CN110082122B - Intelligent network vehicle-connecting test platform - Google Patents

Intelligent network vehicle-connecting test platform Download PDF

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CN110082122B
CN110082122B CN201910357575.1A CN201910357575A CN110082122B CN 110082122 B CN110082122 B CN 110082122B CN 201910357575 A CN201910357575 A CN 201910357575A CN 110082122 B CN110082122 B CN 110082122B
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speed
vehicle
traffic
model
mode
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CN110082122A (en
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王建强
王裕宁
黄嘉皓
胡钰彬
王波
胡屹明
李研强
王勇
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Tsinghua University
Institute of Automation Shandong Academy of Sciences
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Institute of Automation Shandong Academy of Sciences
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    • GPHYSICS
    • G01MEASURING; TESTING
    • G01MTESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M17/00Testing of vehicles
    • G01M17/007Wheeled or endless-tracked vehicles
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01SRADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/38Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
    • G01S19/39Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/42Determining position
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01SRADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/38Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
    • G01S19/39Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/52Determining velocity

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  • General Physics & Mathematics (AREA)
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Abstract

The invention discloses an intelligent network vehicle test platform which comprises a vehicle to be tested, a traffic object simulation device, a communication topological structure and a motion control unit, wherein the vehicle to be tested is arranged in a traffic scene; the traffic object simulation device comprises a full-terrain robot, a height-adjustable doll model and an animal model; the communication topological structure outputs the planned track to the tested vehicle and obtains the information of the tested vehicle from the tested vehicle, and the communication topological structure outputs the information of the tested vehicle to the motion control unit; the motion control unit acquires the information of the detected vehicle and the information of the hologeorobot obtained by the feedback of the hologeorobot from the communication topological structure; the motion control unit controls the path and the speed of the full-terrain robot, the height adjustable doll model and the periodic activities of the animal model. The invention can change the participating objects and environments, provides convenient conditions for testing the simulation of any traffic scene, and realizes the test functions of low cost, zero risk, multiple traffic objects and multiple scenes.

Description

Intelligent network vehicle-connecting test platform
Technical Field
The invention relates to the technical field of intelligent vehicle test fields, in particular to an intelligent network vehicle test platform.
Background
In recent years, automobiles and artificial intelligence have become one of the most concerned problems in the industry and the academia. In the aspect of intelligent network connection technology, the whole system tends to be perfect, and has theoretical support and practical engineering application. However, the ICV (English is called "Intelligent and Connected Vehicles" all; Chinese is called "Intelligent networking automobile") has relatively few research fields in the testing field, the system is not perfect enough, and no completely unified standard exists at present. For vehicles, safety is always the first. Each of the automatically driven intelligent networked automobiles, from development to commercial use, is subjected to a large number of tests, which can be roughly classified into simulation tests and real vehicle tests.
At present, there are two main ICV real vehicle test mechanisms on the market, one is closed field test, and the other is real road condition test. However, the test cost of the closed field is high, the simulation mode is simple and crude, and the reference value is low; although the real road condition test is more real, accidents are easy to happen, the potential safety hazard is high, and the test is limited by law. Therefore, at present, a safe and reliable test mechanism which meets the requirement does not exist.
It is therefore desirable to have a solution that overcomes or at least alleviates at least one of the above-mentioned drawbacks of the prior art.
Disclosure of Invention
It is an object of the present invention to provide an intelligent networked vehicle testing platform that overcomes or at least alleviates at least one of the above-mentioned deficiencies of the prior art.
In order to achieve the above object, the present invention provides an intelligent vehicle networking test platform, which comprises a vehicle to be tested, a traffic object simulation device, a communication topology structure and a motion control unit, wherein: the tested vehicle is arranged in a traffic scene, and the traffic scene is built by a plurality of splicing units; the traffic object simulation device comprises a hologeoid robot, a height-adjustable doll model and an animal model, wherein the height-adjustable doll model or the animal model is arranged on the hologeoid robot; the communication topological structure outputs the planned track to the tested vehicle and obtains the information of the tested vehicle from a positioning system of the tested vehicle, wherein the information of the tested vehicle comprises the speed and the position information of the tested vehicle, and the communication topological structure outputs the collected information of the tested vehicle to the motion control unit; the motion control unit simulates a behavior mode of a traffic object model through a motion track dimension and an consciousness reaction dimension, wherein the behavior mode comprises a route and a speed and a period corresponding to each point on the route; the motion control unit interacts with at least one piece of the hologeorobot information, the motion control unit collects the tested vehicle information and hologeorobot information fed back by the hologeorobot from the communication topological structure, and the hologeorobot information comprises speed and position information of the hologeorobot; the motion control unit controls the route of the all-terrain robot and the speed corresponding to each point on the route according to the route in the behavior mode and the speed corresponding to each point on the route, and the motion control unit also controls the left shoulder joint, the right shoulder joint and the left knee joint of the height-adjustable doll model to periodically move according to the period in the behavior mode so as to simulate the gait of the pedestrian; the motion control unit also controls the limb joints of the animal model to periodically move according to the period in the behavior mode so as to simulate the gait of the animal.
The test platform provided by the invention initiatively simulates the traffic object by means of the all-terrain robot, and restores the traffic scene for testing by simulating the motion trail and the behavior consciousness of the traffic object. According to the requirement of the test, the test platform provided by the embodiment can change the participating objects and the environment, provides a convenient condition for testing the simulation of any traffic scene, and realizes the test functions of low cost, zero risk, multiple traffic objects and multiple scenes.
Drawings
FIG. 1-1 is a schematic block diagram of an intelligent networked vehicle testing platform provided by an embodiment of the invention;
FIG. 1-2 is a schematic test state diagram of the intelligent Internet vehicle test platform shown in FIG. 1-1;
1-3 are schematic views of traffic scenarios in the intelligent networked vehicle testing platform shown in FIG. 1-1;
FIG. 2-1 is a schematic diagram of a communication topology in the intelligent networked vehicle testing platform shown in FIG. 1-1;
fig. 3-1 is a schematic structural diagram of a traffic object simulation device for an intelligent internet vehicle test according to an embodiment of the present invention;
FIG. 3-2 is a schematic side view of the traffic object simulation apparatus shown in FIG. 3-1;
3-3 are schematic structural diagrams of another embodiment of the traffic object simulation device provided by the invention;
3-4 is a schematic structural view of the first traffic object attitude adjustment mechanism shown in FIG. 3-1;
3-5 are side schematic views of a support stand in the traffic object simulation apparatus shown in FIG. 3-1;
3-6 are top views of the support stand shown in FIGS. 3-5;
3-7 are schematic views of the connection between the support stand of FIGS. 3-5 and the height adjustable figure model;
fig. 4-1 is a schematic flow chart of a test vehicle control method for intelligent online vehicle testing according to an embodiment of the present invention;
FIG. 4-2 is a schematic diagram of a bicycle motion profile;
4-3 and 4-4 are X-direction and Y-direction partial speed diagrams, respectively, of the bicycle illustrated in FIG. 4-2;
4-5 are schematic diagrams of the motion trajectory of young people;
4-6 are schematic diagrams of the motion trajectory of a middle aged person;
FIGS. 4-7 are schematic diagrams of the reaction of a person traversing a road;
fig. 4-8 are schematic diagrams of the reaction of cats traversing the road.
