A highway safety marking self-adaptive construction system

Abstract

A highway safety marking self-adaptive construction system is composed of a transverse and longitudinal laser radar, an embedded control box, a multi-mode marking spraying mechanism, etc. The transverse laser radar scans the road boundary at 20 Hz, and uses Kalman filtering algorithm to predict the turning radius; the longitudinal laser radar combines TOF ranging and IMU data to identify longitudinal slope. The embedded control box eliminates radar interference through swing arc tracking algorithm, dynamically adjusts the temperature and extrusion amount of paint. The multi-mode spraying mechanism can automatically switch between solid / dashed line modes, and quickly enable dual-component marking spray heads in tunnel scenarios. The system integrates a self-propelled sweeping module and a gradient temperature control device, realizes intelligent control of road surface cleaning and paint temperature, and corrects the construction trajectory through GNSS and BIM data interface, effectively solving the problems of curve marking positioning error, tunnel marking performance deficiency and winter construction, and significantly improving the intelligentization and all-weather adaptability of marking construction.

Description

Technical Field

[0001] This utility model belongs to the technical field of intelligent transportation facility construction equipment, and specifically relates to an adaptive construction system for highway traffic safety markings. Background Technology

[0002] Current highway marking construction primarily utilizes semi-automatic hot-melt marking vehicles, relying on drivers' visual judgment of road alignment changes. This presents three major technical drawbacks: 1) Large positioning errors at the start and end points of solid lines on curves, easily leading to mis-marking of solid lines in permitted overtaking areas; 2) The use of ordinary hot-melt markings in tunnels fails to meet the JTGD81 standard in terms of wear resistance and reflectivity; 3) Rapid curing of the paint during winter construction causes cracking of the markings. While patent CN201810235.X proposes a marking control system based on machine vision, the camera suffers from high failure rates in rain, fog, and backlight conditions. Patent CN202010568.Z uses a single laser rangefinder to adjust line width, failing to address the issue of adaptive three-dimensional road alignment. Therefore, there is an urgent need to develop marking equipment with multi-dimensional environmental perception, intelligent material adaptation, and all-weather construction capabilities. Summary of the Invention

[0003] The technical problem to be solved by this utility model is to provide an adaptive construction system for highway traffic safety markings. This system uses a lateral laser radar to predict the turning radius and a longitudinal laser radar to identify the longitudinal slope. Combined with an embedded control box, it dynamically adjusts the paint temperature and extrusion amount to solve the problem of large positioning errors in curve markings.

[0004] To solve the above-mentioned technical problems, the technical solution adopted by this utility model is as follows:

[0005] An adaptive construction system for highway traffic safety markings includes a transverse lidar, a longitudinal lidar, an embedded control box, a multi-mode marking spraying mechanism, a self-propelled sweeping robot module, and a gradient temperature control preheating device.

[0006] The horizontal and vertical lidars are electrically connected to the embedded control box, which is electrically connected to the multi-mode road marking spraying mechanism. The self-propelled sweeping robot module and the gradient temperature control preheating device are electrically connected to the multi-mode road marking spraying mechanism, which is electrically connected to the system centralized control platform. The system centralized control platform is electrically connected to the horizontal lidar, the vertical lidar, the self-propelled sweeping robot module, and the gradient temperature control preheating device.

[0007] Preferably, the lateral lidar scans the roadside boundaries at a frequency of 20Hz, calculates the lateral offset using a Kalman filter algorithm, and predicts the turning radius.

[0008] Preferably, the longitudinal lidar uses the TOF ranging principle to generate an elevation profile map, and combines it with IMU inertial unit data to identify the longitudinal slope.

[0009] Preferably, the embedded control box has a built-in DSP signal processor, which uses an oscillating arc tracking algorithm to eliminate multipath interference in the radar signal and generate a dynamic compensation coefficient to adjust the coating melting temperature (±5℃) and extrusion rate (0.2-1.5L / min).

