CN110767026A

CN110767026A - Automatic drive machine learning device

Info

Publication number: CN110767026A
Application number: CN201911037990.5A
Authority: CN
Inventors: 崔雍浩; 朴海音; 詹光; 郝建业; 王征
Original assignee: Tianjin University
Current assignee: Tianjin University
Priority date: 2019-10-29
Filing date: 2019-10-29
Publication date: 2020-02-07

Abstract

The invention discloses an automatic driving machine learning device which comprises a base plate, a supporting plate, a simulation cockpit, a box body, a main controller and a buffer mechanism, wherein vibration motors are arranged on the left side and the right side of the top end of the base plate, a servo motor is fixed at the center position of the top end of the supporting plate, a rotating shaft is arranged at the output end of the servo motor through a coupler, the top end of the rotating shaft is fixedly connected with the bottom end of the simulation cockpit, the buffer mechanism is arranged at the corner position between the supporting plate and the simulation cockpit, the main controller is arranged on the left side inside the simulation cockpit, the box body is fixed at the top of the simulation cockpit, and a composite filter screen, an air blower, a partition plate, a depth filter and a positioning frame are sequentially arranged inside the box. The automatic driving machine learning device not only improves the internal environment of the learning device and improves the authenticity of the learning device during simulation, but also enhances the practical effect of the learning device.

Description

Automatic drive machine learning device

Technical Field

The invention relates to the technical field of automatic driving learning, in particular to an automatic driving machine learning device.

Background

With the continuous development of traffic engineering, the concept of automatic driving is gradually developed, and so-called automatic driving refers to that the road condition is analyzed mainly by a computer and the conventional driving is carried out, and when the road condition is in a complicated road section, the driving mode is changed into a manual driving mode. Therefore, in order to better help people to understand and experience the operation, related personnel design an automatic driving machine learning device.

However, the existing automatic driving machine learning device still has certain problems, and the specific problems are as follows:

1. the conventional learning device is generally only provided with a head part, the internal space of the conventional learning device is relatively compact, an effective air conditioning system is lacked, and the internal air environment of the conventional learning device is rapidly deteriorated after a plurality of times of continuous use;

2. the general learning device does not have an all-dimensional and high-sensitivity simulation mechanism, so that the picture and the sense organ are relatively separated, and the reality is low during simulation;

3. in the prior art, an operation system in the learning device is relatively crude, the driving process is difficult to judge in a multi-aspect and comprehensive mode, and the practical effect is insufficient.

Disclosure of Invention

Technical problem to be solved

Aiming at the defects of the prior art, the invention provides the automatic driving machine learning device which has the advantages of improving the internal environment, improving the authenticity in simulation, enhancing the learning effect and the like, and solves the problems of lack of an effective air conditioning system, low authenticity in simulation and relatively crude operation system.

(II) technical scheme

In order to achieve the purpose, the invention provides the following technical scheme: an automatic driving machine learning device comprises a base plate, a supporting plate, a simulation cockpit, a box body, a main controller and a buffer mechanism, wherein the left side and the right side of the top end of the base plate are both provided with a vibration motor, the output ends of the vibration motors are all fixedly connected with the bottom end of the supporting plate, a servo motor is fixed at the center position of the top end of the supporting plate, and the output end of the servo motor is provided with a rotating shaft through a coupler, the top end of the rotating shaft is fixedly connected with the bottom end of the simulation cockpit, and the corner position between the supporting plate and the simulation cockpit is provided with a buffer mechanism, the left side inside the simulation cockpit is provided with a main controller, the top of the simulation cockpit is fixed with a box body, and the interior of the box body is sequentially provided with a composite filter screen, a blower, a clapboard, a depth filter and a positioning frame from right to left, and the output end of the blower penetrates through the partition plate, and a radiator is fixed on the right side wall of the positioning frame.

Preferably, the left and right outer side walls of the box body are provided with ventilation openings, and the wind direction inside the box body is from right to left.