Detailed Description
In the drawings, the same or similar reference numerals are used to denote the same or similar elements or elements having the same or similar functions. Embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
The invention aims to simulate three traffic objects by using a machine, restore the possible complex road conditions in a real road and test the response of the intelligent vehicle in the complex environment. As shown in fig. 1-1, the intelligent networked vehicle testing platform provided in this embodiment includes a vehicle under test 10, a traffic object simulation apparatus, a communication topology, and a motion control unit. Each of which will be described later.
The vehicle 10 under test is arranged in a traffic scene which is built by a plurality of spliceable units, and the environment for restoring a real road through the traffic scene is used as a test site. As shown in fig. 1-3, in fig. 3, a and B are spliceable units with different shapes, where a denotes a general road and B denotes an intersection roadside. The building of traffic scene aims at restoring real road conditions environment, adopts the thought similar to happy high building blocks, discretizes all traffic scenes, becomes the module that can splice, what the scene of test demand is like this, this embodiment alright with what scene of building, module reuse has reduced test field area greatly, has practiced thrift the resource. These traffic scenarios can be abstracted as a combination of individual modules: common roadside, intersection roadside and traffic signal lights. In this embodiment, the unit fabrication is performed by using EPE pearl wool board, PP hard plastic board, and rubber road shoulder.
The test vehicle control method for the intelligent internet vehicle test provided by the embodiment simulates the behavior mode of the traffic object model through two dimensions, namely the motion trail dimension and the consciousness reaction dimension.
According to the classification in road traffic science, the participating objects in real traffic can be roughly classified into: automotive, non-automotive, pedestrian and animal (e.g., cat, dog, etc.), in view of this, the present embodiment classifies the population of traffic objects to be simulated into 6 categories: humans, non-motorized vehicles, pets, poultry, and livestock. The following describes the principles of motion trajectory dimension simulation and conscious reaction dimension simulation in detail in conjunction with the population classification of traffic objects.
(one) dimension about motion trajectory
The motion trail dimension simulation comprises speed, route and period. Those of ordinary skill in the art will recognize that: no matter what kind of population, the movement is not simple uniform motion, but periodic motion, and the period depends on the motion characteristics of the population. For example: for a pedestrian, the movement of the arm of the pedestrian forms a movement cycle; for dogs, their motion may be defined by a period of time when both pawns are touching. That is, the population difference mainly lies in the length of the period, the sequence of the movement, the track direction within the period, and the like. According to a plurality of related documents of bionics and traffic behaviors, a series of motion trail and speed curve graphs of the population are abstracted. Data from certain populations is inconvenient to collect, and therefore this embodiment requires the use of real-time human or animal sample data.
Meanwhile, different populations have different speeds, and even the same population can switch different movement rates according to the conditions of mood, age, physical conditions and the like. This embodiment focuses on the classification of moods, "moods" mainly refer to the change of rate in a period. In the study, moods are classified into three categories: slow, average and reactive, respectively, corresponding to low, medium and high rates. Through two dimensions of the population and the mood, the method can better correspond any traffic object model to the corresponding characteristics. For example, the aged person corresponds to (human, slow), the young person corresponds to (human, active), the wild cat corresponds to (pet, active), and the general dog corresponds to (pet, normal).
(II) simulation of the dimensions of the conscious response
In consideration of the consciousness of traffic objects, the traffic objects should respond when receiving external stimulus. Different objects react differently. Taking a road crossing as an example, when an object encounters a side-to-side vehicle crossing the road, there are three expressions: 1) speeding up the pass with a slight turn; 2) stopping until the vehicle passes; 3) and backing to ensure safety. The investigation shows that: humans tend to react more often than 2) and 3), while pets tend to accelerate passage.
It should be noted that the reaction is not a definite event but a probability distribution, so that the difference in consciousness is not reflected in the response itself, but is not divided into the difference in probability among various behaviors. Of 100 people, 80 people may choose to wait for the vehicle to pass, and 20 people choose to rob the vehicle to pass; and 20 of the 100 cats select waiting for passing and 80 select robbing for passing. For one individual and one cat, it is likely that they will respond identically to the applied stimulus, but as the test sample approaches infinity, the differences will be apparent.
In terms of code, the present invention also uses probabilities to describe such differences in dimensions of consciousness. The distribution from population to population is very different, and the mood is slightly different. For the judgment of a single communicated object model, the invention generates a random number for judgment and adjusts the judgment threshold value to change different reaction modes. For the entire complete series of actions, the invention is implemented using a decision tree and the program will continue to run until the external stimulus disappears.
In view of the above principle, as shown in fig. 4-1, the test vehicle control method for the intelligent internet vehicle test provided by this embodiment includes:
step 1, presetting a traffic scene. Wherein: the traffic scene can be, for example, a crossroad pedestrian-vehicle intersection, a same-direction overtaking pedestrian-vehicle intersection, a turning pedestrian-vehicle intersection, and the like.
And 2, determining the required traffic object model and the group and mood of the traffic object model according to the traffic scene preset in the step 1.
And 3, generating a behavior mode of the traffic object model in the traffic scene according to the traffic object model determined in the step 2 and the group and mood of the traffic object model.
The behavior patterns are classified into a regular pattern and an excitation pattern.
In the normal mode, the traffic object model has normal consciousness in the preset traffic scene and a behavior mode matched with the normal consciousness; in the incentive mode, the reactions of the traffic object model after being subjected to the external incentive in the preset traffic scene are divided into a first reaction, a second reaction and a third reaction, the sum of the probability Pi1 of the first reaction, the probability Pi2 of the second reaction and the probability Pi3 of the third reaction is 1, and i is determined by the external incentive and the population of the preset traffic scene.
And if the behavior mode is the excitation mode, generating a random number range, and enabling the traffic object model to move according to the behavior mode which is matched with the reaction and corresponding to the probability falling into the random number range, wherein the behavior mode comprises the route and the speed and the period corresponding to each point on the route. Wherein: the "speed" in the behavior pattern of the traffic object model is switched according to the population and its mood. The 'route' in the behavior pattern of the traffic object model is determined according to the motion trail and the speed curve graph of the population, the acquisition method of the motion trail of the population is literature research and physical sampling, the motion trail determines the motion direction of the all-terrain robot 1, and the speed obtained by the speed curve graph determines the motion speed of the all-terrain robot 1 in the direction determined by the motion trail. The 'period' in the behavior mode of the traffic object model is determined according to the motion characteristics and the mood of the population, and the period determines the time length of one cycle of the movement of the left shoulder joint, the right shoulder joint, the left knee joint and the right knee joint of the height-adjustable doll model 3 or the limb joint of the animal model 4.
