acceleration. With this, after the running speed of the simulation object is increased to the second running speed, the deceleration running can be started with the opposite number of the target acceleration as the running acceleration, and the entire acceleration or deceleration judgment process is circulated again until the target running speed is decelerated, so that the current gear shift instruction information is acquired again.

By the above-mentioned process, if acceleration running is required when the running speed of the simulation object reaches the target running speed, the running acceleration of the simulation object may gradually decrease from the target acceleration to 0 (i.e., from rapid acceleration to slow acceleration until no acceleration is caused) in the process that the running speed of the simulation object increases to the second running speed, and after the running speed of the simulation object increases to the second running speed, the running acceleration of the simulation object may gradually change from the opposite number of the target acceleration (negative acceleration) to 0 (i.e., from rapid deceleration to slow deceleration until no deceleration is caused), until the running speed reaches the target running speed again, and the current speed change instruction information is acquired again.

By the above process, the calculation of the running acceleration of the simulation object at each time point is realized in the process that the running speed of the simulation object needs to fluctuate.

It is understood that if the target acceleration is a negative value, the running acceleration of the simulation object may fluctuate within a range between the target acceleration and 0, and if the target acceleration is a positive value, the running acceleration of the simulation object may fluctuate within a range between 0 and the target acceleration. Further, it is understood from the above-described process that the traveling speed of the simulation object can be made to fluctuate within different adjacent ranges of the target traveling speed by setting different target speed change ratios to the simulation object.

For example, taking the case where the shift indication information is used to indicate that the simulated object needs to run at a speed reduction, if the target running speed is 70 (alternatively, the unit may be kilometers per hour), the target acceleration is-10 (may be the first acceleration), and the target speed change ratio is 1/3, when the simulated object runs at a speed reduction of-10 acceleration from the running speed of 70 (during the speed reduction running, since the running speed changes, the difference between the running speed and the target running speed changes, the acceleration adjustment value also changes, and the running acceleration also changes), so that when the running speed becomes 60, the running acceleration at this time may change to: 10- [ (70-60) × (1/3) ], i.e. a change of about 6.67, and when the running speed becomes approaching 40, the running acceleration may be changed to approach: 10- [ (70-40) × (1/3) ], i.e., approaching 0, and then acceleration running (in the acceleration running process, since the running speed changes, the difference between the running speed and the target running speed changes, and thus the acceleration adjustment value also changes, so that the running acceleration also changes), and when the running speed again increases to 70, the shift instruction information can be re-acquired, and the simulation object can perform subsequent running according to the same principle as described above.

Further, the processing apparatus may also generate the lane indicating information of the simulation object at the i-th time point by the lane change pattern, the lane preference pattern, and the lane indicating information of the simulation object at the i-1 th time point, as described below.

For example, the driving lane may refer to a lane (may include a left lane, a middle lane, a right lane, and the like). Therefore, it is also possible to set an initial travel lane for the simulation object, that is, a travel lane where the simulation object starts traveling from the start traveling position. Since the travel speed of the simulation object is not changed until the travel speed is changed from the initial travel speed to the target travel speed, the travel path indication information of each point in time when the simulation object is changed from the initial travel speed to the target travel speed and before the change to the target travel speed may be the initial travel path indication information, and the travel path indication information may be indication information that does not need to change the path, that is, indication information that indicates that the simulation object keeps the current travel path for traveling without changing the travel path.

Thus, for example, it is described below how the travel-to-indication information of the simulation object at the i-th point in time is generated by the travel-lane changing pattern, the travel-lane preference pattern, and the travel-lane indication information of the simulation object at the i-1-th point in time after the travel speed of the simulation object is changed from the initial travel speed to the target travel speed.

If the simulation object needs to change the track, the processing device may acquire a track changing duration of the simulation object, where the track changing duration may be a duration from starting to ending of the track changing, and the track changing duration may be a preset duration (for example, 3 seconds or 5 seconds). Therefore, if the driving lane indication information of the i-1 th time point is used for indicating that the simulation object is in the continuous lane change state in the target period (the time length is equal to the lane change time length), and the i-th time point belongs to the time point in the target period, it can be determined that the simulation object is also in the lane change state at the i-th time point, and the lane change state is kept for continuous lane change, so that the driving lane indication information of the simulation object at the i-th time point can also be the indication information that the simulation object is in the continuous lane change state in the target period. In the above scenario, the i-1 th time point may be any one of time points within the target period.

If the lane indicator information at the i-1 th time point is used to indicate that the simulation object has no lane change at the i-1 th time point (i.e. is not in a lane change state), the processing device may determine whether the simulation object needs to start lane change at the i-1 th time point and which lane needs to be changed if a lane change is desired (i.e. which lane). And if the driving lane indication information of the i-1 th time point is used for indicating that the simulation object is in the continuous lane change state in the target period and the i-th time point does not belong to the time point in the target period, the processing device can also judge whether the simulation object needs to start lane change at the i-th time point and which lane needs to be changed if the lane needs to be changed.

By way of example, the following detailed description will determine whether the simulation object needs to start lane change at the i-th point in time and the flow of which lane needs to be changed if a lane is to be changed, by the lane change mode and the lane preference mode.

First, the processing apparatus may determine a lane on which the simulation object needs to travel at the i-th point in time, which may be referred to as a target lane, by a lane change pattern and a lane preference pattern set to the simulation object, and the process may include:

the lane change pattern set by the simulation object may be associated with a numerical sub-range within the target numerical range, which may be a range for determining that the simulation object does not need to change lanes, and since the simulation object is currently traveling to the i-1 th time point and is not traveling to the i-th time point (because the traveling parameter of the i-th time point is also being calculated), the lane where the simulation object is located at the i-1 th time point may be referred to as the current lane, and the numerical sub-range associated with the lane change pattern set by the simulation object may be a range for determining whether the simulation object needs to remain in the current lane without changing lanes.

The range size of the numerical sub-range associated with the driving lane change mode set by the simulation object can be used for guaranteeing the magnitude of the lane change probability of the simulation object, and the larger the numerical sub-range (the larger the numerical value is, the larger the range is) the larger the probability of lane change of the simulation object is, and the smaller the numerical sub-range is, the smaller the probability of lane change of the simulation object is.

The numerical sub-range associated with the mode of the slight lane change may be smaller than the numerical sub-range associated with the mode of the normal lane change, and the numerical sub-range associated with the mode of the normal lane change may be smaller than the numerical sub-range associated with the mode of the frequent lane change. The numerical subrange associated with the various lane change patterns may be a fixed numerical subrange set in advance.

The simulation object may have at least one running lane (one or more running lanes) that can run at the i-th point in time, and the processing apparatus may acquire a numerical sub-range in which each of the at least one running lane except the current running lane is within the target numerical range, respectively, and one running lane may correspond to one numerical sub-range by a running lane preference mode set by the simulation object.

According to the different driving lane preference modes, the range sizes of the numerical value sub-ranges corresponding to the driving lanes except the current driving lane in at least one driving lane may also be different, the numerical value sub-ranges corresponding to the driving lanes (such as a left lane, a middle lane or a right lane) which are set in the driving lane preference mode and are suitable for driving may be larger than the numerical value sub-ranges corresponding to the driving lanes (such as a left lane, a middle lane or a right lane) which are suitable for driving, that is, the proportion of the numerical value sub-ranges corresponding to the driving lanes (such as a left lane, a middle lane or a right lane) which are suitable for driving in the target numerical value range may be larger than the proportion of the numerical value sub-ranges corresponding to the driving lanes corresponding to the other driving lanes in the target numerical value range, and the numerical value sub-ranges corresponding to the driving lanes in the driving lane preference mode may also be preset.

