CN111753425A - Simulation method, simulation device, electronic equipment and storage medium - Google Patents
Simulation method, simulation device, electronic equipment and storage medium Download PDFInfo
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Abstract
The application discloses a simulation method, a simulation device, electronic equipment and a storage medium, and relates to the field of intelligent traffic and traffic flow simulation. The specific implementation scheme is as follows: receiving a simulation request, wherein the simulation request at least indicates that the running characteristics of a target vehicle under a specified simulation environment are calculated; determining road information based on the simulation environment specified by the simulation request, and obtaining lane change characteristics of the target vehicle under the road information; calculating to obtain reference driving characteristics of the target vehicle under the lane change characteristics, wherein the reference driving characteristics at least comprise a reference speed and a reference driving direction; and selecting target driving characteristics matched with the reference speed and the reference driving direction included in the reference driving characteristics from a preset real traffic flow database, and taking the target driving characteristics as the driving characteristics of the target vehicle in the simulation environment. Therefore, the diversity of the simulation scheme is enriched, and meanwhile, the authenticity is also improved.
Description
Technical Field
The application relates to the technical field of computers, in particular to the field of intelligent traffic and traffic flow simulation.
Background
In the conventional traffic flow simulation technology, firstly, a fixed traffic flow simulation of a prescribed route is generally adopted, namely a traffic flow motion mode and a trajectory are artificially prescribed, the trajectory, the speed, the direction, the turning, the lane changing, the parking and other actions of vehicles are preset, and the vehicles in the traffic flow move according to an expected manner and are only suitable for the recurrence of a specific scene; secondly, performing simulation based on a vehicle following model and a lane changing model, namely determining the speed of the vehicle according to the distance between the vehicles and the expected speed, and performing vehicle merging lane changing when the distance between the vehicles is larger than the distance capable of being merged; obviously, the above-mentioned methods are poor in diversity and poor in authenticity.
Disclosure of Invention
The application provides a simulation method, a simulation device, electronic equipment and a storage medium.
According to an aspect of the present application, there is provided a simulation method, including:
receiving a simulation request, wherein the simulation request at least indicates that the running characteristics of a target vehicle under a specified simulation environment are calculated;
determining road information based on the simulation environment specified by the simulation request, and obtaining lane change characteristics of the target vehicle under the road information;
calculating to obtain reference driving characteristics of the target vehicle under the lane change characteristics, wherein the reference driving characteristics at least comprise a reference speed and a reference driving direction;
and selecting target driving characteristics matched with the reference speed and the reference driving direction included in the reference driving characteristics from a preset real traffic flow database, and taking the target driving characteristics as the driving characteristics of the target vehicle in the simulation environment. .
According to another aspect of the present application, there is provided a simulation apparatus including:
a request receiving unit configured to receive a simulation request indicating at least a running characteristic of a calculation target vehicle in a specified simulation environment;
a road information determining unit, configured to determine road information based on the simulation environment specified by the simulation request, and obtain lane change characteristics of the target vehicle under the road information;
the calculation unit is used for calculating and obtaining reference running characteristics of the target vehicle under the lane change characteristics, and the reference running characteristics at least comprise a reference speed and a reference running direction;
and the selection unit is used for selecting the target driving characteristics matched with the reference speed and the reference driving direction included by the reference driving characteristics from a preset real traffic flow database, and the target driving characteristics are used as the driving characteristics of the target vehicle in the simulation environment.
According to another aspect of the present application, there is provided an electronic device including:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method described above.
According to another aspect of the present application, there is provided a non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method described above.
According to the technology of this application has solved the relatively poor, lower problem of authenticity of prior art variety, has improved the variety of simulation scheme, has also promoted the authenticity of simulation result simultaneously.
It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present application, nor do they limit the scope of the present application. Other features of the present application will become apparent from the following description.
Drawings
The drawings are included to provide a better understanding of the present solution and are not intended to limit the present application. Wherein:
FIG. 1 is a schematic flow chart diagram of a simulation method according to an embodiment of the present application;
FIG. 2 is a schematic diagram of a simulation method in a specific example according to an embodiment of the application;
FIG. 3 is a first schematic diagram of a simulation apparatus according to an embodiment of the present application;
FIG. 4 is a second schematic structural diagram of a simulation apparatus according to an embodiment of the present application;
FIG. 5 is a schematic diagram of a third exemplary embodiment of an emulation apparatus according to the present application;
fig. 6 is a block diagram of an electronic device for implementing the simulation method according to the embodiment of the present application.
