Highway lane dimension single vehicle path guidance method combined with unmanned aerial vehicle monitoring

Abstract

This invention discloses a single-vehicle path guidance method for elevated roads using drone monitoring, relating to the field of traffic control technology. The method includes: accurately monitoring vehicle information at the elevated mainline and entrance / exit ramp lane dimensions using a drone equipped with a high-definition wide-angle camera and millimeter-wave radar; accurately identifying and analyzing traffic flow density at the elevated mainline lane dimensions and queue length at the entrance / exit ramp lane dimensions based on a GIS map; guiding the target vehicle's path according to the traffic flow status and congestion conditions of the elevated mainline and entrance / exit ramps; optimizing parameters for the allowed lane crossing traffic density threshold and the elevated mainline congestion density judgment threshold based on compliance levels; and ensuring the full utilization of the spatial and temporal resources of elevated roads.

Description

Technical Field

[0001] This invention relates to the field of traffic control technology, specifically a single-vehicle path guidance method that combines drone monitoring along elevated lanes. Background Technology

[0002] To alleviate traffic pressure on surface roads and reduce traffic conflicts and congestion, numerous elevated roads have been constructed. However, the reality is that during rush hours and holidays, elevated main roads and their entrance / exit ramps still frequently experience congestion. To address this, the current main technical approach involves installing traffic lights at the entrances of elevated ramps: when traffic volume is excessive, yellow flashing or all-red control strategies are used to limit traffic flow on the elevated main road, or to regulate vehicles merging from single or multiple entrance ramps into the main road, reducing interference from ramp traffic. However, this method fails to adequately consider the dynamic control between the starting and ending points of the elevated road and all entrance / exit ramps, and it also fails to comprehensively and fully dynamically allocate the temporal and spatial resources of the entire elevated road's lane dimensions. This directly leads to an unreasonable allocation of temporal and spatial resources on many elevated roads, thus failing to alleviate congestion on the elevated main roads and their entrance / exit ramps in a timely and effective manner. It is worth noting that while current internet map navigation software can provide vehicle navigation guidance and assist users in choosing appropriate entrances / exits and routes to avoid congested areas, its limited access to only a portion of floating car data (a small sample size) results in insufficient comprehensiveness and accuracy in road condition assessment. Furthermore, this type of navigation guidance only focuses on path-level planning and fails to achieve precise guidance at the lane level, making it difficult to meet the needs of refined traffic planning and guidance for elevated roads. Therefore, there is an urgent need for a technological means to achieve accurate, real-time detection of traffic flow across the entire lane dimension of elevated roads and combine this with lane-level path guidance algorithms to dynamically allocate the spatiotemporal resources of vehicle traffic on elevated roads.

[0003] Current methods for monitoring elevated road conditions mostly involve installing a large number of detection devices on the roadside. This approach requires deploying a significant number of equipment poles, resulting in high initial investment costs and substantial manpower and resources for subsequent maintenance. Furthermore, limitations in the monitoring angle lead to numerous missed or incorrect data captures (for example, if a large vehicle in front obstructs the view, smaller vehicles behind are likely to be missed). However, with the booming development of the low-altitude economy, drone monitoring technology has become increasingly mature, demonstrating unique advantages in monitoring elevated road conditions. Drones offer excellent field of view, providing comprehensive, unobstructed coverage of all lanes of the elevated road from high altitude, clearly capturing vehicle traffic status. This broad and flexible perspective is unmatched by traditional roadside equipment, enabling more efficient and accurate acquisition of traffic status data across the elevated mainline and entrance / exit ramp lanes. Therefore, it is necessary to integrate the advantages of drone monitoring technology to dynamically allocate spatiotemporal resources across all entrance and exit ramps and lane dimensions of the entire elevated road network in real time. By comprehensively collecting traffic flow data from the elevated mainline and entrance / exit ramps using drones, combined with route planning and guidance methods, accurate lane-dimensional navigation can be provided for vehicles traveling on the elevated road. This measure will help fully tap the potential of the spatiotemporal resources of elevated roads, comprehensively improve their traffic capacity, and thus effectively alleviate the frequency of elevated road congestion and reduce the impact of such congestion events. Summary of the Invention

[0004] To effectively alleviate the frequency of elevated highway congestion and reduce its impact, this invention leverages the advantages of drone monitoring technology to provide a single-vehicle path guidance method based on elevated highway lane dimensions. By deploying drones equipped with high-definition wide-angle cameras and millimeter-wave radar along the elevated highway, it achieves full-coverage monitoring of traffic flow status on the main line and entrance / exit ramps, and accurately identifies and analyzes traffic density at the main line lane dimension and queue length at entrance / exit ramp lane dimensions. Based on the traffic flow status and congestion conditions of the main line and entrance / exit ramps, combined with the subsequent vehicle traffic demand analysis provided by the navigation map, the system obtains the optimal travel path for subsequent vehicles on the elevated highway and the optimal lane information for different sections of the elevated road. This information is then pushed to the driver via the navigation map to guide vehicles to travel according to the planned path and lane, ensuring the full utilization of the spatial and temporal resources of the elevated highway.

