CN116679580A - Simulation verification method and system for intelligent network-connected automobile under closed scene - Google Patents
Simulation verification method and system for intelligent network-connected automobile under closed scene Download PDFInfo
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Abstract
The present disclosure provides a simulation verification method and system for an intelligent network-connected vehicle in a closed scene, which acquire environmental parameter data in the closed scene, state data of the intelligent network-connected vehicle, road side monitoring data and preset operation rule data in the closed scene; mapping the acquired data into a preset virtual model of the closed scene to obtain the running state of the intelligent network-connected automobile in the virtual scene; according to the running state of the intelligent network-connected automobile in the virtual scene, running state simulation in a preset time period in the future is carried out, and a risk early warning instruction and/or a control instruction for intelligent network-connected automobile control in the real scene are generated according to simulation results; the method and the device realize virtual-real linkage in the closed scene, and can effectively prevent the safety risk under the extreme working condition by collecting real-time vehicle data and scene data in the closed scene, performing vehicle operation simulation in a preset time period and generating the risk and control preparation instructions according to simulation results.
Description
Technical Field
The disclosure relates to the technical field of intelligent network-connected automobile simulation, in particular to a simulation verification method and system for an intelligent network-connected automobile in a closed scene.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
The degree of automation of the vehicle driving technology is an important link of intelligent network-connected automobile development, and the analog simulation technology is widely accepted in the industry in the development, test and verification links of the automatic driving technology. At present, the test verification of the automatic driving algorithm is about 90% completed through a simulation platform, 9% completed in a test field and 1% completed through an actual road side. The automatic driving algorithm in the common scene is perfect, and breaks through the difficulty in some extreme scenes. The scenes can be conveniently generated through the simulation platform, and targeted test and verification can be carried out. In order to solve the problem of extreme scene test, the industry has the common knowledge of increasing the duty ratio of simulation test verification in automatic driving test verification. With the improvement of the simulation technology level and the popularization of application, the industry aims to achieve the completion of 99.9% of test quantity through a simulation platform, 0.09% of closed field test and finally 0.01% to real-time completion.
The current automatic driving simulation technology is mostly based on simulation verification of a scene library. The simulation verification mainly realizes closed-loop simulation verification of algorithms such as automatic driving perception, decision planning, control and the like by constructing a simulation scene library, and meets the verification requirement of the maturity of the universal automatic driving technology; the scene library is the basis of automatic driving simulation verification, and the higher the coverage rate of the scene library to the real world is, the more the simulation verification result is real. In addition, because of specific closed scenarios such as: the proportion of the areas such as airports, mining areas, ports, scenic spots and the like in the whole application industry of automatic driving is limited, so that the construction of scene libraries for the areas alone is not started; the requirements of different stages of development of the automatic driving automobile on the scene library are also different, and the scene library is required to realize different verification functions; the existing simulation verification system is mostly used for testing and verification of the automatic driving technology such as perception, decision and control.
The inventor finds that the current simulation test method for the specific closed scene is less, and intelligent networking automobile simulation in the preset specific scene cannot be realized; in addition, most of the existing automatic driving simulation is based on the constructed virtual scene to simulate the real scene before constructing so as to realize better real scene construction, and the main purpose is to better realize the construction of the real scene and lack the dynamic adjustment of the closed scene after constructing; meanwhile, after the real closed scene is built, real-time data of the automatic driving vehicle cannot be communicated with data of the virtual scene, analysis of running trend of the automatic driving vehicle in the scene cannot be carried out according to the real scene data, and safe running of the automatic driving vehicle in the closed scene cannot be guaranteed.
Disclosure of Invention
In order to solve the defects of the prior art, the present disclosure provides a simulation verification method and a system for intelligent network-connected vehicles in a closed scene, which realize virtual-real linkage in the closed scene, perform vehicle operation simulation in a preset time period by collecting real-time vehicle data and scene data in the closed scene, generate risks and control preparation instructions according to simulation results, and can effectively prevent safety risks under extreme working conditions.
In order to achieve the above purpose, the present disclosure adopts the following technical scheme:
the first aspect of the present disclosure provides a method for simulating and verifying an intelligent network-connected vehicle in a closed scene.