Alternatively, in various driving lane preference modes, for each possible current driving lane, the numerical sub-ranges associated with each driving lane change mode may be combined separately, and the corresponding numerical sub-ranges may be set for driving lanes other than the current driving lane according to the above-described rule, so that the numerical sub-ranges corresponding to the current driving lane and the numerical sub-ranges corresponding to driving lanes other than the current driving lane in the at least one driving lane do not have an overlap therebetween, and may together form the target numerical range.

Through the above process, the numerical value sub-ranges corresponding to the driving lanes of the simulation object at the ith time point can be obtained, the numerical value sub-ranges corresponding to the driving lanes can be reasonably set in advance according to the changing modes of the driving lanes and the preference modes of the driving lanes, the numerical value sub-ranges corresponding to the driving lanes are specifically which numerical value sub-ranges, and the numerical value sub-ranges can be set by themselves according to the actual application scene, so that the method is not limited.

Further, the processing device may generate a random number for determining the target travel lane within the target numerical value range, the random number may be referred to as a third random number, and the processing device may set a travel lane corresponding to a numerical value sub-range in which the numerical value of the third random number is located, as the target travel lane, in at least one travel lane in which the i-th travel lane is drivable by the simulation object.

Therefore, if the target lane is different from (i.e., inconsistent with) the lane in which the simulation object is located at the i-1 th time point (i.e., the current lane), it indicates that the simulation object needs to change lanes at the i-th time point, that is, from the current lane to the target lane, and therefore, in this case, the lane indication information of the simulation object at the i-th time point may include an indication that the simulation object needs to change lanes (indicating that the simulation object needs to change lanes to the target lane) and the target lane (indicating that the simulation object needs to change lanes to the target lane).

In this case, the lane indicating information of the simulation object at the i-th time point may be indicating information indicating that the simulation object does not need to change lanes (i.e., indicating that the simulation object does not need to change lanes at the i-th time point and is kept traveling on the current lane).

Alternatively, the process of determining the target driving lane may be a process of determining the driving lane indication information of the simulation object at the i-th time point in a case where the at least one driving lane on which the simulation object can drive at the i-th time point includes the current driving lane.

For example, if at least one driving lane that the simulation object can drive at the i-th point in time does not contain the current driving lane, the following rule may be set in such a scenario: if the current driving lane is the most marginal driving lane (e.g., the leftmost lane or the rightmost lane), the lane may be changed directly to the nearest driving lane to the current driving lane at the i-th time point.

For example, if the current driving lane where the simulation object is located at the i-1 th time point is the leftmost lane, the lane where the simulation object can drive at the i-1 th time point can be directly found as the target driving lane, so that the simulation object can start lane change to the target driving lane at the i-1 th time point. The lane change from the current lane to the target lane may be a single lane change if the target lane is immediately adjacent to the current lane, or a continuous lane change if the target lane is further separated from the current lane by another lane.

For another example, if the current driving lane where the simulation object is located at the i-1 th time point is the rightmost lane, the lane where the simulation object can drive at the i-1 th time point can be directly found as the target driving lane, so that the simulation object can start lane changing to the target driving lane at the i-1 th time point. Similarly, if the target driving lane is the driving lane adjacent to the current driving lane, the lane change from the current driving lane to the target driving lane may be a single lane change, and if the target driving lane is further separated from the current driving lane by another driving lane, the lane change from the current driving lane to the target driving lane may be a continuous lane change.

More, if the current driving lane where the simulation object is located at the i-1 th time point is the driving lane in the middle of the road (such as the middle lane), and the driving lanes where the simulation object can drive at the i-1 th time point do not include the current driving lane, then the corresponding numerical value sub-ranges (which can jointly form the target numerical value range) may be set for the driving lanes where the simulation object can drive at the i-th time point, so that the driving lane where the numerical value sub-range where the random number is located may be generated as the target driving lane where the simulation object needs to change lanes at the i-th time point, and thus the driving lane where the simulation object can drive to the left side or the driving lane where the simulation object can drive to the right side may be changed (which may also be a single lane changing lane or a continuous changing lane). In this case, the numerical sub-ranges corresponding to the driving lanes on which the simulation object can drive at the ith time point may be determined according to the actual application scenario, which is not limited.

For example, if the simulation object needs to travel on the ramp (which can be understood as an auxiliary road or a sub-road) at the i-1 th time point and needs to be converged into the main road (main road) at the subsequent time point, the simulation object can be changed to the lane capable of converging into the main road on the ramp in advance, so that the simulation object can accurately and truly converge into the main road from the ramp. For example, in this scenario, if it is required to enter the main road 10 meters before reaching the junction of the ramp and the main road (i.e., the road junction where the ramp merges into the main road), the i-th time point may be the time point when the simulation object travels 10 meters before reaching the junction.

Optionally, after the target path is obtained, the present application may also obtain the road information (for example, may include information such as a road identifier, a road type, a lane width, a lane type (for example, an emergency lane, a non-motor vehicle lane, a motor vehicle lane, etc.), a longitude and latitude of a center line of a lane, a longitude and latitude of a starting point of a road, etc.) of each section of the road included in the target path in the high-precision map, and further, the processing device may perform lane planning of the above process on the simulated object according to the road information of each section of the road on which the simulated object is traveling in the target path, where the lane planning includes, but is not limited to: the road information of each section of road is used for determining the runnable lanes of the simulation object at each time point, such as emergency lanes and non-runnable motor vehicle lanes, and the runnable lanes before the ramp is converged into the main road are only the lanes at the connection part with the main road, and the like.

It will be appreciated that the lane indication information generated at the i-th time point of the simulation object may be used to determine a lane (e.g., a lane) on which the simulation object needs to travel at the i-th time point. By the above-described process, the travel speed, the travel acceleration, and the travel direction information of the simulation object at the i-th time point are obtained, and the travel speed, the travel acceleration, and the travel direction information of the simulation object at the i-th time point can be used as the travel parameter of the simulation object at the i-th time point.

By adopting the method, the driving parameters of the simulation object at each time point indicated by the target time interval in the driving process can be obtained.

Step S202, driving the simulation object to travel according to the corresponding travel parameter at the time point indicated by the target time interval.

Optionally, the simulation object is configured to perform the driving according to the driving parameter at any time point, such as the simulated driving on the corresponding driving lane according to the driving speed, the driving acceleration and the driving lane indication information included in the driving parameter at any time point, in a period from any time point indicated by the target time interval to a next time point of the any time point.

Thus, the processing device may drive the simulation object to travel on the target path at each point in time indicated by the target time interval according to the travel parameter corresponding to the each point in time, respectively. Optionally, since the target path may be a road-level planned path, and does not include a running lane where the simulated object specifically needs to run, the processing device may determine, according to the running parameters of the time points indicated by the target time intervals, the running lane (e.g., a lane) where the simulated object runs at each time point indicated by the target time intervals, and further map the target path onto the specific running lane (e.g., onto the specific lane) where the simulated object runs at each time point in the high-precision map, so as to implement lane-level simulated running of the simulated object.