[0010] Preferably, the multi-mode road marking spraying mechanism includes a solid / dashed line switching valve group, a two-component road marking nozzle, and a reflective glass bead applicator. When the lateral laser radar detects a turning radius of <500m, the control box triggers the solenoid valve to lock the solid line mode and simultaneously increases the glass bead application density to 450g / m².

[0011] Preferably, the self-propelled sweeping robot module integrates a nylon brush, a scraper dust collector, and a 5kW vacuum fan. The cleaning width is adjustable from 0.8 to 1.5m, and the operating speed matches the speed of the construction vehicle (3-8km / h). The gradient temperature control preheating device adopts a zoned electric heating tube design, which can adjust the paint chamber temperature in three stages (<5℃, 5-15℃, >15℃) according to the data from the external temperature sensor.

[0012] Preferably, the embedded control box is equipped with a tunnel recognition algorithm. When the longitudinal laser radar detects that the distance between the two side boundaries has decreased by more than 40% within 3 seconds, it automatically starts the two-component marking nozzle and injects polyurethane primer, while switching the construction parameters to the tunnel-specific mode (line width 20cm, thickness 2.5mm).

[0013] Preferably, this system is equipped with a GNSS positioning module and a BIM road design data interface, which can realize real-time deviation correction between the construction trajectory and the design drawings (accuracy ±2cm).

[0014] The present invention can achieve the following beneficial effects:

[0015] 1. By using a horizontal lidar to predict the turning radius and a vertical lidar to identify the longitudinal slope, combined with an embedded control box to dynamically adjust the paint temperature and extrusion rate, the problem of large positioning errors in curve markings can be solved.

[0016] 2. Integrates GNSS positioning and BIM data interface to achieve real-time calibration of construction trajectory and design drawings; the multi-mode spraying mechanism automatically switches between solid line and dashed line, and locks the solid line mode when the turning radius is <500m and increases the glass bead spreading density to 450g / m², improving safety and construction efficiency. Attached Figure Description

[0017] The present invention will be further described below with reference to the accompanying drawings and embodiments:

[0018] Figure 1 This is a system structure diagram of the present invention;

[0019] Figure 2 This is a structural diagram of the construction equipment of this utility model;

[0020] Figure 3 This is a flowchart of the signal processing of this utility model;

[0021] Figure 4 This is a diagram illustrating the effect of the front-mounted lidar of this utility model through horizontal scanning.

[0022] In the diagram: 1. Horizontal LiDAR; 2. Vertical LiDAR; 3. Embedded control box; 4. Multi-mode marking spraying mechanism; 5. Self-propelled sweeping robot module; 6. Gradient temperature control preheating device. Detailed Implementation

[0023] Preferred solutions include Figures 1 to 4 As shown, an adaptive construction system for highway traffic safety markings includes a transverse lidar 1, a longitudinal lidar 2, an embedded control box 3, a multi-mode marking spraying mechanism 4, a self-propelled sweeping robot module 5, and a gradient temperature control preheating device 6.

[0024] The horizontal lidar 1 and the vertical lidar 2 are electrically connected to the embedded control box 3, and the embedded control box 3 is electrically connected to the multi-mode road marking spraying mechanism 4; the self-propelled sweeping robot module 5 and the gradient temperature control preheating device 6 are electrically connected to the multi-mode road marking spraying mechanism 4, and the multi-mode road marking spraying mechanism 4 is electrically connected to the system centralized control platform; the system centralized control platform is electrically connected to the horizontal lidar 1, the vertical lidar 2, the self-propelled sweeping robot module 5, and the gradient temperature control preheating device 6.