An analog simulation verification method of an intelligent network-connected automobile in a closed scene comprises the following steps:
acquiring environment parameter data in a closed scene, state data of an intelligent network-connected automobile, road side monitoring data and preset operation rule data in the closed scene;
mapping the acquired data into a preset virtual model of the closed scene to obtain the running state of the intelligent network-connected automobile in the virtual scene;
and according to the running state of the intelligent network-connected automobile in the virtual scene, running state simulation in a preset time period in the future is carried out, and a risk early warning instruction and/or a control instruction for intelligent network-connected automobile control in the real scene is generated according to a simulation result.
Further, the preset closed scene virtual model is constructed according to the real closed scene, and comprises the following steps:
acquiring equipment data, size data and control parameter data of a real closed scene;
generating a virtual scene model matched with the real closed scene according to the acquired data;
and automatically performing data conversion on the virtual scene model according to real scene data injected in real time.
Further, performing operation state simulation within a preset time period in the future, including the following steps:
according to the intelligent network-connected automobile running state in the virtual scene and the closed scene data currently mapped to the virtual scene, simulation under various extreme conditions is carried out, and a vehicle running simulation result under each extreme condition is generated and stored;
and generating and storing a risk early warning instruction according to a preset intelligent network-connected automobile safe operation working condition and a vehicle operation simulation result.
Further, the acquired data are mapped into a preset virtual model of the closed scene, the operation simulation of the vehicle is carried out in the virtual model of the closed scene, and the construction of the real scene is carried out according to the operation simulation result.
Further, the extreme conditions include at least one or more of extreme weather, safety accidents in the enclosed scene, traffic jams in the enclosed scene, or high personnel concentration in the enclosed scene.
Further, the current operation condition in the closed scene is obtained according to the acquired environment parameter data in the closed scene, the state data of the intelligent network-connected automobile, the road side monitoring data and the preset operation rule data in the closed scene;
if the current operation condition is matched with the pre-stored extreme operation condition, directly sending out alarm information or a preset control instruction.
Further, the preset control instructions at least comprise control of the position, speed and azimuth of the intelligent network-connected car or other traffic participants.
Further, the preset closed scene virtual model includes:
the cloud control system comprises a virtual fence, a cloud control terminal, a plurality of road side devices, vehicle end devices and handheld devices, wherein the cloud control terminal, the plurality of road side devices, the vehicle end devices and the handheld devices are arranged in the virtual fence;
the road side equipment, the vehicle end equipment and the handheld equipment are all in communication connection with the cloud control terminal, and the cloud control terminal controls the automatic driving vehicle according to data collected by the equipment and task requirements of a closed scene.
The second aspect of the present disclosure provides an analog simulation verification system for an intelligent network-connected vehicle in a closed scene.
An analog simulation verification system of an intelligent network-connected automobile in a closed scene, comprising:
a data acquisition module configured to: acquiring environment parameter data in a closed scene, state data of an intelligent network-connected automobile, road side monitoring data and preset operation rule data in the closed scene;
a virtual run module configured to: mapping the acquired data into a preset virtual model of the closed scene to obtain the running state of the intelligent network-connected automobile in the virtual scene;
the simulation early warning module is configured to: and according to the running state of the intelligent network-connected automobile in the virtual scene, running state simulation in a preset time period in the future is carried out, and a risk early warning instruction and/or a control instruction for intelligent network-connected automobile control in the real scene is generated according to a simulation result.
A third aspect of the present disclosure provides a computer readable storage medium having stored thereon a program which when executed by a processor performs the steps in a method for simulated authentication of an intelligent network-connected vehicle in a closed scenario according to the first aspect of the present disclosure.
A fourth aspect of the present disclosure provides an electronic device, including a memory, a processor, and a program stored on the memory and executable on the processor, where the processor implements the steps in the method for analog simulation verification of an intelligent network-connected vehicle in a closed scenario according to the first aspect of the present disclosure when the program is executed by the processor.
Compared with the prior art, the beneficial effects of the present disclosure are:
1. according to the simulation verification method and system, virtual-real linkage in the closed scene is achieved, real-time vehicle data and scene data in the closed scene are collected, vehicle operation simulation in a preset time period is conducted, risks are generated according to simulation results, and control preparation instructions are generated, so that safety risks under extreme working conditions can be effectively prevented.
