Intelligent network connection vehicle driving planning method and device

Abstract

The invention discloses an intelligent network connection vehicle driving planning method and device, and the method comprises the steps: data collection, data processing, carrying out the fusion processing of the collected data through a vehicle-mounted computing platform or a cloud server, and extracting key information; dynamic map construction: dynamically updating a local map of the vehicle according to the processed data; driving intention recognition: determining a driving target and preference of the vehicle through driver input or an automatic recognition algorithm; performing multi-objective optimization to generate an alternative driving path set; selecting and adjusting a path according to the real-time traffic information and the vehicle state; and executing control. The method has the beneficial effects that the traffic time used by the intersection optimal traffic strategy generated by considering the driving risk, the steering intention of surrounding vehicles, the driving style and other information is the shortest, the acceleration change is stable in the whole process, and the risk value and the acceleration value are always within the required ranges of safety rewards and comfort; and the requirements of safety, passing efficiency and comfort can be met.

Description

Technical Field

[0001] The present invention relates to the field of driving planning devices, and in particular to a driving planning method and device for an intelligent networked vehicle. Background Art

[0002] The driving planning device is a key component of an autonomous vehicle or an advanced driver assistance system. The device is responsible for calculating in real time a safe, efficient and traffic-compliant driving path based on the vehicle's current state, surrounding environment, traffic rules, and the driver's or system's intentions, and generating corresponding control instructions to control the vehicle to travel along this path. Intelligent connected vehicles refer to the organic combination of vehicle networking and smart cars. It is an emerging automotive system that spans technologies and industries. This type of vehicle is equipped with advanced on-board sensors, controllers, actuators and other devices, and integrates modern communication and network technologies to achieve the exchange and sharing of intelligent information between vehicles and people, vehicles, roads, and background.

[0003] Intelligent connected vehicles require the use of driving planning devices during the driving process. Since the camera of the driving planning device is exposed to the outside, external pollutants such as dust, dirt, rainwater, etc. are easily attached to the detection head, which may affect the performance of the detection head and cause the driving planning device to make misjudgments, resulting in safety hazards to the driving system and increasing the risk of traffic accidents.

[0004] Therefore, in response to the above technical problems, it is necessary to propose a driving planning method and device for intelligent connected vehicles. Summary of the invention

[0005] In order to make up for the shortcomings of the prior art, since the camera of the driving planning device is exposed to the outside, external pollutants such as dust, dirt, rainwater, etc. are easily attached to the detection head, which may affect the performance of the detection head and cause the driving planning device to make misjudgments, resulting in safety hazards to the driving system and increased risks of traffic accidents. The present invention proposes a driving planning method and device for intelligent connected vehicles.

[0006] The technical solution adopted by the present invention to solve its technical problem is:

[0007] A driving planning method for an intelligent connected vehicle, the method steps are as follows:

[0008] S1. Data collection: Collect vehicle status information, surrounding environment information and traffic condition information through on-board driving planning equipment;

[0009] S2. Data processing: Use the on-board computing platform or cloud server to integrate and process the collected data to extract key information, such as lane lines, traffic signs, obstacle locations, traffic flow, etc.

[0010] S3, dynamic map construction: dynamically update the vehicle's local map based on the processed data, including information such as road structure, traffic rules, temporary events, etc.;

[0011] S4, driving intention recognition: determine the vehicle's driving goals and preferences, such as destination, expected arrival time, driving mode, etc., through driver input or automatic recognition algorithms;

[0012] S5, multi-objective optimization: comprehensively consider factors such as driving time, energy consumption, safety, etc., establish a multi-objective optimization model, and generate a set of alternative driving routes;

[0013] S6, Path selection and adjustment: Based on real-time traffic information and vehicle status, machine learning algorithms are used to evaluate the pros and cons of alternative paths, select the optimal path, and dynamically adjust it according to real-time conditions;

[0014] S7, control execution: Convert the planning results into control instructions and execute them through the vehicle control system to achieve automatic driving or assisted driving functions.