[0005] To achieve the above objectives, the present invention provides the following technical solution: A single-vehicle path guidance method combining drone monitoring along elevated lanes includes the following steps: (1) Accurately monitor vehicle information in lane dimension of elevated main line and entrance / exit ramps by using UAVs equipped with high-definition wide-angle cameras and millimeter-wave radar; (2) Based on the GIS map, the positions of each lane of the elevated main line and each lane of the entrance and exit ramps are marked. The corresponding binding relationship is established according to the vehicle and lane coordinate information. The traffic flow density of each lane of the elevated main line and the queuing length of the lane dimension of the entrance and exit ramps are calculated. (3) Based on the navigation start and end point of the target vehicle, obtain the information of the entrance ramp and exit ramp of the vehicle to enter the elevated road by connecting to the GIS map. Compare the information calculated in step (2) with the maximum design queuing length of the entrance and exit ramps, the traffic flow density threshold of the allowed crossing lanes and the congestion density judgment threshold of the elevated main line to guide the target vehicle to the path. (4) The driving trajectory of the target vehicle is continuously monitored through the GIS map. When the driving trajectory is inconsistent with the planned path, the target vehicle is given an early warning. The parameters of the allowed lane crossing traffic density threshold and the elevated main line congestion density judgment threshold are optimized in combination with the driver's compliance with the planned path.

[0006] In this invention, the UAV adopts the deployment principle of unit partitioning + overlapping coverage. The main line of the elevated road is divided into 1-kilometer basic monitoring units, and each ramp is an independent monitoring unit. Each monitoring unit is equipped with a UAV for fixed-point hovering monitoring, and the monitoring range of UAVs in adjacent units is guaranteed to have overlapping detection areas.

[0007] In this invention, the flight altitude of the elevated mainline UAV H The range should be controlled between 80 and 100 meters, with a horizontal coverage radius D of no less than 600 meters. The monitoring range of adjacent drone units should have at least a 50-meter overlap area. The drones flying over the ramps are kept at an altitude of 40-60m, focusing on the ramp lanes and merging areas to ensure that the monitoring area covers the ramp lanes and a 100m range connecting to the main line. To address any potential omissions at the intersection of ramps and the main line, supplementary inspections will be conducted in these areas using blind spot drones to fill the blind spots detected by the main line drones.

[0008] In this invention, the elevated main line is segmented by cutting the elevated main line according to each exit ramp, and each segment and each lane is treated as an independent calculation and analysis unit.

[0009] In this invention, the formulas for calculating the traffic flow density of each lane in each segment of the elevated mainline and the queue length of the entrance / exit ramp lanes are as follows: (1); (2); in, K mn Traffic density for m segments and n lanes on the elevated main line. X mn Real-time vehicle count for m segments and n lanes of the elevated mainline; L m The length of segment m for the elevated main line; Q ij for i Entrance and exit ramps j Lane queue length; Y ij for i Entrance and exit ramps j Real-time number of vehicles in each lane; L ijc for iEntrance and exit ramps j Average length of vehicle body in lane; S ij for i Entrance and exit ramps j Average spacing between vehicles in a queue.

[0010] In this invention, millimeter-wave radar is used to identify the vehicle outline and obtain... i Entrance and exit ramps j All vehicle body lengths in the lane L ijk Calculate i Entrance and exit ramps j Average length of vehicle in lane Average spacing between queuing vehicles S ij The distances between adjacent vehicles were obtained through actual measurement, using drones to identify the distances between them, and the average value was taken.