Referring to fig. 7, fig. 7 is a schematic view of another scenario in which a simulation object performs a simulated driving according to the present application. As shown in fig. 7, through the above-mentioned process, it is possible to achieve flexible lane changing of the simulation object on the road, where the lane changing from the leftmost lane to the middle lane is possible, and after the middle lane has traveled a certain distance, the lane changing from the middle lane to the rightmost lane is possible.

Referring to fig. 8 again, fig. 8 is a schematic view of a scene of a simulated running of a simulated object according to the present application. As shown in FIG. 8, the track formed by the small circles can be the driving track of the simulation object, and by adopting the lane changing method of the application, the simulation object can reasonably and accurately gather into the main road from the ramp.

Referring to fig. 9, fig. 9 is a schematic view of a scene of a simulated running of a simulated object according to the present application. As shown in fig. 9, the track formed by the small circles can be the driving track of the simulation object, and by adopting the method provided by the application, the non-driving lanes and the driving lanes of the simulation object at each time point can be judged at first, and further, the simulation object can be changed from the current lane to the driving lane (the driving lane can be changed in advance).

Here, the simulated object needs to merge from the ramp into the main road (e.g., a specified distance or a specified duration before traveling to the junction of the ramp and the main road), the lanes on which the simulated object can travel may include lane 3 and lane 4, and the lanes on which the simulated object cannot travel may include lane 1 and lane 2.

In the present application, when the simulation object travels on the travel path (including no lane change process), the simulation object may be considered to travel along the center line of the travel path, and thus, the travel position of the simulation object calculated later when the simulation object is not in the lane change state may be the position on the center line of the travel path. The simulated object may have a lane-changing track in the lane-changing process, the lane-changing track may be a diagonal line segment, the starting position of the diagonal line segment may be a position on a central line of the lane where the simulated object starts to change lanes, the ending position of the diagonal line segment may be a position on a central line of the lane where the simulated object starts to change lanes after the lane-changing is completed, and the length of the diagonal line segment may be calculated according to a lane-changing duration (i.e., a duration of a target period), a running speed and a running acceleration of the simulated object in the lane-changing process, so that the running position of the simulated object in the lane-changing process may be a position on the lane-changing track.

The application can carefully simulate the running behavior of the real running object by the aid of a series of fine running behavior modes including the speed range mode, the speed change mode, the running lane change mode and the running lane preference mode which are set by the simulation object, so that more real simulation positioning information can be obtained.

Referring to fig. 10, fig. 10 is a flowchart of a method for generating simulated positioning information according to the present application. As shown in fig. 10, the method may include:

step S301, acquiring a starting travel position of a target path.

Alternatively, the processing device may acquire a start travel position of the target path, that is, a position at which the simulation object starts traveling on the target path.

Step S302, calculating a simulated driving position of the simulated object at the target time point based on the driving parameters of each time point before the target time point indicated by the start driving position and the target time interval.

Alternatively, any one of the time points indicated by the target time interval may be referred to as a target time point, and one of the time points indicated by the target time interval may generate one piece of simulated positioning information. The processing device may calculate a driving position of the simulation object at the target time point (may be referred to as a target driving position) by the above-described starting driving position and driving parameters at respective time points before the target time point.

The processing device may calculate, through the driving parameters of each time point before the target time point, a total driving distance (may be referred to as a total driving distance) of the processing device before the target time point, where the total driving distance is also a total driving distance of the simulation object before the target time point, and further, a center line (may be a curve, a straight line, or a combination of a straight line and a curve) of all driving tracks of the simulation object before the target time point and a lane change track (oblique line segment) may form (are connected to) a curve, which is referred to as a driving track of the simulation object before the target time point, and may start along the driving track from a starting driving position (may also be on the driving track), and a position where a distance between the driving track and the starting driving position is the total driving distance is taken as a driving position of the simulation object at the target time point.

For example, since the distance traveled by a simulation object from a point in time to a next point in time can be calculated from the travel parameter of the point in time, the distance traveled by the simulation object from each point in time to the next point in time can be calculated from the travel parameter of each point in time preceding the target point in time, and the distances traveled by each point in time to the next point in time form the total travel distance.

Wherein the total distance travelled may be calculated by invoking a location model, which may be expressed as a formulaA represents a running acceleration, the formula may be a formula for calculating a distance traveled by the simulation object from any point in time to a next point in time of the any point in time by a running parameter of the any point in time, and a running position of the simulation object may be determined by the calculated distance.

Further, since the obtained driving position usually contains some noise (such as noise caused by the scene or signal quality) in the actual positioning navigation scene, the noise distribution approaches to gaussian distribution, and the target driving position is the calculated accurate driving position, so the processing device may further perform the noise adding process on the target driving position to more truly simulate the driving position in the real scene, the driving position obtained after the noise adding process on the target driving position may be referred to as a simulated driving position, and the noise adding process on the target driving position may be described as follows.

The target travel position may include a plurality of position components. For example, the target travel position may be a 3-dimensional position in a coordinate system of the simulation object (may be a coordinate system with a center of the simulation object as an origin), and the coordinate system of the simulation object may include 3 coordinate axes in total, such that the plurality of position components included in the target travel position may include a position component in the x-axis (i.e., a value in the x-axis), a position component in the y-axis (i.e., a value in the y-axis), and a position component in the z-axis (i.e., a value in the z-axis).

Therefore, the processing device may acquire a gaussian noise distribution (i.e., noise appearing as a gaussian distribution) associated with each of the position components of the target running position, the gaussian noise distribution associated with each of the position components may be preset, one of the position components is associated with one of the gaussian noise distributions, and the gaussian noise distribution associated with one of the position components is used for noise adding processing of the position component. The gaussian noise distributions associated with the components at different positions can be the same or different, and can be specifically set according to actual application scenes without limitation.

The processing device may sample the gaussian noise for each location component separately in a gaussian noise distribution associated with each location component (i.e., the noise sampled in the gaussian noise distribution may be declared to be gaussian noise), and the gaussian noise sampled for each location component may be declared to be additive gaussian noise for each location component. Alternatively, the noise-added gaussian noise may be a smaller noise, e.g., the noise may be smaller than a noise threshold, which may be the maximum of the gaussian noise distribution, which may be a smaller threshold set. I.e. for one of the target driving positions, the gaussian noise added to that position component may be obtained by sampling (which may be a random sampling) in a gaussian noise distribution associated with that position component.

Furthermore, the processing device may perform noise adding processing on each position component of the target running position by using the noise adding gaussian noise of each position component of the target running position (for example, the noise adding gaussian distribution of each position component is superimposed on each position component) to obtain a noise added position component corresponding to each position component, where the noise added position component corresponding to each position component of the target running position may form the simulated running position, that is, the simulated running position may include the noise added position component corresponding to each position component in the target running position.

The noise adding gaussian noise of any one position component of the target driving position may be used to add noise to the any one position component, and the noise adding process of any one position component may be understood as performing position offset on any one position component, so as to obtain the offset position component of any one position component. The simulated running position is composed of the shifted position components of the respective position components of the target running position, and may correspond to a real position on a map (e.g., a high-definition map), i.e., the simulated running position may be a position in the real world.