Detailed Description
The following description of the exemplary embodiments of the present application, taken in conjunction with the accompanying drawings, includes various details of the embodiments of the application for the understanding of the same, which are to be considered exemplary only. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present application. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
The traffic flow simulation technology is a technology for researching traffic behaviors by using a simulation technology, is a technology for tracking and describing the change of traffic motion along with time and space, and can be divided into microscopic traffic simulation, mesoscopic traffic simulation and macroscopic traffic simulation according to the granularity of a simulation object. The microscopic Traffic simulation has the highest degree of detail granularity description on elements and behaviors of a Traffic System, and the description on the Traffic flow takes a single vehicle as a basic unit, so that the microscopic behaviors of the vehicle such as car following, car passing, lane change and the like on a road can be truly reflected, and the microscopic Traffic simulation has good application in Traffic engineering theoretical research, road geometric design scheme analysis, Traffic management System design scheme evaluation analysis, road Traffic safety analysis, Intelligent Traffic System (ITS) and the like, and therefore, the microscopic Traffic simulation has great development.
Based on this, in order to solve the problems of poor diversity, poor adaptability and poor authenticity in the prior art, the scheme of the application provides a simulation method, a simulation device, electronic equipment and a storage medium. It should be noted that the scheme of the application is not only suitable for microscopic traffic simulation, but also suitable for mesoscopic traffic simulation and macroscopic traffic simulation.
Specifically, fig. 1 is a schematic flow chart of a simulation method according to an embodiment of the present application, and specifically, as shown in fig. 1, the method includes:
step S101: a simulation request is received that indicates at least a travel characteristic of a computing target vehicle in a specified simulation environment.
Step S102: and determining road information based on the simulation environment specified by the simulation request, and obtaining lane change characteristics of the target vehicle under the road information.
Step S103: calculating to obtain reference driving characteristics of the target vehicle under the lane change characteristics, wherein the reference driving characteristics at least comprise a reference speed and a reference driving direction;
step S104: and selecting target driving characteristics matched with the reference speed and the reference driving direction included in the reference driving characteristics from a preset real traffic flow database, and taking the target driving characteristics as the driving characteristics of the target vehicle in the simulation environment.
In practical applications, the simulation request further indicates an initial state of the target vehicle, such as an initial position, an initial speed, and the like, so as to ensure that the reference driving state of the target vehicle in the simulation environment is effectively calculated.
Therefore, the target driving characteristics of the target vehicle in the simulation environment can be calculated without specifying a specific line, so that the method and the device are strong in diversity and strong in adaptability; in addition, the obtained reference running characteristics are not directly used as the running characteristics of the target vehicle in the simulation environment, but the target running characteristics matched with the reference running characteristics are inquired based on the preset real traffic flow database and are used as the running characteristics of the target vehicle in the simulation environment, so that the reality of the simulation result obtained based on the scheme of the application is stronger.
In a specific example of the scheme of the present application, the following manner may be adopted to obtain the road information, which specifically includes: determining a specified road from real road network information based on the simulation environment, and determining vehicle information and obstacle information positioned in the specified road; determining road information of the specified road based on the vehicle information and the obstacle information. That is to say, in this example, the real road network information is established in advance, for example, the real road network information is established based on a map, and the specified road is determined from the real road network information based on the simulation environment, so as to improve the authenticity of the simulation result of the scheme of the present application. Moreover, real road network information is constructed in advance, the real road network information is constructed based on a real road network structure, and surrounding vehicle information and obstacle information are fully considered, so that application scenes are enriched, and meanwhile, the scheme of the application has good adaptability and mobility.
In practical application, the vehicle information and the obstacle information in the specified road can be obtained based on the traffic flow density required by the simulation environment, and then the road information containing the vehicle information and the obstacle information is obtained; or, the vehicle information and the obstacle information may be obtained based on a traffic flow density required by the simulation environment, and then the specified road may be determined from the real road network information based on the vehicle information and the obstacle information, and then the road information may be obtained, where the road information at least can represent the vehicle information and the obstacle information on the specified road. That is to say, in practical application, a specified road may be obtained based on a simulation environment, and then vehicle information and obstacle information located on the specified road are determined, so as to obtain road information corresponding to the simulation environment; or, the vehicle information and the obstacle information may be determined based on the simulation environment, and then the specified road matched with the determined vehicle information and obstacle information is found in the real road network information, so as to obtain the road information.
Here, the vehicle information may specifically include: vehicle information of a simulated vehicle in the simulation environment, such as vehicle attributes, vehicle position, initial speed and the like, attributes of a driver, such as an incentive coefficient and the like; the destination and driving route of the simulated vehicle, etc.; meanwhile, vehicle information of the target vehicle, the attribute of the driver, the destination, and the like are also included. The obstacle information may be embodied as an obstacle in the road, or as another vehicle, a pedestrian, or the like, in addition to the dummy vehicle and the target vehicle. Therefore, the real scene is simulated to the maximum extent, the diversity is enriched, and the foundation is laid for improving the reality of the simulation result.
In a specific example of the scheme of the application, the lane change feature is determined based on active lane change information and/or random lane change information; wherein the active lane change information is obtained at least based on a destination and/or a traveling path constraint condition corresponding to the target vehicle under the road information; the random lane change information is obtained based on a random lane change condition corresponding to the road information.