And 4, monitoring whether external excitation exists or not, if so, entering the excitation mode, and otherwise, entering the conventional mode.
In one embodiment, step 1 is preceded by:
step 5, the population is set as: human, non-motor vehicle, pet, poultry and livestock, the mood being set to: slow, normal and active. Constructing the population and the mood into a traffic object library, wherein in the traffic object library: the population difference is expressed as a curve shape difference, and the mood difference is expressed as a curve amplitude difference. The traffic object library may refer to table 1 below (the table is only an example, and not all classifications), and determine a speed pattern according to a population and a mood, which specifically includes: the speed mode corresponding to the slow speed is a low speed mode, and the magnitude of the low speed can be understood as the value obtained by multiplying all speed values of the original movement period by 0.8. The speed mode corresponding to the normal mode is a medium speed mode, and the magnitude of the medium speed can be understood as all speed values of the original movement period. The speed mode corresponding to the activity is a high speed mode, and the high speed value can be understood as the value obtained by multiplying all speed values of the original movement period by 1.25.
TABLE 1
Slow down Is normal Activating
Human being The elderly and the disabled Middle-aged people Young male
Bicycle with a wheel Manpower tricycle Common bicycle Mountain bike
Electric vehicle Electric vehicle in short of electricity Common electric vehicle Take-out electric vehicle
Cat and dog Young cat Domesticated dogs Wild cat
Poultry / Goose (goose) /
Livestock Cattle Sheep (sheep) Deer shaped food
The general methods for establishing the object library are two, one is real 3D sampling, namely artificial wearing sampling points, and an acquisition technology is utilized to capture motion to establish a model, so that the established model is relatively accurate, but the method is limited by time and technical equipment, and cannot be achieved by the invention; the second method is a literature research, and the existing literature, especially in human biology and traffic kinematics, is a large amount of literature. In addition, some subjects have less information, such as most animals. For the traffic objects, the invention adopts a mode of video collection and manual curve drawing. After the data collection and calibration are completed, the invention establishes a corresponding program library to reproduce the movement.
In one embodiment, in step 3, the transportation object model is set on the holomorphic robot 1 through the support stand 2, the holomorphic robot 1 moves according to the route in the behavior pattern and the corresponding speed of each point on the route, the transportation object model comprises a height adjustable doll model 3 and an animal model 4, wherein: and the left shoulder joint, the right shoulder joint and the left knee joint of the height-adjustable doll model 3 periodically move according to the period in the behavior mode so as to simulate the gait of the pedestrian. The limb joints of the animal model 4 move periodically according to the period in the behavioral pattern to simulate animal gait.
In one embodiment, the method for acquiring the "speed in the behavior pattern" in step 3 includes:
step 31, determining the speed corresponding to the speed mode of the traffic object model according to the population to which the traffic object model belongs, wherein: the speed mode is determined according to a speed curve graph of each population abstracted by the literature of bionics and traffic behaviors, and the speed curve graph comprises the low speed mode, the medium speed mode and the high speed mode. According to the bionics and traffic behavior documents, the motion trail and speed curve chart of each population is abstracted (such as the motion trail of a bicycle shown in fig. 4-2, the component speeds in the X direction and the Y direction of the bicycle shown in fig. 4-2 are respectively shown in fig. 4-3 and fig. 4-4, the motion trail of young people is shown in fig. 4-5, and the motion trail of middle-aged people is shown in fig. 4-6).
And 32, converting the speed determined in the step 31 into the speed and the direction at each moment, calculating the respective angular speeds of the left wheel and the right wheel of the holonomic robot 1, and converting the angular speeds into a hexadecimal database to construct a control object library of the holonomic robot 1.
In one embodiment, the step 3 of generating the behavior pattern of the traffic object model in the preset traffic scene according to the population and the mood thereof specifically includes: matching the group and mood of the traffic object model and the corresponding behavior mode thereof with the preset traffic scene in the conventional mode; and matching the population and the mood of the traffic object model and the corresponding behavior mode with the preset traffic scene and the external stimulus in the stimulus mode.
As shown in fig. 4-7 and fig. 4-8, the reaction of the person (human) when the person (human) traverses the road and the reaction of the cat (cat) when the cat (cat) traverses the road are shown in fig. 4-7, in one embodiment, in step 2, when the preset traffic scene is that the traffic object model passes the road and encounters a side-to-side vehicle, the first reaction is to accelerate to pass and accompany a slight turn, the second reaction is to stop until the vehicle passes, and the third reaction is to retreat to ensure safety in the excitation mode.
As shown in fig. 3-1 to 3-7, the traffic object simulation apparatus for intelligent networked vehicle testing according to the embodiment of the present invention includes a traffic object model, a global robot 1, a support gantry 2, a first traffic object posture adjustment mechanism 5 and a second traffic object posture adjustment mechanism 6, wherein:
the traffic object model is erected above the supporting rack 2, and the traffic object model is divided into 6 types in the embodiment: human, non-motor vehicle, pet, poultry and livestock, and therefore the traffic object model may be understood to generally include a height adjustable doll model 3 and an animal model 4, the height adjustable doll model 3 being for simulating pedestrians in the above classification, and the animal model 4 being for simulating pets, poultry and livestock in the above classification. Other classes of traffic objects may be similar in the manner of simulation given in this embodiment and therefore will not be described again.
In one embodiment, the height-adjustable doll model 3 is divided into a head portion, a trunk portion, arm and hand portions, and leg and foot portions, wherein the trunk portion and the leg and foot portions are two relatively independent portions. The trunk part and the legs and the feet are connected through a telescopic rod component which is vertically arranged, and the up-and-down telescopic motion of the telescopic rod component can adjust the height of the height-adjustable doll model 3 within a preset adjusting range. According to the height distribution of Chinese people, namely the data recorded in GB10000-88, the height range of Chinese people is 1620 +/-150 mm, namely on the basis of 1620 mm, the maximum vertical upward adjustment amount is 150 mm, and the maximum vertical downward adjustment amount is 150 mm.
In this embodiment, the telescopic link subassembly adopts hydraulic telescoping rod. The height simulation has the following advantages in practical application:
1. the applicability of the height-adjustable doll model 3 is improved, most scenes can be dealt with by means of the height-adjustable doll model 3, and the height-adjustable doll model can be adjusted according to the average height characteristics of people in different regions.
2. The hydraulic control mode is simple, and an electronic board control system can be introduced to automatically change the height in the test process through a motor in the future.
3. The trouble of frequently replacing the height-adjustable doll model 3 is saved, the purchase quantity of the height-adjustable doll model 3 can be reduced, and the cost of manpower and material resources is reduced.