Referring to fig. 11, fig. 11 is a schematic view of a scenario for generating a simulated driving position according to the present application. As shown in fig. 11, the target travel position may include a branch component 1 on the x-axis, a position component 2 on the y-axis, and a position component 3 on the z-axis.

The gaussian noise distribution associated with the position component 1 may be the gaussian noise distribution 1, the gaussian noise distribution associated with the position component 2 may be the gaussian noise distribution 2, and the gaussian noise distribution associated with the position component 3 may be the gaussian noise distribution 3.

The processing device can perform random sampling of noise from the Gaussian noise distribution 1 to obtain the noise-added Gaussian noise 1 of the position component 1, can perform random sampling of noise from the Gaussian noise distribution 2 to obtain the noise-added Gaussian noise 2 of the position component 2, and can also perform random sampling of noise from the Gaussian noise distribution 3 to obtain the noise-added Gaussian noise 3 of the position component 3.

Furthermore, the processing device may perform the noise adding process on the position component 1 by using the noise adding gaussian noise 1, may obtain a position component after the noise adding on the x-axis, may perform the noise adding process on the position component 2 by using the noise adding gaussian noise 2, may obtain a position component after the noise adding on the y-axis, may further perform the noise adding process on the position component 3 by using the noise adding gaussian noise 3, and may obtain a position component after the noise adding on the z-axis.

The above-mentioned position component after noise addition on x axis, position component after noise addition on y axis and position component after noise addition on z axis form the simulation running position.

Step S303, generating simulation positioning information based on the simulation running position.

Optionally, the processing device may perform conversion processing on the satellite signal of the obtained simulated driving position to generate a simulated satellite signal of the simulated object at the target time point (the simulated satellite signal is a simulated GPS signal).

The process of converting satellite signals by the processing equipment for the simulated driving position comprises the following steps: the processing device may convert the longitude and latitude of the simulated travel location to obtain the longitude and latitude of the simulated travel location, which may be the simulated satellite signal (i.e., the simulated satellite signal) of the simulated object at the target point in time.

Alternatively, the processing device may also acquire satellite signals of the satellite base station (i.e. GPS signals at the satellite base station), which may be monitored by the satellite base station at the location of the satellite base station, which may be referred to as reference satellite signals.

Furthermore, the processing device may perform differential processing on the reference satellite signal and the simulated satellite signal, so as to generate a differential satellite signal (i.e., a simulated RTK signal) of the simulated object at the target time point.

It will be appreciated that, since the navigation object generally moves following the simulation object within the simulation object, the position of the navigation object (the position to which the navigation object moves following) and the position of the simulation object (e.g. the driving position) may be considered to be the same, and the GPS signal of the navigation object and the GPS signal of the simulation object may also be considered to be the same, the processing device may directly use the calculated simulated satellite signal of the simulation object at the target time point as the simulated satellite signal of the navigation object at the target time point, and may directly use the calculated differential satellite signal of the simulation object at the target time point as the differential satellite signal of the navigation object at the target time point.

The simulated positioning information of the navigation object may include a simulated satellite signal (i.e., a simulated GPS signal) and a differential satellite signal (i.e., a simulated RTK signal) of the navigation object at the target time point. It will be appreciated that a simulated satellite signal and a differential satellite signal corresponding to the navigation object may be generated at each time point indicated by the target time interval, and thus the simulated positioning information of the navigation object may include the simulated satellite signal and the differential satellite signal of the navigation object at each target time point indicated by the target time interval.

By adopting the method, the calculated target running position is subjected to noise adding treatment, so that a more real simulated running position can be obtained through simulation, and further more accurate simulated positioning information of the navigation object can be generated through the simulated running position.

Referring to fig. 12, fig. 12 is a flowchart illustrating another method for generating simulated positioning information according to the present application. As shown in fig. 12, the method may include:

in step S401, if the simulation object is not in the lane change state at the target time point, the default angular velocity and the running acceleration of the simulation object at the target time point are determined as the target sensing signal of the simulation object at the target time point.

Optionally, the target time point is any one of time points indicated by the target time interval. If the simulation object is not in the lane change state at the target time point, it indicates that the simulation object is in the straight running state at the target time point, at this time, the default angular velocity (may be a default running angular velocity set in advance) and the running acceleration of the simulation object at the target time point may be used as the sensing signal of the simulation object at the target time point, and the sensing signal of the simulation object at the target time point may be referred to as the target sensing signal (belonging to the simulated IMU signal).

Wherein, since the simulation object is straight, indicating that there is no rotation of the simulation object, the rotation angle is 0, the default angular velocity may be 0.

In step S402, if the simulation object is in the lane change state at the target time point, the driving angular velocity of the simulation object is determined based on the lane change trajectory of the simulation object at the target time point, and the driving angular velocity and the driving acceleration of the simulation object at the target time point are determined as the target sensing signal of the simulation object at the target time point.

Alternatively, if the simulation object is in the lane change state at the target time point, the driving angular velocity of the simulation object at the target time point may be determined by simulating the lane change track of the simulation object at the target time point, as described below.

In the physical sense, the traveling angular velocity of the simulation object at the target time point may be a velocity at which the simulation object makes an angular rotation at the target time point. The driving angular velocity can also be calculated by simulating the slope of the lane change track where the object is at the target time point:

firstly, the processing device can obtain the slope of the lane change track (which can be a diagonal line segment) of the simulation object at the target time point, further, the processing device can calculate the inclination angle of the lane change track compared with the straight track through the slope, and further, the ratio obtained by dividing the inclination angle by the lane change duration can be used as the running angular speed of the simulation object at the target time point.

Further, the processing device may use the calculated travel angular velocity of the simulation object at the target time point and the calculated travel acceleration of the simulation object at the target time point as target sensor signals of the simulation object at the target time point.

Step S403, based on the target sensing signal, generating a simulated sensing signal of the navigation object at a target time point; the simulated positioning information comprises a simulated sensing signal.

Alternatively, the navigation object may be located in a first reference coordinate system, where the first reference coordinate system may use the position of the navigation object (such as the central position of the navigation object, in fact, since the navigation object is usually smaller in volume, it may also be any position on the navigation object) as the origin point coordinate system; the simulated object may be in a second reference coordinate system, which may be a coordinate system with the position of the simulated object (e.g., the center position of the simulated object, particularly the center position of the vehicle) as an origin.

The navigation object can be placed in the simulation object, so that the user terminal can be simulated to be placed in the driving object (vehicle), and then the scene of positioning navigation test on the driving object by using the user terminal can be simulated through the simulation positioning information of the user terminal.

Since the target sensing signal is a sensing signal calculated from the analog object, the target sensing signal may be a signal belonging to the second reference frame. The application can convert and map the target sensing signal from the second reference coordinate system to the first reference coordinate system, thereby obtaining the simulated sensing signal of the navigation object at the target time point (i.e. the IMU signal simulated for the navigation object).

For example, the process of converting and mapping the target sensor signal from the second reference frame to the first reference frame may include: the processing device may obtain a coordinate system conversion parameter between the first reference coordinate system and the second reference coordinate system, where the coordinate system conversion parameter belongs to an external parameter, and the coordinate system conversion parameter may be reasonably set in advance for the first reference coordinate system and the second reference coordinate system, and how to set the coordinate system conversion parameter specifically may be set according to an actual application scenario, which is not limited.