Here, in practical application, the triggering condition of the active lane change may specifically be: the subsequent road corresponding to the current road of the target vehicle cannot drive into the preset driving path indicated by the driving path constraint condition or cannot reach the target; at the moment, if the triggering condition of the active lane change is met, the target vehicle is triggered to actively change the lane and drive into the adjacent lane. Accordingly, the active lane change information at least includes a lane change processing result (such as a position of a lane after lane change) obtained based on a trigger condition of the active lane change. The random lane change is generally a lane change selection performed when a random lane change condition is satisfied in pursuit of a desired speed. In practical applications, a random lane change condition may be set based on actual requirements, and after the random lane change condition is satisfied, a lane change starting probability may be set, for example, the lane change starting probability is equal to the lane change probability × a driver incentive coefficient of the target vehicle, so as to obtain a lane change processing result as random lane change information.
Therefore, the lane changing condition of the vehicle in the actual scene is fully considered, the diversity of vehicle motion is improved, and a foundation is laid for improving the authenticity.
In a specific example of the present application, the reference driving characteristics may be obtained in the following manner, specifically including: obtaining a road direction of the road on which the target vehicle is located based on the position (updated position or initial position) of the target vehicle in the road information and a farthest preset road end point corresponding to the position of the target vehicle in the road information, for example, taking a vector direction of a connecting line between the position of the target vehicle in the road information and the farthest preset road end point (such as a farthest straight end point) corresponding to the position of the target vehicle in the road information as the road direction; calculating a reference vehicle rotation direction of the target vehicle based on the lane change characteristics, the position of the target vehicle and the road direction; and obtaining a reference driving direction of the target vehicle based on the reference vehicle rotating direction, wherein at least the reference driving direction is used as the reference driving characteristic.
Here, in practical applications, since the steering wheel is generally used for controlling the vehicle rotation direction, the reference vehicle rotation direction may be specifically a steering wheel rotation angle.
Therefore, the reference driving direction of the target vehicle can be obtained by the scheme, so that the microscopic simulation of the vehicle is realized, the dimensionality of a simulation result is enriched, and the use scene of the scheme is enriched; and the simulation process is close to a real scene, so that a foundation is laid for improving the reality of a simulation result.
In another specific example of the scheme of the present application, the reference driving characteristics may also be obtained in the following manner, specifically including: calculating a reference distance characteristic between the target vehicle and an adjacent vehicle (such as a vehicle located in front of the target vehicle or the like or a vehicle located in an adjacent lane with the target vehicle) within a preset range in the road information at least based on the road information and the speed (such as an initial speed or an updated speed) of the target vehicle corresponding to the road information; obtaining a reference acceleration of the target vehicle based on the reference distance feature and the lane change feature; and calculating a reference speed of the target vehicle by using the reference acceleration, and at least using the reference speed as the reference running characteristic.
Therefore, the reference speed of the target vehicle can be obtained by the scheme, so that the microscopic simulation of the vehicle is realized, the dimensionality of a simulation result is enriched, and the use scene of the scheme is enriched. And the simulation process is close to a real scene, so that a foundation is laid for improving the reality of a simulation result.
In practical application, in order to accurately and quickly determine a reference driving direction or a reference speed, a constraint range can be calculated, and specifically, a dynamic constraint condition and an attribute constraint condition corresponding to a target vehicle are obtained; obtaining a speed constraint range and a vehicle rotation range (such as a steering wheel rotation range) of the target vehicle based on the dynamic constraint condition and the attribute constraint condition corresponding to the target vehicle; specifically, the maximum curvature of the road where the position of the target vehicle is located is obtained based on the road information, and the speed constraint range is obtained based on the maximum curvature of the road and the maximum speed at which the target vehicle does not sideslip; the method comprises the steps of obtaining the maximum curvature of a road where a target vehicle is located based on road information, obtaining a vehicle rotation range based on the maximum curvature of the road and the road information, and obtaining a reference driving direction based on a road direction and the vehicle rotation range. Of course, a constraint condition also exists between the speed and the rotation range of the vehicle, and in practical application, the constraint range can be selected according to a specific scene.
In a specific example of the scheme of the application, in order to further improve the authenticity of the simulation result and improve the simulation experience, the target driving characteristics may be mapped to the real road network information to obtain driving characteristics in a three-dimensional space, and the driving characteristics in the three-dimensional space are used as the driving characteristics of the target vehicle in the simulation environment. For example, the real road network information is constructed based on a high-precision three-dimensional map, and at the moment, the driving characteristics of a three-dimensional space can be obtained by the mapping method of the scheme, so that the scheme is more authentic compared with the driving information of a two-dimensional space.
In a specific example of the present application, in order to ensure the integrity and authenticity of the simulation process, the present application further performs an update operation on the simulation system after obtaining the driving characteristics of the target vehicle in the simulation environment, that is, based on the speed and the driving direction included in the target driving characteristics of the target vehicle, the position, the speed and the driving direction of the target vehicle in the road information are updated. Therefore, the integrity of the simulation process is ensured, and a foundation is laid for engineering application.
