Intelligent road network medium for vehicle-road cooperation triboelectricity self-driven perception

Abstract

The invention belongs to the field of vehicle-road cooperation self-driven sensing, and particularly relates to an intelligent road network medium for vehicle-road cooperation triboelectricity self-driven sensing. Comprising an embedded high-elasticity triboelectric self-driven sensing unit (1), a grating type middle interlayer (2), an upper steel base plate (301), a lower steel base plate (302), a steel strut and spring (303), cushioning foam (4), a high-strength flexible nano-modified caulking layer (5) and a high-strength high-toughness waterproof packaging layer (6). The embedded high-elastic triboelectricity self-driven sensing unit (1) is prepared by selecting two flexible materials with remarkable electronegativity difference according to triboelectrification and electrostatic induction effects. The method is suitable for sensing vehicle and road information such as road average speed, vehicle weight, road surface state and the like, and the sensing range is 10-120km / h of vehicle speed, 2-20t of vehicle weight and 0.35-0.8 of road surface friction coefficient. Compared with the prior art, the method has the advantages of multiple sensing information, wide sensing range, high sensing precision, high sensing network coverage rate and the like.

Description

Technical Field

[0001] The present invention belongs to the field of vehicle-road collaborative self-driving perception, and in particular relates to an intelligent road network medium for vehicle-road collaborative friction electric self-driving perception. Background Art

[0002] With the rapid development of urbanization in my country, the traffic volume has increased rapidly, and the development of intelligent transportation systems has emerged. However, traditional traffic management strategies are not enough to meet the needs of existing complex traffic scenarios, and research on the development of vehicle-road collaboration is imminent. Therefore, the invention of intelligent road network media for vehicle-road collaborative self-driving perception provides a new solution for the development of intelligent transportation. On the one hand, intelligent road network media can achieve efficient connectivity between vehicles and road infrastructure, reduce the heterogeneity of vehicle-road information, and thus improve the ability to obtain and process traffic information. On the other hand, intelligent road network media can promote collaborative perception and unified decision-making between vehicles, improve the safety and traffic efficiency of the transportation system, and provide vehicle intelligent driving, path planning, obstacle avoidance and other functions, thereby reducing the occurrence of traffic accidents.

[0003] Existing intelligent traffic management technology mainly relies on roadside sensing devices such as cameras and integrated radar vision devices. Although they can efficiently scan and identify vehicles and road information through images or videos, they cannot judge the safe speed and following distance in real time in bad weather conditions such as rain and fog. Therefore, starting from the surface structure of road infrastructure, developing a self-driving sensing medium that can be implanted in the road surface structure is the main solution to solve the low sensing efficiency in complex environments.

[0004] At present, CN202410832062.2 discloses a method and device for providing traffic information services based on vehicle-road collaborative intelligent driving. It mainly proposes a traffic information service strategy from an architectural perspective, but never considers the design and optimization of hardware such as sensing facilities, and cannot fundamentally solve the problems of low perception efficiency and poor safety in complex environments.

[0005] In addition, most of the sensors currently used in the field of pavement structures are based on the piezoelectric effect. By polarizing piezoelectric ceramics, the positive piezoelectric effect of piezoelectric materials is used to sense information and collect energy under external loads, such as CN 111893835 A, CN 113077636 B, and CN 114293429 A. The material must be piezoelectric, which is inconvenient to use and highly brittle, and the durability is difficult to meet the requirements. Summary of the invention

[0006] The purpose of the present invention is to provide an intelligent road network medium for vehicle-road cooperative triboelectric self-driving perception. Aiming at the complex traffic and climate scenes in smart transportation, it has the advantages of wide selection of materials, passive perception, diverse perception information, wide perception range, high perception accuracy, and high perception network coverage.

[0007] The purpose of the present invention can be achieved by the following technical solutions: An intelligent road network medium for vehicle-road cooperative triboelectric self-driving perception, comprising: an embedded high-elastic triboelectric self-driving perception unit, a grid-type middle partition, an upper steel pad, a lower steel pad, steel pillars and springs, shock-absorbing foam, a high-strength flexible nano-modified filling layer and a high-strength and high-toughness waterproof packaging layer.