Wherein the coordinate system conversion parameters comprise rotation parameters that can be used to characterize the rotation relationship between the first reference coordinate system and the second reference coordinate system and translation parameters that can be used to characterize the translation relationship between the first reference coordinate system and the second reference coordinate system. The second reference frame is rotated according to the rotation parameter and translated according to the translation parameter, and then the second reference frame can be converted into the first reference frame, which can be understood that the second reference frame can be overlapped with the first reference frame after being rotated (such as rotated by a designated angle) according to the rotation parameter and translated (such as translated by a designated distance) according to the translation parameter. It will be appreciated that the coordinate system conversion parameter may be used to indicate a positional relationship (e.g., translational and rotational) between the simulated object and the navigation object, in other words, the coordinate system conversion parameter may also be used to indicate a relative position between the simulated object and the navigation object, e.g., it may also be understood that the coordinate system conversion parameter indicates how much distance the central position of the simulated object needs to be translated and how much angle the central position of the navigation object is rotated to be reached.

Thus, the processing device may map the target sensor signal from the second reference frame to the first reference frame by the coordinate system conversion parameter. The target sensing signal can be understood as a point under the second reference coordinate system, the point can be converted into the first reference coordinate system by rotating and translating the point according to the coordinate system conversion parameters, the point under the first reference coordinate system can represent the simulated sensing signal of the navigation object at the target time point, and the simulated sensing signal can represent the direction and the position of the simulated navigation object placed in the simulated object at the target time point.

The simulated positioning information of the navigation object may comprise simulated sensory signals of the navigation object at the target point in time. It will be appreciated that according to the above principle, the simulated sensing signal of the navigation object may be generated at each time point indicated by the target time interval, i.e. the navigation object has a corresponding simulated sensing signal at each time point indicated by the target time interval.

Therefore, the simulated positioning information of the navigation object in the application can comprise simulated satellite signals, differential satellite signals and simulated sensing signals of the navigation object at the target time point, and further, the simulated positioning information of the navigation object can comprise simulated satellite signals, differential satellite signals and simulated sensing signals of the navigation object at each time point indicated by the target time interval.

In general, the acquisition frequency of the IMU signal is higher than the acquisition frequency of the GPS signal, so it may be considered that the simulated sensing signal of the navigation object at the target time point may include the sensing signal of the navigation object at each sensing time point in the period of the target time point and the next time point (belonging to the time point indicated by the target time interval) of the target time point, that is, the simulated sensing signal of the navigation object at the target time point may include a plurality of sensing signals in the period of the target time point and the next time point of the target time point.

Wherein, since the lane change track of the simulation object from the target time point to the next time point of the target time point is the same, the sensing signals of the simulation object at each sensing time point within the target time point and the next time point (the time point indicated by the target time interval) of the target time point can be considered to be the same regardless of whether the simulation object is in the lane change state at the target time point or not, and therefore, the sensing signals of the navigation object at each sensing time point within the target time point and the next time point (the time point indicated by the target time interval) of the target time point are also the same.

The sensing time point may be a time point taken within a period between a target time point and a time point next to the target time point according to a time interval indicated by the acquisition frequency of the IMU signal. For example, if the IMU signal acquisition frequency is 10 hz, and the 10 hz is 0.1 seconds and 1 time, the time interval indicated by the IMU signal acquisition frequency is 0.1 seconds, i.e., the time interval between any two adjacent sensing time points may be 0.1 seconds.

The application realizes that the related running parameters such as the running position (like the simulated running position) of the simulated object in the running process are determined, and then the simulated positioning information aiming at the navigation object is deduced based on the related running parameters such as the running position, so that the positioning information of the running object is not required to be acquired in a real scene by consuming a great amount of manpower and material resources, and the test of the positioning navigation of the running object in the running process can be realized through the simulated positioning information.

Through the process, the accurate generation of the simulated positioning information of the navigation object in the simulated running process of the simulated object is realized, and subsequently, the simulated positioning information can be used for performing navigation test on the position of the positioning object in the running process of the simulated object.

The simulation system provided by the application can save the cost of acquiring the positioning information of the real driving object by spending a great deal of manpower and material resources. In addition, the application can accurately simulate the driving lane (such as a lane) on which the simulated object is driven when the simulated object is driven, so that the obtained simulated positioning information can be used for testing the lane-level navigation positioning function of the driving object.

For example, a navigation system (which may be a navigation system associated with a simulated navigation object, and the navigation system may be a real system that needs to perform a navigation test) may be invoked to simulate and locate (e.g. locate at the acquisition frequency of the IMU signal) the driving position of the simulated object in the driving process (i.e. through the GPS signal, the RTK signal, and the IMU signal simulated for the navigation object, the driving position of the navigation object may be located) through the simulated positioning information of the navigation object. It can be understood that, at the time point of acquiring the GPS signal and the RTK signal (such as the time point indicated by the target time interval), the corresponding driving position can be calculated by the GPS signal and the RTK signal, and the acquisition frequency of the GPS signal and the RTK signal is relatively low, so that the problem of low acquisition frequency of the GPS signal and the RTK signal can be compensated by the IMU signal, and the driving position of the simulated object at each sensing time point can be calculated and simulated by the IMU signal in the interval period of acquiring the GPS signal and the RTK signal (such as the interval period between any two adjacent time points indicated by the target time interval).

Then, the specific lane on which the simulated object is driven can be further determined by the driving position of the simulated positioning, the navigation of the simulated object can be realized based on the driving position and the driving lane of the simulated object, and a simulated navigation log can be output, and the simulated navigation log can contain the simulated positioning information generated by the simulated object, and can contain the driving position, the driving lane and the like which are simulated and positioned by the simulated positioning information. And the running position and the running lane which are positioned by simulation can be compared with the running position and the running lane of the simulation object which are actually calculated and determined in the process to judge whether the positioning navigation of the navigation system is accurate or not (or whether the running position and the running lane are different greatly), if the positioning navigation of the navigation system is inaccurate, the prompt information of inaccurate positioning of the navigation system can be reported for reference of a developer of the navigation system, and therefore the test of the positioning navigation function of the navigation system is realized.

Referring to fig. 13, fig. 13 is a schematic view of a scenario for generating simulated positioning information according to the present application. As shown in fig. 13, the user may set a start travel position (i.e., a start position) and an end travel position (i.e., an end position) of the simulation object (i.e., the simulation vehicle herein), and may generate an SD route, which may be the target route described above, through the start travel position and the end travel position.

The user may also set a driving mode (i.e., a target driving mode) of the simulation object, and then, the target driving mode may be combined with a driving model of the vehicle to drive the simulation object to perform lane-level driving on a target path of the high-precision map.

The driving model of the vehicle may include a vehicle speed model, a speed change model, a lane change model, and a position model, among others. The vehicle speed model defines a calculation mode of the running speed of the simulation object (such as the mode described in the corresponding embodiment of fig. 5) and is used for calculating the running speed of the simulation object during running (such as the running speed of the simulation object at each time point indicated by the target time interval); the speed change model defines a calculation mode of the running acceleration of the simulation object (such as the mode described in the corresponding embodiment of fig. 5) and is used for calculating the running acceleration of the simulation object during running (such as the running acceleration of the simulation object at each time point indicated by the target time interval); the lane change model defines a determination mode of speed change indication information of the simulation object so as to determine whether the simulation object needs lane change at each time point indicated by a target time interval and to determine which lane needs to be changed if the lane needs to be changed; the position model defines a calculation manner of the traveling position of the simulation object (such as the calculation manner of the target traveling position described above) for calculating the traveling position of the simulation object during traveling (such as the target traveling position of the simulation object at each time point indicated by the target time interval).