[0011] In this invention, the path guidance for the target vehicle in step (3) includes the following situations: Scenario 1: When the target vehicle approaches the entrance ramp, obtain the real-time queue length of each lane of the current entrance ramp. Q 入ij and the maximum design queue length of the current entrance ramp L i入max Comparison, if any lane Q 入ij All greater than L i入max If the current entrance ramp is congested, the target vehicle is guided to enter the elevated road from the next entrance ramp; otherwise, if the current ramp is unobstructed, the target vehicle is guided to enter the entrance ramp from the lane with the shortest queue length. Scenario 2: When the target vehicle is on the elevated mainline, obtain the traffic flow density at the lane dimension of the next segment. K mn and the congestion density determination threshold K b Compare, if any lane in the next segment K mn All greater than K b If the system determines the next lane segment is congested, it will guide the target vehicle to exit the elevated road at the nearest exit ramp. Conversely, if the next lane segment is clear, the system will guide the target vehicle to enter the lane with the lowest traffic density. However, to ensure the safety of lane changes and minimize the impact on following vehicles, the system needs to determine whether lane changes require crossing lanes and the traffic density of the lanes crossed. K mn With respect to the threshold for permitted cross-lane traffic density Ka The size relationship, if it is necessary to cross lanes and the traffic density of the lanes to be crossed. K mn Greater than K a If the current conditions for changing lanes are not met, the target vehicle will be guided to continue along its original path. Otherwise, if the conditions for changing lanes are met, the target vehicle will be guided to enter the lane with the lowest traffic density in the next segment. Scenario 3: When the target traffic flow approaches the exit ramp, obtain the real-time queue length of each lane on the current exit ramp. Q 出ij and the current maximum design queue length of the exit ramp L i出max Comparison, if any lane Q 出ij All greater than L i出max If the current exit ramp is deemed congested, the system will continue to determine the traffic density in the lane dimension of the next segment below the elevated main road. K mn Congestion density determination threshold K b The size relationship, if any lane in the next segment K mn All greater than K b If the next section of the elevated mainline is also considered congested, the target vehicle is guided to exit the elevated road at the current exit ramp. Conversely, if the next section is considered uncongested, the target vehicle is guided to continue on the elevated mainline and exit at the next exit ramp. If there is a queue length at the exit ramp... Q 出ij Less than or equal to L i出max If the system determines that the current exit ramp is clear, it will guide the target vehicle to enter the exit ramp from the lane with the shortest queue length. Scenario 4: If the target vehicle is not in any of the above three locations, guide the target vehicle to continue traveling along the pre-planned route.

[0012] In this invention, corresponding planned guidance paths are provided for three different position states of the target vehicle: 1-2km from the entrance ramp, entering the elevated main line, and 2-3km from the exit ramp, in combination with the real-time traffic conditions at the corresponding locations.

[0013] In this invention, the parameter optimization of the allowed lane crossing traffic density threshold and the elevated mainline congestion density determination threshold in step (4) is specifically shown in the following equations (3) and (4): (3); (4); In formula (3) For the first The optimization results for allowing lane crossings based on traffic density thresholds. f 1 is the correction factor. This is used to determine the frequency of events where a driver violates route planning information and enters the lane with the lowest traffic density, even though the conditions for crossing lanes are not met. To determine the frequency of events where the driver has the conditions to cross lanes but fails to change lanes and enters the lane with the least traffic density; in equation (4) For the first The optimized results of the congestion density determination threshold. f 2 is the correction factor. To determine the frequency of events where the next segment of the elevated mainline is congested but drivers fail to leave the elevated road ahead of schedule according to their planned routes. This is used to determine the frequency of events where the system determines that the next segment of the elevated main line is not congested, but the driver leaves the elevated road ahead of time and finally arrives at the destination that was pre-set on the navigation map.

[0014] Compared with the prior art, the beneficial effects of the present invention are: Unlike previous elevated highway traffic management measures that only focused on signal control for one or more ramps and used conventional navigation technology based on partial floating car data for vehicle path guidance, this invention addresses the challenge of comprehensively monitoring traffic flow at the lane dimensions of the elevated mainline and entrance / exit ramps, and accurately planning and guiding vehicles along lanes. This invention utilizes a drone equipped with a high-definition wide-angle camera and millimeter-wave radar to accurately identify and monitor traffic flow at the lane dimensions of the elevated mainline and entrance / exit ramps, outputting lane-dimensional traffic evaluation parameters that can be used to assess road conditions.

[0015] 1. This invention utilizes drones equipped with high-definition wide-angle cameras and millimeter-wave radar deployed along elevated highways to achieve full-coverage monitoring of traffic flow on the main road and entrance / exit ramps. It also enables precise identification and analysis of traffic density along the main road lanes and queue lengths along the entrance / exit ramps, providing a data foundation for precise lane-based vehicle planning and guidance. Integrating the advantages of drone monitoring technology will help fully exploit the spatiotemporal resource potential of elevated roads, comprehensively improve their traffic capacity, and effectively alleviate the frequency and impact of elevated road congestion.

[0016] 2. This invention provides corresponding lane-dimensional path planning guidance schemes based on three different states of the target vehicle: entering the entrance ramp, driving on the elevated main line, and entering the exit ramp, combined with the traffic flow status of the elevated main line and the entrance / exit ramps. This improves the accuracy of vehicle path planning guidance and maximizes the utilization rate of road space-time resources.

[0017] 3. In the process of route planning and guidance, the present invention can further utilize navigation maps to continuously track and monitor the driving trajectory of the target vehicle, and further verify the system threshold parameters according to the driver's compliance with the planned route, so as to avoid subjective errors caused by manually setting threshold parameters based on experience, and ensure that the system's route planning mechanism meets the actual road conditions and traffic needs in the long term. Attached Figure Description

[0018] Figure 1 This is a flowchart of the method of the present invention.

