Projection type road marking method and system based on dynamic traffic environment perception

Abstract

The application relates to the field of intelligent transportation and automobile electronic technology, in particular to a projection type road marking method and system based on dynamic traffic environment perception, which comprises the following steps: collecting and fusing real-time traffic flow, weather conditions and event data to form an environment state data set; calculating a traffic state index to evaluate the current road traffic state; triggering preset road marking rules based on the traffic state index to generate a marking scheme; constructing a dynamic space mapping mechanism based on a two-dimensional coordinate system to map marking elements into coordinate data; performing geometric distortion correction and smooth transition processing on the coordinate data to obtain final marking graphic data; dynamically calculating the brightness parameters of the finally projected road marking graphics in combination with real-time environment states to complete dynamic marking projection. The application constructs a "perception-decision-projection" integrated network, cooperatively judges based on the whole road traffic situation, and realizes evolution from "isolated projection" to "whole-network cooperative intelligence".

Description

Technical Field

[0001] This invention belongs to the field of intelligent transportation and automotive electronics technology, specifically relating to a projection-based road marking method and system based on dynamic traffic environment perception. Background Technology

[0002] Road markings play a crucial role as key infrastructure for guiding traffic flow and ensuring driving safety. For a long time, traditional road markings have relied primarily on static application of materials such as paint and hot-melt coatings to create fixed road markings. However, with the rapid development of intelligent transportation and autonomous driving technologies, the limitations of traditional fixed road markings in terms of adaptability, visibility, and maintainability have become increasingly prominent, making it difficult to meet the complex and ever-changing demands of modern traffic. Specifically, existing technologies have the following significant shortcomings:

[0003] (1) Lack of dynamic response capability. Traditional road markings use a fixed coating method, which results in a solidified and static form that cannot be dynamically adjusted according to real-time conditions such as traffic flow, weather and events, and lacks self-adaptive and dynamic response capabilities.

[0004] (2) Insufficient visibility and durability. Traditional road markings have poor visibility in complex optical environments such as backlight, nighttime, or waterlogged roads, and are prone to wear and aging, resulting in poor durability and long-term stability.

[0005] (3) Limited functionality and lack of interaction. Traditional road markings can only provide fixed, non-interactive visual instructions and cannot communicate with traffic participants such as connected vehicles and pedestrians in real time.

[0006] In summary, there is a need in this field for a new type of road marking technology that can systematically overcome the shortcomings of traditional road markings and possess dynamic perception, intelligent decision-making, high-brightness projection, and multi-terminal interaction capabilities, so as to improve road traffic safety, traffic efficiency, and intelligence level. Summary of the Invention

[0007] This invention overcomes the above-mentioned defects and provides a projection-based road marking system and method based on dynamic traffic environment perception, which solves the problems of existing road markings lacking dynamic response capability, insufficient visibility and durability, and limited functionality and interaction.

[0008] To achieve the above objectives, the present invention provides a projection-based road marking method based on dynamic traffic environment perception, comprising the following steps:

[0009] S1. Collect and integrate real-time traffic flow, meteorological conditions and event data to form an initial environmental state dataset;

[0010] S2. Using the dataset described in S1, input it into the traffic state assessment model to calculate the traffic state index and comprehensively assess the real-time traffic status of the current road.

[0011] S3. Based on the traffic state index, trigger the corresponding logical conditions of the preset road marking generation rule base, and generate a marking scheme in combination with the traffic template library;

[0012] S4. Construct a dynamic spatial mapping mechanism based on a two-dimensional coordinate system to map the marking elements in the marking scheme to the coordinates of the markings on the projector image plane;

[0013] S5. Perform geometric distortion correction on the coordinates obtained in S4 to obtain accurate datum line graphic data;

[0014] S6. Apply a smooth transition process to the paving pattern after correction in S5 to obtain the final paving pattern data;

[0015] S7. Based on real-time environmental status data, dynamically calculate and determine the brightness parameters of the final projected marking graphic to complete the dynamic marking projection.

[0016] Furthermore, the formula for calculating the traffic state index is as follows:

[0017] ,

[0018] Where Q represents the current actual traffic flow, This represents the maximum designed traffic capacity of the road, where V is the current average vehicle speed. α represents the free flow velocity, β represents the weather factor, γ represents the incident level, and δ represents the weight coefficients of each factor.

[0019] Furthermore, step S4 is implemented as follows:

[0020] S41 extracts key geometric parameters from the logical marking scheme, including the marking type and target area. The target global coordinate area is: , ;

[0021] S42 extracts the coverage parameters of all projection modules, where the coverage of the i-th module is... , ;

[0022] S43 If the coverage area of ​​the projection module includes the target area, then it is determined that the module is responsible for projecting the mark;

[0023] After S44 determines the projection module, it converts the global coordinates of the marking line into the local coordinates of each projection module.

[0024] S45 is based on the distance D between adjacent light poles and the length of the fixed overlapping area. The local coordinates of each module are sequentially associated and integrated into a unified global coordinate system to form a collaborative projection network covering the entire road segment.

[0025] Furthermore, the transformation method between global coordinates and local coordinates of each projection module is as follows:

[0026] a) Calculate projection coverage parameters:

[0027] The total length of the coverage area of ​​a single projection module is ,

[0028] Coverage radius ,

[0029] Where D is the distance between adjacent street light poles. The desired fixed overlap region length;

[0030] b) Based on the projection coverage parameters, establish a two-dimensional local coordinate system for each projection module:

[0031] The origin is the projection point of the i-th projection module on the road plane. The X-axis is parallel to the lane lines, with the positive direction being the vehicle's forward direction, and the coverage area is... Meters; the Y-axis is perpendicular to the lane lines and points positively toward the center of the road or the opposite lane, with the range determined according to the road width;

[0032] c) Establish a two-dimensional global road coordinate system, with its origin at the origin of the first projection module. The X and Y axes are aligned with the local coordinate system. Then, the coordinates of the origin of the local coordinate system of the i-th projection module in the global coordinate system are: ;

[0033] d) Local coordinate to global coordinate transformation:

[0034] ,

[0035] in, For local coordinates, These are global coordinates.