[0015] The driving intention recognition uses the TCN-Transformer network to build a driving intention prediction model for vehicles around the intersection, and improves the prediction accuracy by integrating the multimodal features in the vehicle motion state sequence data.

[0016] A driving planning device for an intelligent networked vehicle includes a vehicle-mounted driving planning device, including a body, a vehicle-mounted sensor, a camera and a radar, wherein the body includes a shell, a top of an inner cavity of the shell is provided with a heat dissipation hole, and the number of the heat dissipation holes is multiple, a power connection is fixedly connected to the bottom of the back side of the shell, a planning control body is installed on the right side of the inner cavity of the shell, a mounting block is fixedly connected to the front side of the top of the shell, and a camera is fixedly connected to the front side of the mounting block;

[0017] A cleaning mechanism is installed on the front side of the shell, and the cleaning mechanism includes a fixed frame, the front side of the fixed frame is fixedly connected to the inner wall of the shell, the inner cavity of the fixed frame is fixedly connected to a motor, the output end of the motor is fixedly connected to a rotating disk, the top of the front side of the rotating disk is fixedly connected to a rotating rod, the surface of the rotating rod is movably connected to a moving plate, the bottom of the inner cavity of the moving plate is movably connected to a rotating column, the top of the back side of the moving plate is movably connected to a microfiber cloth, and the back side of the microfiber cloth is movably connected to the front side of the camera.

[0018] Preferably, the back side of the rotating column is fixedly connected to a support block, the back side of the support block is fixedly connected to the bottom of the front side of the shell, the front side of the rotating column is fixedly connected to a first limit block, and the back side of the first limit block is movably connected to the bottom of the front side of the movable plate.

[0019] Preferably, a fixed block is fixedly connected to the top of the front side of the shell, the number of the fixed blocks is two, a fixed rod is fixedly connected to the inner side of the fixed block, a slider is movably connected to the surface of the fixed rod, and a guide column is fixedly connected to the front side of the slider.

[0020] Preferably, a movable groove is opened at the bottom of the movable plate inner cavity, the surface of the rotating rod is movably connected to the inside of the movable groove, a guide groove is opened at the center of the movable plate inner cavity, and the surface of the guide column is movably connected to the inside of the guide groove.

[0021] Preferably, a groove is provided at the top of the back side of the inner cavity of the movable plate, and the surface of the microfiber cloth is movably connected to the inside of the groove.

[0022] Preferably, the front side of the rotating rod is fixedly connected to a second limit block, the back side of the second limit block is movably connected to the front side of the movable plate, the front side of the guide column is fixedly connected to a third limit block, and the back side of the third limit block is movably connected to the center of the front side of the movable plate.

[0023] Preferably, a fixing mechanism is installed on the top of the back side of the movable plate, and the fixing mechanism includes a support plate, the front side of the support plate is fixedly connected to the back side of the movable plate, the number of the support plates is two, the inner side of the support plate is fixedly connected to a fixing column, the surface of the fixing column is movably connected to the fixing plate, and the front side of the fixing plate is movably connected to the back side of the microfiber cloth.

[0024] Preferably, both sides of the surface of the fixing column are movably connected with torsion springs, one end of the torsion spring is fixedly connected to the inner wall of the support plate, and the other end of the torsion spring is fixedly connected to the surface of the fixing plate.

[0025] Beneficial effects of the present invention:

[0026] 1. The optimal traffic strategy for intersections generated by the present invention, which takes into account information such as driving risks, turning intentions of surrounding vehicles and driving styles, takes the shortest travel time, and the acceleration changes smoothly during the whole process. The risk value and the jerk value are always within the required range of safety bonus and comfort, which can meet the requirements of safety, traffic efficiency and comfort, and has good adaptability to intersection interaction scenarios with different traffic directions and traffic flow densities.

