A fully automatic traffic fault warning method and system based on drone

Abstract

The present invention discloses a fully automatic traffic fault warning method and system based on a drone, comprising: (1) starting a drone equipped with a fault warning sign and hovering at a position F meters behind the faulty vehicle; (2) taking a real-time image of the lane behind the drone through a camera and performing data processing on the image to obtain vehicle position information and lane position information; obtaining the speed of the vehicle in the lane where the faulty vehicle is located in real time through a speed measuring radar installed on the drone; (3) identifying the vehicle closest to the fault warning sign on the lane where the current faulty vehicle is located by comparing the vehicle position information with the lane position information, and calculating the speed recommended value of the vehicle in the lane where the faulty vehicle is located according to the speed corresponding to the vehicle; (4) obtaining the speed recommended value and transmitting it to the fault warning sign for display. The present invention can safely place the warning sign and provide a speed recommended interval for the rear vehicles, thereby improving the safety and efficiency of placing the warning sign when the vehicle fails on the highway.

Description

Technical Field

[0001] The present invention relates to the technical field of safe driving applications, and in particular to a fully automatic traffic fault warning method and system based on an unmanned aerial vehicle. Background Art

[0002] When a vehicle breaks down on a highway, it is often necessary to place a triangular warning sign 150-200 meters behind the vehicle to alert the vehicles behind that the vehicle in front has broken down. The existing traffic warning equipment is usually a spare car warning sign in the trunk of the car. Since the operators are mostly inert and wrong in their operations, and people usually do not place the car warning signs according to regulations in case of emergency and dangerous conditions on site, even if the car warning signs are placed according to regulations, the placement time is very long and the placement speed is slow. During this period, it is very easy to have a secondary car accident, and it is easy to cause the highway to be blocked in the future. Therefore, in order to avoid the danger of secondary accidents that may occur during the manual placement of traffic warning signs, it is necessary to set up an efficient, safe and convenient warning device to provide warnings to vehicles behind the faulty vehicle, and at the same time provide a recommended speed range for vehicles coming from behind, so as to improve the road operation efficiency of the accident section and prevent blockage. Summary of the invention

[0003] Purpose of the invention: In view of the above technical problems, the present invention provides a fully automatic traffic fault warning method based on drones, which can safely place warning signs and provide recommended speed intervals for vehicles coming from behind, thereby improving the safety and efficiency of placing warning signs when a vehicle breaks down on a highway. At the same time, the present invention also provides a fully automatic traffic fault warning system based on drones. When a vehicle breaks down, the intelligent drone can conveniently place safety warning equipment and provide recommended speed intervals for vehicles coming from behind for safe lane changes.

[0004] Technical solution: To solve the above problems, the present invention discloses a fully automatic traffic fault warning method based on a drone, which specifically includes the following steps:

[0005] (1) Starting the UAV and hovering the UAV at a position F meters behind the faulty vehicle; a fault warning sign is installed at the bottom of the UAV;

[0006] (2) Using a camera installed on the drone to capture real-time images of all lanes behind the drone and process the images to obtain vehicle location information and lane location information; using a speed measuring radar installed on the drone to obtain the speed of vehicles in the lane where the faulty vehicle is located in real time;

[0007] (3) By comparing the vehicle position information with the lane position information, it is determined whether there is an oncoming vehicle behind the lane where the faulty vehicle is currently located. If there is an oncoming vehicle, the vehicle closest to the fault warning sign in the lane where the faulty vehicle is currently located is identified; a recommended speed value of the vehicle in the lane where the faulty vehicle is currently located is calculated based on the speed corresponding to the vehicle closest to the fault warning sign; the formula for the recommended speed value is:

[0008]

[0009]

[0010]

[0011] In the formula, v t is the recommended speed; v1 is the operating speed corresponding to the maximum traffic volume; K j is the lane blocking density; v0 is the speed of the vehicle closest to the fault warning sign on the lane where the faulty vehicle is located; L is the distance between the faulty vehicle and the vehicle closest to the fault warning sign on the lane where the faulty vehicle is located; w1 is the driver's intuitive reaction time, w2 is the driver's reaction time, and w3 is the driver's actual operation time; j max represents the vehicle momentum performance; weather = 1 represents sandstorm, haze, rain and snow weather, and weather = 0 represents other weather conditions; t represents the acceleration lane change time; θ represents the lateral angle between the front of the vehicle and the road when the vehicle changes lanes; a represents the width of the vehicle closest to the fault warning sign on the lane where the faulty vehicle is located, and m represents the width of the lane where the faulty vehicle is located;