[0036] Furthermore, in step S5, the geometric distortion correction employs a factual digital pre-distortion correction technique based on the homography matrix, as detailed below:

[0037] The mapping relationship between the image plane and the road plane established by the precise calibration of the projector is as follows:

[0038] ,

[0039] in, These are the coordinates of the target point on the road surface, representing the position of the ideal road marking. is the coordinate of the corresponding point on the projector image plane, s is a non-zero scale factor used for normalization of homogeneous coordinates, and H is a 3×3 homography matrix.

[0040] For each point on the grading graph Calculate its predistortion coordinates on the projector image plane. The formula is:

[0041] ,

[0042] in, The homography matrix H is the inverse matrix; normalizing the above equation yields... The normalization formula is:

[0043] ,

[0044] in, .

[0045] Furthermore, in step S6, the smooth transition algorithm is as follows:

[0046] Within a preset transition time window T, the visual attributes and geometric vertices of the markings are calculated in real time based on an easing function. For any attribute A that needs to be transitioned, its current value is... The formula for calculating time t is:

[0047] ,

[0048] in, This is the initial value for the attribute. The attribute target value, t is the time elapsed since the start of the transition, 0≤t≤T, and the easing function is adopted. A cubic easing function.

[0049] Furthermore, in step S7, the projection brightness parameters are calculated as follows:

[0050] ,

[0051] in, For the final calculated projection brightness, Based on brightness, For ambient light intensity, This is the illumination compensation coefficient. This is the road surface reflection compensation value. This is the road surface reflection compensation coefficient.

[0052] Furthermore, the road marking generation rule base is defined in the form of logical conditions: the corresponding marking scheme that should be triggered under a specific combination of traffic conditions, event levels, and weather conditions.

[0053] Furthermore, a clear priority arbitration logic is set to ensure the safety and effectiveness of the lane marking scheme. The priority arbitration logic is: event level > weather conditions > traffic congestion.

[0054] The present invention also includes a system for implementing the above-mentioned projection-based road marking method based on dynamic traffic environment perception, comprising a roadside control subsystem and an in-vehicle interaction subsystem;

[0055] The roadside control subsystem includes:

[0056] The central processing module has a built-in road marking decision engine and coordinate system management unit. By integrating real-time traffic conditions, weather conditions and emergency information, it intelligently generates the optimal road marking scheme in real time based on preset traffic rules and optimization algorithms. It constructs and manages two-dimensional local coordinate system and global coordinate system, realizes the accurate mapping from logical road marking scheme to physical projection coordinates, and outputs precise control commands to drive the projection module.

[0057] The high-brightness projection module transforms the decision instructions from the central processing module into high-definition, high-precision road visual markings, and inputs the installation position and angle parameters of the projection module into the roadside control subsystem as the basic parameters for coordinate system construction and geometric correction.

[0058] The communication module exchanges data with the in-vehicle interaction subsystem in real time, accurately issues dynamic lane marking commands, and builds a low-latency, highly reliable collaborative communication network.

[0059] The storage module is used to store system programs, historical traffic data, lane marking scheme library, event logs and vehicle interaction data, providing continuous data support for decision analysis.

[0060] The power module provides a stable and uninterrupted power supply for all roadside equipment and integrates comprehensive lightning protection and overload protection functions to ensure the continuous and reliable operation of the system in various harsh environments.

[0061] The in-vehicle interaction subsystem includes:

[0062] Central processing module: parses and integrates real-time lane marking instructions from the communication module and high-precision vehicle position information from the positioning module, generates matching AR visual elements and voice scripts, and drives the display module and voice prompt module to output synchronously;

[0063] Communication module: Receives dynamic road marking graphics and personalized guidance instructions issued by the roadside in real time, and establishes a low-latency, highly reliable two-way data link with the roadside control subsystem;

[0064] Positioning module: Acquires vehicle location information in real time to ensure that the vehicle's own position and the dynamic lane marking information issued by the roadside system are accurately matched in space, providing reliable information for vehicle guidance;

[0065] Display module: Deeply integrated with the vehicle screen, it clearly renders the road markings of the current road segment and intuitively prompts the driver with recommended lanes;

[0066] Voice prompt module: Provides real-time, natural voice guidance to the driver based on the received lane marking instructions.

[0067] Compared with the prior art, the advantages of the present invention are as follows:

[0068] (1) This invention constructs a dynamic perception network covering the entire road segment that includes traffic flow, weather conditions and emergencies, and designs a marking decision engine based on multi-factor weighted evaluation. This enables real-time monitoring of road conditions and instant generation and switching of marking schemes, allowing markings to be dynamically reconstructed according to actual traffic needs, thus overcoming the shortcomings of traditional markings being fixed and unchanging.

[0069] (2) This invention introduces high-brightness adaptive projection technology. By dynamically calculating and adjusting the projection brightness based on ambient light and road conditions, and by using anti-distortion calibration and smooth transition algorithms, it ensures that the projected markings remain clear, conspicuous and accurate under any lighting and weather conditions. At the same time, it achieves "zero physical wear" and avoids maintenance costs and traffic safety hazards caused by the wear of the markings.

[0070] (3) This invention adopts a vehicle-road cooperative two-way interactive mechanism, which sends the road marking information and voice prompts to the vehicle interactive subsystem through V2X communication, and provides personalized guidance to the driver using the vehicle screen and voice module. This not only upgrades the road marking from a single visual indication to a multi-dimensional interactive guidance, but also realizes deep collaboration between the roadside control subsystem and the connected vehicle, providing key environmental perception input for high-level autonomous driving.

[0071] This invention adopts a distributed roadside deployment and center-edge collaborative architecture. The system is supported by existing facilities along the road and builds a continuously covered integrated network of "perception-decision-projection". It can make collaborative judgments based on the traffic situation of the entire road section and dynamically reorganize the lane markings in response to emergencies such as traffic accidents, thereby realizing the evolution from "isolated projection" to "network-wide collaborative intelligence". Attached Figure Description

[0072] Figure 1 This is a flowchart of the projection-based road marking method for dynamic traffic perception according to the present invention;

[0073] Figure 2 This is a schematic diagram showing the deployment orientation and projection of the high-brightness projection module of the present invention;

[0074] Figure 3 This is a schematic diagram illustrating the relationship between the two-dimensional global coordinate system and the local coordinate system in an embodiment of the present invention;

[0075] Figure 4 This is a schematic diagram of global projection in an embodiment of the present invention;

[0076] Figure 5 This is a scenario diagram illustrating the normal passage state according to an embodiment of the present invention;

[0077] Figure 6 This is a diagram showing the normal passage prompt for vehicles according to an embodiment of the present invention;

[0078] Figure 7 This is a traffic congestion scenario diagram according to an embodiment of the present invention;

[0079] Figure 8 This is a vehicle-side prompt diagram for a tidal lane according to an embodiment of the present invention;

[0080] Figure 9 This is a scenario diagram of severe weather conditions according to an embodiment of the present invention;

[0081] Figure 10 This is a vehicle-side weather warning diagram according to an embodiment of the present invention;

[0082] Figure 11 This is a scenario diagram of an emergency situation according to an embodiment of the present invention;

[0083] Figure 12 This is a vehicle-side notification diagram for an emergency event, as shown in an embodiment of the present invention.