Through the process, the simulation object can perform related driving behaviors such as acceleration driving, deceleration driving, uniform speed driving, left lane changing, right lane changing, straight driving and the like in the driving process. During the running process of the simulation object, signal estimation can be performed, and the simulation positioning information can be output.

Referring to fig. 14, fig. 14 is a schematic structural diagram of a processing device for driving data according to the present application. The processing device 1 for travel data may include: an acquisition module 11, a driving module 12 and a generation module 13.

An obtaining module 11, configured to obtain a target path to be traveled by the simulation object; the simulated object is provided with a corresponding navigation object, and the navigation object moves along with the running of the simulated object;

a driving module 12, configured to acquire a target driving mode set by the simulation object, and drive the simulation object to drive on a target path according to the target driving mode;

the generation module 13 is used for generating simulation positioning information of the navigation object corresponding to the simulation object in the driving process of the simulation object; the simulation positioning information is used for simulating a simulation test of navigating the simulation object by adopting the navigation object in the target driving mode.

Optionally, the driving module 12 drives the simulated object to travel on the target path according to the target travel mode, including:

the driving module 12 calculates a driving parameter of the simulation object at a time point indicated by the target time interval based on the target driving mode according to the target time interval, including:

the driving module 12 calculates a manner of simulating the running parameter of the object at the i-th time point based on the target running mode and the running parameter at the i-1-th time point, including:

Optionally, the driving module 12 determines the manner of driving acceleration of the simulation object at the ith time point based on the speed range mode, the speed variation mode and the driving speed of the simulation object at the ith time point, including:

Optionally, the speed change mode is associated with a first acceleration and a second acceleration, the first acceleration is smaller than the target value, the second acceleration is larger than the target value, the first acceleration corresponds to a first speed change proportion, and the second acceleration corresponds to a second speed change proportion; the manner in which the drive module 12 obtains the target acceleration and the target speed change ratio associated with the speed change pattern includes:

Optionally, the manner in which the driving module 12 obtains the shift indication information of the simulation object includes:

Optionally, the driving module 12 determines a manner of simulating the running acceleration of the object at the ith time point based on the target acceleration and the acceleration adjustment value, including:

Optionally, the driving module 12 determines the manner of driving lane indication information of the simulation object at the i-th time point based on the driving lane change mode, the driving lane preference mode and the driving lane indication information of the simulation object at the i-1 th time point, including:

Optionally, the above device 1 is further configured to:

Wherein the i-1 th time point belongs to a time point within the target period.

Optionally, the simulation object has at least one travelable travel path at the ith point in time; the driving module 12 determines a manner of a target lane on which the simulation object is to travel at the i-th point in time based on the lane change pattern and the lane preference pattern, including:

generating a third random number within the target numerical range;

Optionally, any time point indicated by the target time interval is a target time point; the generating module 13 generates the simulated positioning information of the navigation object during the driving process of the simulated object, which comprises the following steps:

Acquiring an initial driving position of a target path;

Optionally, the generating module 13 generates the mode of the simulated positioning information based on the simulated driving position, including:

Optionally, the generating module 13 calculates, based on the starting running position and the running parameters of each time point before the target time point indicated by the target time interval, a mode of simulating the running position of the simulation object at the target time point, including:

Optionally, the target driving location comprises a plurality of location components; the generating module 13 performs noise adding processing on the target driving position to obtain a mode of simulating the driving position, and the method comprises the following steps:

the generating module 13 generates a simulated sensing signal of the navigation object at the target time point based on the target sensing signal, including:

Optionally, the method for acquiring the target path to be travelled by the simulation object by the acquiring module 11 includes:

selecting a target path from at least one candidate path;

According to an embodiment of the present application, the steps involved in the processing method of the travel data shown in fig. 3 may be performed by respective modules in the processing apparatus 1 of the travel data shown in fig. 14. For example, step S101 shown in fig. 3 may be performed by the acquisition module 11 in fig. 14, and step S102 shown in fig. 3 may be performed by the drive module 12 in fig. 14; step S103 shown in fig. 3 may be performed by the generation module 13 in fig. 14.

The application can acquire the target path to be driven by the simulation object; the simulated object is provided with a corresponding navigation object, and the navigation object moves along with the running of the simulated object; the target running mode set by the simulation object can be obtained, and the simulation object is driven to run on the target path according to the target running mode; and, in the course of driving of the simulation object, can produce the simulation positioning information of the correspondent navigation object of the simulation object; the simulation positioning information is used for simulating a simulation test of navigating the simulation object by adopting the navigation object in the target driving mode. Therefore, the device provided by the application can flexibly set the corresponding running mode (such as the target running mode) of the simulated object (the simulated running object), and can drive the simulated object to run on the target path according to the set target running mode, and as the navigation object can move along with the running of the simulated object, the simulation positioning information (namely the simulated positioning information) of the navigation object can be quickly and conveniently generated in the running process of the simulated object, so that the efficiency of acquiring the information (such as the positioning information) of the navigation object for positioning and navigation of the running object is improved, and then the simulation positioning information can simulate the simulation test of navigation of the simulated object by adopting the navigation object; in addition, the application can acquire the simulated positioning information of the navigation object in the simulated running process of the simulated object without acquiring the positioning information of the real running object in the running process, thereby reducing the cost of acquiring the positioning and navigation information of the navigation object on the running object.

According to an embodiment of the present application, each module in the running data processing apparatus 1 shown in fig. 14 may be separately or completely combined into one or several units, or some (some) of the units may be further split into a plurality of sub-units with smaller functions, so that the same operation may be implemented without affecting the implementation of the technical effects of the embodiment of the present application. The above modules are divided based on logic functions, and in practical applications, the functions of one module may be implemented by a plurality of units, or the functions of a plurality of modules may be implemented by one unit. In other embodiments of the application, the processing device 1 of the driving data may also comprise other units, and in practical applications, these functions may also be realized with the assistance of other units, and may be realized by cooperation of a plurality of units.

According to one embodiment of the present application, the processing apparatus 1 for running data as shown in fig. 14 can be constructed by running a computer program capable of executing the steps involved in the respective methods shown in the embodiments of the present application on a general-purpose computer device which may contain a processing element and a storage element such as a Central Processing Unit (CPU), a random access storage medium (RAM), a read only storage medium (ROM), etc. The above-described computer program may be recorded on, for example, a computer-readable recording medium, and may be loaded into and executed in the above-described computer apparatus through the computer-readable recording medium.

Referring to fig. 15, fig. 15 is a schematic structural diagram of a computer device according to the present application. As shown in fig. 15, the computer device 1000 may include: processor 1001, network interface 1004, and memory 1005, and, in some embodiments, computer device 1000 may further comprise: a user interface 1003, and at least one communication bus 1002. Wherein the communication bus 1002 is used to enable connected communication between these components. The user interface 1003 may include a Display (Display), a Keyboard (Keyboard), and the optional user interface 1003 may further include a standard wired interface, a wireless interface, among others. The network interface 1004 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface). The memory 1005 may be a high-speed RAM memory or a non-volatile memory (non-volatile memory), such as at least one disk memory. The memory 1005 may also optionally be at least one storage device located remotely from the processor 1001. As shown in fig. 15, an operating system, a network communication module, a user interface module, and a device control application program may be included in the memory 1005, which is one type of computer storage medium.