[0008] The lower steel pad is installed above the high-strength and high-toughness waterproof packaging layer; Several steel pillars are fixed on the lower steel pad by internal bolts, and springs are placed on top of the steel pillars to buffer the vehicle load; The grid-type middle partition is a glass fiber reinforced plastic grid, which is fixed on the top of the lower steel pad, and the center and four sides are aligned with the lower steel pad; Steel struts and springs pass through the grille of the lattice-type center compartment; The grid-type middle partition is provided with a number of large holes, in which embedded high-elastic triboelectric self-driven sensing units are installed; Infusing highly elastic and highly flexible nano-modified materials into the small holes of the grid-type middle partition layer to fill the original holes of the grid-type middle partition layer and form a high-strength and flexible nano-modified gap filling layer; The lower surface of the upper steel pad is provided with shock-absorbing foam and is installed above the grid-type middle partition.

[0009] The embedded high-elastic triboelectric self-driven sensing unit 1 is prepared based on the triboelectric and electrostatic induction effects, preferably using two flexible materials with significant electronegativity differences, and includes: an electrode layer 101, a positive friction layer 102 and a negative friction layer 103, the wiring of the positive friction layer and the negative friction layer is led out through a grid-type intermediate spacer and connected to an external STM 32 microcontroller for data acquisition.

[0010] Preferably, the electronegativity of the positive electrode friction layer is 2.5-3.5, and the electronegativity of the negative electrode friction layer is 1.5-2.5.

[0011] Preferably, the material of the positive electrode friction layer is polytetrafluoroethylene with an electronegativity of 3.0, and the material of the negative electrode friction layer is aluminum foil with an electronegativity of 1.5.

[0012] The steps for installing the components of the intelligent road network medium for vehicle-road cooperative self-driving perception are as follows: The steel support column is fixed on the lower steel pad by internal bolts; Cut large holes in the FRP grille according to the design size of 10cm×7cm; The FRP grille is fixed on the top of the lower steel plate, and the center and four sides should be aligned with the corresponding positions of the lower steel plate; The flexible packaged triboelectric self-driven sensing unit is fixed in the large hole cut in the fiberglass grille, and the signal transmission line is led out; Springs are placed on top of the steel pillars to cushion vehicle loads; An elastic foam is fixed on the inner surface of the upper steel pad to protect the triboelectric sensing unit; Infuse highly elastic and flexible nano-modified materials into the small holes of the FRP grille to fill the original holes of the FRP grille; After the pouring material solidifies, cover it with an upper steel plate and make a waterproof packaging layer on top of the upper steel plate.

[0013] The height of the grid-type middle partition is 15-30 mm, the inner side length of the small hole is 25-35 mm, and the compressive strength is 30-50 MPa.

[0014] The steel structure support layer, the upper and lower steel pads, have a yield strength of 200-800 MPa. The spring is made of thermoplastic resin as a matrix, and is obtained by adding 0.05%-0.1% of nanoparticles as a 3D printing composite consumable in an additive manufacturing manner. The elastic coefficient is 4500-8000 N / mm.

[0015] The highly flexible nano-modified material has a flexural strength of 10-15 Mpa, a compressive strength of 35-60 Mpa and a rebound rate of 50-70% after curing.

[0016] The high-strength and high-toughness waterproof packaging layer is composed of high-performance silica gel and nano-SiO2, wherein the weight parts are: 1000-1500 parts of sodium silicate solution and 1-3 parts of sodium hydroxide particles.

[0017] The high-strength and high-toughness waterproof packaging layer has a curing time of 15-40 minutes at room temperature and a tear strength of 30-80 pli.

[0018] The intelligent road network medium is buried at a depth of 0-10 cm in the road structure, and at a longitudinal spacing of 10-60 m.

[0019] The intelligent road network medium is used to perceive the open circuit voltage signal as an indicator of the average vehicle speed, vehicle weight, road surface status and other signals of the road section, which is specifically calibrated by parameters such as amplitude and single peak interval.

[0020] The intelligent road network medium has a sensing range of vehicle speed of 10 to 120 km / h, vehicle weight of 2 to 20 tons and road friction coefficient of 0.35 to 0.8.