[0027] 2. The present invention drives the rotating disk to rotate through the operation of the motor, drives the rotating rod to rotate through the rotating disk, drives the moving plate to move through the rotating rod, and the bottom of the moving plate rotates around the surface of the rotating column, and drives the microfiber cloth to move through the moving plate, so that the microfiber cloth can be moved in front of the camera, achieving the effect of cleaning the pollutants adhered to the front side of the camera, and solving the problem that the camera of the driving planning device is exposed to the outside, which leads to external pollutants such as dust, dirt, rainwater, etc., which are easily attached to the detection head, thereby possibly affecting the performance of the detection head, causing the driving planning device to misjudge, resulting in safety hazards to the driving system and increasing the risk of traffic accidents. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0029] Figure 1 This is a flow chart of the intelligent connected vehicle driving planning method of the present invention;

[0030] Figure 2 This is the TCN-Transformer network structure diagram of the present invention

[0031] Figure 3 It is a structural schematic diagram of the present invention;

[0032] Figure 4 is a cross-sectional view of the housing structure of the present invention;

[0033] Figure 5 It is a connection schematic diagram of the rotating disk structure of the present invention;

[0034] Figure 6 It is a rear view of the movable plate structure of the present invention;

[0035] Figure 7 It is a schematic diagram of the connection between the support plate and the fixing plate structure of the present invention.

[0036] 10. The reference numerals in the figure are as follows: 1. body; 101. shell; 102. heat dissipation hole; 103. power connection; 104. planning control body; 105. mounting block; 106. camera; 2. cleaning mechanism; 201. motor; 202. fixing frame; 203. rotating disk; 204. moving plate; 205. supporting block; 206. fixing block; 207. sliding block; 208. fixing rod; 209. rotating column; 210. first limiting block; 211. moving groove; 212. second limiting block; 213. rotating rod; 214. guide groove; 215. third limiting block; 216. guide column; 217. groove; 218. microfiber cloth; 3. fixing mechanism; 301. supporting plate; 302. torsion spring; 303. fixing column; 304. fixing plate. DETAILED DESCRIPTION

[0037] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0038] The following is combined with Figure 1-7 To further explain this application in detail,

[0039] A driving planning method for an intelligent connected vehicle, the method steps are as follows:

[0040] S1. Data collection: Collect vehicle status information, surrounding environment information and traffic condition information through on-board driving planning equipment;

[0041] S2. Data processing: Use the on-board computing platform or cloud server to integrate and process the collected data to extract key information, such as lane lines, traffic signs, obstacle locations, traffic flow, etc.

[0042] S3, dynamic map construction: dynamically update the vehicle's local map based on the processed data, including information such as road structure, traffic rules, temporary events, etc.;

[0043] S4, driving intention recognition: determine the vehicle's driving goals and preferences, such as destination, expected arrival time, driving mode, etc., through driver input or automatic recognition algorithms;

[0044] S5, multi-objective optimization: comprehensively consider factors such as driving time, energy consumption, safety, etc., establish a multi-objective optimization model, and generate a set of alternative driving routes;

[0045] S6, Path selection and adjustment: Based on real-time traffic information and vehicle status, machine learning algorithms are used to evaluate the pros and cons of alternative paths, select the optimal path, and dynamically adjust it according to real-time conditions;

[0046] S7, control execution: Convert the planning results into control instructions and execute them through the vehicle control system to achieve automatic driving or assisted driving functions.

[0047] The driving intention recognition uses the TCN-Transformer network to build a driving intention prediction model for vehicles around the intersection, and improves the prediction accuracy by integrating the multimodal features in the vehicle motion state sequence data.