[0012] (4) Based on the vehicle position information and lane position information, determine whether all lanes except the lane where the faulty vehicle is currently located are occupied. If all lanes are occupied, a warning sign indicates that no passage is allowed. If there is an unoccupied lane, the recommended speed value is transmitted to the fault warning sign display, and the recommended speed and direction displayed on the fault warning sign are used to indicate the vehicles in the lane where the faulty vehicle is currently located.

[0013] Furthermore, the value range of θ in step (3) is:

[0014]

[0015] Where b represents the length of the vehicle closest to the fault warning sign on the lane where the faulty vehicle is located.

[0016] Furthermore, in step (3), the value range of w1 is [0.3, 1.0]; the value range of w2 is [0.2, 0.6]; and the value range of w3 is [2.5, 3.0].

[0017] In addition, the present invention provides a fully automatic traffic fault warning system based on a drone, comprising: a drone, a fault warning sign, and a vehicle information acquisition module;

[0018] The drone is used to hover at a position F meters behind the faulty vehicle when the vehicle breaks down;

[0019] The fault warning sign is installed at the bottom of the drone and is used to warn vehicles in the lane where the faulty vehicle is located and behind the faulty vehicle and to display the recommended speed value and direction;

[0020] The vehicle information acquisition module installed on the drone includes a vehicle speed acquisition module and a vehicle image acquisition and processing module; the vehicle image acquisition and processing module is used to obtain real-time images of all lanes behind the drone and perform data processing on the images to obtain vehicle position information and lane position information; the vehicle speed acquisition module is used to obtain the speed of the vehicle in the lane where the faulty vehicle is located;

[0021] The UAV has a recommended speed generation module, which includes an information acquisition module and a recommended speed calculation module; the information acquisition module is used to receive the vehicle position information, lane position information and vehicle speed information acquired by the vehicle information acquisition module; the recommended speed calculation module is used to compare the vehicle position information with the lane position information, and determine whether there is an oncoming vehicle behind the lane where the current faulty vehicle is located. If there is an oncoming vehicle, the vehicle closest to the fault warning sign on the lane where the current faulty vehicle is located is identified, and the speed recommended value of the vehicle in the lane where the faulty vehicle is located is calculated according to the speed corresponding to the vehicle closest to the fault indicator sign; according to the vehicle position information and the lane position information, it is determined whether all lanes except the lane where the current faulty vehicle is located are occupied. When all lanes are occupied, the warning sign displays "No Passage"; when there is an unoccupied lane, the speed recommendation value is transmitted to the fault warning sign display, and the vehicle in the lane where the faulty vehicle is located is indicated by the recommended speed and direction displayed on the fault warning sign; the specific speed recommendation value calculation formula is:

[0022]

[0023]

[0024]

[0025] In the formula, v t is the recommended speed; v1 is the operating speed corresponding to the maximum traffic volume; K jis the lane blocking density; v0 is the speed of the vehicle closest to the fault warning sign on the lane where the faulty vehicle is located; L is the distance between the faulty vehicle and the vehicle closest to the fault warning sign on the lane where the faulty vehicle is located; w1 is the driver's intuitive reaction time, w2 is the driver's reaction time, and w3 is the driver's actual operation time; j max represents the vehicle momentum performance; weather = 1 represents sandstorm, haze, rain and snow weather, and weather = 0 represents other weather conditions; t represents the acceleration lane change time; θ represents the lateral angle between the front of the vehicle and the road when the vehicle changes lanes; a represents the width of the vehicle closest to the fault warning sign on the lane where the faulty vehicle is located, and m represents the width of the lane where the faulty vehicle is located.

[0026] Furthermore, the fault warning sign is foldable; the vehicle image acquisition and processing module uses a high-definition camera; and the vehicle speed acquisition module uses a millimeter-wave speed measurement radar.