[0019] Figure 2 This is a schematic diagram illustrating the deployment and monitoring range of the UAV in this invention.

[0020] Figure 3 This is a schematic diagram of lane zoning in this invention.

[0021] Figure 4 This is a schematic diagram of lane parameter calibration and the lane to which the vehicle belongs in this invention.

[0022] Figure 5 This is a flowchart illustrating the single-vehicle trajectory planning and guidance process based on the congestion status of elevated lanes in this invention.

[0023] Figure 6 This is a schematic diagram of the guidance path for the target vehicle to enter the elevated road (entrance ramp congestion) in this invention.

[0024] Figure 7 This is a schematic diagram of the guidance path for the target vehicle to enter the elevated road (with no congestion at the entrance ramp) in this invention.

[0025] Figure 8 This is a schematic diagram of the guidance path for the target vehicle to travel on the main line (next segment congestion) in this invention.

[0026] Figure 9 This is a schematic diagram of the guidance path for the target vehicle to travel on the main line in this invention (the next segment is not congested and does not have the conditions to cross lanes).

[0027] Figure 10 This is a schematic diagram of the guidance path for the target vehicle to travel on the main line in this invention (the next segment is not congested and has the conditions to cross the lane).

[0028] Figure 11 This is a schematic diagram of the guidance path for the target vehicle to leave the elevated road (where the exit ramp is congested and the next section is also congested) in this invention.

[0029] Figure 12 This is a schematic diagram of the guidance path for the target vehicle to leave the elevated road (where the exit ramp is congested but the next section is not congested) in this invention.

[0030] Figure 13This is a schematic diagram of the guidance path for the target vehicle to leave the elevated road (without congestion at the exit ramp) in this invention.

[0031] Figure 14 This is a flowchart of the elevated lane-dimensional path guidance monitoring and early warning and system parameter dynamic optimization mechanism in this invention. Detailed Implementation

[0032] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0033] The following is combined Figures 1 to 14 The present invention will be described in further detail below.

[0034] like Figure 1 As shown, drones equipped with high-definition wide-angle cameras and millimeter-wave radar accurately monitor vehicle location information in the lane dimensions of the elevated mainline and entrance / exit ramps. Based on GIS maps, the location of each lane in each segment of the elevated mainline and each lane in the entrance / exit ramps is marked. A corresponding binding relationship is established based on vehicle and lane coordinate information, and further combined with lane feature attribute information to determine the traffic flow density of each lane in each segment of the elevated mainline. K mn Queue length relative to entrance / exit ramp lane dimensions Q 出ij , Q 入ij The calculation and judgment of their respective thresholds for congestion determination on elevated main lines are performed. K b Maximum design queue length of entrance and exit ramps L i出max , L i入max The system determines the congestion status of the elevated mainline and entrance / exit ramps based on the relative sizes of the ramps. If, at some point in the future, the system determines that the elevated mainline or entrance / exit ramps are congested, it will guide subsequent vehicles to implement path planning strategies based on the different congestion locations of the entrance / exit ramps and the elevated mainline, such as delaying entry onto the elevated road, delaying exit from the elevated road, or exiting the elevated road earlier. If the system determines that the corresponding entrance / exit ramps or the elevated mainline are not congested, it will guide the target vehicles to enter the lane with the shortest queue on the entrance / exit ramps or the lane with the lowest traffic density on the elevated mainline (if entering the lane with the lowest traffic density requires crossing other lanes, it must ensure that the traffic density of the crossed lane does not exceed the allowed crossing lane traffic density threshold). K aAfter route guidance is completed, the driving trajectory of the target vehicle can be further monitored through the navigation map. If the driver does not follow the planned route, a warning message can be sent to the driver through the navigation map to remind them to follow the planned route. If the driver still does not make corresponding route adjustments after receiving the warning message, it can be considered that the current recommended route does not meet the driver's travel needs, and this information will be retained for use in setting the traffic density threshold for allowed lane crossings. K a Threshold for determining congestion density on elevated main lines K b Adaptive parameter verification based on the rate of change of deviation is performed to ensure that the system's path planning mechanism meets the actual traffic needs of road conditions in the long term.