[0048] The steps of the TCN-Transformer network algorithm are as follows: the vehicle driving data is converted into a local feature sequence through multiple convolutional layers and residual blocks of the TCN module, and then the extracted local feature sequence is converted into a global feature sequence using the multi-head attention layer and feedforward neural network of the Transformer module. Then, the global feature sequence is mapped to the prediction output space using a fully connected layer, and finally the driving intention prediction result is obtained by normalization through the SoftMax function. The driving feature sequence input to the network is as follows:

[0049] x={x1,x2,…,x t-1 , x t}, (1)

[0050]

[0051] Where: x t represents the driving characteristics input at time t, l t is the distance from the target vehicle to the center of the intersection at time t, v x_t 、v y_t are the lateral and longitudinal speeds of the target vehicle at time t, a x_t 、a y_t are the lateral and longitudinal accelerations of the target vehicle at time t, is the yaw angle of the target vehicle at time t.

[0052] The TCN module uses residual blocks to replace convolutional layers. Through two rounds of extended causal convolution, normalization, ReLU activation function and Dropout, the model's ability to represent and learn driving sequence data is enhanced, overfitting problems are reduced, and the generalization ability of the model is improved. Then, a one-dimensional convolutional layer is used to ensure that the output feature dimension is the same as the input. Among them, the extended causal convolution can ensure that the training process does not involve future time data. At the same time, the receptive field of the convolutional layer is increased by increasing the convolution kernel length and the expansion factor, thereby improving the model's ability to learn long-distance dependencies. The specific expression is as follows:

[0053]

[0054] Where: w k represents the convolution kernel of size k, is the dilation factor, and the local feature sequence output by the TCN module is as follows:

[0055] h t =R(F(x t )). (4)

[0056] Where: R represents the nonlinear activation function of the fully connected layer.

[0057] The Transformer module is mainly composed of a self-attention layer and a feed-forward neural network. The local feature sequence h output by the TCN module is converted into t Convert to global feature sequence z t , use LayerNorm to normalize the data:

[0058] z t =LayerNorm(h t +MHA(h t W Q ,h t W K ,h t W V )+FFN(h t )), (5)

[0059]

[0060] FFN(x t ) = RELU(x t W1+b1)W2+b2. (7)

[0061] Where: MHA is a multi-layer self-attention layer, W Q , W K , W V are the weight matrices for query, key, and value, respectively. γ and β are learnable scaling factors and translation factors, respectively. FFN is a feedforward neural network. W1 and W2 are weight matrices. b1 and b2 are bias vectors. S and σ are mean and standard deviation, respectively. RELU is the rectified linear unit activation function.

[0062] The network finally obtains the prediction results of the surrounding vehicle driving intention through the fully connected layer and the Softmax layer:

[0063]

[0064] FC(z)=zW fc +b fc , (9)

[0065]

[0066] Where: is the driving intention category; W fc and b fc are the weight matrix and bias vector of the fully connected layer respectively; K is the number of categories, K=3; FC(z) i represents the i-th output of the fully connected layer.

[0067] A driving planning device for an intelligent networked vehicle includes a vehicle-mounted driving planning device, including a body, a vehicle-mounted sensor, a camera and a radar, wherein the body 1 includes a shell 101, a heat dissipation hole 102 is provided at the top of the inner cavity of the shell 101, and the number of the heat dissipation holes 102 is multiple, a power connection 103 is fixedly connected to the bottom of the back side of the shell 101, a planning control body 104 is installed on the right side of the inner cavity of the shell 101, a mounting block 105 is fixedly connected to the front side of the top of the shell 101, and a camera 106 is fixedly connected to the front side of the mounting block 105;

[0068] A cleaning mechanism 2 is installed on the front side of the shell 101, and the cleaning mechanism 2 includes a fixed frame 202, the front side of the fixed frame 202 is fixedly connected to the inner wall of the shell 101, the inner cavity of the fixed frame 202 is fixedly connected to the motor 201, the output end of the motor 201 is fixedly connected to the rotating disk 203, the top of the front side of the rotating disk 203 is fixedly connected to the rotating rod 213, the surface of the rotating rod 213 is movably connected to the moving plate 204, the bottom of the inner cavity of the moving plate 204 is movably connected to the rotating column 209, the top of the back side of the moving plate 204 is movably connected to the microfiber cloth 218, and the back side of the microfiber cloth 218 is movably connected to the front side of the camera 106.