The all-terrain robot 1 adopts an Autolabor Pro all-terrain robot, and the motion control principle is that a hexadecimal number is input into an industrial personal computer, and different bits in the numbers control different quantities, so that the motion state of the robot can be updated in real time only by continuously inputting the hexadecimal number into the robot essentially. In this context, "front" and "rear" are defined as the longitudinal traveling direction of the all-terrain robot 1, and the traveling direction is "front" and "rear" on the contrary. "left" and "right" are determined in the lateral direction of the holomorphic robot 1. "vertical" is to be understood as meaning the "height direction" or the "direction of gravity".
The Autolabor is developed based on an ROS system, a differential GPS is installed at the top of the all-terrain robot 1, the geographic position coordinates of the robot can be updated in real time in an industrial personal computer of a vehicle body, and corresponding data can be called in a program of the upper computer to serve as input quantity of motion control. The following table shows the control protocol for the all-terrain robot.
Figure GDA0002410792950000081
The method comprises the steps of converting an abstracted speed curve graph of people, animals and non-motor vehicles into speed and direction at each moment, then calculating the angular speed of a left wheel and a right wheel respectively, converting the angular speed into a hexadecimal number library, and establishing a hardware control object library of the method.
In order to vividly simulate the appearance and the action characteristics of pedestrians and animals in a real scene, the embodiment of the invention designs three sets of innovative refits aiming at Autolabor through analysis and practical adjustment, and firstly, a mechanical structure is designed by means of a natural rotating pair of a hub to push leg and foot parts and arm and hand parts of a height-adjustable doll model 3 to periodically swing so as to simulate human gait; secondly, a load platform is built, and a variable joint height adjustable doll model 3 is additionally arranged to simulate pedestrians with different heights and postures; thirdly, the running posture of the animal is simulated by means of the detachable outer plate and the four-limb rotating pair, so that the 'one generation all' simulation is realized, namely, various objects which may appear on the actual road are simulated by one all-terrain robot 1. For each design, the embodiment of the invention determines the design criterion by consulting the data and considering the establishment of the mechanical model of the important stress point, thereby ensuring that the final design meets the requirements. In the embodiment, by arranging the height-adjustable doll model 3, the all-terrain robot 1 of the embodiment of the invention can simulate adults with different postures and ages, and can truly simulate the gaits of various pedestrians in reality by combining a speed adjustment algorithm.
The 'periodic swinging of the leg and foot parts and the arm and hand parts of the figure model 3 with adjustable body height' in the embodiment of the invention is mainly realized by utilizing a mechanical transmission structure provided by the following embodiment.
For the placement position of the height-adjustable doll model 3 on the holomorphic robot 1, the embodiment of the invention provides support for the height-adjustable doll model 3 by means of the support stand 2. The support rack 2 chooses for use the aluminium alloy as the material of buildding, and the leading cause has:
1. the whole rectangular aluminum profile is installed at the top of the all-terrain robot 1, and the whole rectangular aluminum profile can be perfectly jointed with an external aluminum profile through a T-shaped nut and a corner piece.
2. The aluminum profile is fast to mount and dismount, the size is flexibly adjusted, and fine adjustment of various sizes in projects can be dealt with.
3. The density of the aluminum is only about 2.7g/cm3The weight of the product is lighter than that of steel under the same volume, the tensile strength is more than 160MPa, the yield strength is more than 110MPa, and the strength can overcome the borne load.
4. The aluminum material has good corrosion resistance and can well cope with outdoor rainy environment.
As shown in fig. 3-1, 3-5 and 3-6, the vertical section of the support stand 2 is zigzag, and the bending positions are right angles. The support stand 2 has an L-shaped connecting frame 21 and an external platform assembly 22, wherein:
the number of the L-shaped connecting frames 21 is two, the L-shaped connecting frames are arranged in a longitudinal front-back direction of the all-terrain robot 1 in a spaced mode, one end of each L-shaped connecting frame is connected with the vehicle-mounted cross beam 23 on the top face of the all-terrain robot 1, and the other end of each L-shaped connecting frame is connected with the front end and the back end of the inner side of the external platform. One daughter board of the L-shaped connecting frame 21 is horizontally fixedly connected to the holomorphic robot 1, and the other daughter board of the L-shaped connecting frame 21 is vertically disposed next to the side of the holomorphic robot 1, and is fixedly connected to the external platform assembly 22. Of course, this way saves more weight than making the L-shaped link 21 as a plate structure, which is advantageous for reducing the load of the all-terrain robot 1.
The external platform assembly 22 includes a platform panel 221, the inner side of the platform panel 221 is connected to the lower end of the other daughter board of the L-shaped connecting frame 21 in a reinforced manner, and the platform panel 221 extends out along the outer side of the all-terrain robot 1 in the horizontal direction, and the bottom surface of the extended end contacts the ground through the universal wheel 7. Through setting up universal wheel 7, can guarantee the normal removal of all-terrain robot 1, can provide important ground support power at the platform other end again via universal wheel 7, share the moment of flexure of L type aluminium alloy upper end, reduced the amount of deflection of platform panel 221 to a great extent.
In one embodiment, the circumscribing platform assembly 22 further comprises a support frame in the form of an inverted U-shape, comprising: and a front pillar 222 and a rear pillar 223 perpendicular to the upper surface of the platform panel 221, wherein the front pillar 222 and the rear pillar 223 are disposed at the front side and the rear side of the upper surface of the platform panel 221, respectively, spaced apart in the longitudinal direction of the all-terrain robot 1. The upper portions of the front and rear uprights 222 and 223 are integrally connected by platform beams 224 and support beams 225 arranged in a vertically spaced-apart manner. Two legs of the height-adjustable doll model 3 are respectively positioned at the left side and the right side of the platform cross beam 224 and straddle on the supporting cross beam 225, and the supporting cross beam 225 can provide upward supporting force for the pelvis of the height-adjustable doll model 3. In order to ensure that the hands and feet of the height-adjustable doll model 3 have enough movement space, the legs of the height-adjustable doll model are not required to be in direct contact with the upper surface of the platform panel 221, and therefore, the foot surface of the height-adjustable doll model 3 is positioned above the platform panel 221 and has a vertical gap with the platform panel 221. As can be seen from the top views of the support bench 2 shown in fig. 3-6: the space directly above the X position on the platform panel 221 corresponds to the space where the traffic object model is located. As shown in fig. 3-1 and 3-7, the top surface of the supporting beam 225 is provided with a first posture stabilizing bar 226 and a second posture stabilizing bar 227, the first posture stabilizing bar 226 is located in front of the trunk of the height-adjustable doll model 3 to prevent the height-adjustable doll model 3 from falling forward; the second posture stabilizer bar 227 is located behind the trunk of the height-adjustable doll model 3 to prevent the height-adjustable doll model 3 from toppling forward. Therefore, the torso of the height-adjustable doll model 3 can be maintained in an upright state when the pedestrian walks by the first posture stabilizer bar 226 and the second posture stabilizer bar 227.