Therefore, the target driving characteristics of the target vehicle in the simulation environment can be calculated without specifying a specific line, so that the method and the device are strong in diversity and strong in adaptability; in addition, the obtained reference running characteristics are not directly used as the running characteristics of the target vehicle in the simulation environment, but the target running characteristics matched with the reference running characteristics are inquired based on the preset real traffic flow database and are used as the running characteristics of the target vehicle in the simulation environment, so that the reality of the simulation result obtained based on the scheme of the application is stronger.
The scheme of the present application is further described in detail below with reference to specific application scenarios, specifically, in this example, real road network information is first constructed based on map information; the method comprises the steps of establishing initial traffic flow vehicle information and obstacle information in real road network information according to a simulation environment indicated by a calculation request (namely a simulation request) to obtain road information, further obtaining the speed and the vehicle running direction of a vehicle (namely a target vehicle) aimed at by the calculation request in the simulation environment by referring to a speed model and a speed search strategy based on a lane change decision model, converting a calculation result from two-dimension (2D) to three-dimension (3D), updating road information at the next moment based on the conversion result, and circularly calculating the vehicle running characteristics and driving traffic flow to move.
The specific process is as follows, as shown in fig. 2, and comprises the following steps:
first, the initial process:
(1) constructing real road network information: real network information is constructed based on a high-precision map, and a point sequence is adopted to describe road tracks, such as road front-back relation, traffic rule indication, signal lamps and the like, so that a K-D (K-Dimensional) tree of a real road network is obtained.
(2) Constructing a real traffic flow database: and extracting vehicle running information based on the real road data, and establishing a real traffic flow database representing information such as vehicle speed, road direction, vehicle occurrence probability distribution and the like based on the vehicle running information.
Secondly, calculating the flow:
(1) vehicle initialization: the vehicle information and the obstacle information are obtained based on the traffic flow density required for the calculation request, where the vehicle information includes determination of vehicle attributes (such as vehicle type, size, acceleration range, desired speed coefficient, etc.), vehicle position, initial speed, acceleration, angular velocity, driver attributes (such as aggressive coefficient), destination, and driving route, etc. The obstacle information may be specifically an obstacle in a road, or other vehicles, pedestrians, etc. except the simulated vehicle and the target vehicle, and the vehicle initialization process is completed.
(2) And (3) updating road information: and obtaining road information corresponding to the simulation environment required by the calculation request based on the vehicle information and the obstacle information, and finishing an initialization process of the road information, namely a road information updating process. Specifically, in practical application, the nearest search of the K-D tree can be carried out according to the position of a vehicle and the position of an obstacle, so as to obtain a specified road and further obtain road information, wherein the road information can represent the relationship among vehicles, the relationship between the vehicle and the obstacle, the expected speed of the road and the like; here, the road desired speed vexp＝vlimit×ρexpWherein v islimitFor road speed limitation, rhoexpIs the desired speed factor.
(3) Lane change decision model: and obtaining lane change characteristics based on the updated road information and a lane change decision model, wherein the lane change characteristics comprise active lane change information and/or random lane change information.
Here, the active lane change information means that the driver actively changes lanes to other roads for the purpose of restricting the destination and the travel route.
Active lane changeThe trigger condition of (1): the subsequent road corresponding to the current lane of the target vehicle cannot enter the preset driving path indicated by the driving path constraint condition or cannot reach the target; at the moment, if the triggering condition of the active lane change is met, the target vehicle is triggered to actively change the lane and drive into the adjacent lane. Position after active lane change (i.e. lane change processing result): a vehicle (referred to as a first vehicle, which is located in a different lane from the target vehicle, and a road on which the first vehicle is located is hereinafter referred to as a first lane) closest to the current lane of the target vehicle lags the target vehicle by a distance greater than L in the road directionc/2+Lm/2+SVm-VcAnd if so, the target vehicle enters the front of the first vehicle in the first lane, otherwise, the target vehicle decelerates to wait for the first vehicle. Wherein L iscLength of first vehicle being first vehicle, LmIs the length of the target vehicle, SVm-VcIs (V)m-Vc) Braking distance at speed, VmIs the speed of the target vehicle, VcIs the speed of the first vehicle.
The random lane change information refers to a lane change selection performed when a random lane change condition is satisfied in pursuit of a desired speed.
Triggering conditions of random lane change: 1. there is an accessible lane adjacent to the current lane of the target vehicle that satisfies the travel path constraints (this lane is called a second lane, in the actual scene, there may be multiple second lanes); 2. 1/2 in which the preceding vehicle distance S of the current lane of the target vehicle is smaller than the distance of the preceding vehicle corresponding to the target vehicle in the second lane (4/3 when the preceding vehicle of the second vehicle is a large vehicle, 2 times when the preceding vehicle of the current lane is stationary, 1/2 when the preceding vehicle of the second lane is stationary); 3. the distance from the front vehicle of the second lane in the lane direction is greater than the braking distance of the target vehicle (when the target vehicle is a large vehicle, the braking distance is greater than the braking distance multiplied by 2 of the target vehicle); 4. and the distance of the rear vehicle corresponding to the target vehicle in the second lane is greater than the preset safety distance along the lane direction.