[0069] Reference Figure 2 and Figure 3 The back side of the rotating column 209 is fixedly connected to a support block 205, and the back side of the support block 205 is fixedly connected to the bottom of the front side of the shell 101. The front side of the rotating column 209 is fixedly connected to a first limit block 210, and the back side of the first limit block 210 is movably connected to the bottom of the front side of the moving plate 204. Through the setting of the support block 205, the rotating column 209 is supported, so that the moving plate 204 is more stable when rotating. Through the setting of the first limit block 210, and the diameter of the first limit block 210 is larger than the diameter of the rotating column 209, the first limit block 210 forms a blocking surface, which can prevent the bottom of the moving plate 204 from separating from the surface of the rotating column 209 when rotating.

[0070] A fixed block 206 is fixedly connected to the top of the front side of the shell 101, and there are two fixed blocks 206. A fixed rod 208 is fixedly connected to the inner side of the fixed block 206. A slider 207 is movably connected to the surface of the fixed rod 208. A guide column 216 is fixedly connected to the front side of the slider 207. The setting of the fixed block 206 provides stable support for the fixed rod 208 to prevent the fixed rod 208 from tilting or deflecting. The setting of the guide column 216 guides the movement of the movable plate 204 to prevent the movable plate 204 from deflecting during rotation.

[0071] A moving groove 211 is provided at the bottom of the inner cavity of the moving plate 204, and the surface of the rotating rod 213 is movably connected to the inside of the moving groove 211. A guide groove 214 is provided at the center of the inner cavity of the moving plate 204, and the surface of the guide column 216 is movably connected to the inside of the guide groove 214. Through the setting of the moving groove 211, a suitable moving space can be provided for the rotating rod 213, so that the rotating rod 213 can move at the bottom of the inner cavity of the moving plate 204. Through the setting of the guide groove 214, a movable channel can be formed for the guide column 216, so that the guide column 216 can move inside the moving plate 204 and can guide the movement of the guide column 216.

[0072] A groove 217 is provided at the top of the back side of the inner cavity of the movable plate 204, and the surface of the microfiber cloth 218 is movably connected to the inside of the groove 217. Through the setting of the groove 217 and the shape of the groove 217 being the same as the shape of the microfiber cloth 218, a movable space is provided for the microfiber cloth 218, so that the microfiber cloth 218 can be accurately placed inside the groove 217.

[0073] A second limit block 212 is fixedly connected to the front side of the rotating rod 213, and a back side of the second limit block 212 is movably connected to the front side of the movable plate 204. A third limit block 215 is fixedly connected to the front side of the guide column 216, and a back side of the third limit block 215 is movably connected to the center of the front side of the movable plate 204. By setting the second limit block 212, the diameter of the second limit block 212 is larger than the diameter of the rotating rod 213, and the second limit block 212 can fit tightly to the front side of the movable plate 204, thereby preventing the movable plate 204 from separating from the surface of the rotating rod 213 during the rotation process. By setting the third limit block 215, and the size of the third limit block 215 is larger than the size of the guide column 216, the guide column 216 is more stable when moving inside the guide groove 214, and can prevent the guide column 216 from separating from the inside of the guide groove 214 during the movement.