The first traffic object posture adjusting mechanism 5 is arranged on the connecting plate 21, the first traffic object posture adjusting mechanism 5 is connected with the left shoulder joint, the right shoulder joint and the left knee joint of the height-adjustable doll model 3, external force is applied to the left shoulder joint, the right shoulder joint and the left knee joint of the height-adjustable doll model 3, the left shoulder joint, the right shoulder joint and the left knee joint of the height-adjustable doll model 3 are pushed to move periodically, gait of a pedestrian is simulated, the gait of the pedestrian comprises coordinated reciprocating motion of hands and legs when the pedestrian walks, and the characteristic of the reciprocating motion comprises the period and the amplitude of the reciprocating motion. Achieving this motion is important to ensure anthropomorphic validity during testing of the all-terrain robot 1: in a real environment, when the pedestrian swings the arm and takes a leg, the hand and the foot are ahead of the body, and the posture is probably captured and utilized by a part of unmanned algorithm, so that the accuracy and the robustness are improved, and if the all-terrain robot 1 does not have the characteristic, the test result is inaccurate.
In one embodiment, shown in conjunction with fig. 3-1 and 3-4, the first traffic object attitude adjustment mechanism 5 includes a motor 51, a worm 52, a slider 54, and a U-shaped support structure 55, wherein:
the motor 51 is a stepper motor powered by an external power source (not shown), and the rotational speed of the motor 51 controls the period of coordinated reciprocating motion of the hands and legs of the person while walking in the pedestrian gait. Two ends of the worm 52 are mounted on a bracket 53 on the connecting plate 21 through bearings, and one end is connected with a power output end of the motor 51 in a driving mode. The slider 54 fits over the worm 52 and the distance of movement of the slider 54 controls the amplitude of the coordinated reciprocating motion of the hands and legs of the person walking in said pedestrian gait. The slide blocks 54 are respectively connected with the left shoulder joint, the right shoulder joint and the left knee joint of the height-adjustable doll model 3 through U-shaped supporting structures 55, and control the left shoulder joint, the right shoulder joint and the left knee joint to move periodically. Reference numeral 3 in fig. 3 to 4 may indicate left and right shoulder joints and left and right knee joints of the figure model 3 for the height-adjustable doll. The U-shaped supporting structure 55 clamps and fixes the left and right shoulder joints and the left and right knee joints of the height-adjustable doll model 3 through the clamping part. Then, when the first transportation object posture adjustment mechanism 5 controls the left and right shoulder joints and the left and right knee joints of the height-adjustable doll model 3 to periodically move, firstly, the rotation speed of the motor 51, the working distance and the initial movement position of the slide block 54 are set and fixed; then, the motor 51 is electrified, the worm 52 rotates, the slide block 54 starts to translate, and the U-shaped support structure 55 also translates along with the slide block 54, so that the left shoulder joint, the right shoulder joint and the left knee joint of the height-adjustable doll model 3 are pushed to start to move. In the above steps, the period of the rotation speed control and the working distance control range.
An external power supply is utilized to provide electric energy for the stepping motor, the worm pushes the sliding block to realize linear motion, the controller compiles the motor to realize forward rotation and reverse rotation, the speed of the motor is adjusted through the speed regulator, and the frequency of the sliding block reciprocating once is further adjusted and controlled. Therefore, the embodiment of the invention successfully constructs the sliding pair which realizes the reciprocating motion at a certain frequency, and then designs the power transmission route, in order to minimize the mechanism complexity and the design complexity, the embodiment of the invention adopts the thin rope to be connected with the hand and the foot of the figure model 3 with the adjustable height, the other end of the thin rope is connected with the sliding block, and the hand swinging is realized by the pulling force drawn by the rope plate. This embodiment simple structure, the realization of being convenient for, the motor operates independently can not influence the motion of all-terrain robot 1 itself, and the length of string can be according to actual adjustment, also easily adjusts the swing frequency simultaneously.
As shown in fig. 3-1 and 3-2, in one embodiment, the first traffic object posture adjustment mechanism 5 includes a first gear 51 ' and a second gear 52 ', and the first gear 51 ' is fixedly coupled to the hub on the side of the all-terrain robot 1 and rotates at a preset reduction ratio (e.g., 0.32) from the wheel rotation frequency of the all-terrain robot 1. The second gear 52 ' is meshed with the first gear 51 ' and is connected with the left shoulder joint, the right shoulder joint, the left knee joint and the right knee joint of the figure model 3 with adjustable height through a connecting rod transmission mechanism 53 ', and the left shoulder joint, the right shoulder joint and the left knee joint are controlled to move periodically.
The hub of the all-terrain robot 1 is provided with four hexagonal nuts, the hexagonal nuts are fixedly connected with a first gear 51 'through four matched hexagonal sleeves, the first gear 51' is driven to rotate at the wheel rotation frequency, a second gear 52 'is meshed with the second gear, and a sliding pair is driven to move through a connecting rod transmission mechanism 53', so that the left shoulder joint, the right shoulder joint and the left knee joint of the figure model 3 with the adjustable height are pushed to move. The embodiment has the advantages that the existing revolute pair can be fully utilized, an additional power supply is not required to be provided, in addition, the frequency and the reduction ratio are adjustable, and the adjustment can be carried out according to the hand and foot swinging frequency.
As shown in fig. 3-1 and 3-3, the second posture adjustment mechanism 6 is disposed on the connecting plate 21 and used for controlling the limb joints of the animal model 4 to perform periodic movement, so as to simulate animal gait, wherein the animal gait includes limb reciprocating motion of the animal during movement, and the characteristics of the reciprocating motion include the period and the amplitude of the reciprocating motion.
In one embodiment, the second traffic object attitude adjusting mechanism 6 includes a third gear 61 and a second pinion gear 62, a second link transmission mechanism 63, and a third link transmission mechanism 64, wherein: the third gear 61 is fixedly coupled to a hub at the front side of the holonomic robot 1 and rotates at a predetermined reduction ratio to the wheel rotation frequency (e.g., 3.5-4.5) of the holonomic robot 1. The second pinion gear 62 is fixedly coupled to a hub at the rear side of the holonomic robot 1 and rotates at a predetermined reduction ratio to the wheel rotation frequency (e.g., 3.5-4.5) of the holonomic robot 1. The limb joints of the animal model 4 are controlled to periodically move by controlling the traveling speed of the all-terrain robot 1. One end of the second connecting rod transmission mechanism 63 is hinged to the outer side face of the third gear 61, and the other end is connected with the forelimb joint of the animal model 4. One end of the third connecting rod transmission mechanism 64 is hinged to the outer side face of the fourth gear 62, and the other end is connected with the hind limb joint of the animal model 4. The limb joints of the animal model 4 are controlled to periodically move by controlling the traveling speed of the all-terrain robot 1.