[0027] Beneficial effects: The present invention provides a fully automatic traffic fault warning method based on drones. Compared with the prior art, its significant advantages are: by installing a warning sign and hovering at the warning position, there is no need for manual placement and recovery, which solves the risk of secondary accidents that may occur during the manual placement of traffic warning signs; the Greenhill model is used to build a speed recommendation model to provide a recommended speed range for the rear vehicle for safe lane change. The present invention also provides a fully automatic traffic fault warning system based on drones. Compared with the prior art, its significant advantages are that it warns the vehicles behind the faulty vehicle and provides a recommended speed range and direction. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 Shown is a flow chart of the method of the present invention;

[0029] Figure 2 The figure shows the intelligent drone lane change warning model 1 in the present invention;

[0030] Figure 3 The figure shows the intelligent drone lane change warning model 2 in the present invention;

[0031] Figure 4 The figure shows the intelligent drone lane change warning model 3 in the present invention;

[0032] Figure 5 The figure shows the intelligent UAV lane change warning model 4 in the present invention. DETAILED DESCRIPTION

[0033] The technical solution of the present invention is further described below in conjunction with the accompanying drawings.

[0034] The main reason for the low traffic capacity of the road section in the fault area is the low traffic efficiency of vehicles in the operation area. The present invention mainly takes the road section where the faulty vehicle is located as the basic object, introduces the Greenhill parabola model and the operation efficiency-speed model based on the relationship between traffic capacity, operation efficiency and speed, and comprehensively considers the influence of factors such as the driver, real-time vehicle speed, and section length, and constructs a speed recommendation value calculation model, and then obtains the recommended speed range to improve the vehicle operation efficiency and safety performance of the fault area section. The objective function of the speed recommendation range model of the fault area section is obtained with the Greenhill value model as the basic function, and the relatively optimal speed range is solved.

[0035] like Figure 1 As shown, the fully automatic traffic fault warning method based on drone described in the present invention specifically includes the following steps:

[0036] Step 1: Start the drone and wait for it to fly to 150-200 meters behind the faulty vehicle and keep it in a hovering state.

[0037] Step 2: Use the high-definition camera installed on the drone to capture real-time images of all lanes behind the drone and process the images to obtain vehicle information of all lanes, including the number of vehicles, vehicle location information, and lane location information.

[0038] The speed of vehicles in the lane where the faulty vehicle is located can be obtained in real time by installing a speed measuring radar on the drone.

[0039] Step 3: Compare the real-time vehicle position information with the lane position information to determine whether there is an oncoming vehicle behind the lane where the faulty vehicle is currently located. If there is an oncoming vehicle, identify the vehicle closest to the fault warning sign on the lane where the faulty vehicle is currently located; calculate the recommended speed value and direction of the vehicle on the lane where the faulty vehicle is located based on the speed corresponding to the vehicle closest to the fault warning sign; if there is no oncoming vehicle, do not calculate the recommended speed value.

[0040] Specifically, in the theory of transportation engineering, the relationship between speed, density and flow can be intuitively expressed through mathematical models, such as speed-flow and speed-density models. The speed-flow is a linear relationship, and the speed-density model is a quadratic polynomial relationship. Therefore, based on the Greenhills model, the function calculation of the traffic volume and speed of the accident area section can reflect the relationship between the two variables, and the formula is expressed as:

[0041]

[0042] Where Q represents the traffic volume of the road section; K j is the road block density (pcu / km); v is the vehicle speed (km / h); v f is the free flow speed of the road section (km / h).

[0043] The model expresses the relationship between vehicle speed and traffic volume as a parabola model, that is, a quadratic equation. The parabola has a critical point, which is the maximum traffic volume. Before reaching the maximum value, the speed and flow are positively correlated; after reaching the critical point, the vehicle speed and traffic volume are negatively correlated.

[0044] By simulating at the 85th percentile speed, we can obtain a quadratic equation of traffic volume and vehicle speed, which can determine the operating speed v1 corresponding to the maximum traffic volume on the road section.

[0045]

[0046]

[0047] Where: Q m is the maximum traffic volume (pcu / h); v1 is the operating speed corresponding to the maximum traffic volume (km / h).