[0021] Beneficial Effects Compared with the prior art, the present invention has the following advantages: (1) The triboelectric self-driven sensing unit of the present invention has a wide range of functional components and can work normally without external power supply. It can sense vehicle and road information at the same time, and can better reduce the complexity of multi-heterogeneous information in smart transportation.

[0022] (2) The present invention uses an open circuit voltage signal as a characteristic signal for sensing information, with a response speed of <1ms and is not affected by vehicle speed, vehicle weight, etc.

[0023] (3) The intelligent road perception network adopted by the present invention can be applied to key traffic scenarios such as long tunnels, complex intersections, and viaducts. It has the advantages of good economy and over 90% perception accuracy and coverage. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a composition structure diagram of the present invention; wherein, 1—embedded high-elastic self-driven sensing unit, 2—grid-type middle partition, 301—upper steel pad, 302—lower steel pad, 303—steel pillar and spring, 4—shock-absorbing foam, 5—high-strength flexible nano-modified caulking layer, 6—high-strength and high-toughness waterproof packaging layer; Figure 2 This is a structural diagram of the embedded high-elastic self-driven sensing unit of the present invention; wherein 101 is an electrode layer, 102 is a positive electrode friction layer, and 103 is a negative electrode friction layer; Figure 3 This is a diagram of vehicle information perception results in an embodiment of the present invention; Figure 4 A schematic diagram of the layout of an intelligent road sensing network in an embodiment of the present invention; Figure 5 This is a diagram of the perception result of road section vehicle motion information based on the intelligent road perception network in an embodiment of the present invention; Figure 6 A diagram showing a scene of an intelligent road perception network applied to a tunnel in an embodiment of the present invention; Figure 7 A search space diagram in a tunnel according to an embodiment of the present invention; Figure 8 It is the coverage rate of the intelligent road perception network in the tunnel in the embodiment of the present invention. DETAILED DESCRIPTION

[0025] 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 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 should fall within the scope of protection of the present invention.

[0026] An intelligent road network medium for vehicle-road cooperative triboelectric self-driving perception, the structure of which is as follows Figure 1 As shown, it includes: an embedded high-elastic triboelectric self-driven sensing unit 1, a grid-type middle partition layer 2, an upper steel pad 301, a lower steel pad 302, steel pillars and springs 303, a shock-absorbing foam 4, a high-strength flexible nano-modified filling layer 5 and a high-strength and high-toughness waterproof packaging layer 6.

[0027] The lower steel pad 302 is installed above the high-strength and high-toughness waterproof packaging layer 6; A number of steel pillars are fixed to the lower steel pad 302 by internal bolts, and springs 303 are sleeved above the steel pillars to buffer the vehicle load; The grid-type middle partition 2 is a glass fiber reinforced plastic grid, which is fixed above the lower steel pad 302, and the center and four sides are aligned with the lower steel pad 302; The steel struts and springs 303 pass through the grid of the grid-type intermediate partition 2; The grid-type middle partition 2 is provided with a plurality of large holes, in which the embedded high-elastic triboelectric self-driven sensing units 1 are installed; Infusing the small holes of the grid-type middle partition layer 2 with a highly elastic and highly flexible nano-modified material to fill the original holes of the grid-type middle partition layer 2 to form a high-strength and flexible nano-modified gap-filling layer 5; The lower surface of the upper steel backing plate is provided with a shock absorbing foam 4, and is installed above the grid-type middle partition 2; The embedded highly elastic triboelectric self-driven sensing unit 1 is prepared based on the triboelectric and electrostatic induction effects, preferably using two flexible materials with significant electronegativity differences. Figure 2 As shown, it includes: an electrode layer 101, a positive friction layer 102 and a negative friction layer 103. The wiring of the positive friction layer and the negative friction layer is led out through a grid-type middle partition and connected to an external STM 32 microcontroller for data acquisition.

[0028] Preferably, the electronegativity of the positive electrode friction layer is 2.5-3.5, and the electronegativity of the negative electrode friction layer is 1.5-2.5.