And when the triggering condition of random lane change is met, changing the lane to the second lane, or when the triggering condition of random lane change is met, determining whether to change the lane to the second lane or not based on a lane change starting probability, wherein the lane change starting probability is the lane change probability multiplied by the driver incentive coefficient.
(4) Reference speed model: after the lane change decision model determines a lane change processing result, the driving direction and the speed of the target vehicle in the simulation environment indicated by the calculation request are obtained by using a reference speed model; in particular, the amount of the solvent to be used,
firstly, determining a range, namely obtaining a speed constraint range and a steering wheel rotation range based on a dynamic constraint condition in a reference speed model and an attribute constraint condition corresponding to a target vehicle; here, the speed constraint range is obtained based on at least road information and a maximum speed at which the vehicle does not sideslip; the steering wheel rotation range is obtained based on the maximum curvature of the road within the braking distance obtained from the road information.
Wherein, the kinematic constraint conditions are as follows: the speed direction change angle Δ θ is obtained from the formula Δ θ of tan (Φ)/L × v × Δ t, where Φ is the wheel angle, L is the wheel base, and v is the vehicle speed, and here, for simplification of calculation, the present example assumes that the wheel angle coincides with the steering wheel angle, and Δ t is the update time step. It can be seen from the above formula that there is a constrained relationship between the speed direction change angle and the vehicle speed.
And secondly, calculating to obtain the road direction of the lane where the target vehicle is located and the rotation direction of the reference steering wheel of the target vehicle based on the track decision in the reference speed model.
Here, the road direction calculating step includes: acquiring the current position of the target vehicle and the farthest straight road terminal point in front of the current position of the target vehicle, wherein the cumulative curvature between the two points is less than a threshold value thetatThe lateral offset distance is less than a threshold St. For example, the vector direction of the line connecting the current lane point and the farthest straight road end point is used as the road direction lanedir.
The reference steering wheel turning direction calculating step includes:
θ＝ρlaneDir×θlanedir-ρlanePos×Slane；
where ρ islaneDirAs coefficient of direction of travel, θlanedirIs the included angle, rho, between the current driving direction of the target vehicle and the road directionlanePosIs a lateral distance coefficient, SlaneThe current position of the target vehicle is the lateral distance from the road direction. And then obtaining the reference driving direction of the target vehicle under the simulation environment based on the current driving direction of the target vehicle and the reference steering wheel rotating direction.
And finally, obtaining the reference speed and the front distance of the target vehicle based on the reference speed model.
Wherein the reference speed calculating step includes: obtaining the maximum speed V of the vehicle without measuring the slip according to a centrifugal force formulacur，min(Vcur，Vexp) As a desired speed of the final restraint vehicle, wherein VexpIs determined based on attributes of the link, such as the link constraining speed.
Reference acceleration arefCalculation when Smin>＝SdWhen a isref＝min(ρacc×(Vexp-Vm)，amax) Where min () denotes taking the smaller of these, ρaccIs the acceleration factor. When S ismin<Sd，asafe＝max(ρac×(Smin-Sd)，amin) Where max () denotes taking the larger of these, pacIs the deceleration factor.
The front vehicle distance calculating step comprises the following steps: desired distance Sd＝Vt×treac+v2/(2×amin) In which V istIs the current speed of the target vehicle, treacThe brake reaction time is; smin is the minimum distance between the target vehicle and the preceding vehicle (or the preceding vehicle after lane change), SjunctionThe minimum distance S between the front signal lamp and the intersection when the front signal lamp is redd＝min(Smin，Sjunction)；aminThe minimum acceleration is characterized.
In summary, the reference traveling direction θ of the target vehicle is obtainedmAnd a reference velocity Vm。
(5) Speed search strategy: in a pre-established database of real traffic flow, and at Vm±Δv，θmSearching and referencing a travel direction θ within a range of ± Δ θmAnd a reference velocity VmAnd calculating an energy function under the speed according to the matched driving direction and the matched speed, and further obtaining a final optimal result based on the energy function to be used as the driving characteristic of the target vehicle under the simulation environment. In particular enResult＝enRep+enDir+enVelLimitWherein en isRep＝ρrep×min|Sd-Sp |, where ρrepIs a weight, tsafeFor safe time, SpThe distance between the next moment and the front vehicle at the speed is obtained; en is a radical ofDir＝ρdir×|θ-θpL where ρdirAs a weight, θpTherefore, the included angle between the next moment and the road direction at the speed is obtained; en is a radical ofVelLimit＝ρvelLimit×V-VexpL where ρvelLimitIs a weight; to enRepThe result falling within the confidence range is randomly (probability × database occurrence probability distribution) extracted V, θ as the vehicle speed search result at the next time.