[0048] Since the traffic efficiency of the traffic fault area is affected by many factors such as road capacity and vehicle running speed, the specific calculation formula for the recommended running speed is as follows:

[0049]

[0050] In the formula, v t is the recommended speed; K j is the lane blocking density; v0 is the speed of the vehicle closest to the fault warning sign in the lane where the faulty vehicle is located, that is, the first vehicle that can see the fault warning sign; w1 is the driver's intuitive reaction time, w2 is the driver's reaction time, and w3 is the driver's actual operation time; the value range of w1 is [0.3, 1.0]; the value range of w2 is [0.2, 0.6]; the value range of w3 is [2.5, 3.0] max represents the vehicle momentum performance; where:

[0051]

[0052] L represents the distance between the faulty vehicle and the vehicle closest to the fault warning sign on the lane where the faulty vehicle is located. The above calculation formula is based on the speed basic formula Calculate the speed v t , the density K is calculated by the headway formula The headway hd here is replaced by the distance L at which the vehicle stops in the braking distance model, which can give the vehicle the maximum tolerance for driving errors. The final recommended speed v t Depend on Calculated.

[0053] Considering the situation of vehicle lane change, determine the restrictions on the recommended operating speed:

[0054]

[0055] Among them, weather=1 indicates special weather conditions such as sandstorm, haze, rain and snow. Since the visibility is within 100~200m, the recommended speed of the vehicle is limited to 40~60km / s. weather=0 indicates other good weather; t indicates the acceleration lane change time; a is the width of the vehicle closest to the fault warning sign on the lane where the faulty vehicle is located, m indicates the width of the lane where the faulty vehicle is located; F ranges from 150-200 meters; θ indicates the lateral angle between the front of the vehicle and the road when the vehicle changes lanes, such as Figure 5 As shown, the range of θ is:

[0056]

[0057] b represents the length of the vehicle closest to the fault warning sign in the lane where the faulty vehicle is located.

[0058] Step 4: Determine whether all lanes except the lane where the faulty vehicle is located are occupied based on the vehicle position information and lane position information; that is, there is a vehicle in the lane in front of the vehicle closest to the fault warning sign in the lane where the faulty vehicle is located. When all lanes are occupied, the faulty vehicle warning sign will display "No Passing"; when there is an unoccupied lane, the speed recommendation value will be transmitted to the fault warning sign display, and the vehicle in the lane where the faulty vehicle is located will be warned by the recommended speed displayed on the fault warning sign, and the fault warning sign can sound an alarm to remind the vehicles coming from behind.

[0059] Specifically, the fault warning sign is installed under the drone. The fault warning sign and the drone transmit data information through wireless communication. The fault warning sign can be an electronic screen or other device that can display the recommended speed value. After determining that the first vehicle has completed the lane change according to the processed image data, the vehicle closest to the fault warning sign in the lane where the faulty vehicle is located is re-determined at the current moment, and the corresponding recommended speed is calculated according to the speed of the vehicle.

[0060] Step 5: The vehicles in the lane where the faulty vehicle is located travel at the corresponding recommended speed.

[0061] like Figure 2 or Figure 3As shown in the figure, a car M was driving in the leftmost lane of the Beijing-Shanghai Expressway from Huai'an to Yangzhou when a traffic accident suddenly occurred. The driver got off the car and released the drone. The drone flew to 200 meters behind the accident site, hovered in the air, and deployed a fault warning sign. The recommended speed was calculated and displayed on the fault warning sign. The vehicles in the lane where the faulty vehicle was located accelerated to the left or slowed down to the right to change lanes according to the corresponding recommended speed. After the highway traffic police and the tow truck arrived at the scene of the accident for preliminary handling, the driver gave instructions to operate the drone to fold and recycle the warning sign, and then automatically flew back and matched the charging compartment for charging for the next use.

[0062] like Figure 4 As shown, car N was driving in the rightmost lane of the Changshen Expressway from Huai'an to Nanjing. It suddenly encountered rain and snow, causing the road to slip and collide with the guardrail, resulting in a traffic accident. At that time, visibility was less than 200m. For the safety of others and himself, the driver chose to release the fully automatic traffic fault warning method and system based on drones. Due to the rain and snow, the driver selected the IW (Inclement weather) mode of the drone. At this time, the drone will automatically determine that it is special weather. When the environmental visibility is less than 200m, the recommended speed is 40-60km / h. The drone will fly to 200m behind the accident site, hover in the air and deploy a fault warning sign. The vehicles in the lane where the faulty vehicle is located will accelerate to the left or decelerate to the right to change lanes according to the corresponding recommended speed. After the accident is initially handled, the driver will give instructions to operate the drone to fold and recycle the warning sign.