[0074] A fixing mechanism 3 is installed on the top of the back side of the movable plate 204, and the fixing mechanism 3 includes a supporting plate 301. The front side of the supporting plate 301 is fixedly connected to the back side of the movable plate 204. There are two supporting plates 301. A fixing column 303 is fixedly connected to the inner side of the supporting plate 301. The surface of the fixing column 303 is movably connected to the fixing plate 304. The front side of the fixing plate 304 is movably connected to the back side of the microfiber cloth 218. Through the setting of the supporting plate 301, the fixing column 303 is provided with stable support to avoid shaking caused by external force. Through the setting of the fixing column 303, the rotation of the fixing plate 304 is supported, so that the fixing plate 304 is more stable during the rotation process, and the deviation of the fixing plate 304 during the rotation process is avoided.

[0075] Torsion springs 302 are movably connected to both sides of the surface of the fixed column 303, one end of the torsion spring 302 is fixedly connected to the inner wall of the support plate 301, and the other end of the torsion spring 302 is fixedly connected to the surface of the fixed plate 304. Through the setting of the torsion spring 302, when the fixed plate 304 rotates, the torsion spring 302 is compressed and deformed. When the compression force of the torsion spring 302 disappears, the fixed plate 304 is pushed to quickly reset.

[0076] Working principle: The operator installs the housing 101 in the car, and then connects it to the car's control system through the power connection 103 to use this design. Then, the camera 106 collects information from the outside and transmits the information to the planning control body 104. After planning, it is used to intelligently control the car. Next, the operator holds the microfiber cloth 218 and places the microfiber cloth 218 inside the groove 217. Then, the operator rotates the fixing plate 304 by hand. One end of the fixing plate 304 rotates around the surface of the fixing column 303. The rotation of the fixing plate 304 causes the torsion spring 302 to deform under force. After the deformation is restored, the fixing plate 304 can be driven to quickly reset. When the fixing plate 304 rotates to the surface of the microfiber cloth 218, It is fixed to prevent the microfiber cloth 218 from shifting during cleaning. The motor 201 drives the rotating disk 203 to rotate, and the rotating disk 203 drives the rotating rod 213 to move inside the moving groove 211 while driving the moving plate 204 to move. The bottom of the moving plate 204 rotates around the surface of the rotating column 209, and the moving plate 204 drives the guide column 216 to move inside the guide groove 214. At the same time, the movement of the guide column 216 drives the slider 207 to move on the surface of the fixed rod 208. The moving plate 204 drives the microfiber cloth 218 to move left and right in front of the camera 106, thereby cleaning the pollutants adhering to the front side of the camera 106, so that the camera 106 can operate normally.

[0077] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments, and the above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, and these changes and improvements all fall within the scope of the present invention to be protected.

Claims

1. A driving planning method for an intelligent connected vehicle, characterized in that: The method steps are: S1. Data collection: Collect vehicle status information, surrounding environment information and traffic condition information through on-board driving planning equipment; S2, data processing: using the vehicle computing platform or cloud server to integrate and process the collected data and extract key information; S3, dynamic map construction: dynamically update the local map of the vehicle based on the processed data; S4, driving intention recognition: determine the vehicle's driving goals and preferences through driver input or automatic recognition algorithms; S5, multi-objective optimization: comprehensively consider driving time, energy consumption, and safety factors, establish a multi-objective optimization model, and generate a set of alternative driving routes; S6, Path selection and adjustment: Based on real-time traffic information and vehicle status, machine learning algorithms are used to evaluate the pros and cons of alternative paths, select the optimal path, and dynamically adjust it according to real-time conditions; S7, control execution: Convert the planning results into control instructions and execute them through the vehicle control system to achieve automatic driving or assisted driving functions.

2. The method for driving planning of an intelligent connected vehicle according to claim 1, characterized in that: The driving intention recognition uses the TCN-Transformer network to build a driving intention prediction model for vehicles around the intersection, and improves the prediction accuracy by integrating the multimodal features in the vehicle motion state sequence data.