(6)2D to 3D conversion: the real road network information is road network 3D structure information, and at this time, after the driving direction and speed of the target vehicle are obtained through calculation, the driving direction and speed (i.e., 2D plane information) of the target vehicle are mapped into the road network 3D structure information, so that the driving characteristics in the 3D space are obtained.
(7) And updating the information such as the vehicle position, the direction and the like of the target vehicle by using the calculated running direction and the speed of the target vehicle, and circularly solving the traffic flow speed in such a way.
Thus, the scheme of the application has the following advantages that:
first, adaptability and mobility are strong, and here, because the scheme of the application constructs real road network information in advance and fully considers real scenes such as surrounding vehicle information and obstacle information, the scheme of the application has good adaptability and mobility.
Secondly, the method and the device have diversity, and the attributes of the simulated vehicles, the attributes of drivers and the like can be preset based on the simulation request, so that the vehicle individuals in the traffic flow have obvious difference, and the diversity of the traffic flow is greatly enhanced.
Thirdly, the method has authenticity, the running characteristics of the target vehicle indicated by the simulation request are matched and obtained by utilizing the preset real traffic flow database, and therefore the authenticity of vehicle motion is greatly improved.
Fourthly, the scheme of the application is irrelevant to the vehicle state, namely the scheme of the application does not need to store the states of the vehicle information, the barrier information and the like, and only needs to acquire the traffic flow state indicated by the simulation request during simulation calculation, so that the scheme of the application has better adaptability to interfaces of different traffic flow systems.
And fifthly, the three-dimensional (3D) display effect is achieved, namely a 3D road network structure is established based on a high-precision map, so that the traffic flow can output 3D space information and provide richer and more real information than the traditional 2D traffic flow.
The present application discloses a simulation apparatus, as shown in fig. 3, including:
a request receiving unit 301 configured to receive a simulation request indicating at least a running characteristic of a calculation target vehicle in a specified simulation environment;
a road information determination unit 302, configured to determine road information based on the simulation environment specified by the simulation request, and obtain lane change characteristics of the target vehicle under the road information;
a calculating unit 303, configured to calculate a reference driving characteristic of the target vehicle under the lane change characteristic, where the reference driving characteristic at least includes a reference speed and a reference driving direction;
a selecting unit 304, configured to select, from a preset real traffic flow database, a target driving feature that matches a reference speed and a reference driving direction included in the reference driving feature, as the driving feature of the target vehicle in the simulation environment.
In a specific example of the aspect of the present application, the road information determination unit includes:
a road determining subunit, configured to determine a specified road from real road network information based on the simulation environment, and determine vehicle information and obstacle information located in the specified road;
a road information generating subunit operable to determine road information of the specified road based on the vehicle information and the obstacle information.
In a specific example of the scheme of the application, the lane change feature is determined based on active lane change information and/or random lane change information; wherein,
the active lane change information is obtained at least based on the destination and/or the traveling path constraint condition corresponding to the target vehicle under the road information;
the random lane change information is obtained based on a random lane change condition corresponding to the road information.
In a specific example of the present disclosure, the calculation unit includes:
the road direction calculating subunit is configured to obtain a road direction of a road on which the target vehicle is located, based on the position of the target vehicle in the road information and a farthest preset road end point corresponding to the position of the target vehicle in the road information;
a reference vehicle rotation direction calculating subunit, configured to calculate a reference vehicle rotation direction of the target vehicle based on the lane change feature, the position of the target vehicle, and the road direction;
and the reference driving direction calculating subunit is used for obtaining a reference driving direction of the target vehicle based on the reference vehicle rotating direction, and at least using the reference driving direction as the reference driving characteristic.
In a specific example of the present disclosure, the calculation unit includes:
a reference distance feature calculating subunit, configured to calculate, based on at least the road information and a speed of the target vehicle corresponding to the road information, a reference distance feature between the target vehicle and an adjacent vehicle within a preset range in the road information;
a reference accelerometer operator unit for obtaining a reference acceleration of the target vehicle based on the reference distance feature and the lane change feature;
and the reference speed calculation subunit is used for calculating a reference speed of the target vehicle by using the reference acceleration, and at least using the reference speed as the reference running characteristic.
In a specific example of the scheme of the present application, as shown in fig. 4, the apparatus further includes:
a three-dimensional space mapping unit 305, configured to map the target driving characteristics into the real road network information, to obtain driving characteristics in a three-dimensional space, and use the driving characteristics in the three-dimensional space as the driving characteristics of the target vehicle in the simulation environment.
In a specific example of the present application, as shown in fig. 5, the apparatus further includes:
an updating unit 306, configured to update the position, the speed, and the driving direction of the target vehicle in the road information based on the speed and the driving direction included in the target driving feature of the target vehicle.
According to an embodiment of the present application, an electronic device and a readable storage medium are also provided.
Fig. 6 is a block diagram of an electronic device according to an emulation method of an embodiment of the present application. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the present application that are described and/or claimed herein.