In the computer device 1000 shown in FIG. 15, the network interface 1004 may provide network communication functions; while user interface 1003 is primarily used as an interface for providing input to a user; and the processor 1001 may be used to invoke a device control application stored in the memory 1005 to implement:

It should be understood that the computer device 1000 described in the embodiments of the present application may perform the description of the processing method of the driving data in the embodiments of the present application, and may also perform the description of the processing apparatus 1 of the driving data in the embodiment corresponding to fig. 14, which is not repeated herein. In addition, the description of the beneficial effects of the same method is omitted.

Furthermore, it should be noted here that: the present application also provides a computer readable storage medium, and a computer program is stored in the computer readable storage medium, and when the processor executes the computer program, the description of the processing method of the driving data in each embodiment of the present application can be executed, so that a detailed description will not be given here. In addition, the description of the beneficial effects of the same method is omitted. For technical details not disclosed in the embodiments of the computer storage medium according to the present application, please refer to the description of the method embodiments of the present application.

As an example, the above-described computer program may be deployed to be executed on one computer device or on a plurality of computer devices that are located at one site, or alternatively, may be executed on a plurality of computer devices that are distributed across a plurality of sites and interconnected by a communication network, and the plurality of computer devices that are distributed across the plurality of sites and interconnected by the communication network may constitute a blockchain network.

The computer readable storage medium may be an internal storage unit of the computer device, such as a hard disk or a memory of the computer device. The computer readable storage medium may also be an external storage device of the computer device, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a flash card (flash card) or the like, which are provided on the computer device. Further, the computer-readable storage medium may also include both internal storage units and external storage devices of the computer device. The computer-readable storage medium is used to store the computer program and other programs and data required by the computer device. The computer-readable storage medium may also be used to temporarily store data that has been output or is to be output.

The present application provides a computer program product comprising a computer program stored in a computer readable storage medium. The processor of the computer device reads the computer program from the computer-readable storage medium, and the processor executes the computer program, so that the computer device performs the description of the processing method of the driving data in the embodiments of the present application, and thus, a detailed description thereof will not be provided herein. In addition, the description of the beneficial effects of the same method is omitted. For technical details not disclosed in the embodiments of the computer-readable storage medium according to the present application, please refer to the description of the method embodiments of the present application.

The terms first, second and the like in the description and in the claims and drawings of embodiments of the application are used for distinguishing between different objects and not for describing a particular sequential order. Furthermore, the term "include" and any variations thereof is intended to cover a non-exclusive inclusion. For example, a process, method, apparatus, article, or device that comprises a list of steps or elements is not limited to the list of steps or modules but may, in the alternative, include other steps or modules not listed or inherent to such process, method, apparatus, article, or device.

Those of ordinary skill in the art will appreciate that the elements and algorithm steps described in connection with the embodiments disclosed herein may be embodied in electronic hardware, in computer software, or in a combination of the two, and that the elements and steps of the examples have been generally described in terms of function in the foregoing description to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

The foregoing disclosure is illustrative of the present application and is not to be construed as limiting the scope of the application, which is defined by the appended claims.

Claims

1. A method of processing travel data, the method comprising:

Acquiring a target running mode set for the simulation object, and driving the simulation object to run on the target path according to the target running mode;

generating simulation positioning information of the navigation object corresponding to the simulation object in the driving process of the simulation object; the simulation positioning information is used for simulating a simulation test of navigating the simulated object by adopting the navigation object in the target driving mode;

the simulation object is used for running according to running parameters of time points indicated by the target time interval, and any time point indicated by the target time interval is a target time point; the generating the simulation positioning information of the navigation object corresponding to the simulation object comprises the following steps:

generating a target sensing signal of the simulation object at the target time point based on the running parameter of the simulation object at the target time point; the target sensing signal is a signal under a second reference coordinate system where the simulation object is located, and the navigation object is located in a first reference coordinate system;

acquiring a coordinate system conversion parameter between the first reference coordinate system and the second reference coordinate system, and mapping the target sensing signal from the second reference coordinate system to the first reference coordinate system based on the coordinate system conversion parameter to obtain a simulated sensing signal of the navigation object at the target time point; the simulated positioning information comprises the simulated sensing signal.

2. The method of claim 1, wherein said driving the simulated object to travel on the target path in accordance with the target travel pattern comprises:

wherein the driving parameters at any time point comprise at least one of the following: the driving speed of the simulation object at any time point, the driving acceleration of the simulation object at any time point, and the driving track of the simulation object at any time point indicate information.

3. The method of claim 2, wherein the time points indicated by the target time interval include an i-1 th time point and an i-th time point, i being a positive integer, and the time interval between the i-1 th time point and the i-th time point being the target time interval;

The calculating, according to the target time interval, a driving parameter of the simulation object at a time point indicated by the target time interval based on the target driving mode, including:

acquiring a driving parameter of the simulation object at the i-1 time point; the driving parameters of the i-1 th time point are determined based on the target driving mode and the initial driving parameters set for the simulation object;

and calculating the running parameters of the simulation object at the ith time point based on the target running mode and the running parameters of the ith-1 time point.

4. A method according to claim 3, wherein the target travel pattern comprises: a speed range mode, a speed change mode, a driving lane change mode and a driving lane preference mode during driving;

the calculating the running parameter of the simulation object at the ith time point based on the target running mode and the running parameter of the ith-1 time point comprises the following steps:

Determining a traveling acceleration of the simulation object at the ith time point based on the speed range mode, the speed change mode and the traveling speed of the simulation object at the ith time point;

and determining the running speed, the running acceleration and the running track indicating information of the simulation object at the ith time point as the running parameters of the ith time point.

5. The method of claim 4, wherein the determining the travel acceleration of the simulated object at the i-th point in time based on the speed range pattern, the speed change pattern, and the travel speed of the simulated object at the i-th point in time comprises:

acquiring a target running speed associated with the speed range mode; the running speed of the simulation object fluctuates in the adjacent range of the target running speed;

acquiring a target acceleration and a target speed change proportion associated with the speed change mode; the target acceleration is used for determining a change range of the running acceleration of the simulation object, and the target speed change proportion is used for determining the adjacent range of the running speed fluctuation of the simulation object;

Acquiring a speed difference value between the target running speed and the running speed of the simulation object at the ith time point, and taking a product value of an absolute value of the speed difference value and the target speed change ratio as an acceleration adjustment value;

and determining the running acceleration of the simulation object at the ith time point based on the target acceleration and the acceleration adjustment value.

6. The method of claim 5, wherein the speed change pattern is associated with a first acceleration that is less than a target value and a second acceleration that is greater than the target value, the first acceleration corresponding to a first speed change ratio and the second acceleration corresponding to a second speed change ratio; the obtaining the target acceleration and the target speed change proportion related to the speed change mode comprises the following steps:

acquiring speed change indication information of a time point when the running speed of the simulation object is equal to the target running speed; the ith time point is any time point when the running speed of the simulation object changes from the initial running speed to the target running speed or after the running speed changes to the target running speed;

If the speed change instruction information indicates that the simulation object needs to run at a reduced speed, the first acceleration is taken as the target acceleration, and the first speed change proportion is taken as the target speed change proportion;

and if the speed change instruction information indicates that the simulation object needs to accelerate, taking the second acceleration as the target acceleration, and taking the second speed change proportion as the target speed change proportion.