[0029] Preferably, the material of the positive electrode friction layer is polytetrafluoroethylene with an electronegativity of 3.0, and the material of the negative electrode friction layer is aluminum foil with an electronegativity of 1.5.

[0030] Embodiment 1: In this embodiment, the embedded highly elastic triboelectric self-driven sensing unit uses elastic and scalable metamaterials as the spacing layer, and the surface is coated with carbon nanotube materials as the electrode layer. In the absence of external force, the elastic metamaterial isolates the positive and negative friction layers; under the action of force, the elastic metamaterial deforms under force to produce contact and separation movement.

[0031] Compared with traditional sensing devices, the embedded high-elastic triboelectric self-driven sensing unit uses polytetrafluoroethylene with an electronegativity of 3.0 as the negative friction layer material and aluminum foil with an electronegativity of 1.5 as the positive friction layer material. The material selection is wide and the preparation process is simple. There is no need for polarization treatment of functional materials and other processes, and the flexibility is high. Through multi-layer packaging protection, the durability of the sensing device and its ability to withstand large vehicle loads are improved, and the minimum load that can be tolerated is expanded to more than 2 tons.

[0032] In this implementation, the steel structure support layer, upper and lower steel pads, have a yield strength of 500 MPa. The 3D printed spring consumables are: thermoplastic resin: nano-SiO2 particles: 1000:1, and the elastic coefficient is 6815.8 N / mm.

[0033] In this embodiment, the high-flexibility nano-modified material has a flexural strength of 12.8 Mpa, a compressive strength of 35 Mpa, and a rebound rate of 50% after curing.

[0034] In this embodiment, the high-strength and high-toughness waterproof encapsulation layer is composed of high-performance silica gel and nano-SiO2, wherein the weight parts are: 1200 parts of sodium silicate solution and 1 part of sodium hydroxide particles. The tear strength after curing is 38 pli.

[0035] In this implementation, the intelligent road network medium uses open circuit voltage peak value and interval to characterize vehicle-road information.

[0036] The intelligent road network medium has a sensing range of vehicle speed of 10 to 120 km / h, vehicle weight of 2 to 20 tons and road friction coefficient of 0.35 to 0.8.

[0037] The usability test of the assembled intelligent road network medium is carried out, and the results are shown in Figure 2 , the vehicle passes by at a speed of 10km / h, and two obvious peaks can be observed at the relative time points of 4.890s and 5.786s, representing the time points when the front and rear wheels pass by. According to the distance between the front and rear wheels of the vehicle L=2.670m, the calculated vehicle speed is 10.95km / h, and the perception accuracy is as high as 90.5%. The feasibility of the invented intelligent road network medium for vehicle-road information perception is proved.

[0038] Embodiment 2: In this embodiment, the intelligent road network medium for vehicle-road cooperative triboelectric self-driving perception of the present invention is arranged at a longitudinal interval of 10m on the surface of a 3.5m wide road structure. Figure 4 . In order to more accurately reflect the actual working conditions, in this embodiment, a wooden frame mold with the same size as the intelligent road network medium is first manufactured, and the location of the packaging structure installation is measured and determined with a 100-meter tape measure. Next, the wooden frame mold is fixed on the surface of the gravel road surface, and an electric drill is used to drill the outline of the packaging structure position along the inner wall of the mold. Finally, the wooden frame mold is removed, and a 5 cm thick groove structure prototype is obtained by digging down along the outline with a shovel, and the assembled intelligent road sensing medium is further buried in the road surface structure.

[0039] This embodiment is mainly aimed at the needs of road maintenance departments, and determines traffic safety and efficiency through the changing trends of information such as the average speed of the road section, vehicle movement, and road surface roughness.

[0040] According to the embodiment, the intelligent road network medium is arranged as a cross section every 10 m, that is, the longitudinal distance D between two intelligent road network media and the time difference between the vehicle passing two adjacent sensing devices are used to calculate the average vehicle speed of the corresponding road section. The average vehicle speed and vehicle weight calculation process of multiple road sections is shown in Figure 5 .