3. A device for a driving planning method for an intelligent connected vehicle as described in any one of claims 1-2, characterized in that: The vehicle-mounted driving planning device comprises a body (1), the body (1) comprises a shell (101), a heat dissipation hole (102) is provided at the top of the inner cavity of the shell (101), the number of the heat dissipation holes (102) is multiple, a power supply connection (103) is fixedly connected to the bottom of the back side of the shell (101), a planning control body (104) is installed on the right side of the inner cavity of the shell (101), a mounting block (105) is fixedly connected to the front side of the top of the shell (101), and a camera (106) is fixedly connected to the front side of the mounting block (105); A cleaning mechanism (2) is installed on the front side of the housing (101), and the cleaning mechanism (2) comprises a fixing frame (202), the front side of the fixing frame (202) is fixedly connected to the inner wall of the housing (101), the inner cavity of the fixing frame (202) is fixedly connected to a motor (201), the output end of the motor (201) is fixedly connected to a rotating disk (203), the top of the front side of the rotating disk (203) is fixedly connected to a rotating rod (213), the surface of the rotating rod (213) is movably connected to a moving plate (204), the bottom of the inner cavity of the moving plate (204) is movably connected to a rotating column (209), the top of the back side of the moving plate (204) is movably connected to a microfiber cloth (218), and the back side of the microfiber cloth (218) is movably connected to the front side of the camera (106).

4. The driving planning device for an intelligent networked vehicle according to claim 3, characterized in that: The back side of the rotating column (209) is fixedly connected to a support block (205), and the back side of the support block (205) is fixedly connected to the bottom of the front side of the housing (101). The front side of the rotating column (209) is fixedly connected to a first limit block (210), and the back side of the first limit block (210) is movably connected to the bottom of the front side of the moving plate (204).

5. The driving planning device for an intelligent networked vehicle according to claim 3, characterized in that: A fixing block (206) is fixedly connected to the top of the front side of the housing (101), and the number of the fixing blocks (206) is two. A fixing rod (208) is fixedly connected to the inner side of the fixing block (206), and a sliding block (207) is movably connected to the surface of the fixing rod (208). A guide column (216) is fixedly connected to the front side of the sliding block (207).

6. The driving planning device for an intelligent networked vehicle according to claim 5, characterized in that: A moving groove (211) is provided at the bottom of the inner cavity of the moving plate (204), the surface of the rotating rod (213) is movably connected to the inside of the moving groove (211), a guide groove (214) is provided at the center of the inner cavity of the moving plate (204), and the surface of the guide column (216) is movably connected to the inside of the guide groove (214).

7. The driving planning device for an intelligent networked vehicle according to claim 5, characterized in that: A groove (217) is provided at the top of the back side of the inner cavity of the movable plate (204), and the surface of the microfiber cloth (218) is movably connected to the inside of the groove (217).

8. The driving planning device for an intelligent networked vehicle according to claim 5, characterized in that: The front side of the rotating rod (213) is fixedly connected to a second limit block (212), the back side of the second limit block (212) is movably connected to the front side of the moving plate (204), the front side of the guide column (216) is fixedly connected to a third limit block (215), and the back side of the third limit block (215) is movably connected to the center of the front side of the moving plate (204).

9. The intelligent connected vehicle driving planning device according to claim 3, characterized in that: A fixing mechanism (3) is installed at the top of the back side of the movable plate (204), and the fixing mechanism (3) comprises a support plate (301), the front side of the support plate (301) is fixedly connected to the back side of the movable plate (204), the number of the support plates (301) is two, the inner side of the support plate (301) is fixedly connected to a fixing column (303), the surface of the fixing column (303) is movably connected to the fixing plate (304), and the front side of the fixing plate (304) is movably connected to the back side of the microfiber cloth (218).

10. A driving planning device for an intelligent networked vehicle as claimed in claim 9, characterized in that: Torsion springs (302) are movably connected to both sides of the surface of the fixed column (303), one end of the torsion spring (302) is fixedly connected to the inner wall of the support plate (301), and the other end of the torsion spring (302) is fixedly connected to the surface of the fixed plate (304).

Images