[0035] 1. Establish a vehicle traffic status recognition system for elevated lanes based on drone monitoring. like Figure 2 As shown, this system uses drones equipped with high-definition wide-angle cameras and millimeter-wave radar as monitoring equipment to accurately monitor the traffic flow status of the elevated mainline and entrance / exit ramps. The drones are deployed using a "unit-based zoning + overlapping coverage" principle, with one drone assigned to each 1-kilometer stretch of the elevated mainline, each entrance / exit ramp, and the mainline-ramp merging triangle as an independent monitoring unit for fixed-point hovering monitoring. The drone's flight altitude on the mainline is... H The drones' flight altitude is controlled between 80 and 100 meters, with a horizontal coverage radius D of no less than 600 meters. Adjacent drone monitoring units must have at least a 50-meter overlap to avoid blind spots, enabling real-time monitoring of traffic flow in both directions within each monitoring unit of the elevated mainline. For ramp drones, the flight altitude is controlled between 40 and 60 meters, focusing on ramp lanes and merging areas, ensuring coverage of ramp lanes and a 100-meter range connecting to the mainline. For any missed areas at the intersection of ramps and the mainline, supplementary drones will be used to fill in the blind spots. To ensure power supply for the drones, one drone battery swapping station will be set up every 3 kilometers along the elevated line, utilizing under-bridge space and roadside parking lots. Each station will be equipped with 2-3 automatic battery swapping cabinets, supporting autonomous drone return for battery swapping. A backup drone parking area will also be provided, equipped with 2-3 fully charged drones to handle drone rotation and unexpected malfunctions. When the drone has 10 minutes of flight time remaining, it automatically triggers a return-to-home battery swap command. At the same time, a backup drone is dispatched to take off from the battery swap station and arrive at the detection area before the original drone returns, so as to achieve seamless drone rotation and ensure the continuity of traffic flow monitoring.

[0036] 2. Construct a method for recognizing the traffic flow status of elevated lanes with second-level dynamic analysis. like Figure 3As shown, based on the GIS map and the spatial distribution of functional units of the elevated line, the elevated main line is divided into several segments according to the exit ramp locations. Each single lane of the main line segment and each single lane of the entrance / exit ramp is treated as an independent calculation and analysis unit, and each lane is uniquely labeled using two-dimensional coordinates under a unified coordinate system. The drone transmits the two-dimensional coordinate information of vehicles in each segment of the elevated main line and the entrance / exit ramps to the backend in real time via a 5G private network. Combined with the pre-labeled lane coordinate information, the spatial position binding relationship between each vehicle and the lane is calculated (using the ray method: starting from the target vehicle coordinates, a ray is drawn in any direction, and the number of intersections between the ray and the boundary of each lane is counted. If the number of intersections is odd, the target vehicle is considered to be inside the lane; if the number of intersections is even, the target vehicle is considered to be outside the lane). Figure 4 As shown, target vehicle 1 is in lane 1 of segment A of the elevated mainline, and target vehicle 2 is in lane 2 of entrance ramp A. Further calculations are needed to determine the real-time number of vehicles per lane in each segment of the elevated mainline and at the entrance / exit ramps. X mn and Y ij Based on the length of each segment of the elevated main line L m Average length of vehicle body at entrance and exit ramps L ijc Millimeter-wave radar can achieve vehicle contour recognition and obtain the length of all vehicle bodies. L ijk ,in , k (Vehicle number) i Entrance and exit ramps j Average spacing between queuing vehicles S ij The distance between adjacent vehicles was obtained by means of actual measurement and identification using drones. The average value was taken, and the traffic flow density of the elevated mainline lane was calculated according to the following formulas (1) and (2). K mn Vehicle queue length in lane dimension of entrance and exit ramps Q 出ij , Q 入ij : (1); (2); By comparison K mn , Q 出ij , Q 入ij Congestion density determination threshold K b Maximum designed queue length at entrances and exitsL i出max , L i入max (Relevant parameters are as follows) Figure 4 (As indicated by the calibration) Determine the congestion status of the elevated main line and entrance / exit ramps. If K mn > K b Then it is considered that the elevated main line m Segmentation n The lane is congested; if Q 出ij > L i出max Then it is believed i Exit ramp j The lane is congested; if Q 入ij > L i入max Then it is believed i Entrance ramp j If a lane is congested, the opposite is assumed to indicate that there is no traffic congestion at that location.

[0037] 3. Establish a single-vehicle trajectory planning and guidance system based on the congestion status of elevated lanes. like Figure 5 As shown, based on the driver's travel needs and the traffic flow status of the elevated mainline and entrance / exit ramps, the system considers the traffic congestion status of the elevated entrance ramps, the elevated mainline, and the exit ramps respectively, guiding the driver to choose the optimal travel route (selecting suitable entrance / exit ramps) and the optimal travel lane to maximize the utilization of road space and time resources. The system uses the driver's origin and destination information entered through the navigation map and combines it with the GIS map to obtain the preliminary planned entrance / exit ramp information (i.e., the closest entrance / exit ramp to the origin and destination) and route information for the target vehicle within the elevated area, guiding the target vehicle to the preliminary planned route. Based on three different location states of the target vehicle—approaching an entrance ramp (1-2km away), entering the elevated mainline, or approaching an exit ramp (2-3km away)—and the corresponding real-time traffic conditions, corresponding planned guidance routes are provided. Figures 6 to 13 (Demonstration content: Target vehicle 1 plans to enter the elevated road from entrance ramp A and exit from exit ramp C. Based on the different road conditions encountered by target vehicle 1 on routes A, B, and C, provide corresponding lane-dimensional path planning schemes.) Further details on the above: Scenario 1: When the target vehicle approaches the entrance ramp, obtain the real-time queue length of each lane of the current entrance ramp. Q 入ij and the maximum design queue length of the current entrance ramp L i入max Comparison, if any laneQ 入ij All greater than L i入max If the current entrance ramp is considered congested, the target vehicle will be guided to enter the elevated road from the next entrance ramp (e.g., Figure 6 As shown, if the target vehicle plans to enter the elevated road from entrance ramp A, but is congested at entrance ramp A, the system guides the target vehicle to enter the elevated road from entrance ramp B; otherwise, it assumes the current ramp is clear and guides the target vehicle to enter the entrance ramp from the lane with the shortest queue length (e.g., ...). Figure 7 As shown, there was no traffic congestion at entrance ramp A, and the system guided the target vehicle to enter the elevated road in the lane with the shortest queue length at entrance ramp A.