2. According to the simulation verification method and system, the current operation working condition is compared with the prestored extreme operation working condition, and the preset alarm instruction and/or control instruction can be quickly called to conduct risk prevention and control, so that the disposal capability of the extreme working condition is greatly improved.
3. According to the simulation verification method and system, the closed scene virtual model is strictly constructed according to the actual scene, so that better virtual-real combination can be realized, and the accuracy of a virtual result is ensured.
4. According to the simulation verification method and system, vulnerabilities in the real closed scene can be found according to the virtual simulation result, namely, when the real-time data simulation result of the intelligent network-connected automobile has more risks or has more risks, risk point identification in the closed scene is carried out, and layout modification of the real scene is carried out according to the risk point identification result.
5. According to the simulation verification method and system, the acquired data are mapped into the preset closed scene virtual model, the operation simulation of the vehicle is carried out in the closed scene virtual model, the real scene is constructed according to the operation simulation result, the accuracy of the real scene is greatly improved, and the accuracy of intelligent network-connected automobile control in the closed scene combined by virtual and real is further improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the disclosure, illustrate and explain the exemplary embodiments of the disclosure and together with the description serve to explain the disclosure, and do not constitute an undue limitation on the disclosure.
Fig. 1 is a flow chart of a method for simulating and verifying an intelligent network-connected vehicle in a closed scene provided in embodiment 1 of the disclosure.
Detailed Description
The disclosure is further described below with reference to the drawings and examples.
It should be noted that the following detailed description is illustrative and is intended to provide further explanation of the present disclosure. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments in accordance with the present disclosure. As used herein, the singular is also intended to include the plural unless the context clearly indicates otherwise, and furthermore, it is to be understood that the terms "comprises" and/or "comprising" when used in this specification are taken to specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof.
Embodiments of the present disclosure and features of embodiments may be combined with each other without conflict.
Example 1:
as shown in fig. 1, embodiment 1 of the present disclosure provides an analog simulation verification method for an intelligent network-connected vehicle in a closed scene, which includes the following steps:
acquiring environment parameter data in a closed scene, state data of an intelligent network-connected automobile, road side monitoring data and preset operation rule data in the closed scene;
mapping the acquired data into a preset virtual model of the closed scene to obtain the running state of the intelligent network-connected automobile in the virtual scene;
and according to the running state of the intelligent network-connected automobile in the virtual scene, running state simulation in a preset time period in the future is carried out, and a risk early warning instruction and/or a control instruction for intelligent network-connected automobile control in the real scene is generated according to a simulation result.
In this embodiment, the preset closed scene virtual model is constructed according to a real closed scene, and includes the following steps:
acquiring equipment data, size data and control parameter data of a real closed scene;
generating a virtual scene model matched with the real closed scene according to the acquired data;
and automatically performing data conversion on the virtual scene model according to real scene data injected in real time.
In this embodiment, the operation state simulation in the future preset time period is performed, which includes the following procedures:
according to the intelligent network-connected automobile running state in the virtual scene and the closed scene data currently mapped to the virtual scene, simulation under various extreme conditions is carried out, and a vehicle running simulation result under each extreme condition is generated and stored;
and generating and storing a risk early warning instruction according to a preset intelligent network-connected automobile safe operation working condition and a vehicle operation simulation result.
In this embodiment, the extreme conditions include at least one or more of extreme weather, safety accidents in the closed scene, traffic jams in the closed scene, or high personnel concentration in the closed scene.
In the embodiment, the current operation condition in the closed scene is obtained according to the acquired environment parameter data in the closed scene, the state data of the intelligent network-connected automobile, the road side monitoring data and the preset operation rule data in the closed scene;
if the current operation condition is matched with the pre-stored extreme operation condition, directly sending out alarm information or a preset control instruction.
In this embodiment, the preset control command includes at least control of the position, speed and azimuth of the intelligent network-connected car or other traffic participants.