[0084] Figure 13 These are scenario diagrams illustrating various conditions (accidents and rainy days) in embodiments of the present invention;

[0085] Figure 14 These are vehicle-side prompts under various conditions (accidents and rainy weather) according to embodiments of the present invention. Detailed Implementation

[0086] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0087] The projection-based road marking method based on dynamic traffic environment perception described in this application specifically includes the following steps, the flowchart of which is shown below. Figure 1 As shown.

[0088] I. Data Acquisition: Collect and integrate real-time traffic flow, meteorological conditions, and time data to form an initial environmental state dataset.

[0089] When any sensing unit—including traffic flow detection unit, weather and road condition detection unit, or event detection unit—identifies a preset abnormal condition (such as traffic flow exceeding a set threshold, meteorological parameters reaching a severe weather level, or a confirmed emergency), the unit will immediately generate a trigger signal and upload it to the central processing module in real time.

[0090] After receiving the signal, the central processing module drives the entire system out of standby mode and activates the built-in road marking decision engine, entering full working state. It collects and integrates real-time traffic flow, weather conditions and event data to form a unified and complete initial environmental state dataset. This dataset is uploaded to the central processing module in real time, and then serves as the input for the next stage of "comprehensive traffic condition assessment", providing a data foundation for subsequent traffic condition index calculation and dynamic road marking decision.

[0091] Second, based on the environmental condition dataset, a comprehensive traffic condition assessment model is used to calculate the traffic condition index in order to assess the real-time traffic status of the current road.

[0092] The formula for calculating the Traffic State Index is as follows:

[0093] ,

[0094] in, This indicates the current actual traffic flow. This indicates the maximum designed traffic capacity of the road. The current average vehicle speed, Here, represents the free-flow velocity, Weather Factor is the meteorological impact factor, Incident Level is the event severity level, and α, β, γ, and δ represent the weighting coefficients of each factor. Furthermore, Real-time traffic flow (vehicles / hour) at the cross-section detected by radar cameras. To preset static parameters, they are pre-entered into the system storage module based on road design standards (such as the number of lanes, design speed, and road grade). The ratio reflects the road's load level; a value close to 1 indicates saturation. The average speed (km / h) of all currently detected vehicles is measured by a combination of radar and camera. The preset static parameters refer to the ideal vehicle speed under unobstructed road conditions, which are preset according to road type and design standards.

[0095] Furthermore, the weight coefficients of each influencing factor in the comprehensive traffic condition assessment model have been carefully configured, with a total of 1.0. The model assigns the highest weight to average vehicle speed (β=0.4) because it is the most direct and sensitive indicator reflecting traffic flow. Traffic flow (α=0.3), as the basis for measuring road load, is a key basis for triggering dynamic lane allocation. Weather conditions (γ=0.2) reflect the systematic impact of severe weather on road safety capacity and are an important parameter for achieving proactive prevention. While emergencies (δ=0.1) have the lowest weight, they have the highest priority in the decision-making logic; once detected, the system will immediately activate a mandatory response mechanism. This weighting system (α=0.3, β=0.4, γ=0.2, δ=0.1) was determined based on principal component analysis and regression analysis of a large amount of historical traffic data. The highest weight is given to average vehicle speed (β) because the "Road Capacity Manual" and multiple studies have shown that vehicle speed is the most sensitive and direct indicator of traffic flow operation. This weighting system ensures that the system prioritizes traffic efficiency under normal conditions, while seamlessly switching to a safety-oriented response mode in abnormal situations. Finally, the Weather Factor values ​​are shown in Table 1; the Incident Levels are shown in Table 2.

[0096] Table 1. Weather Factor Values

[0097]

[0098] Table 2 Incident Level Table

[0099]

[0100] Third, the traffic state index is used as a direct input to trigger the logical conditions corresponding to the pre-set road marking generation rule base, thereby initiating the corresponding marking scheme generation process.

[0101] The road marking scheme generation process relies heavily on a pre-built road marking scheme library. This library is a logical collection that uses its internal road marking generation rule library and traffic template library to achieve end-to-end decision-making from state assessment to graphic generation. The functions of the road marking generation rule library and traffic template library are as follows:

[0102] (1) Road marking generation rule base: Defines, in the form of logical conditions, which marking scheme should be triggered under what combination of traffic state (TrafficIndex threshold), event level (Incident Level), or weather condition (Weather Factor). The road marking generation rule base is shown in Table 3.

[0103] Table 3 Road Marking Generation Rule Base

[0104]

[0105] (2) Traffic Template Library: This library stores digital graphic templates for various standard road markings (such as vector graphic files for lane lines, arrows, guide lines, and shoulder lines). These templates strictly adhere to national and industry standards such as "Road Traffic Signs and Markings" (GB 5768), and pre-set standard geometric shapes, size ratios, and color attributes (such as lane line width, arrow length and angle) to ensure the standardization and legality of the generated markings, and to guarantee the flexible deployment and dynamic adjustment of the markings while complying with national standards.

[0106] (3) Priority arbitration logic: In order to ensure that the safest and most effective lane marking scheme can be executed in any complex scenario, priority arbitration logic is set: event level > weather conditions > traffic congestion. This logic is the final decision principle for selecting the "most suitable" scheme.

[0107] When multiple conditions are met simultaneously, according to the aforementioned priority arbitration logic, lower-priority conditions are ignored, and only the solution corresponding to the highest-priority condition is executed. This mechanism ensures that in complex scenarios (such as simultaneous accidents and congestion), the system can prioritize responding to the highest safety level requirements and correctly handle the spatial relationships between lane markings.