[0038] Scenario 2: When the target vehicle is on the elevated mainline, obtain the traffic flow density at the lane dimension of the next segment. K mn and the congestion density determination threshold K b Compare, if any lane in the next segment K mn All greater than K b If the next segment is considered congested, the target vehicle will be guided to exit the elevated road at the nearest exit ramp (e.g., Figure 8 As shown, if traffic congestion occurs on the main line in segment C, the system guides the target vehicle to exit the elevated road at exit ramp B. Conversely, if the traffic is smooth in the next segment, the system assumes the target vehicle needs to enter the lane with the lowest traffic density in the next segment. However, to ensure the safety of lane changes and minimize the impact on following vehicles, the system needs to determine whether lane changes require crossing lanes and the traffic density of the lanes crossed. K mn With respect to the threshold for permitted cross-lane traffic density K a The size relationship, if it is necessary to cross lanes and the traffic density of the lanes to be crossed. K mn Greater than K a If the current conditions do not permit lane changing, the target vehicle will be guided to continue along its original path (e.g., ...). Figure 9 As shown, the system determines that lane 1 in segment C has the lowest traffic density in that segment and plans to guide the target vehicle from lane 3 into lane 1, but is limited by the traffic density of lane 2 that needs to be crossed. K C2 Exceeding the allowed lane crossing traffic density threshold K a Therefore, the system determines that the target vehicle needs to remain in its original lane; otherwise, it considers the current conditions for changing lanes to be met and guides the target vehicle to enter the lane with the least traffic density in the next segment (e.g., ...). Figure 10 As shown, the traffic density of lane 2 that needs to be crossed K C2 Traffic density below the allowed lane crossing threshold K a The system guides the target vehicle to cross from lane 3 to lane 2 and enter lane 1. Scenario 3: When the target traffic flow approaches the exit ramp, obtain the real-time queue length of each lane on the current exit ramp. Q 出ij and the current maximum design queue length of the exit ramp L i出max Comparison, if any lane Q 出ij All greater than L i出max If the current exit ramp is deemed congested, the system will continue to determine the traffic density in the lane dimension of the next segment below the elevated main road. K mn Congestion density determination threshold K b The size relationship, if any lane in the next segment K mn All greater than K b If the section below the elevated main road is also congested, then the target vehicle is guided to exit the elevated road at the current exit ramp (e.g., Figure 11 As shown, the target vehicle plans to exit the elevated road from Exit C, but Exit C is currently congested. The system continues to determine whether the target vehicle can be guided to travel along the main line and exit from the next exit ramp, but this is limited by the traffic density of each lane on the elevated main line in section D. K Dn All are greater than the congestion density threshold. K b Therefore, the system determines that the target vehicle should continue to exit the elevated road from Exit C ramp; otherwise, it considers the next segment to be in a smooth state and guides the target vehicle to continue traveling on the elevated mainline and exit the elevated road at the next exit ramp (e.g.). Figure 12 As shown, exit ramp C is congested, while the elevated mainline in section D is clear. Therefore, the target vehicle should be guided to continue traveling on the mainline and exit the elevated road from the next exit ramp. (If there is a queue length at the exit ramp...) Q 出ij Less than or equal to L i出max If the system determines that the current exit ramp is clear, it guides the target vehicle to enter the exit ramp from the lane with the shortest queue length (e.g., ...). Figure 13 As shown, there was no traffic congestion at the C ramp exit, and the system guided the target vehicle to choose the lane with the shortest queue length at the C ramp exit to leave the elevated road. Scenario 4: If the target vehicle is not in any of the above three locations, guide the target vehicle to continue traveling along the pre-planned route.