7. The method of claim 6, wherein the obtaining shift indication information of the simulated object comprises:

generating a first random number within a target numerical range; the target numerical range comprises a first numerical sub-range and a second numerical sub-range;

and if the value of the first random number is in the second value sub-range, determining that the speed change indication information is information for indicating that the simulation object needs to accelerate.

8. The method of claim 6, wherein the determining the travel acceleration of the simulated object at the i-th point in time based on the target acceleration and the acceleration adjustment value comprises:

If the target acceleration is the first acceleration and the i-th time point is a time point before the running speed of the simulation object is reduced from the target running speed to the first running speed, determining the sum of the first acceleration and the acceleration adjustment value as the running acceleration of the simulation object at the i-th time point; the first running speed is equal to the difference value between the target running speed and a first ratio, wherein the first ratio is the ratio of the absolute value of the first acceleration to the change ratio of the target speed;

if the target acceleration is the first acceleration and the i-th time point is a time point when the running speed of the simulation object is reduced from the target running speed to the first running speed or after the running speed is reduced, determining the acceleration adjustment value as the running acceleration of the simulation object at the i-th time point;

if the target acceleration is the second acceleration and the i-th time point is a time point before the running speed of the simulation object increases from the target running speed to a second running speed, determining a difference between the second acceleration and the acceleration adjustment value as the running acceleration of the simulation object at the i-th time point; the second running speed is equal to the sum of the value of the target running speed and a second ratio, wherein the second ratio is the ratio of the value of the second acceleration to the change proportion of the target speed;

If the target acceleration is the second acceleration and the i-th time point is a time point when the traveling speed of the simulation object increases from the target traveling speed to the second traveling speed or after increasing to the second traveling speed, determining the opposite number of the acceleration adjustment value as the traveling acceleration of the simulation object at the i-th time point.

9. The method of claim 4, wherein the determining the lane-indicating information for the simulated object at the i-th point in time based on the lane-change pattern, the lane-preference pattern, and the lane-indicating information for the simulated object at the i-1-th point in time comprises:

if the driving channel indication information of the ith-1 time point indicates that the simulation object does not have a lane change at the ith-1 time point, determining a target driving channel required to be driven by the simulation object at the ith time point based on the driving channel change mode and the driving channel preference mode;

if the driving lane indication information of the i-1 th time point indicates that the simulation object is in a continuous lane change state in a target time period and the i-th time point does not belong to the time point in the target time period, determining a target driving lane required to be driven by the simulation object at the i-th time point based on the driving lane change mode and the driving lane preference mode;

and if the target driving lane is consistent with the driving lane where the simulation object is positioned at the ith-1 time point, determining that the driving lane indication information at the ith time point is the indication information without changing lanes.

10. The method of claim 9, wherein the method further comprises:

if the driving lane indication information of the ith-1 time point indicates that the simulation object is in a continuous lane change state in a target period and the ith time point belongs to the time point in the target period, determining that the driving lane indication information of the ith time point is the indication information of the simulation object in the continuous lane change state in the target period;

wherein the i-1 th time point belongs to a time point within the target period.

11. The method of claim 9, wherein the simulated object has at least one lane that is travelable at the i-th point in time; the determining, based on the lane change mode and the lane preference mode, a target lane on which the simulation object needs to travel at the i-th time point includes:

acquiring a numerical value sub-range corresponding to the current driving lane in the at least one driving lane in a target numerical value range based on the driving lane change mode;

acquiring a numerical value sub-range corresponding to each driving lane except the current driving lane in the at least one driving lane in a target numerical value range respectively based on the driving lane preference mode;

generating a third random number within the target numerical range;

and determining the driving lane corresponding to the numerical value sub-range where the numerical value of the third random number is in the at least one driving lane as the target driving lane.

12. The method of claim 2, wherein any point in time indicated by the target time interval is a target point in time; during the driving process of the simulation object, generating the simulation positioning information of the navigation object corresponding to the simulation object comprises the following steps:

acquiring an initial driving position of the target path;

calculating a simulated driving position of the simulated object at the target time point based on the starting driving position and driving parameters of each time point before the target time point;

And generating the simulation positioning information based on the simulation running position.

13. The method of claim 12, wherein the generating the simulated positioning information based on the simulated travel position comprises:

performing satellite signal conversion processing on the simulated driving position to generate a simulated satellite signal of the simulated object at the target time point;

acquiring a reference satellite signal of a satellite base station, performing differential processing on the simulated satellite signal and the reference satellite signal, and generating a differential satellite signal of the simulated object at the target time point;

determining the simulated satellite signal and the differential satellite signal of the simulated object at the target time point as the simulated satellite signal and the differential satellite signal of the navigation object at the target time point;

14. The method of claim 12, wherein the calculating the simulated travel position of the simulated object at the target time point based on the start travel position and travel parameters at respective time points before the target time point indicated by the target time interval comprises:

and carrying out noise adding processing on the target running position to obtain the simulation running position.

15. The method of claim 14, wherein the target travel location comprises a plurality of location components; the step of carrying out noise adding processing on the target driving position to obtain the simulation driving position comprises the following steps:

acquiring Gaussian noise distribution respectively associated with each position component of the target driving position;

sampling the noise-added Gaussian noise of each position component in the Gaussian noise distribution associated with each position component;

and adopting the Gaussian noise added to each position component to carry out noise adding processing on each position component respectively to obtain the simulated driving position.

16. The method of claim 1, wherein generating the target sensor signal of the simulated object at the target point in time during the driving of the simulated object comprises:

If the simulation object is not in the lane change state at the target time point, determining a default angular velocity and a running acceleration of the simulation object at the target time point as target sensing signals of the simulation object at the target time point;

if the simulation object is in a lane change state at the target time point, determining the running angular speed of the simulation object based on the lane change track of the simulation object at the target time point, and determining the running angular speed and the running acceleration of the simulation object at the target time point as target sensing signals of the simulation object at the target time point;

the driving acceleration of the simulation object at the target time point and whether the simulation object is in a lane change state at the target time point are determined based on the driving parameters of the simulation object at the target time point.

17. A processing device for travel data, the device comprising:

The driving module is used for acquiring a target running mode set for the simulation object and driving the simulation object to run on the target path according to the target running mode;

the generation module is used for generating simulation positioning information of the navigation object corresponding to the simulation object in the driving process of the simulation object; the simulation positioning information is used for simulating a simulation test of navigating the simulated object by adopting the navigation object in the target driving mode;

the simulation object is used for running according to running parameters of time points indicated by the target time interval, and any time point indicated by the target time interval is a target time point; the generating module generates simulation positioning information of the navigation object corresponding to the simulation object, including:

18. A computer device comprising a memory and a processor, the memory storing a computer program that, when executed by the processor, causes the processor to perform the steps of the method of any of claims 1-16.

19. A computer readable storage medium, characterized in that the computer readable storage medium stores a computer program adapted to be loaded by a processor and to perform the method of any of claims 1-16.