[0041] Figure 5 The figure shows the output voltage information of three adjacent intelligent road network media A2, B2 and C2 in the actual field test when a car is driving on the anti-skid road surface at a speed of 5km / h. The relative time when the peak signal of each intelligent road network medium appears is extracted as T. A , T B and T C The time difference between the peak values ​​of adjacent sensing devices represents the time required for the vehicle to pass between the two corresponding sensing devices. A2-B2 =T B -T A It indicates the time required for the car to pass A2 and B2. Figure 4 The calculation results show that the average speed of cars passing through the A2-B2 section is 4.74 km / h, and the average speed passing through the B2-C2 section is 5.194 km / h. The above steps have completed the calculation and evaluation of the average speed of the road section. The calculation of the average anti-skid resistance of the road section, the number of vehicles, and other road surface and vehicle information can be completed by referring to the ideas in the above steps.

[0042] Embodiment three: According to the "Technical Standards for Highway Engineering" (JTGB01-2023), taking a two-lane one-way highway tunnel as an example, an intelligent road network medium for vehicle-road collaborative friction electric self-driving perception is deployed in the present invention to improve the light and dark effects of tunnel entrances and exits, traffic bottlenecks, slippery roads, and blind spots.

[0043] This embodiment takes into account the potential safety hazards at tunnel entrances and exits, such as visual adaptation, traffic congestion, weather and environmental impacts, and unreasonable road design. In addition, issues such as light differences inside and outside the tunnel, slippery roads, and air quality may also increase the driver's operating difficulty and accident risk.

[0044] like Figure 6 , when the width of a single lane is 3.75 m, the width of a double lane is 7.5 m. According to the normal distribution law of wheel tracks when the vehicle is driving, the initialized sensing devices are arranged in the center area of ​​the wheel track distribution in the middle of the lane. Considering that the 95% confidence interval of the normal distribution range of wheel tracks is between [0.4880, 1.5120] and [2.2380, 3.2620], a grid layout is performed in the range of 2 m horizontally (along the lane width) and 10 m vertically (along the driving direction), and the initial number of layouts is 8.

[0045] In this embodiment, a particle swarm optimization algorithm is used to evaluate the coverage accuracy of the sensing network, and its search space is as follows: Figure 6 .It can be found that the search space is distributed in a step-like manner.

[0046] In this embodiment, the intelligent road network medium can sense the range of 1.0m, and the network optimization is performed on the 1500m tunnel space. As shown in Table 1, with the increase of the number of iterations, the coverage rate increases from 82.07% to 90.67%, and the calculation time is only 8.28s. When iterates 10,000 times, the coverage rate of the intelligent road network in the tunnel is Figure 8 , which proves the advantages of the self-driving intelligent road network medium proposed in the present invention in vehicle-road collaborative perception.

[0047] Table 1 Intelligent road network medium coverage and time consumption The preferred specific embodiments of the present invention are described in detail above. It should be understood that a person skilled in the art can make many modifications and changes based on the concept of the present invention without creative work. Therefore, any technical solution that can be obtained by a person skilled in the art through logical analysis, reasoning or limited experiments based on the concept of the present invention on the basis of the prior art should be within the scope of protection determined by the claims.

Claims

1. An intelligent road network medium for vehicle-road cooperative triboelectric self-driving perception, characterized in that: include: An embedded high-elastic triboelectric self-driven sensing unit (1), a grid-type intermediate partition (2), an upper steel pad (301), a lower steel pad (302), steel pillars and springs (303), shock-absorbing foam (4), a high-strength flexible nano-modified caulking layer (5), and a high-strength and high-toughness waterproof packaging layer (6); The lower steel pad (302) is installed above the high-strength and high-toughness waterproof packaging layer (6); A plurality of steel pillars are fixed on the lower steel pad (302) by means of internal bolts, and springs (303) are sleeved on the steel pillars to buffer the vehicle load; The grid-type middle partition (2) is a glass fiber reinforced plastic grid, fixed on the top of the lower steel pad (302), with the center and four sides aligned with the lower steel pad (302); Steel struts and springs (303) pass through the grid of the grid-type intermediate partition (2); The grid-type middle partition (2) is provided with a plurality of large holes, and an embedded high-elastic triboelectric self-driven sensing unit (1) is installed in the large holes; Infusing the small holes of the grid-type intermediate spacer (2) with a highly elastic and highly flexible nano-modified material to fill the original holes of the grid-type intermediate spacer (2) to form a highly strong and flexible nano-modified gap filling layer (5); A shock-absorbing foam (4) is arranged on the lower surface of the upper steel pad (301), and the upper steel pad (301) is installed above the grid-type middle partition (2).