[0039] 4. Establish a mechanism for monitoring and early warning of elevated lane-based path guidance and dynamic optimization of system parameters. like Figure 14 As shown, to ensure the effectiveness of lane-dimensional route planning guidance for vehicles traveling on elevated roads and to guarantee that the system's threshold parameters consistently meet the actual road conditions and traffic requirements, the system sends lane-dimensional route guidance information to drivers via the navigation map while simultaneously monitoring the target vehicle's trajectory in real time. If the target vehicle's trajectory deviates from the planned route, a warning is sent to the driver via the navigation map, reminding them to follow the planned route. If the driver still does not adjust their vehicle's trajectory to match the planned route, the system determines that the recommended route does not meet the actual road conditions and requires an adaptive parameter optimization algorithm based on the deviation rate to adjust the allowed lane crossing traffic density threshold. K a (Initial value is 75 pcu / km) and congestion density determination threshold K b (The initial value is 60 pcu / km) The two system threshold parameters are corrected as shown in equations (3) and (4) below: (3); (4); In formula (3) For the first The optimization results for allowing lane crossings based on traffic density thresholds. f 1 is the correction factor. This is used to determine the frequency of events where a driver violates route planning information and enters the lane with the lowest traffic density, even though the conditions for crossing lanes are not met. To determine the frequency of events where the driver has the conditions to cross lanes but fails to change lanes and enters the lane with the least traffic density; in equation (4) For the first The optimized results of the congestion density determination threshold. f 2 is the correction factor. To determine the frequency of events where the next segment of the elevated mainline is congested but drivers fail to leave the elevated road ahead of schedule according to their planned routes. This is used to determine the frequency of events where the system determines that the next segment of the elevated main line is not congested, but the driver leaves the elevated road ahead of time and finally arrives at the destination that was pre-set on the navigation map.

[0040] The above description is merely a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A single-vehicle path guidance method combining UAV monitoring along elevated lanes, characterized in that, Includes the following steps: (1) Accurately monitor vehicle information in lane dimension of elevated main line and entrance / exit ramps by using UAVs equipped with high-definition wide-angle cameras and millimeter-wave radar; (2) Based on the GIS map, the positions of each lane of the elevated main line and each lane of the entrance and exit ramps are marked. The corresponding binding relationship is established according to the vehicle and lane coordinate information. The traffic flow density of each lane of the elevated main line and the queuing length of the lane dimension of the entrance and exit ramps are calculated. (3) Based on the navigation start and end point of the target vehicle, obtain the information of the entrance ramp and exit ramp of the vehicle to enter the elevated road by connecting to the GIS map. Compare the information calculated in step (2) with the maximum design queuing length of the entrance and exit ramps, the traffic flow density threshold of the allowed crossing lanes and the congestion density judgment threshold of the elevated main line to guide the target vehicle to the path. (4) The driving trajectory of the target vehicle is continuously monitored through the GIS map. When the driving trajectory is inconsistent with the planned path, the target vehicle is given an early warning. The parameters of the allowed lane crossing traffic density threshold and the elevated main line congestion density judgment threshold are optimized in combination with the driver's compliance with the planned path.

2. The elevated lane dimensional bicycle path guiding method according to claim 1, wherein, The drones are deployed using a unit-based partitioning and overlapping coverage principle. The main line of the elevated highway is divided into 1-kilometer basic monitoring units, and each ramp is an independent monitoring unit. Each monitoring unit is equipped with a drone for fixed-point hovering monitoring, and the monitoring range of drones in adjacent units is guaranteed to have overlapping detection areas.

3. The single-vehicle path guidance method based on elevated lane dimensions combined with UAV monitoring according to claim 1, characterized in that, The high-elevation main line unmanned aerial vehicle flight height H The control is at 80-100 m, the horizontal coverage radius D is not less than 600 m, and the adjacent unit unmanned aerial vehicle monitoring range needs to ensure at least a 50 m detection overlap area. The drones flying over the ramps are kept at an altitude of 40-60m, focusing on the ramp lanes and merging areas to ensure that the monitoring area covers the ramp lanes and a 100m range connecting to the main line. To address any potential omissions at the intersection of ramps and the main line, supplementary inspections will be conducted in these areas using blind spot drones to fill the blind spots detected by the main line drones. 4.The elevated lane dimensional single-vehicle path guidance method with UAV monitoring of claim 1, wherein, The elevated main line is segmented by cutting the elevated main line according to the boundaries of each exit ramp.

5. The elevated carriageway dimensional bicycle path guidance method in conjunction with UAV monitoring according to claim 1, wherein, The formulas for calculating the traffic flow density of each lane in each segment of the elevated mainline and the queue length of lane dimensions at entrance and exit ramps are as follows: （1）； （2）； wherein, K mn is the high-speed main line m segment n lane traffic density, X mn is the high-speed main line m segment n lane real-time vehicle quantity; L m is the high-speed main line m segment length; Q ij is i exit ramp j lane queuing length; Y ij is i exit ramp j lane real-time vehicle quantity; L ijc is i exit ramp j lane vehicle body average length; S ij is i exit ramp j queuing vehicle spacing mean.