[0108] Based on the aforementioned traffic state index assessment results, the road marking decision engine performs real-time matching with the logical conditions in the road marking generation rule base, and combines priority arbitration logic to determine the type of road marking scheme that should be triggered at the moment.

[0109] Once the final scheme type is determined, the engine immediately calls the corresponding vector graphics template from the traffic template library to generate a logical marking scheme that conforms to the specifications and has a clearly defined type. The scheme generated at this stage does not yet contain specific spatial coordinate information, but provides structured input for the next stage of dynamic marking space mapping based on a two-dimensional local coordinate system.

[0110] Fourth, a dynamic spatial mapping mechanism based on a two-dimensional coordinate system is constructed to convert the marking elements in the logical scheme into physical projection instructions with specific spatial coordinates, providing an accurate positioning basis for subsequent geometric correction and road surface projection.

[0111] (1) Determine the adaptive relationship between the projection coverage area and the spacing between light poles. In actual road deployment, the spacing between light poles may vary depending on factors such as road grade, lighting requirements, and terrain limitations, with a common range of 30-50 meters. To ensure that the coverage areas of adjacent projection modules always have a sufficient and stable overlap length, the system adopts an adaptive coverage design based on a fixed overlap length.

[0112] Based on the spacing D (meters) between adjacent streetlight poles and the desired length of the fixed overlap area. Let R (meters) be the coverage radius of a single projection module along the X-axis, i.e., the range of the X-axis in the local coordinate system is [-R, R]. Then, the total length of the coverage area of ​​a single projection module is... To ensure overlap, the following conditions must be met: The actual length of the overlapping region is ;

[0113] Therefore, if the length of the overlapping region is required to be a constant value... Then the following relationship exists:

[0114] ,

[0115] ,

[0116] This design allows the invention to flexibly adapt to various existing road infrastructures without the need to customize different hardware for different light pole spacings. The idea is to dynamically adjust the coverage of each module with a fixed overlap length to adapt to varying light pole spacings.

[0117] (2) Constructing a two-dimensional dynamic coordinate system. Based on the projection coverage parameters calculated above, a two-dimensional local coordinate system is established for each projection module (D=35m) to describe the road plane position within its coverage area. Furthermore, the system establishes a unified two-dimensional global coordinate system based on the entire road plane, where the local coordinate system is contained within the global coordinate system, such as... Figure 3 As shown.

[0118] a) Local coordinate system: The origin is the projection point of the i-th projection module on the road plane. Establish a two-dimensional right-handed coordinate system.

[0119] ①X-axis: Parallel to the lane lines, with the positive direction being the direction of vehicle movement.

[0120] ②Y-axis: Perpendicular to the lane lines, pointing positively towards the center of the road or the opposite lane.

[0121] Each projection module's local coordinate system covers its own control range (X: [-R, R] meters, Y: based on road width, such as [3.5, 7] meters), where R is the coverage radius.

[0122] b) Global Coordinate System: Establish a unified two-dimensional global road coordinate system, with the origin at the same point as the first projection module. The X and Y axes are aligned with the local coordinate system. The distance between adjacent lampposts is D meters. Therefore, the coordinates of the origin of the local coordinate system of the i-th projection module in the global coordinate system are: ;

[0123] c) Coordinate transformation: Local coordinates can be transformed into global coordinates through simple translation transformations.

[0124] ,

[0125] in, For local coordinates, These are global coordinates.

[0126] (3) Projection module confirms mapping with datum space.

[0127] a) Determine the projection module. The confirmation of the projection module is based on the global coordinates of the target position of the datum line and the geometric relationship between the coverage area of ​​each projection module.

[0128] ① Extract key geometric parameters from the logical marking scheme, including the marking type and target area. The target global coordinate area is: , ;

[0129] ② Extract the coverage parameters of all projection modules. The coverage of the i-th module is... , ;

[0130] If the coverage area of ​​the projection module includes the target area, then the module is determined to be responsible for projecting the marking.

[0131] b) After determining the projection module, for the i-th projection module, convert the global coordinates of the datum line into the local coordinates of each projection module;

[0132] c) The preset pole spacing D and the fixed overlap length L overlap The local coordinate systems of each module are sequentially associated and integrated into a unified global coordinate system, thereby forming a collaborative projection network covering the entire road segment, such as... Figure 4 As shown, taking a two-way six-lane scenario as an example, the global deployment effect of multiple adjacent projection modules is presented intuitively.

[0133] 5. After obtaining the coordinates of the marking line on the projector image plane through two-dimensional spatial mapping, a real-time digital pre-distortion correction technology based on homography matrix is ​​used to solve the geometric distortion problem caused by the oblique installation of the projection module.

[0134] (1) Calibration and matrix generation

[0135] During the system deployment phase, each projector requires precise calibration to establish a mathematical mapping between its image plane and the road plane. This process is achieved using the homography matrix H. The homography matrix is ​​a 3×3 linear transformation matrix that describes a two-dimensional projection transformation, mapping points on the projector's image plane to corresponding points on the road plane. Figure 2 The diagram shows the deployment orientation and projection schematic of the high-brightness projection module of this invention.

[0136] The calibration process typically uses known pairs of reference points. For example, a set of markers with known world coordinates are placed on the road surface, and the corresponding pixel coordinates of these points on the projector's image plane are captured using the projector's built-in camera or external measuring equipment. Mathematically, this mapping is defined by the following homogeneous coordinate formula:

[0137] ,

[0138] in, These are the coordinates (in meters) of the target point on the road surface, representing the position of the ideal road marking. is the coordinates of the corresponding point on the projector image plane (in pixels), s is a non-zero scale factor used for normalizing homogeneous coordinates, and H is a 3×3 homography matrix, specifically in the form of:

[0139] ,

[0140] Matrix H contains information such as the projector's installation angle, position, and optical parameters. Through a calibration program, the system calculates a unique H matrix for each projector and stores it in the storage module for real-time processing. This step forms the theoretical basis for subsequent correction calculations, ensuring the accuracy and consistency of the mapping relationship.

[0141] (2) Real-time pre-distortion processing

[0142] After the central processing module issues the road marking projection command, the system needs to convert standard road marking graphics (such as lane lines, arrows, etc.) into images that can be projected by the projector. Due to the tilted installation of the projector, directly projecting standard graphics will cause distortion. Therefore, the system utilizes the inverse matrix H of the homography matrix. -1 Perform real-time pre-distortion processing on standard graphics.