Preferably, the main controller internally comprises a wireless receiving module, an image processing module, a sensing module and a data processing module.

Preferably, buffer gear from the top down has set gradually support one, flexible loop bar, compression spring and support two, the bottom of support one articulates there is flexible loop bar, and the bottom of flexible loop bar articulates there is support two, the middle part cover of flexible loop bar is equipped with compression spring, and compression spring's upper and lower both ends respectively with support one, two elastic clamping of support.

Preferably, the top ends of the supporting plates at the second support are provided with sinking grooves, bearings are embedded in the sinking grooves, and the bottom ends of the second support and the bearings are mutually nested to form a rotating connection structure.

Preferably, the top of the bearing is sleeved with a positioning ring, and the edge position of the positioning ring is fixedly connected with the supporting plate through screws with equal angles.

Preferably, the depth filter is filled with two groups of activated carbon sheets at equal intervals.

Preferably, a plurality of thin copper sheets are arranged in the radiator at equal intervals.

Preferably, the locating rack is of an L-shaped structure, and the locating rack is obliquely distributed in the box body.

(III) advantageous effects

Compared with the prior art, the invention provides an automatic driving machine learning device, which has the following beneficial effects:

1. according to the automatic driving machine learning device, the composite filter screen, the air blower, the partition plate, the depth filter and the radiator are sequentially arranged in the box body, so that gas in the cabin is subjected to dust removal, deodorization and heat dissipation from right to left;

2. the automatic driving machine learning device is characterized in that a vibration motor is arranged between a base plate and a supporting plate and used for simulating vibration, a servo motor is fixedly connected with a simulated cockpit through a rotating shaft and used for simulating turning, two ends of a telescopic loop bar are respectively hinged with a first support and a second support, the second support is rotatably connected with a bearing and used for auxiliary support, the first support and the second support are elastically connected through a compression spring and used for buffer protection, and therefore authenticity of the learning device during simulation is improved;

3. this automatic drive machine learning device through set up wireless receiving module, image processing module, sensing module and data processing module in the master controller to reach real-time road conditions simulation driving and many-sided function of synthesizing the judgement, thereby strengthened learning device's practical effect.

Drawings

FIG. 1 is a schematic view of a front view semi-section structure of the present invention;

FIG. 2 is an enlarged view of the structure at A in FIG. 1 according to the present invention;

FIG. 3 is a schematic top sectional view of the case according to the present invention;

FIG. 4 is a flow chart of the system process of the present invention.

In the figure: 1. a substrate; 2. a vibration motor; 3. a support plate; 4. a servo motor; 5. a rotating shaft; 6. simulating a cockpit; 7. a box body; 8. a master controller; 9. a buffer mechanism; 901. a first support; 902. a telescopic loop bar; 903. a compression spring; 904. a second support; 10. sinking a groove; 11. a bearing; 12. positioning rings; 13. a vent; 14. compounding a filter screen; 15. a blower; 16. a partition plate; 17. a depth filter; 18. a heat sink; 19. a positioning frame.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

Referring to fig. 1-4, the present invention provides a technical solution: the automatic driving machine learning device comprises a base plate 1, a supporting plate 3, a simulation driving cabin 6, a box body 7, a main controller 8 and a buffer mechanism 9, wherein vibration motors 2 are installed on the left side and the right side of the top end of the base plate 1, the type of each vibration motor 2 can be YZS-100-4, the input ends of the vibration motors 2 are electrically connected with the output end of a PLC (programmable logic controller) inside the main controller 8, the output ends of the vibration motors 2 are fixedly connected with the bottom end of the supporting plate 3, a servo motor 4 is fixed at the central position of the top end of the supporting plate 3, the type of the servo motor 4 can be MR-J2S-40A, the input end of the servo motor 4 is electrically connected with the output end of the PLC inside the main controller 8, a rotating shaft 5 is installed at the output end of the servo motor 4 through a coupler, the top end of the rotating shaft 5 is, Buffer gear 9 is installed at the corner position between the simulation cockpit 6, a main controller 8 is arranged at the left side inside the simulation cockpit 6, the model of the main controller 8 can be M580, a box 7 is fixed at the top of the simulation cockpit 6, a composite filter screen 14, an air blower 15, a partition plate 16, a depth filter 17 and a positioning frame 19 are sequentially installed inside the box 7 from right to left, the model of the air blower 15 can be GY4-73, the input end of the air blower 15 is electrically connected with the output end of a PLC (programmable logic controller) inside the main controller 8, the output end of the air blower 15 penetrates through the partition plate 16, and a radiator 18 is fixed on the right side wall of the positioning frame 19.