6. The single-vehicle path guidance method based on elevated lane dimensions combined with UAV monitoring according to claim 5, characterized in that, The vehicle contour is recognized by using the millimeter wave radar, and the length of the vehicle body is obtained i On-ramp j The length of the vehicle body of all vehicles in the lane L ijk The length of the vehicle body of all vehicles in the lane i On-ramp j The average length of the vehicle body in the lane The average distance between the vehicles in the queue S ij The average distance between the vehicles in the queue is obtained by using the unmanned aerial vehicle to recognize the distance between adjacent vehicles and taking the average.

7. The single-vehicle path guidance method based on elevated lane dimensions combined with UAV monitoring according to claim 1, characterized in that, Step (3) involves guiding the target vehicle to the correct path, including the following situations: Scenario 1: When the target vehicle approaches the entrance ramp, obtain the real-time queue length of each lane of the current entrance ramp. Q 入ij and the maximum design queue length of the current entrance ramp L i入max Comparison, if any lane Q 入ij All greater than L i入max If the current entrance ramp is congested, the target vehicle is guided to enter the elevated road from the next entrance ramp; otherwise, if the current ramp is unobstructed, the target vehicle is guided to enter the entrance ramp from the lane with the shortest queue length. Scenario 2: When the target vehicle is on the elevated mainline, obtain the traffic flow density at the lane dimension of the next segment. K mn and the congestion density determination threshold K b Compare, if any lane in the next segment K mn All greater than K b If the system determines the next lane segment is congested, it will guide the target vehicle to exit the elevated road at the nearest exit ramp. Conversely, if the next lane segment is clear, the system will guide the target vehicle to enter the lane with the lowest traffic density. However, to ensure the safety of lane changes and minimize the impact on following vehicles, the system needs to determine whether lane changes require crossing lanes and the traffic density of the lanes crossed. K mn With respect to the threshold for permitted cross-lane traffic density K a The size relationship, if it is necessary to cross lanes and the traffic density of the lanes to be crossed. K mn Greater than K a If the current conditions for changing lanes are not met, the target vehicle will be guided to continue along its original path. Otherwise, if the conditions for changing lanes are met, the target vehicle will be guided to enter the lane with the lowest traffic density in the next segment. Scenario 3: When the target traffic flow approaches the exit ramp, obtain the real-time queue length of each lane on the current exit ramp. Q 出ij and the current maximum design queue length of the exit ramp L i出max Comparison, if any lane Q 出ij All greater than L i出max If the current exit ramp is deemed congested, the system will continue to determine the traffic density in the lane dimension of the next segment below the elevated main road. K mn Congestion density determination threshold K b The size relationship, if any lane in the next segment K mn All greater than K b If the next section of the elevated mainline is also considered congested, the target vehicle is guided to exit the elevated road at the current exit ramp. Conversely, if the next section is considered uncongested, the target vehicle is guided to continue on the elevated mainline and exit at the next exit ramp. If there is a queue length at the exit ramp... Q 出ij Less than or equal to L i出max If the system determines that the current exit ramp is clear, it will guide the target vehicle to enter the exit ramp from the lane with the shortest queue length. Scenario 4: If the target vehicle is not in any of the above three locations, guide the target vehicle to continue traveling along the pre-planned route.

8. The single-vehicle path guidance method based on elevated lane dimensions combined with UAV monitoring according to claim 7, characterized in that, The system provides corresponding planning and guidance routes for three different location states: 1-2km from the entrance ramp, entering the elevated main line, and 2-3km from the exit ramp, based on the real-time traffic conditions at each location.

9. The single-vehicle path guidance method based on elevated lane dimensions combined with UAV monitoring according to claim 1, characterized in that, In step (4), the parameters for optimizing the threshold for traffic flow density allowed to cross lanes and the threshold for determining congestion density on the elevated main line are shown in equations (3) and (4) below: （3）； （4）； In formula (3) For the first The optimization results for allowing lane crossings based on traffic density thresholds. f 1 is the correction factor. This is used to determine the frequency of events where a driver violates route planning information and enters the lane with the lowest traffic density, even though the conditions for crossing lanes are not met. To determine the frequency of events where the driver has the conditions to cross lanes but fails to change lanes and enters the lane with the least traffic density; in equation (4) For the first The optimization results of the secondary congestion density determination threshold f 2 is the correction factor. To determine the frequency of events where the next segment of the elevated mainline is congested but drivers fail to leave the elevated road ahead of schedule according to their planned routes. This is used to determine the frequency of events where the system determines that the next segment of the elevated main line is not congested, but the driver leaves the elevated road ahead of time and finally arrives at the destination that was pre-set on the navigation map.

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