[0063] In addition, the present invention provides a fully automatic traffic fault warning system based on a drone, comprising: a drone, a fault warning sign, and a vehicle information acquisition module.

[0064] The drone is used to hover at a position F meters behind the faulty vehicle when the vehicle breaks down;

[0065] The fault warning sign is installed under the drone and is used to warn vehicles in the lane where the faulty vehicle is located and behind the faulty vehicle and display the recommended speed value;

[0066] The vehicle information acquisition module installed on the drone includes a vehicle speed acquisition module and a vehicle image acquisition and processing module; the vehicle image acquisition and processing module is used to obtain real-time images of all lanes behind the drone and perform data processing on the images to obtain vehicle position information and lane position information; the vehicle speed acquisition module is used to obtain the speed of the vehicle in the lane where the faulty vehicle is located;

[0067] The UAV has a recommended speed generation module, which includes an information acquisition module and a recommended speed calculation module; the information acquisition module is used to receive the vehicle position information, lane position information and vehicle speed information acquired by the vehicle information acquisition module; the recommended speed calculation module is used to compare the vehicle position information with the lane position information, identify the vehicle closest to the fault warning sign on the lane where the current faulty vehicle is located; calculate the speed recommendation value of the vehicle on the lane where the faulty vehicle is located according to the speed corresponding to the vehicle closest to the fault warning sign; determine whether all lanes except the lane where the current faulty vehicle is located are occupied according to the vehicle position information and the lane position information, and when all are occupied, the warning sign displays "No Passage"; when there is an unoccupied lane, transmit the speed recommendation value to the fault warning sign display, and indicate the vehicle on the lane where the faulty vehicle is located through the recommended speed and direction displayed on the fault warning sign; the specific speed recommendation value calculation formula is:

[0068]

[0069]

[0070]

[0071] In the formula, v t is the recommended speed; v1 is the operating speed corresponding to the maximum traffic volume; K j is the lane blocking density; v0 is the speed of the vehicle closest to the fault warning sign on the lane where the faulty vehicle is located; L is the distance between the faulty vehicle and the vehicle closest to the fault warning sign on the lane where the faulty vehicle is located; w1 is the driver's intuitive reaction time, w2 is the driver's reaction time, and w3 is the driver's actual operation time; j max represents the vehicle momentum performance; weather = 1 represents sandstorm, haze, rain and snow weather, and weather = 0 represents other weather conditions; t represents the acceleration lane change time; θ represents the lateral angle between the front of the vehicle and the road when the vehicle changes lanes; a represents the width of the vehicle closest to the fault warning sign on the lane where the faulty vehicle is located, and m represents the width of the lane where the faulty vehicle is located.

Claims

1. A fully automatic traffic fault warning method based on drone, characterized in that: The following steps are involved: (1) Starting the UAV and hovering the UAV at a position F meters behind the faulty vehicle; a fault warning sign is installed at the bottom of the UAV; (2) Using a camera installed on the drone to capture real-time images of all lanes behind the drone and process the images to obtain vehicle position information and lane position information; The speed of the vehicle in the lane where the faulty vehicle is located is obtained in real time by installing a speed measuring radar on the drone; (3) By comparing the vehicle position information with the lane position information, determine whether there is an oncoming vehicle behind the lane where the faulty vehicle is currently located. If there is an oncoming vehicle, identify the vehicle closest to the fault warning sign in the lane where the faulty vehicle is currently located; The recommended speed value of the vehicle in the lane where the faulty vehicle is located is calculated based on the speed corresponding to the vehicle closest to the fault warning sign; the formula for the recommended speed value is: In the formula, v t is the recommended speed; v1 is the operating speed corresponding to the maximum traffic volume; K j is the lane blocking density; v0 is the speed of the vehicle closest to the fault warning sign on the lane where the faulty vehicle is located; L is the distance between the faulty vehicle and the vehicle closest to the fault warning sign on the lane where the faulty vehicle is located; w1 is the driver's intuitive reaction time, w2 is the driver's reaction time, and w3 is the driver's actual operation time; j max represents the vehicle momentum performance; weather = 1 represents sandstorm, haze, rain and snow weather, and weather = 0 represents other weather conditions; t represents the acceleration lane change time; θ represents the lateral angle between the front of the vehicle and the road when the vehicle changes lanes; a represents the width of the vehicle closest to the fault warning sign on the lane where the faulty vehicle is located, and m represents the width of the lane where the faulty vehicle is located; (4) Based on the vehicle position information and lane position information, determine whether all lanes except the lane where the faulty vehicle is currently located are occupied. If all lanes are occupied, a warning sign indicates that no passage is allowed. If there is an unoccupied lane, the recommended speed value is transmitted to the fault warning sign display, and the recommended speed and direction displayed on the fault warning sign are used to indicate the vehicles in the lane where the faulty vehicle is currently located.