In this embodiment, the preset closed scene virtual model includes:
the cloud control system comprises a virtual fence, a cloud control terminal, a plurality of road side devices, vehicle end devices and handheld devices, wherein the cloud control terminal, the plurality of road side devices, the vehicle end devices and the handheld devices are arranged in the virtual fence;
the road side equipment, the vehicle end equipment and the handheld equipment are all in communication connection with the cloud control terminal, and the cloud control terminal controls the automatic driving vehicle according to data collected by the equipment and task requirements of a closed scene.
In this embodiment, the virtual scene includes the following:
a roadside apparatus comprising: RSU (Road Side Unit), sensing device (millimeter wave radar, laser radar, camera), MEC (Mobile Edge Computing, edge computing Unit), and hand-held terminal (traffic participant interaction Unit);
the vehicle dispatching system (cloud control terminal) is connected with the RSU through a wired network, data are exchanged in a TCP mode, and the vehicle dispatching system sends a vehicle passing permission instruction and a vehicle passing prohibition instruction to the RSU;
the RSU is used as a TCP (Transmission Control Protocol ) server, the vehicle scheduling system is used as a TCP client, and a control instruction is broadcasted when a vehicle is about to arrive at an intersection, for example, an airport plane guided vehicle is used as an allowed pass, and the guided vehicle guides the plane to normally pass through the intersection; if the traffic order is passed, the guided vehicle stops in front of the intersection, waits for the vehicle dispatching system to send and the RSU broadcasts the traffic allowing order and then passes.
The sensing equipment is used for acquiring the coordinates and the speed of the traffic participants; the handheld terminal is used for acquiring coordinates, speed and azimuth angle of the traffic participants and carrying out real-time interaction.
A vehicle end apparatus comprising: OBU terminal (vehicle, traffic participant), vehicle end sensing device (fusion sensing), vehicle body controller, vehicle end assembly controller, etc.;
wherein, the OBU is used as a Server, the guiding vehicle is used as a Client, and the guiding vehicle is connected with an OBU (On Board Unit) and then the OBU issues information at regular intervals (frequency 10 hz); after the boot car is connected with the OBU, the OBU issues information periodically (frequency 10 hz), and the method comprises the following steps: red light information (red light, green light) and simulated aircraft and vehicle position and speed information (ID, coordinates, position, azimuth).
Vehicle end sensing device (fusion sensing) for sensing:
POSITION information (POSITION Message) refers to the current actual POSITION of the vehicle, and comprises a path number, an offset, a speed, a relative direction with a road, a lane occupied by the current POSITION, POSITION information credibility and the like;
road information (SEGMENT Message), which refers to the most important attribute in a certain section of a path, including path number, road grade, road type (such as expressway, loop, parking lot, etc.), road composition (expressway, single/double lane, etc.), speed limit, number of lanes, direction, tunnel, bridge, branch road, emergency lane, calculation path, service area, and complex intersection mark;
road intersection information (STUB Message) refers to the starting point of a new path, and comprises a path number, the number of sub-paths, a corner (an included angle with the next path section), intersection occurrence probability, road types and compositions, the number of forward and reverse lanes, turning points, whether the current intersection is a complex intersection or not, and the like;
the road feature information (PROFILE Message) can use 10bits or 32bits to represent the attribute of the path, including path number, path PROFILE type, PROFILE sequence point, curvature, etc.;
system information (META-DATA Message), DATA for applications including country code, region (county state) code, driving position (left, right), speed units, protocol size version, hardware version, map provider, map version, ADAS Horizon Provider compatibility, and mode information.
And the vehicle body controller is used for controlling the action signals to be transmitted to the integrated controller assembly in a centralized way, and the integrated controller assembly is used for controlling the vehicle body elements after the signals are subjected to operational amplification.
The vehicle end assembly controller integrates vehicle end sensing information and vehicle state (vehicle elements such as drivers, steering gears, brakes and the like) information.
Cloud control terminal includes: a host system and a vehicle control system;
the upper system is used for in-site traffic rules, road right rules, flight information (in and out of ports), vehicle operation flows, original maps, air management information, weather information, vehicle demands and the like.
The vehicle control system is used for task scheduling, path planning, traffic prediction, real-time monitoring and the like.