Animal simulation is another great characteristic of the project, the embodiment of the invention simulates the shape of a real animal by adding the outer shape of the animal to the all-terrain robot 1, and a lever mechanism is designed to simulate the limb movement of the animal.
As shown in the figure, the wheels and the gears of the all-terrain robot 1 are connected to drive the light bar mechanism to move on the wheels, the additional moving pair constraint ensures the free movement of the mechanism, and if the straight bar can be provided with additional materials to simulate the running of the front and rear limbs of an animal, the effect is more vivid.
The main reason why the item can be made from local materials is that the mechanical mechanism does not need additional gears except for the fixed gear, and can directly utilize a revolute pair carried by the wheel (in the embodiment of the invention in the simulation of the figure model 3 with adjustable height, the revolute pair is expected to be converted into periodic movement of the arm, so that the conversion is more difficult), and the link mechanism is light in motion and convenient to design and implement. The main disadvantages of this solution are that the frequency of movement of the animal limbs is not adjustable and that the simulated fidelity of the animal planking is to be considered.
Just because a better test system is lacked, the embodiment of the invention hopes to combine two existing modes, integrates advantages and avoids defects, and designs a safe, stable, real and reliable universal test system for the intelligent networked automobile.
As shown in fig. 1-1, fig. 1-2, and fig. 2-1, the communication topology for the intelligent internet vehicle testing provided by this embodiment includes a vehicle-end unit and a drive test unit, where: the vehicle-end unit comprises a vehicle-mounted control device 9 and a vehicle-end communication device 11, the road test unit comprises a road-end communication device 12, and the vehicle-mounted control device 9 and the vehicle-end communication device 11 are mounted on a tested vehicle 10. The vehicle-mounted control device 9 outputs the planned trajectory to the vehicle 10 under test and acquires vehicle information from a positioning system of the vehicle 10 under test. The vehicle information includes speed and position information of the vehicle 10, the central control PC8 interacts with at least one all-terrain robot 1 through the same local area network or the internet, the central control PC8 acquires the vehicle information from the vehicle-mounted control device 9 and the all-terrain robot information fed back by the all-terrain robot 1, the all-terrain robot information includes speed and position information of the all-terrain robot 1, and the central control PC8 controls the route of the all-terrain robot 1 and the speed corresponding to each point on the route and the periodic movement of the traffic object model on the all-terrain robot 1.
The communication topological structure provided by the embodiment of the invention organically connects all parts in the test field, thereby not only realizing information acquisition, but also realizing the functions of detection and control.
In one embodiment, the vehicle-mounted control device 9 communicates with the vehicle-side communication device 11 through a virtual CAN communication method. The virtual CAN bus is adopted for replacing a physical bus in the vehicle-end communication, and practically all the in-vehicle information is integrated on one vehicle-mounted control device 9. The information of the tested vehicle is differential GPS data from a positioning system of the tested vehicle 10, signals of the differential GPS are stored to a virtual CAN bus in a Json text format, the Json format differential GPS data are sent to the vehicle-mounted control equipment 9 by using the Zeromq, and then the data are sent to the vehicle-end communication equipment 11 by using a udp protocol.
The vehicle-end communication device 11 communicates with the road-end communication device 12 through an udp protocol, the vehicle-mounted control device 9 outputs the detected vehicle information to the road-end communication device 12 through the vehicle-end communication device 11, and the central control PC8 collects the detected vehicle information from the road-end communication device 12. The vehicle-side communication device 11 forwards the differential GPS data obtained before to the roadside communication device 12.
In one embodiment, the central control PC8 and each all-terrain robot 1 are set to Ubuntu Master-slave mode, the central control PC8 is set to Master, each all-terrain robot 1 is set to a service, the central control PC8 is provided with a talker program based on tcp protocol, the all-terrain robots 1 are provided with a listener program based on tcp protocol, after configuring a network port ip, each all-terrain robot 1 sends speed and position information to the central control PC8 in real time by starting the talker program and the listener program, and the central control PC8 uses ssh remote login to control the route of the all-terrain robot 1 and the speed corresponding to each point on the route.
When the test is started, firstly, the central control PC8 is connected with the all-terrain robot 1, a network port ip is configured, and smooth information transmission is confirmed; then, the communication test between the vehicle-end communication equipment 11 and the road-end communication equipment 12 ensures that the central control PC8 works normally; then the central control PC8 is connected with the road-side communication equipment 12; controlling the movement of the tested vehicle 10, sending the information of the tested vehicle to the road-end communication equipment 12 by the vehicle-end communication equipment 11 through the vehicle-end control equipment 9, and calling data in the road-end communication equipment 12 by the central control PC 8; meanwhile, the holomorphic robot 1 is controlled by the central control PC8 to move, and simultaneously, the holomorphic robot 1 feeds back holomorphic robot information to the central control PC 8; and finally, the central control PC8 integrates the information of the tested vehicle 10 and the all-terrain robot 1 and displays the information visually through the RVIZ. The above processes are all circulating processes, and communication is continued as long as the test is performed.
The central control PC8 of the embodiment of the invention interacts information with at least one all-terrain robot 1 through the same local area network or the internet, because: the distance between well accuse PC8 and all terrain robots 1 is no longer than ten meters, and can artificially control both in same LAN, therefore the internet access is fairly smooth and stable, and at this moment, the bandwidth and the cost advantage of wifi communication just can embody, well accuse PC8 is the receiving terminal promptly simultaneously, also is the control end, uses wifi can not influence its remote control's function. In addition, the scheme is simpler and less compact than the vehicle-mounted terminal in terms of code quantity.
In one embodiment, the laws of motion of all traffic simulation objects can be decoupled into two parts: motion characteristics and motion characteristics. The motion characteristics refer to motions accompanying the traffic simulation object during motion, for example, a leg swing and an arm swing when a person walks. The action characteristics are controlled and simulated through a motor and a series of mechanical structures, and the action characteristics are independent of the all-terrain robot 1, so that the image of a test object can be ensured. The motion characteristic refers to a change rule of each kinematic physical quantity of the traffic simulation object during motion, and is specifically a speed-time curve or a displacement-time curve of the traffic simulation object in the items of the embodiments of the present invention. The embodiment of the invention controls the speed of the holomorphic robot 1 through codes, so that the motion characteristic of the holomorphic robot 1 is close to or even consistent with that of a traffic simulation object, thereby completely replacing an actual test object.
In view of this, the central control PC8 generates a curve relationship of the actual speed with respect to time from the acquired speed information of the all-terrain robot 1, compares the curve relationship of the actual speed with respect to time with a graph of the abstracted speed with respect to time, and adjusts the speed of the all-terrain robot 1 to be close to the corresponding speed on the graph. The "curve relationship between actual speed and time" is obtained by the central control PC8 from the acquired speed information of the global robot 1, and at the same time, one frame of data (one frame, that is, data sent once) is time-stamped, so that a speed-time relationship is obtained, and a curve corresponding to speed and time can be drawn after derivation.