As shown in fig. 6, the electronic apparatus includes: one or more processors 601, memory 602, and interfaces for connecting the various components, including a high-speed interface and a low-speed interface. The various components are interconnected using different buses and may be mounted on a common motherboard or in other manners as desired. The processor may process instructions for execution within the electronic device, including instructions stored in or on the memory to display graphical information of a GUI on an external input/output apparatus (such as a display device coupled to the interface). In other embodiments, multiple processors and/or multiple buses may be used, along with multiple memories and multiple memories, as desired. Also, multiple electronic devices may be connected, with each device providing portions of the necessary operations (e.g., as a server array, a group of blade servers, or a multi-processor system). In fig. 6, one processor 601 is taken as an example.
The memory 602 is a non-transitory computer readable storage medium as provided herein. The memory stores instructions executable by at least one processor to cause the at least one processor to perform the simulation method provided herein. The non-transitory computer-readable storage medium of the present application stores computer instructions for causing a computer to perform the simulation method provided herein.
The memory 602, which is a non-transitory computer-readable storage medium, may be used to store non-transitory software programs, non-transitory computer-executable programs, and modules, such as program instructions/modules corresponding to the simulation method in the embodiment of the present application (for example, the request receiving unit 301, the road information determining unit 302, the calculating unit 303, the selecting unit 304, the three-dimensional space mapping unit 305, and the updating unit 306 shown in fig. 5). The processor 601 executes various functional applications of the server and data processing by running non-transitory software programs, instructions and modules stored in the memory 602, that is, implementing the simulation method in the above method embodiment.
The memory 602 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to use of the electronic device of the simulation method, and the like. Further, the memory 602 may include high speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory 602 optionally includes memory located remotely from the processor 601, and these remote memories may be connected to the electronics of the emulation method via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The electronic device of the simulation method may further include: an input device 603 and an output device 604. The processor 601, the memory 602, the input device 603 and the output device 604 may be connected by a bus or other means, and fig. 6 illustrates the connection by a bus as an example.
The input device 603 may receive input numeric or character information and generate key signal inputs related to user settings and function control of the electronic apparatus of the simulation method, such as a touch screen, a keypad, a mouse, a track pad, a touch pad, a pointing stick, one or more mouse buttons, a track ball, a joystick, or the like. The output devices 604 may include a display device, auxiliary lighting devices (e.g., LEDs), and tactile feedback devices (e.g., vibrating motors), among others. The display device may include, but is not limited to, a Liquid Crystal Display (LCD), a Light Emitting Diode (LED) display, and a plasma display. In some implementations, the display device can be a touch screen.
Various implementations of the systems and techniques described here can be realized in digital electronic circuitry, integrated circuitry, application specific ASICs (application specific integrated circuits), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
These computer programs (also known as programs, software applications, or code) include machine instructions for a programmable processor, and may be implemented using high-level procedural and/or object-oriented programming languages, and/or assembly/machine languages. As used herein, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, apparatus, and/or device (e.g., magnetic discs, optical disks, memory, Programmable Logic Devices (PLDs)) used to provide machine instructions and/or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term "machine-readable signal" refers to any signal used to provide machine instructions and/or data to a programmable processor.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), and the Internet.
The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so as to solve the defects of high management difficulty and weak service expansibility in the traditional physical host and Virtual Private Server (VPS) service.
Therefore, the target driving characteristics of the target vehicle in the simulation environment can be calculated without specifying a specific line, so that the method and the device are strong in diversity and strong in adaptability; in addition, the obtained reference running characteristics are not directly used as the running characteristics of the target vehicle in the simulation environment, but the target running characteristics matched with the reference running characteristics are inquired based on the preset real traffic flow database and are used as the running characteristics of the target vehicle in the simulation environment, so that the reality of the simulation result obtained based on the scheme of the application is stronger.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present application may be executed in parallel, sequentially, or in different orders, and the present invention is not limited thereto as long as the desired results of the technical solutions disclosed in the present application can be achieved.
The above-described embodiments should not be construed as limiting the scope of the present application. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (16)
1. A simulation method, comprising:
receiving a simulation request, wherein the simulation request at least indicates that the running characteristics of a target vehicle under a specified simulation environment are calculated;
determining road information based on the simulation environment specified by the simulation request, and obtaining lane change characteristics of the target vehicle under the road information;
calculating to obtain reference driving characteristics of the target vehicle under the lane change characteristics, wherein the reference driving characteristics at least comprise a reference speed and a reference driving direction;
and selecting target driving characteristics matched with the reference speed and the reference driving direction included in the reference driving characteristics from a preset real traffic flow database, and taking the target driving characteristics as the driving characteristics of the target vehicle in the simulation environment.
2. The method of claim 1, wherein the determining road information based on the simulation environment specified by the simulation request comprises:
determining a specified road from real road network information based on the simulation environment, and determining vehicle information and obstacle information positioned in the specified road;
determining road information of the specified road based on the vehicle information and the obstacle information.