2. The fully automatic traffic fault warning method based on drone according to claim 1 is characterized in that: The value range of θ in step (3) is: Where b represents the length of the vehicle closest to the fault warning sign on the lane where the faulty vehicle is located.

3. The fully automatic traffic fault warning method based on drone according to claim 1 is characterized in that: The value range of w1 in step (3) is [0.3, 1.0]; the value range of w2 is [0.2, 0.6]; the value range of w3 is [2.5, 3.0].

4. A fully automatic traffic fault warning system based on drones, characterized in that: include: Drones, fault warning signs, and vehicle information acquisition modules; The drone is used to hover at a position F meters behind the faulty vehicle when the vehicle breaks down; The fault warning sign is installed at the bottom of the drone and is used to warn vehicles in the lane where the faulty vehicle is located and behind the faulty vehicle and display the recommended speed value; The vehicle information acquisition module installed on the drone includes a vehicle speed acquisition module and a vehicle image acquisition and processing module; the vehicle image acquisition and processing module is used to obtain real-time images of all lanes behind the drone and perform data processing on the images to obtain vehicle position information and lane position information; The vehicle speed acquisition module is used to acquire the speed of the vehicle in the lane where the faulty vehicle is located; The drone has a recommended speed generation module, which includes an information acquisition module and a recommended speed calculation module; the information acquisition module is used to receive the vehicle position information, lane position information and vehicle speed information acquired by the vehicle information acquisition module; The recommended speed calculation module is used to compare the vehicle position information with the lane position information to determine whether there is an oncoming vehicle behind the lane where the current faulty vehicle is located. If there is an oncoming vehicle, the vehicle closest to the fault warning sign on the lane where the current faulty vehicle is located is identified, and the recommended speed value of the vehicle in the lane where the faulty vehicle is located is calculated based on the speed corresponding to the vehicle closest to the fault warning sign; According to the vehicle position information and lane position information, it is determined whether all lanes except the lane where the faulty vehicle is currently located are occupied. If all lanes are occupied, the warning sign will display "No Passage"; if there is an unoccupied lane, the recommended speed value is transmitted to the fault warning sign display, and the recommended speed and direction displayed on the fault warning sign are used to indicate the vehicles in the lane where the faulty vehicle is located; the specific speed recommendation value calculation formula is: In the formula, v t is the recommended speed; v1 is the operating speed corresponding to the maximum traffic volume; K j is the lane blocking density; v0 is the speed of the vehicle closest to the fault warning sign on the lane where the faulty vehicle is located; L is the distance between the faulty vehicle and the vehicle closest to the fault warning sign on the lane where the faulty vehicle is located; w1 is the driver's intuitive reaction time, w2 is the driver's reaction time, and w3 is the driver's actual operation time; j max represents the vehicle momentum performance; weather = 1 represents sandstorm, haze, rain and snow weather, and weather = 0 represents other weather conditions; t represents the acceleration lane change time; θ represents the lateral angle between the front of the vehicle and the road when the vehicle changes lanes; a represents the width of the vehicle closest to the fault warning sign on the lane where the faulty vehicle is located, and m represents the width of the lane where the faulty vehicle is located.

5. The fully automatic traffic fault warning system based on drone according to claim 4 is characterized in that: The fault warning sign is foldable; the vehicle image acquisition and processing module uses a high-definition camera; the vehicle speed acquisition module uses a millimeter-wave speed measurement radar.

Images