In one embodiment, the local area network cannot be used for the communication of the vehicle-end unit because: the range exceeding several tens of meters is very unstable, the connection is easily broken, and the reconnection after the disconnection requires at least a time of the order of seconds, and for the traffic condition, the vehicle can move for ten meters within one second, which is fatal to safety management and accurate monitoring, so the vehicle-end communication device 11 of the embodiment of the present invention processes the vehicle-end communication by using DSRC.
The vehicle-end communication equipment 11 and the road-end communication equipment 12 both adopt DSRC and use the star-cloud interconnection T-station as communication network hardware equipment. DSRC has the advantages of wide coverage, low latency (on the order of milliseconds), and small data transfer volume. As a test platform for all intelligent networked automobiles, the system should be compatible with all vehicle-end links on the market, that is, no matter the vehicle 10 to be tested adopts a vehicle-mounted DSRC, LTE or 5G, the embodiment of the present invention needs a corresponding data link for support. The experimental vehicle 10 used in this embodiment uses on-vehicle DSRC communication, and therefore the system of this embodiment is preferentially made to be an on-vehicle DSRC data communication network. Through investigation, the embodiment of the invention finds some relatively mature vehicle-mounted terminal equipment suppliers at home and famous vehicle-mounted terminal products at foreign countries.
The test platform provided by the invention has five advantages: in the aspects of cost and money, compared with a large closed demonstration area, the invention occupies little land, realizes one-vehicle multiple purposes, has no humanization in the whole process, and saves a large amount of land cost and manpower cost; in the aspect of time cost, the platform can call rare special road conditions to be tested at any moment along with requirements, so that the test period is shortened, and the efficiency is improved; the whole testing process has no real person, no casualty possibility, meanwhile, the trolley can forcibly intervene by the pedestrians, potential accidents are avoided, the whole process is visually monitored, and accidents are prevented; the communication efficiency is high, and the robustness is strong. Dsrc is used for vehicle-road communication, and the delay is wide in low range; the control of the trolley uses local master slave, the information transmission is fast, and the anti-interference is strong.
The platform has five major innovation points: the research object is changed, and the development of a test system is focused; the simulation effect of 'one vehicle with more objects' is realized through a program and a mechanical structure: designing a proper communication topological structure aiming at the test system to realize the unification of the whole test; simplifying an object library by utilizing two characteristics of emotion and attribute; the simulation object makes corresponding reaction according to the traffic road condition.
Finally, it should be pointed out that: the above examples are only for illustrating the technical solutions of the present invention, and are not limited thereto. Those of ordinary skill in the art will understand that: modifications can be made to the technical solutions described in the foregoing embodiments, or some technical features may be equivalently replaced; such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.

Claims (9)

1. An intelligent networked vehicle test platform, which is characterized in that the intelligent networked vehicle test platform simulates a traffic object by means of an all-terrain robot, and by simulating the motion trail and behavior awareness of the traffic object, comprises a vehicle (10) to be tested, a traffic object simulation device, a communication topology structure and a motion control unit, wherein: the vehicle (10) under test is arranged in a traffic scene, and the traffic scene is built by a plurality of splicing units; the traffic object simulation device comprises a hologeoid robot (1), a height-adjustable doll model (3) and an animal model (4), wherein the height-adjustable doll model (3) or the animal model (4) is arranged on the hologeoid robot (1); the communication topological structure outputs the planned track to the tested vehicle (10) and obtains the information of the tested vehicle from a positioning system of the tested vehicle (10), the information of the tested vehicle comprises the speed and position information of the tested vehicle (10), and the communication topological structure outputs the collected information of the tested vehicle to the motion control unit; the motion control unit simulates a behavior mode of a traffic object model through a motion track dimension and an consciousness reaction dimension, wherein the behavior mode comprises a route and a speed and a period corresponding to each point on the route; the motion control unit interacts with information of at least one hologeorobot (1), the motion control unit collects the tested vehicle information and hologeorobot information fed back by the hologeorobot (1) from the communication topological structure, and the hologeorobot information comprises speed and position information of the hologeorobot (1); the motion control unit controls the route of the all-terrain robot (1) and the corresponding speed of each point on the route according to the route in the behavior mode and the corresponding speed of each point on the route, and the motion control unit also controls the left shoulder joint, the right shoulder joint and the left knee joint of the height-adjustable doll model (3) to periodically move according to the period in the behavior mode so as to simulate the gait of the pedestrian; the motion control unit also controls the limb joints of the animal model (4) to periodically move according to the period in the behavior pattern so as to simulate the gait of the animal;
the motion control unit also determines a required traffic object model and the belonging population and mood thereof according to the traffic scene, and generates the behavior mode of the traffic object model in the traffic scene according to the determined traffic object model and the belonging population and mood thereof; wherein: the behavior mode is divided into a normal mode and an excitation mode; in the normal mode, the traffic object model has normal awareness in the traffic scene and a behavior mode matched with the normal awareness; in the incentive mode, the reactions of the traffic object model after being subjected to the external incentive in the traffic scene are divided into a first reaction, a second reaction and a third reaction, the traffic scene is that the traffic object model encounters a side-on vehicle through a road, the first reaction is accelerated to pass and accompanied by a slight turn, the second reaction is stopped until the vehicle passes, the third reaction is retreated to ensure safety, each reaction has a behavior pattern matched with the reaction, the sum of the probability Pi1 of the first reaction, the probability Pi2 of the second reaction and the probability Pi3 of the third reaction is 1, and the subscript i of the Pi1, the Pi2 and the Pi3 is determined by the external incentive and the population of the traffic scene; if the behavior mode is the excitation mode, generating a random number range, and enabling the traffic object model to move according to the behavior mode which is matched with the reaction and corresponding to the probability falling into the random number range; in case an external excitation is monitored, the motion control unit enters the excitation mode; and entering the normal mode when no external excitation is monitored.
2. The intelligent networked vehicle test platform of claim 1, wherein the population is pre-set to: human, non-motor, pet, poultry and livestock, said mood being pre-set as: slowly, normally and actively, constructing the preset population and mood into a traffic object library, wherein in the traffic object library: the population difference is represented by curve shape difference, and the mood difference is represented by curve amplitude difference; the speed mode corresponding to the slow speed is a low speed mode, the speed mode corresponding to the normal speed is a medium speed mode, and the speed mode corresponding to the active speed is a high speed mode.