As in FIG. 3, the left and right outer side walls of the box 7 are provided with vents 13, and the wind direction inside the box 7 is from right to left for fresh air circulation.

As shown in fig. 1, the main controller 8 includes a wireless receiving module, an image processing module, a sensing module and a data processing module, and is used for realizing real-time road condition simulation driving and multi-aspect comprehensive judgment.

As shown in fig. 2, the buffering mechanism 9 is sequentially provided with a first support 901, a telescopic loop bar 902, a compression spring 903 and a second support 904 from top to bottom, the bottom of the first support 901 is hinged with the telescopic loop bar 902, the bottom end of the telescopic loop bar 902 is hinged with the second support 904, the compression spring 903 is sleeved at the middle of the telescopic loop bar 902, and the upper end and the lower end of the compression spring 903 are elastically clamped with the first support 901 and the second support 904 respectively for auxiliary support and buffer protection.

As shown in fig. 2, the top ends of the supporting plates 3 at the position of the second support 904 are all provided with a sinking groove 10, a bearing 11 is embedded inside the sinking groove 10, and the bottom end of the second support 904 and the bearing 11 are nested with each other to form a rotating connection structure for synchronous rotation and extension.

As shown in fig. 2, the top of the bearing 11 is sleeved with a positioning ring 12, and the edge of the positioning ring 12 is fixedly connected with the supporting plate 3 through screws with equal angles for mounting and locking the bearing 11.

Two groups of activated carbon sheets are filled in the depth filter 17 at equal intervals as shown in fig. 3, and are used for fully contacting with gas and sterilizing and deodorizing.

As shown in fig. 3, a plurality of thin copper sheets are disposed inside the heat sink 18 at equal intervals for exchanging heat and cooling the gas.

The positioning frame 19 is in an L-shaped structure as shown in fig. 3, and the positioning frame 19 is obliquely distributed in the box body 7 for increasing the contact area of the radiator 18 and the gas.

The working principle is as follows: when the intelligent driving simulation system is used, as shown in attached figures 1 and 4, a learner enters the simulation cockpit 6, firstly, the master controller 8 is operated, the system is started and the identity of the system is verified, and as the wireless receiving module, the image processing module, the sensing module and the data processing module are arranged inside the master controller 8, the learner can randomly select road sections, and real-time road condition pictures of the road sections are obtained through a wireless network, so that driving is simulated and comprehensive judgment is carried out in multiple aspects;

in the process, as shown in fig. 3, the blower 15 continuously operates, so that air inside the simulated cockpit 6 circulates in the box 7 from right to left through the vent 13, and sequentially passes through the composite filter screen 14, the blower 15, the partition 16, the depth filter 17 and the radiator 18, wherein the composite filter screen 14 is used for multi-layer dust removal, the blower 15 blows filtered air to the depth filter 17 through the partition 16, sterilization and deodorization are completed through two groups of activated carbon sheets in the depth filter 17, and the positioning frames 19 with the L-shaped structures are obliquely distributed in the box 7, so that the contact area between thin copper sheets in the radiator 18 and the air can be increased, the internal environment of the learning device is improved, and a learner can concentrate on simulating and learning;