Taking a closed scene of an airport as an example, a part of traffic rules are set as follows:
1. road speed limit management
1. The method comprises the steps that a flight area carries out regional speed limiting management, the speed per hour of road sections such as a tail service lane of a station, a head service lane of a remote station, a boarding bridge of a terminal building and the like is not more than 30 km, and the speed per hour of a fire fighting channel is not more than 10 km;
2. the distance between the exit of the first-floor/transfer center baggage sorting area of the terminal building (goods station) and the service lane under the boarding bridge is relatively short, the speed of the vehicle should be reduced and slowly moved when the vehicle passes through the road section, and the vehicle should be observed to avoid the goods tractor, and the speed per hour must not exceed 10 km;
3. the speed per hour of the rest road sections must not exceed 40 km.
2. Road height limiting management
1. The height of the fixed end of the boarding bridge of the terminal building and the fire-fighting channel of the XX finger corridor is limited to 3.8 meters;
2. the height of the fixed end of the boarding bridge of the terminal building is limited to 3.95 meters;
3. the height of the downward through passage of the west finger corridor of the transfer center is limited to 2.8 meters, the height of the downward through passage of the west finger corridor is limited to 3.2 meters, and the height of the downward through passage of the east finger corridor is limited to 3.8 meters, and the height of the downward through passage of the east finger corridor is limited to 3.2 meters.
3. The equipment of the superelevation vehicles such as the passenger elevator car, the high working ladder and the like is strictly forbidden to pass through the service lane below the fixed end of the boarding bridge;
4. the tail service lane of the machine station only allows special vehicles of flight guarantee operations such as food vehicles, cargo guarantee vehicles, garbage trucks, clean water vehicles, sewage vehicles, fuelling vehicles, disabled vehicles, and machine service vehicles to pass in principle;
5. the XX vertical contact service lane limits the traffic of vehicles below 60 tons (inclusive).
Other rules are not described in detail.
In this embodiment, vehicle driving simulation is performed according to the aircraft take-off and landing information, according to the traffic rules in the airport, the environmental parameter data in the airport, the state data of the intelligent network-connected vehicle, and the road side monitoring data.
When an extreme condition is met, such as forced landing, extreme weather, in-field collision accidents and the like, according to simulation results under preset various working conditions, after matching is completed, alarming and disposal are directly carried out so as to improve the safety of airplane taking off and landing and personnel in an airport.
Example 2:
the embodiment 2 of the disclosure provides an analog simulation verification system of an intelligent network-connected automobile in a closed scene, which comprises:
a data acquisition module configured to: acquiring environment parameter data in a closed scene, state data of an intelligent network-connected automobile, road side monitoring data and preset operation rule data in the closed scene;
a virtual run module configured to: mapping the acquired data into a preset virtual model of the closed scene to obtain the running state of the intelligent network-connected automobile in the virtual scene;
the simulation early warning module is configured to: and according to the running state of the intelligent network-connected automobile in the virtual scene, running state simulation in a preset time period in the future is carried out, and a risk early warning instruction and/or a control instruction for intelligent network-connected automobile control in the real scene is generated according to a simulation result.
Example 3:
embodiment 3 of the present disclosure provides a computer readable storage medium having a program stored thereon, which when executed by a processor, implements the steps in the method for simulated simulation verification of an intelligent networked automobile in a closed scenario as described in embodiment 1 of the present disclosure.
Example 4:
embodiment 4 of the present disclosure provides an electronic device, including a memory, a processor, and a program stored in the memory and executable on the processor, where the processor implements steps in the method for simulating and verifying an intelligent network-connected vehicle in a closed scenario according to embodiment 1 of the present disclosure when executing the program.
The foregoing description of the preferred embodiments of the present disclosure is provided only and not intended to limit the disclosure so that various modifications and changes may be made to the present disclosure by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present disclosure should be included in the protection scope of the present disclosure.
Claims (10)
1. The simulation verification method of the intelligent network-connected automobile in the closed scene is characterized by comprising the following steps of: the method comprises the following steps:
acquiring environment parameter data in a closed scene, state data of an intelligent network-connected automobile, road side monitoring data and preset operation rule data in the closed scene;
mapping the acquired data into a preset virtual model of the closed scene to obtain the running state of the intelligent network-connected automobile in the virtual scene;
and according to the running state of the intelligent network-connected automobile in the virtual scene, running state simulation in a preset time period in the future is carried out, and a risk early warning instruction and/or a control instruction for intelligent network-connected automobile control in the real scene is generated according to a simulation result.