[0143] Specifically, for each point on the standard grading diagram (In the road coordinate system), the system calculates its pre-distortion coordinates [u′, v′] on the projector image plane. The calculation process is as follows:

[0144] ,

[0145] Among them, H-1 It is the inverse of the homography matrix H. Due to the scale uncertainty of homogeneous coordinates, the calculated [u′,v′,1] is obtained. T Normalization is required to obtain the actual pixel coordinates [u′, v′], as shown in the following formula:

[0146] (6)

[0147] in, .

[0148] The real-time pre-distortion correction mechanism overcomes problems such as trapezoidal distortion and stretching deformation caused by projection angle through rigorous mathematical transformations. It ensures the shape, size, and positional accuracy of lane lines, arrows, and other markings on the road surface, and is a key technological guarantee for achieving high-precision visual guidance.

[0149] VI. A smooth transition algorithm is used to process the accurate grading graphic data obtained after geometric distortion correction to ensure smooth, natural and safe switching between different grading scenes.

[0150] The smooth transition algorithm performs real-time interpolation calculations based on easing functions on the visual attributes (color, brightness) and geometric vertices of the markings within a preset transition time window T (e.g., 3-5 seconds). For any attribute A that needs to be transitioned (e.g., color component, brightness value, vertex coordinates), its current value within the transition time T is... The formula for calculating time t (0 ≤ t ≤ T) is:

[0151] ,

[0152] in, This is the initial value for the attribute. The attribute target value, t is the time elapsed since the start of the transition, 0≤t≤T, and the easing function is adopted. A cubic easing function.

[0153] In this embodiment of the invention, a cubic easing function is used. The first derivative of the function The value is zero at x=0 and x=1, which means that the instantaneous rate of change of the transition at the beginning and end is zero, thus achieving a smooth fade-in and fade-out effect and avoiding the abruptness that linear interpolation may bring.

[0154] This mechanism imbues dynamic lane marking changes with an animated smoothness, serving not only as a key design element to enhance the system's user-friendly interaction but also as an important safety measure. Through visual continuity, it effectively avoids driver startle, misjudgment, and emergency maneuvers caused by sudden changes in lane markings, providing drivers with valuable buffer time to adapt to new traffic organization schemes, thereby significantly improving traffic safety during dynamic lane marking transitions.

[0155] 7. After receiving and integrating the final road marking graphic data after geometric correction and smooth transition processing, the high-brightness projection module dynamically calculates and determines the final projection brightness parameters based on real-time environmental data (such as illuminance and road surface conditions) to ensure that the generated road markings have clear, comfortable and safe visibility under all weather conditions.

[0156] (1) Brightness calculation model

[0157] To ensure optimal visibility of road markings under all weather conditions, the system dynamically calculates projection parameters using the following formula:

[0158] ,

[0159] in, The final calculated projection brightness (lumens); The base brightness (lumens) ensures basic visibility in a completely dark environment; The ambient light intensity (Lux) is collected in real time by the light sensor in the environment sensing module. This is the illumination compensation coefficient, used to counteract the scouring effect of ambient light on the visibility of the markings; This is the road surface reflection compensation value; This is the road surface reflection compensation coefficient, which is dynamically adjusted according to the road surface material and condition.

[0160] (2) Parameter determination and physical meaning

[0161] The base brightness is set to 10,000 lumens. This value is determined based on research into the minimum identifiable brightness threshold for drivers in the absence of ambient light interference, ensuring that lane markings are clearly identifiable without being overly bright or dazzling in scenarios such as tunnels and at night.

[0162] The illumination compensation factor is set to 0.5. This factor is determined by combining measured reflectance data of typical asphalt pavements under different ambient illuminance (0-100000 Lux) with a driver visual recognition model. The derivation of the calculation formula takes into account that ambient light reduces the contrast between the road markings and the road surface, thus requiring a linear increase in projected brightness to maintain visibility.

[0163] Road surface reflection compensation library and Road surface conditions significantly affect light reflectivity. The system incorporates a reflection compensation lookup table established through laboratory measurements and field calibrations. The road surface reflection compensation value is usually set to 1.0. The median value is based on the ASTM E808 standard and is derived from extensive field measurements of pavement samples under different working conditions using standard luminance meters and spectral analyzers in both laboratory settings and typical road sites. An example of the compensation library is shown in Table 4.

[0164] Table 4 Example of a compensation library

[0165]

[0166] (4) Brightness constraint

[0167] To ensure safety, constraints must also be imposed on the final calculated brightness:

[0168] ① Maximum brightness constraint: This upper limit is determined by the hardware performance of the projection module to prevent device overload.

[0169] ②Minimum brightness constraint: This ensures that even in the most optimized calculations, the markings have a minimum level of visibility.

[0170] Through the aforementioned precise adaptive brightness calculations, the dynamic projection markings are ensured to serve as a reliable, clear, and comfortable visual guide under any lighting and road surface conditions, greatly enhancing the system's practicality and all-weather operation capability.

[0171] This application also includes a system for implementing the above-described dynamic traffic environment perception projection-based road marking method, comprising:

[0172] This includes the road test control subsystem and the vehicle interaction subsystem;

[0173] The roadside control subsystem includes:

[0174] The central processing module has a built-in road marking decision engine and coordinate system management unit. By integrating real-time traffic conditions, weather conditions and emergency information, it intelligently generates the optimal road marking scheme in real time based on preset traffic rules and optimization algorithms. It constructs and manages two-dimensional local coordinate system and global coordinate system, realizes the accurate mapping from logical road marking scheme to physical projection coordinates, and outputs precise control commands to drive the projection module.

[0175] The high-brightness projection module transforms the decision instructions from the central processing module into high-definition, high-precision road visual markings, and inputs the installation position and angle parameters of the projection module into the roadside control subsystem as the basic parameters for coordinate system construction and geometric correction.

[0176] The communication module exchanges data with the in-vehicle interaction subsystem in real time, accurately issues dynamic lane marking commands, and builds a low-latency, highly reliable collaborative communication network.

[0177] The storage module is used to store system programs, historical traffic data, lane marking scheme library, event logs and vehicle interaction data, providing continuous data support for decision analysis.

[0178] The power module provides a stable and uninterrupted power supply for all roadside equipment and integrates comprehensive lightning protection and overload protection functions to ensure the continuous and reliable operation of the system in various harsh environments.