meanwhile, according to the attached

drawings

1 and 2, according to the real-time road condition picture and the operation behavior of the learner, the two vibration motors 2 on the base plate 1 apply vibration of different degrees to the supporting plate 3 for simulating a vibration environment, and the servo motor 4 drives the simulation cockpit 6 to rotate left and right within an allowed angle through the rotating shaft 5 under the action of pulses for simulating turning, in addition, as two ends of the telescopic loop bar 902 are respectively hinged with the first support 901 and the second support 904, and the second support 904 is rotatably connected with the bearing 11, synchronous rotation and extension of the buffer mechanism 9 are realized, so that auxiliary support is provided for the simulation cockpit 6, wherein the first support 901 and the second support 904 are elastically connected through the compression spring 903, the buffer protection can be realized, the buffer mechanism 9 is prevented from being damaged, and the automatic driving learning process is finished until the system prompts.

In conclusion, the automatic driving machine learning device not only improves the internal environment of the learning device and the authenticity of the learning device during simulation, but also enhances the practical effect of the learning device.

It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.

Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.

Claims

1. The utility model provides an autopilot machine learning, includes base plate (1), layer board (3), simulation cockpit (6), box (7), master controller (8) and buffer gear (9), its characterized in that: the left side and the right side of the top end of the base plate (1) are provided with vibration motors (2), the output ends of the vibration motors (2) are fixedly connected with the bottom ends of the supporting plates (3), the center positions of the top ends of the supporting plates (3) are fixed with servo motors (4), the output ends of the servo motors (4) are provided with rotating shafts (5) through shaft couplings, the top ends of the rotating shafts (5) are fixedly connected with the bottom ends of the simulation cockpit (6), the corner positions between the supporting plates (3) and the simulation cockpit (6) are provided with buffer mechanisms (9), the left side inside the simulation cockpit (6) is provided with a main controller (8), the top of the simulation cockpit (6) is fixed with a box body (7), and the box body (7) is sequentially provided with a composite filter screen (14), an air blower (15), a partition plate (16), a depth filter (17) and a positioning frame (19) from right inside, the output end of the blower (15) penetrates through the partition plate (16), and a radiator (18) is fixed on the right side wall of the positioning frame (19).

2. The autonomous driving machine learning apparatus of claim 1, wherein: the ventilation openings (13) are formed in the left outer side wall and the right outer side wall of the box body (7), and the wind direction inside the box body (7) is from right to left.

3. The autonomous driving machine learning apparatus of claim 1, wherein: the main controller (8) comprises a wireless receiving module, an image processing module, a sensing module and a data processing module.

4. The autonomous driving machine learning apparatus of claim 1, wherein: buffer gear (9) from the top down has set gradually support one (901), flexible loop bar (902), compression spring (903) and support two (904), the bottom of support one (901) articulates there is flexible loop bar (902), and the bottom of flexible loop bar (902) articulates there is support two (904), the middle part cover of flexible loop bar (902) is equipped with compression spring (903), and the upper and lower both ends of compression spring (903) respectively with support one (901), support two (904) elasticity joint.

5. The autonomous driving machine learning apparatus of claim 4, wherein: heavy groove (10) have all been seted up on layer board (3) top of support two (904) position department, and the inside of heavy groove (10) all inlays and has bearing (11), and the bottom of support two (904) and bearing (11) are nested each other and constitute rotation connection structure.

6. The autonomous driving machine learning apparatus of claim 5, wherein: the top of the bearing (11) is sleeved with a positioning ring (12), and the edge position of the positioning ring (12) is fixedly connected with the supporting plate (3) through screws with equal angles.

7. The autonomous driving machine learning apparatus of claim 1, wherein: two groups of activated carbon sheets are filled in the depth filter (17) at equal intervals.

8. The autonomous driving machine learning apparatus of claim 1, wherein: and a plurality of thin copper sheets are arranged in the radiator (18) at equal intervals.

9. The autonomous driving machine learning apparatus of claim 1, wherein: the positioning frame (19) is of an L-shaped structure, and the positioning frame (19) is obliquely distributed in the box body (7).