2. The method for simulating and verifying the intelligent network-connected automobile in the closed scene as in claim 1, wherein the method comprises the following steps:
the preset closed scene virtual model is constructed according to the real closed scene, and comprises the following steps:
acquiring equipment data, size data and control parameter data of a real closed scene;
generating a virtual scene model matched with the real closed scene according to the acquired data;
according to real scene data injected in real time, the virtual scene model automatically performs data conversion;
or,
mapping the acquired data into a preset closed scene virtual model, performing operation simulation on the vehicle in the closed scene virtual model, and constructing a real scene according to an operation simulation result.
3. The method for simulating and verifying the intelligent network-connected automobile in the closed scene as in claim 1, wherein the method comprises the following steps:
performing operation state simulation in a future preset time period, wherein the operation state simulation comprises the following steps of:
according to the intelligent network-connected automobile running state in the virtual scene and the closed scene data currently mapped to the virtual scene, simulation under various extreme conditions is carried out, and a vehicle running simulation result under each extreme condition is generated and stored;
and generating and storing a risk early warning instruction according to a preset intelligent network-connected automobile safe operation working condition and a vehicle operation simulation result.
4. The simulated simulation verification method of the intelligent network-connected automobile in the closed scene as claimed in claim 3, wherein the method comprises the following steps:
the extreme conditions include at least one or more of extreme weather, safety accidents within the enclosed scene, traffic jams within the enclosed scene, or high personnel concentration within the enclosed scene.
5. The simulated simulation verification method of the intelligent network-connected automobile in the closed scene as claimed in claim 3, wherein the method comprises the following steps:
obtaining the current operation condition in the closed scene according to the obtained environmental parameter data in the closed scene, the state data of the intelligent network-connected automobile, the road side monitoring data and the preset operation rule data in the closed scene;
if the current operation condition is matched with the pre-stored extreme operation condition, directly sending out alarm information or a preset control instruction.
6. The simulated simulation verification method of the intelligent network-connected automobile in the closed scene as claimed in claim 3, wherein the method comprises the following steps:
the preset control instructions include at least control of the location, speed, and azimuth of the automated intelligent network-linked vehicle or other traffic participant.
7. The simulated simulation verification method of the intelligent network-connected automobile in the closed scene as claimed in claim 3, wherein the method comprises the following steps:
the preset closed scene virtual model comprises the following steps:
the cloud control system comprises a virtual fence, a cloud control terminal, a plurality of road side devices, vehicle end devices and handheld devices, wherein the cloud control terminal, the plurality of road side devices, the vehicle end devices and the handheld devices are arranged in the virtual fence;
the road side equipment, the vehicle end equipment and the handheld equipment are all in communication connection with the cloud control terminal, and the cloud control terminal controls the automatic driving vehicle according to data collected by the equipment and task requirements of a closed scene.
8. An intelligent network-connected automobile simulation verification system under a closed scene is characterized in that: comprising the following steps:
a data acquisition module configured to: acquiring environment parameter data in a closed scene, state data of an intelligent network-connected automobile, road side monitoring data and preset operation rule data in the closed scene;
a virtual run module configured to: mapping the acquired data into a preset virtual model of the closed scene to obtain the running state of the intelligent network-connected automobile in the virtual scene;
the simulation early warning module is configured to: and according to the running state of the intelligent network-connected automobile in the virtual scene, running state simulation in a preset time period in the future is carried out, and a risk early warning instruction and/or a control instruction for intelligent network-connected automobile control in the real scene is generated according to a simulation result.
9. A computer readable storage medium having stored thereon a program which when executed by a processor performs the steps of the method for simulated authentication of intelligent networked vehicles in a closed scenario according to any one of claims 1-7.
10. An electronic device comprising a memory, a processor and a program stored on the memory and executable on the processor, wherein the processor, when executing the program, performs the steps in the method for simulated authentication of an intelligent network-connected vehicle in a closed scenario as claimed in any one of claims 1 to 7.
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| CN2022101694546 | 2022-02-23 | ||
| CN202210169454 | 2022-02-23 |
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