[0179] The in-vehicle interaction subsystem includes:

[0180] Central processing module: parses and integrates real-time lane marking instructions from the communication module and high-precision vehicle position information from the positioning module, generates matching AR visual elements and voice scripts, and drives the display module and voice prompt module to output synchronously;

[0181] Communication module: Receives dynamic road marking graphics and personalized guidance instructions issued by the roadside in real time, and establishes a low-latency, highly reliable two-way data link with the roadside control subsystem;

[0182] Positioning module: Acquires vehicle location information in real time to ensure that the vehicle's own position and the dynamic lane marking information issued by the roadside system are accurately matched in space, providing reliable information for vehicle guidance;

[0183] Display module: Deeply integrated with the vehicle screen, it clearly renders the road markings of the current road segment and intuitively prompts the driver with recommended lanes;

[0184] Voice prompt module: Provides real-time, natural voice guidance to the driver based on the received lane marking instructions.

[0185] The following description, in conjunction with the accompanying drawings, illustrates typical application scenarios of the system of this invention.

[0186] Scenario 1: Normal traffic flow

[0187] Under normal traffic conditions, the roadside control subsystem calculates a low traffic state index based on real-time perception data, determining that the traffic flow is stable and there is no need to activate the dynamic lane marking scheme. The in-vehicle interaction subsystem then executes a steady-state guidance mode, continuously providing the driver with clear and reliable basic road guidance through the vehicle screen.

[0188] The lane marking decision engine uses standard lane line templates. After geometric distortion correction, smoothing algorithms, and adaptive brightness optimization, the graphic data is projected onto the road surface by a high-brightness projection module, displaying clear and accurate standard lane markings to provide drivers with stable visual information. Simultaneously, the in-vehicle interaction system sends road status information to the vehicle terminal via V2X communication. The vehicle screen only displays lane marking graphics that perfectly match the road surface, without activating voice prompts, ensuring that necessary auxiliary information is provided without interfering with the driver.

[0189] The process operates continuously in a closed loop, ensuring basic guidance functions and driving safety while maintaining low power consumption and being ready for real-time monitoring and dynamic response.

[0190] in Figure 5 The system operates under typical conditions of smooth traffic and good weather. The roadside sensing units and high-brightness projection modules deployed above the road are in a low-power monitoring state. Clear and standard white lane lines and edge lines are projected onto the road surface, with brightness adaptively adjusted according to ambient light to ensure all-weather visibility. Traffic flow is smooth, with no congestion, events, or severe weather triggering dynamic lane marking switching; the system operates in a highly efficient and energy-saving steady-state mode. This scenario demonstrates that the system can still provide superior visual quality and consistency compared to traditional static lane markings even without dynamic intervention.

[0191] Figure 6 The image showcases the prompts displayed on the in-vehicle interactive subsystem screen under normal traffic conditions. The central control screen clearly renders the current lane lines and road edges using AR fusion, with the graphics perfectly matching the actual projected road markings. The interface design is simple, without additional voice prompts or highlighted warnings, avoiding interference with the driver's normal driving.

[0192] Scenario 2: Traffic congestion

[0193] In traffic congestion, when the Traffic Index is ≥ 0.4, the system, based on the above closed-loop process, achieves a rapid response from perception to guidance, providing drivers with clear and safe dynamic lane guidance.

[0194] The decision engine matches and enables the tidal lane rules, calling the tidal lane lines and arrow templates; through spatial mapping, it determines to generate green markings in the middle lane (such as lane 3); after geometric correction, smooth transition and brightness adjustment, it is projected by the corresponding projection module.

[0195] The vehicle receives information synchronously, displays a green arrow and tidal lane sign on the screen, and broadcasts a voice prompt: "Tidal lane has been opened ahead, please follow the green markings." This enables dynamic allocation of lane resources and improves the traffic capacity of bottleneck sections.

[0196] Figure 7This visually demonstrates a real-world scenario where the system dynamically activates tidal flow lanes to improve traffic capacity when it detects traffic saturation (Traffic Index ≥ 0.4). The image shows the roadside sensing unit detecting dense traffic and decreased vehicle speed on the main lane, triggering the congestion response logic. Based on the decision command, the high-brightness projection module overlays and projects prominent green tidal flow lane markings and green directional arrows onto the existing lane lines, clearly indicating that the lane function has been temporarily switched. Guided by the system, vehicles orderly enter and use the newly opened tidal flow lanes, effectively diverting traffic from the congested direction.

[0197] Figure 8 The image showcases the vehicle screen guidance interface provided to the driver by the in-vehicle interaction subsystem when the tidal lane is activated. The image shows the vehicle screen highlighting the green tidal lane markings, their position and shape perfectly synchronized with the actual road surface projection, creating a strong visual confirmation. The interface clearly displays a green arrow and the words "Tidal Lane," ensuring the driver's unambiguous understanding of the lane function change. A concise voice prompt accompanies the interface, such as "Tidal lane is open ahead, please follow the green markings," providing multimodal information guidance.

[0198] Scenario 3: Severe Weather Conditions

[0199] Under severe weather conditions, when Traffic Index > 0.3 and Weather Factor ≥ 0.4,

[0200] The decision engine matches the "Enable Enhanced Shoulder Markings" rule, calls up the arrow, highlights the blue shoulder line and lane edge line template; spatial mapping determines the projection arrow and enhances the shoulder and edge lines of lane 1 and lane 5; after geometric correction, smooth transition and brightness adjustment, it is projected by the corresponding projection module.

[0201] The vehicle-mounted system displays a blue arrow and enhanced blue road markings, along with a message that reads, "In rainy or snowy weather, the road outline has been enhanced. Please drive carefully along the blue markings." This significantly improves the visibility of road boundaries in low-visibility environments and reduces the risk of accidents.

[0202] Figure 9 The simulation demonstrated the system's enhanced road marking projection in adverse weather conditions such as rain and snow that reduce visibility. The image shows rainy or snowy weather conditions where traditional road markings are difficult to discern due to slippery surfaces, glare, water film, or snow accumulation. Upon system response, the high-brightness projection module automatically switches the projection color of lane edge lines, shoulder lines, and directional arrows to a high-contrast blue based on weather sensor data, significantly increasing brightness. The enhanced blue markings have stronger penetration in low-visibility environments, effectively outlining the road's geometric contours and providing drivers with clear and reliable lane boundaries and directional guidance.