3. The method according to claim 1 or 2, wherein the lane-change characteristic is determined based on active lane-change information and/or random lane-change information; wherein,
the active lane change information is obtained at least based on the destination and/or the traveling path constraint condition corresponding to the target vehicle under the road information;
the random lane change information is obtained based on a random lane change condition corresponding to the road information.
4. The method of claim 1, wherein the calculating a reference driving characteristic of the target vehicle under the lane-change characteristic comprises:
obtaining the road direction of the road where the target vehicle is located based on the position of the target vehicle in the road information and the farthest preset road terminal corresponding to the position of the target vehicle in the road information;
calculating a reference vehicle rotation direction of the target vehicle based on the lane change characteristics, the position of the target vehicle and the road direction;
and obtaining a reference driving direction of the target vehicle based on the reference vehicle rotating direction, wherein at least the reference driving direction is used as the reference driving characteristic.
5. The method of claim 1 or 4, wherein the calculating a reference driving characteristic of the target vehicle under the lane change characteristic comprises:
calculating reference distance characteristics between the target vehicle and adjacent vehicles within a preset range in the road information at least based on the road information and the speed of the target vehicle corresponding to the road information;
obtaining a reference acceleration of the target vehicle based on the reference distance feature and the lane change feature;
and calculating a reference speed of the target vehicle by using the reference acceleration, and at least using the reference speed as the reference running characteristic.
6. The method of claim 1, further comprising:
and mapping the target driving characteristics to real road network information to obtain driving characteristics in a three-dimensional space, and taking the driving characteristics in the three-dimensional space as the driving characteristics of the target vehicle in the simulation environment.
7. The method of claim 1, further comprising:
and updating the position, the speed and the driving direction of the target vehicle in the road information based on the speed and the driving direction included in the target driving characteristics of the target vehicle.
8. An emulation apparatus comprising:
a request receiving unit configured to receive a simulation request indicating at least a running characteristic of a calculation target vehicle in a specified simulation environment;
a road information determining unit, configured to determine road information based on the simulation environment specified by the simulation request, and obtain lane change characteristics of the target vehicle under the road information;
the calculation unit is used for calculating and obtaining reference running characteristics of the target vehicle under the lane change characteristics, and the reference running characteristics at least comprise a reference speed and a reference running direction;
and the selection unit is used for selecting the target driving characteristics matched with the reference speed and the reference driving direction included by the reference driving characteristics from a preset real traffic flow database, and the target driving characteristics are used as the driving characteristics of the target vehicle in the simulation environment.
9. The apparatus of claim 8, the road information determination unit comprising:
a road determining subunit, configured to determine a specified road from real road network information based on the simulation environment, and determine vehicle information and obstacle information located in the specified road;
a road information generating subunit operable to determine road information of the specified road based on the vehicle information and the obstacle information.
10. The apparatus according to claim 8 or 9, wherein the lane-change characteristic is determined based on active lane-change information and/or random lane-change information; wherein,
the active lane change information is obtained at least based on the destination and/or the traveling path constraint condition corresponding to the target vehicle under the road information;
the random lane change information is obtained based on a random lane change condition corresponding to the road information.
11. The apparatus of claim 8, the computing unit comprising:
the road direction calculating subunit is configured to obtain a road direction of a road on which the target vehicle is located, based on the position of the target vehicle in the road information and a farthest preset road end point corresponding to the position of the target vehicle in the road information;
a reference vehicle rotation direction calculating subunit, configured to calculate a reference vehicle rotation direction of the target vehicle based on the lane change feature, the position of the target vehicle, and the road direction;
and the reference driving direction calculating subunit is used for obtaining a reference driving direction of the target vehicle based on the reference vehicle rotating direction, and at least using the reference driving direction as the reference driving characteristic.
12. The apparatus according to claim 8 or 11, the calculation unit comprising:
a reference distance feature calculating subunit, configured to calculate, based on at least the road information and a speed of the target vehicle corresponding to the road information, a reference distance feature between the target vehicle and an adjacent vehicle within a preset range in the road information;
a reference accelerometer operator unit for obtaining a reference acceleration of the target vehicle based on the reference distance feature and the lane change feature;
and the reference speed calculation subunit is used for calculating a reference speed of the target vehicle by using the reference acceleration, and at least using the reference speed as the reference running characteristic.
13. The apparatus of claim 8 or 9, further comprising:
and the three-dimensional space mapping unit is used for mapping the target driving characteristics to the real road network information to obtain the driving characteristics in the three-dimensional space, and taking the driving characteristics in the three-dimensional space as the driving characteristics of the target vehicle in the simulation environment.
14. The apparatus of claim 8 or 9, further comprising:
and the updating unit is used for updating the position, the speed and the running direction of the target vehicle in the road information based on the speed and the running direction included in the target running characteristic of the target vehicle.
15. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-7.
16. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of any one of claims 1-7.
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