2. The intelligent road network medium for vehicle-road cooperative triboelectric self-driving perception according to claim 1 is characterized in that: The embedded high-elastic triboelectric self-driven sensing unit (1) is prepared by selecting two flexible materials with significant electronegativity differences based on triboelectric charging and electrostatic induction effects, and comprises: an electrode layer (101), a positive electrode friction layer (102) and a negative electrode friction layer (103); the wiring of the positive electrode friction layer and the negative electrode friction layer is led out through a grid-type intermediate spacer and connected to an external STM 32 single-chip computer for data collection.

3. The intelligent road network medium for vehicle-road cooperative triboelectric self-driving perception according to claim 2 is characterized in that: The electronegativity of the negative electrode friction layer is 2.5 - 3.5, and the electronegativity of the positive electrode friction layer is 1.5-2.

5.

4. The intelligent road network medium for vehicle-road cooperative triboelectric self-driving perception according to claim 3 is characterized in that: The material of the negative electrode friction layer is polytetrafluoroethylene with an electronegativity of 3.0, and the material of the positive electrode friction layer is aluminum foil with an electronegativity of 1.

5.

5. The intelligent road network medium for vehicle-road cooperative triboelectric self-driving perception according to claim 1 is characterized in that: The height of the grid-type middle partition is 15-30 mm, the inner side length of the small hole is 25-35 mm, and the compressive strength is 30-50 MPa.

6. The intelligent road network medium for vehicle-road cooperative triboelectric self-driving perception according to claim 1 is characterized in that: The steel structure support layer, the upper and lower steel pads have a yield strength of 200-800 MPa; the spring is based on a thermoplastic resin and is obtained by additive manufacturing by adding 0.05%-0.1% of nanoparticles as a 3D printing composite consumable; the elastic coefficient is 4500-8000 N / mm.

7. The intelligent road network medium for vehicle-road cooperative triboelectric self-driving perception according to claim 1 is characterized in that: The highly flexible nano-modified material has a flexural strength of 10-15 Mpa, a compressive strength of 35-60 Mpa, and a rebound rate of 50-70% after curing.

8. The intelligent road network medium for vehicle-road cooperative triboelectric self-driving perception according to claim 1 is characterized in that: The high-strength and high-toughness waterproof packaging layer is composed of high-performance silica gel and nano-SiO2, wherein the weight parts are: 1000-1500 parts of sodium silicate solution and 1-3 parts of sodium hydroxide particles; The high-strength and high-toughness waterproof packaging layer has a curing time of 15-40 minutes at room temperature and a tear strength of 30-80 pli.

9. The intelligent road network medium for vehicle-road cooperative triboelectric self-driving perception according to claim 1 is characterized in that: The intelligent road network medium is buried at a depth of 0-10 cm in the road structure, and at a longitudinal spacing of 10-60 m.

10. The intelligent road network medium for vehicle-road cooperative triboelectric self-driving perception according to claim 1, characterized in that: The installation steps are: (1) The rigid support is fixed on the lower steel plate by internal bolts; (2) Cut large holes in the FRP grille according to the designed size; (3) The FRP grille is fixed on the top of the lower steel plate, and the center and four sides should be aligned with the corresponding positions of the lower steel plate; (4) Fix the triboelectric self-driven sensing unit after flexible packaging in the large hole cut in the FRP grille, and lead out the signal transmission line; (5) Put a spring on top of the rigid support to cushion the vehicle load; (6) Fix elastic foam on the inner surface of the upper steel pad to protect the triboelectric self-driving sensing unit; (7) Infusing highly elastic and highly flexible nano-modified materials into the small holes of the FRP grille to fill the original holes of the FRP grille; (8) After the pouring material solidifies, cover it with the upper steel plate and make a waterproof packaging layer on top of the upper steel plate.

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