3. The intelligent networked vehicle test platform according to claim 2, wherein the method for acquiring the speed corresponding to each point on the route in the behavior pattern comprises:
step 31, determining the speed corresponding to the speed mode of the traffic object model according to the population to which the traffic object model belongs, wherein: the speed mode is determined according to a speed curve graph of each population abstracted by the bionics and the literature of traffic behaviors, and the speed curve graph comprises the low speed mode, the medium speed mode and the high speed mode;
and 32, converting the speed determined in the step 31 into the speed and the direction at each moment, calculating the angular speed of the left wheel and the angular speed of the right wheel of the hologeorobot (1), and converting the angular speeds into a hexadecimal database to construct a control object library of the hologeorobot (1).
4. The intelligent networked vehicle test platform according to any one of claims 1 to 3, wherein the traffic object simulation device further comprises a support gantry (2), a first traffic object attitude adjustment mechanism (5) and a second traffic object attitude adjustment mechanism (6), wherein: the all-terrain robot (1) is provided with a geographical position coordinate positioning device; the supporting rack (2) is Z-shaped in vertical section, the bending part is a right angle, the supporting rack (2) is provided with an L-shaped connecting rack (21) and an external platform assembly (22), the external platform assembly (22) comprises a platform panel (221), one daughter board of the L-shaped connecting rack (21) is horizontally and fixedly connected to the all-terrain robot (1), the other daughter board of the L-shaped connecting rack (21) is vertically arranged next to the side surface of the all-terrain robot (1), the platform panel (221) is fixedly connected to the lower end of the other daughter board of the L-shaped connecting rack (21), the platform panel (221) horizontally extends out along the outer side of the all-terrain robot (1), and the bottom surface of the extending end is in contact with the ground through a universal wheel (7); the first traffic object posture adjusting mechanism (5) is arranged on the connecting plate (21) and is used for controlling the left shoulder joint, the right shoulder joint and the left knee joint of the height-adjustable doll model (3) to periodically move so as to simulate the gait of a pedestrian, and the gait of the pedestrian comprises the characteristics of the coordinated reciprocating motion of the hands and the legs when the pedestrian walks, including the cycle and the amplitude of the reciprocating motion; the second traffic object posture adjusting mechanism (6) is arranged on the connecting plate (21) and used for controlling the limb joints of the animal model (4) to perform periodic movement so as to simulate animal gait, wherein the animal gait comprises the characteristics of limb reciprocating motion of the animal during moving, including the period and amplitude of the reciprocating motion.
5. The intelligent internet protocol vehicle test platform as claimed in claim 4, wherein the trunk part and the leg and foot parts of the height-adjustable doll model (3) are connected through a telescopic rod assembly arranged vertically, the up-and-down telescopic motion of the telescopic rod assembly can adjust the height of the height-adjustable doll model (3) within a range not greater than 30mm, and when the first traffic object posture adjusting mechanism (5) controls the swing arm of the height-adjustable doll model (3) to swing and step the legs, the arm hand part and the leg and foot parts of the height-adjustable doll model (3) are ahead of the trunk part.
6. The intelligent networked vehicle test platform according to claim 5, wherein the first traffic object attitude adjustment mechanism (5) comprises:
a motor (51) powered by an off-board power source, the rotational speed of the motor (51) controlling the cycle of coordinated reciprocating motion of the hands and legs of the person while walking in the pedestrian gait;
the two ends of the worm (52) are mounted on a bracket (53) on the connecting plate (21) through bearings, and one end of the worm is in driving connection with the power output end of the motor (51); and
a slider (54) mounted on the worm screw (52), the working distance of the slider (54) controlling the amplitude of the coordinated reciprocating motion of the hands and legs of the person while walking in the pedestrian gait;
the sliding blocks (54) are respectively connected with left and right shoulder joints and left and right knee joints of the height-adjustable doll model (3) through U-shaped supporting structures (55) to control the left and right shoulder joints and the left and right knee joints to move periodically.
7. The intelligent networked vehicle test platform according to claim 5, wherein the second traffic object attitude adjustment mechanism (6) comprises:
a third gear (61) fixedly connected to a hub at the front side of the hologeorobot (1) and rotated at a predetermined reduction ratio to the rotational frequency of the wheels of the hologeorobot (1);
a fourth gear (62) which is fixedly connected to the hub of the rear side of the holonomic robot (1) together with the third gear (61) and rotates at a preset reduction ratio to the wheel rotation frequency of the holonomic robot (1);
a second connecting rod transmission mechanism (63), one end of which is hinged to the outer side surface of the third gear (61), and the other end of which is connected with the forelimb joint of the animal model (4);
a third connecting rod transmission mechanism (64), one end of which is hinged to the outer side surface of the fourth gear (62), and the other end of which is connected with the hind limb joint of the animal model (4);
controlling the driving speed of the holomorphic robot (1) to control the limb joints of the animal model (4) to perform periodic activities.
8. The intelligent networked vehicle test platform of claim 6 or 7, wherein the circumscribed platform assembly (22) further comprises a support frame, the support frame is in an inverted U shape, and comprises a front upright (222) and a rear upright (223) perpendicular to the upper surface of the platform panel (221), the front upright (222) and the rear upright (223) are respectively arranged on the front side and the rear side of the upper surface of the platform panel (221) at intervals along the longitudinal direction of the all-terrain robot (1), the upper parts of the front upright (222) and the rear upright (223) are connected into a whole by a platform cross beam (224) and a support cross beam (225) arranged at intervals along the vertical direction, two legs of the height-adjustable dummy (3) are respectively arranged on the left side and the right side of the platform cross beam (224), straddle the support cross beam (225), and the foot surface is arranged above the platform panel (221), -having a vertical clearance with the deck panel (221); and a first posture stabilizer bar (226) and a second posture stabilizer bar (227) are arranged on the top surface of the supporting beam (225) and are respectively positioned in front of and behind the trunk of the height-adjustable doll model (3), so that the trunk of the height-adjustable doll model (3) is kept in an upright state when pedestrians walk.
9. The intelligent networked vehicle test platform of claim 8, wherein the communication topology comprises a vehicle end unit and a drive test unit, wherein: the train end unit comprises a train-mounted control device (9) and a train-mounted communication device (11), the road test unit comprises a road-mounted communication device (12), the train-mounted control device (9) communicates with the train-mounted communication device (11) in a virtual CAN communication mode, the train-mounted communication device (11) communicates with the road-mounted communication device (12) through a udp protocol, the central control PC (8) and all the all-terrain robots (1) are set to be in an Ubuntu Master-slave mode, the central control PC (8) is set to be a Master, each all-terrain robot (1) is set to be a Server, the central control PC (8) is provided with a talker program based on the tcp protocol, the all-terrain robots (1) are provided with a listener program based on the tcp protocol, after IP addresses of network ports are configured, the talker program and the listener program are started, all the all-terrain robots (1) send speed and position information to the central control PC (8) in real time, the central control PC (8) controls the route of the all-terrain robot (1) and the speed corresponding to each point on the route by ssh remote login.
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