[0203] Figure 10 The demonstration showcases the collaborative guidance interface provided by the in-vehicle interactive subsystem screen during the inclement weather enhancement mode. The image shows the vehicle screen and AR display system synchronously rendering enhanced blue road markings and arrows, their positions perfectly corresponding to the road surface projection, creating a visual guidance layer inside the vehicle that matches the external environment. Simultaneously, auditory guidance is provided; the system triggers a voice prompt module, broadcasting instructions such as "In rainy or foggy weather, the road outline has been enhanced; please drive cautiously along the blue markings," achieving dual visual and auditory prompts.

[0204] Scenario 4: Emergency Situation

[0205] In the event of an emergency, when Traffic Index > 0.3 and Incident Level ≥ 0.5,

[0206] The decision engine matches and enables the guide line rule, calling the yellow guide line and red restricted area templates; spatial mapping generates a red restricted area and a yellow guide line in the lane at the accident point;

[0207] The vehicle's screen highlights the accident area and detour route, and announces: "Accident ahead, please follow the yellow guide lines on the ground to detour," quickly and forcefully guiding traffic to safely avoid the risk area and prevent secondary accidents.

[0208] Figure 11 The simulation depicts the system's response when detecting sudden traffic events such as traffic accidents. The image shows a vehicle collision on one lane, creating a physical obstacle and threatening the safety of subsequent vehicles. Upon identifying the accident, the event detection unit initiates a mandatory response based on the highest priority. A high-brightness projection module immediately projects a prominent red grid-shaped no-entry zone in front of the accident lane, clearly indicating the danger area. Simultaneously, continuous yellow guide lines are projected onto the lane. This combination of red and yellow high-contrast markings visually creates a strong "prohibition" and "guidance" instruction, enabling drivers of following vehicles to perceive the risk in advance and understand the detour route, thus changing lanes in an orderly and safe manner.

[0209] Figure 12 The image showcases an enhanced emergency guidance interface provided to the driver by the in-vehicle interaction subsystem during an emergency response. The vehicle screen highlights the red accident area and yellow detour paths, their spatial positions precisely matching the road surface projection, creating a view inside the vehicle that is completely synchronized with the external hazardous environment. The interface is typically accompanied by clear warning icons, and simultaneously, a voice prompt module announces: "Attention, accident ahead, please follow the yellow detour lines on the ground."

[0210] Scenario 5: Collaborative Response Scenario for Accidents and Rainy Weather

[0211] In the face of adverse conditions where accidents and rain coexist, the system activates a multi-factor collaborative response mechanism based on its built-in priority arbitration logic (event level > weather conditions > traffic congestion). This enables rapid identification of the accident area, safe detour guidance, and enhancement of low-visibility environments, providing drivers with clear, timely, and weather-adaptive emergency route guidance.

[0212] The system prioritizes responding to accident events, while also overlaying environmental impact parameters from rainy weather to make comprehensive lane marking decisions; it matches the "activate guide lines" rule and calls up the yellow guide lines and red restricted area templates; it also overlays the "enhance severe weather" rule and calls up the arrows, highlighted blue shoulder lines, and lane edge line templates; it generates red restricted areas and yellow guide lines in the lane at the accident site; and it enhances shoulder lines and lane edge lines in other required areas using highlighted blue projection.

[0213] Based on the global coordinates of the accident site and the range of weather impact, the system determines which projection modules will project collaboratively, and performs coordinate transformation and distortion correction. The projection brightness is enhanced by calculation based on ambient light and road surface reflection compensation in rainy weather to ensure clear visibility even under low visibility conditions. The guide lines remain yellow, the restricted area remains red, and the shoulder lines are enhanced to blue, forming a multi-layered, high-contrast visual guidance. The system completes the transition at a relatively fast rate to avoid affecting the driver's reaction time due to weather.

[0214] The in-vehicle screen highlights the accident area (red), the diversion area (yellow), and the enhanced road outline (blue) according to the actual situation; the voice prompt module announces: "Attention: There is an accident ahead. Please detour according to the yellow diversion lines on the ground or in rainy or snowy weather, the road outline has been enhanced. Please drive carefully along the blue markings."

[0215] Figure 13 This simulation addresses the most challenging complex scenario of simultaneous traffic accidents in rainy conditions, visually demonstrating the system's multi-layered, collaborative lane marking projection based on priority arbitration logic. The image shows that due to the accident in lane 5, a red grid no-entry zone and yellow guide lines are projected onto the road surface, clearly marking the absolute danger zone and prohibiting vehicles from entering. Simultaneously, due to the rain, the shoulder and lane lines of lane 1 are highlighted in bright blue to improve outline visibility.

[0216] Figure 14This demonstration showcases the integrated guidance and warning interface presented to the driver by the in-vehicle interaction subsystem in a combined accident and rainy weather scenario. The image shows the vehicle screen displaying different information as needed and depending on the actual situation. Accident sections are precisely marked with a highlighted, dynamic red area, and the absolute danger zone is clearly indicated by yellow guide lines, prohibiting vehicles from entering. In weather-related sections, lane lines and shoulder lines are rendered with enhanced blue markings to remind drivers of the slippery road boundaries in rainy weather. The vehicle screen integrates accident warnings and rainy weather alerts, displaying different prompts as needed and depending on the actual situation, such as "Caution, accident ahead, please detour according to the yellow guide lines on the ground" or "In rainy or snowy weather, the road outline has been enhanced, please drive cautiously along the blue markings."

[0217] The embodiments of the present invention described above do not constitute a limitation on the scope of protection of the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the claims of the present invention.