[0025] The lateral LiDAR 1 scans the curb / guardrail positions with an angular resolution of 0.05°, and fits the road curvature by integrating the scanned areas on both sides with the centerline as the boundary. The longitudinal LiDAR 2, combined with an tilt sensor, constructs a 3D road model to predict the impact of longitudinal slope changes on paint flowability. The embedded control box 3 applies an oscillating arc tracking algorithm: converting radar signals into voltage waveforms, and dynamically matching the optimal filtering frequency band through an arc length controller (ALC) to eliminate signal jitter caused by vehicle vibration (>90% noise suppression rate). The actuator 4 adopts a modular design, including a quick switching device for hot-melt / two-component markings, completing polyurethane primer spraying within 0.5 seconds in tunnel scenarios. The self-propelled sweeping robot module 5 monitors the road surface cleanliness in real time through a pressure sensor, and automatically starts secondary cleaning when oil adhesion is detected to be >0.3MPa. The lateral LiDAR integrates the scanned areas on both sides with the centerline as the boundary, and imports the data in real time into the embedded control box. The Kalman filter algorithm is used to calculate the lateral offset and predict the turning radius, achieving automated and intelligent construction effects.

[0026] Preferably, the lateral lidar 1 scans the roadside boundaries at a frequency of 20Hz, calculates the lateral offset using a Kalman filter algorithm, and predicts the turning radius. The lateral lidar 1 is an RLD-903 type radar with a scanning angle of 120°.

[0027] Preferably, the longitudinal lidar 2 uses the TOF ranging principle to generate an elevation profile map, and combines it with IMU inertial unit data to identify the longitudinal slope. The longitudinal lidar is a VS-1500 type three-dimensional radar with a scanning frequency of 50Hz.

[0028] Preferably, the embedded control box 3 has a built-in DSP signal processor, which uses a swing arc tracking algorithm to eliminate multipath interference in the radar signal and generates a dynamic compensation coefficient to adjust the coating melting temperature (±5℃) and extrusion rate (0.2-1.5L / min). The embedded control box has a built-in STM32H743 main control chip.

[0029] Preferably, the multi-mode road marking spraying mechanism 4 includes a solid / dashed line switching valve group, a two-component road marking nozzle, and a reflective glass bead applicator. When the lateral laser radar 1 detects a turning radius < 500m, the control box 3 triggers the solenoid valve to lock the solid line mode and simultaneously increases the glass bead application density to 450g / m². The solid line mode is activated when the lateral curvature > 0.02m⁻¹ and the vehicle speed > 5km / h.

[0030] Preferably, the self-propelled sweeping robot module 5 integrates a nylon brush, a scraper dust collector, and a 5kW vacuum fan. The cleaning width is adjustable from 0.8 to 1.5m, and the operating speed matches the construction vehicle's travel speed (3-8km / h). The gradient temperature control preheating device 6 adopts a zoned electric heating tube design, which can adjust the paint chamber temperature in three segments (<5℃, 5-15℃, >15℃) according to external temperature sensor data.

[0031] Preferably, the embedded control box 3 is equipped with a tunnel recognition algorithm. When the longitudinal lidar 2 detects that the distance between the two side boundaries has decreased by more than 40% within 3 seconds, it automatically starts the two-component marking nozzle and injects polyurethane primer, while simultaneously switching the construction parameters to tunnel-specific mode (line width 20cm, thickness 2.5mm). The tunnel recognition condition is that five consecutive frames of point cloud data detect a boundary distance shortening rate greater than 1.5m / s.

[0032] Preferably, this system is equipped with a GNSS positioning module and a BIM road design data interface, which can realize real-time deviation correction between the construction trajectory and the design drawings (accuracy ±2cm).

[0033] Working principle:

[0034] Before construction, the BIM road design data is embedded in control box 3, and baseline alignment parameters are set. The transverse lidar 1 outputs the left and right boundary distances at 40ms intervals. When it detects a continuous decrease in the left distance and an increase in the right distance, it determines a right turn. The embedded control box 3 calculates the paint flow compensation amount according to the formula ΔQ=K1·(R-R0)+K2·dV / dt (where R is the real-time turning radius, R0 is the design radius, K1=0.15L·m⁻¹, K2=0.08L·s·m⁻¹). The longitudinal lidar 2 generates an elevation profile every 0.5 meters. When it detects a slope change rate >3% / s, it adjusts the heater power 0.8 seconds in advance to prevent paint dripping. Upon entering the tunnel, when the lidar detects a sudden decrease in boundary distance from 3.5m to 2.8m, the embedded control box 3 completes three operations within 0.3 seconds:

[0035] 1) Close the solenoid valve for hot melt coating;

[0036] 2) Start the two-component road marking mixing pump;

[0037] 3) Increase the nozzle pressure to 0.6 MPa to ensure the permeability of the polyurethane material.