Claims

1. A projection-based road marking method based on dynamic traffic environment perception, characterized in that, Includes the following steps: S1. Collect and integrate real-time traffic flow, meteorological conditions and event data to form an initial environmental state dataset; S2. Using the dataset described in S1, input it into the traffic state assessment model to calculate the traffic state index and comprehensively assess the real-time traffic status of the current road. The formula for calculating the traffic state index is as follows: ， Where Q represents the current actual traffic flow, This represents the maximum designed traffic capacity of the road, where V is the current average vehicle speed. The free flow velocity is represented by Weather Factor, the incident level by Incident Level, and α, β, γ, and δ represent the weighting coefficients of each factor. S3. Based on the traffic state index, trigger the corresponding logical conditions of the preset road marking generation rule base, and generate a marking scheme in combination with the traffic template library; S4. Construct a dynamic spatial mapping mechanism based on a two-dimensional coordinate system to map the marking elements in the marking scheme to the coordinates of the markings on the projector image plane; S41 extracts key geometric parameters from the logical marking scheme, including the marking type and target area. The target global coordinate area is: , ; S42 extracts the coverage parameters of all projection modules, where the coverage of the i-th module is... , ; S43 If the coverage area of ​​the projection module includes the target area, then it is determined that the module is responsible for projecting the mark; After S44 determines the projection module, it converts the global coordinates of the marking line into the local coordinates of each projection module. S45 is based on the distance D between adjacent light poles and the length of the fixed overlapping area. The local coordinates of each module are sequentially associated and integrated into a unified global coordinate system to form a collaborative projection network covering the entire road segment; The transformation method between global coordinates and local coordinates of each projection module is as follows: a) Calculate projection coverage parameters: The total length of the coverage area of ​​a single projection module is , Coverage radius , Where D is the distance between adjacent street light poles. The desired fixed overlap region length; b) Based on the projection coverage parameters, establish a two-dimensional local coordinate system for each projection module: The origin is the projection point of the i-th projection module on the road plane. The X-axis is parallel to the lane lines, with the positive direction being the vehicle's forward direction, and the coverage area is... Meters; the Y-axis is perpendicular to the lane lines and points positively toward the center of the road or the opposite lane, with the range determined according to the road width; c) Establish a two-dimensional global road coordinate system, with its origin at the origin of the first projection module. The X and Y axes are aligned with the local coordinate system. Then, the coordinates of the origin of the local coordinate system of the i-th projection module in the global coordinate system are: ; d) Local coordinate to global coordinate transformation: ， in, For local coordinates, Global coordinates; S5. Perform geometric distortion correction on the coordinates obtained in S4 to obtain accurate datum line graphic data; S6. Apply a smooth transition process to the paving pattern after correction in S5 to obtain the final paving pattern data; S7. Based on real-time environmental status data, dynamically calculate and determine the brightness parameters of the final projected marking graphic to complete the dynamic marking projection.

2. The projection-based road marking method based on dynamic traffic environment perception according to claim 1, characterized in that, In step S5, the geometric distortion correction adopts a fact-based digital pre-distortion correction technique based on the homography matrix, as follows: The mapping relationship between the image plane and the road plane established by the precise calibration of the projector is as follows: ， in, These are the coordinates of the target point on the road surface, representing the position of the ideal road marking. is the coordinate of the corresponding point on the projector image plane, s is a non-zero scale factor used for normalization of homogeneous coordinates, and H is a 3×3 homography matrix. For each point on the grading graph Calculate its predistortion coordinates on the projector image plane. The formula is: ， in, The homography matrix H is the inverse matrix; normalizing the above equation yields... The normalization formula is: ， in, .

3. The projection-based road marking method based on dynamic traffic environment perception according to claim 2, characterized in that, In step S6, the smooth transition algorithm is as follows: Within a preset transition time window T, the visual attributes and geometric vertices of the markings are calculated in real time based on an easing function. For any attribute A that needs to be transitioned, its current value is... The formula for calculating time t is: ， in, This is the initial value for the attribute. The attribute target value, t is the time elapsed since the start of the transition, 0≤t≤T, and the easing function is adopted. A cubic easing function.

4. The projection-based road marking method based on dynamic traffic environment perception according to claim 3, characterized in that, In step S7, the projection brightness parameters are calculated as follows: ， in, For the final calculated projection brightness, Based on brightness, For ambient light intensity, This is the illumination compensation coefficient. This is the road surface reflection compensation value. This is the road surface reflection compensation coefficient.

5. The projection-based road marking method based on dynamic traffic environment perception according to claim 1, characterized in that, The road marking generation rule base is defined in the form of logical conditions: the corresponding marking scheme that should be triggered under a specific combination of traffic conditions, event levels, and weather conditions.

6. The projection-based road marking method based on dynamic traffic environment perception according to claim 5, characterized in that, A clear priority arbitration logic is also set to ensure the safety and effectiveness of the lane marking scheme. The priority arbitration logic is: event level > weather conditions > traffic congestion.

7. A system for implementing the projection-based road marking method based on dynamic traffic environment perception as described in any one of claims 1-6, characterized in that, This includes the roadside control subsystem and the in-vehicle interaction subsystem; The roadside control subsystem includes: The central processing module has a built-in road marking decision engine and coordinate system management unit. By integrating real-time traffic conditions, weather conditions and emergency information, it intelligently generates the optimal road marking scheme in real time based on preset traffic rules and optimization algorithms. It constructs and manages two-dimensional local coordinate system and global coordinate system, realizes the accurate mapping from logical road marking scheme to physical projection coordinates, and outputs precise control commands to drive the projection module. The high-brightness projection module transforms the decision instructions from the central processing module into high-definition, high-precision road visual markings, and inputs the installation position and angle parameters of the projection module into the roadside control subsystem as the basic parameters for coordinate system construction and geometric correction. The communication module exchanges data with the in-vehicle interaction subsystem in real time, accurately issues dynamic lane marking commands, and builds a low-latency, highly reliable collaborative communication network. The storage module is used to store system programs, historical traffic data, lane marking scheme library, event logs and vehicle interaction data, providing continuous data support for decision analysis. The power module provides a stable and uninterrupted power supply for all roadside equipment and integrates comprehensive lightning protection and overload protection functions to ensure the continuous and reliable operation of the system in various harsh environments. The in-vehicle interaction subsystem includes: Central processing module: parses and integrates real-time lane marking instructions from the communication module and high-precision vehicle position information from the positioning module, generates matching AR visual elements and voice scripts, and drives the display module and voice prompt module to output synchronously; Communication module: Receives dynamic road marking graphics and personalized guidance instructions issued by the roadside in real time, and establishes a low-latency, highly reliable two-way data link with the roadside control subsystem; Positioning module: Acquires vehicle location information in real time to ensure that the vehicle's own position and the dynamic lane marking information issued by the roadside system are accurately matched in space, providing reliable information for vehicle guidance; Display module: Deeply integrated with the vehicle screen, it clearly renders the road markings of the current road segment and intuitively prompts the driver with recommended lanes; Voice prompt module: Provides real-time, natural voice guidance to the driver based on the received lane marking instructions.

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