[0038] When the self-propelled sweeping robot module 5 is working, it monitors the brush resistance through a six-axis force sensor. When it detects residue at the joints of the asphalt road surface, it automatically increases the sweeping power to the rated value of 120%.

[0039] During winter construction, the gradient temperature control preheating device has three-level temperature control: below -10℃, the 12kW heating tube is activated; from -10℃ to 0℃, the 8kW heating tube is activated; and above 0℃, it only maintains the heat preservation mode to ensure that the viscosity of the coating remains stable within the range of 180±20cP.

[0040] The above embodiments are merely preferred technical solutions of this utility model and should not be considered as limitations on this utility model. The protection scope of this utility model should be the technical solution described in the claims, including equivalent substitutions of the technical features described in the claims. That is, equivalent substitutions and improvements within this scope are also within the protection scope of this utility model.

Claims

1. An adaptive construction system for highway traffic safety markings, characterized in that: It includes a horizontal lidar (1), a vertical lidar (2), an embedded control box (3), a multi-mode marking spraying mechanism (4), a self-propelled sweeping robot module (5), and a gradient temperature control preheating device (6). The horizontal laser radar (1) and the vertical laser radar (2) are electrically connected to the embedded control box (3), and the embedded control box (3) is electrically connected to the multi-mode marking spraying mechanism (4); the self-propelled sweeping robot module (5) and the gradient temperature control preheating device (6) are electrically connected to the multi-mode marking spraying mechanism (4), and the multi-mode marking spraying mechanism (4) is electrically connected to the system centralized control platform; the system centralized control platform is electrically connected to the horizontal laser radar (1), the vertical laser radar (2), the self-propelled sweeping robot module (5), and the gradient temperature control preheating device (6).

2. The adaptive construction system for highway traffic safety markings according to claim 1, characterized in that: The lateral lidar (1) scans the roadside boundaries at a frequency of 20Hz, calculates the lateral offset and predicts the turning radius using the Kalman filter algorithm.

3. The adaptive construction system for highway traffic safety markings according to claim 1, characterized in that: The longitudinal lidar (2) uses the TOF ranging principle to generate an elevation profile map and combines IMU inertial unit data to identify the longitudinal slope.

4. The adaptive construction system for highway traffic safety markings according to claim 1, characterized in that: The embedded control box (3) has a built-in DSP signal processor, which uses the swing arc tracking algorithm to eliminate multipath interference in the radar signal and generate a dynamic compensation coefficient to adjust the melting temperature and extrusion amount of the coating.

5. The adaptive construction system for highway traffic safety markings according to claim 1, characterized in that: The multi-mode marking spraying mechanism (4) includes a solid line / dashed line switching valve group, a two-component marking special nozzle and a reflective glass bead spreader. When the lateral laser radar (1) detects a turning radius of <500m, the embedded control box (3) triggers the solenoid valve to lock the solid line mode and simultaneously increases the glass bead spreading density to 450g / m².

6. The adaptive construction system for highway traffic safety markings according to claim 1, characterized in that: The self-propelled sweeping robot module (5) integrates a nylon brush, a scraper dust collector and a 5kW vacuum fan. The cleaning width is adjustable from 0.8 to 1.5m, and the operating speed matches the speed of the construction vehicle. The gradient temperature control preheating device (6) adopts a zoned electric heating tube design and adjusts the temperature of the paint chamber in three sections according to the data from the external temperature sensor.

7. The adaptive construction system for highway traffic safety markings according to claim 1, characterized in that: The embedded control box (3) is equipped with a tunnel recognition algorithm. When the longitudinal laser radar (2) detects that the distance between the two side boundaries is reduced by more than 40% within 3 seconds, it automatically starts the two-component marking nozzle and injects polyurethane primer, while switching the construction parameters to tunnel-specific mode.

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