Self-adaptive speed limit control system and method based on Internet of Vehicles

Abstract

The invention discloses a self-adaptive speed-limiting control system and method based on the Internet of Vehicles, and belongs to the technical field of safe driving, the self-adaptive speed-limiting control system based on the Internet of Vehicles comprises a data acquisition module used for acquiring real-time data of a road where a vehicle is located, and the real-time data comprises a curve radius, visibility, a road surface friction coefficient and a gradient; the cloud platform is used for receiving the real-time data of the data acquisition module, analyzing and processing the real-time data through a preset speed limit logic module and further generating a new speed limit instruction; and the self-adaptive speed limiting control module receives the new speed limiting instruction and performs speed limiting reminding or control on the automatic driving vehicle according to the new speed limiting instruction. The curve radius, the visibility, the road surface friction coefficient and the gradient of the road where the vehicle is located are monitored in real time and logically analyzed, and then the speed limit value meeting the requirement for safe driving of the vehicle is generated.

Description

Technical Field

[0001] The present invention belongs to the technical field of safe driving, and in particular relates to an adaptive speed limit control system and method based on an Internet of Vehicles. Background Art

[0002] In recent years, as awareness of vehicle safety has become increasingly widespread, speed limit signs have been installed on highways across the country. Traditionally, speed limit signs on highways typically set a fixed speed limit, typically 120 kilometers per hour. However, in real-world driving, varying road conditions significantly impact speed safety. These factors include, but are not limited to, curve radius, slope, road slipperiness (i.e., the coefficient of friction), and visibility. Relying solely on traditional, fixed speed limit signs will not allow for flexible adjustment to complex and changing road conditions, hindering effective collision prevention and ensuring highway safety. Therefore, it is crucial to implement more scientific and effective dynamic speed limit measures tailored to varying road conditions. Summary of the Invention

[0003] The purpose of the present invention is to provide an adaptive speed limit control system and method based on the Internet of Vehicles, which generates a speed limit value that meets the safety requirements of the vehicle by real-time monitoring and logical analysis of the curve radius, visibility, road friction coefficient and slope of the road on which the vehicle is located.

[0004] To achieve the above object, the present invention provides the following technical solutions:

[0005] A first object of the present invention is to provide an adaptive speed limit control system based on the Internet of Vehicles, comprising:

[0006] A data acquisition module is used to obtain real-time data of the road on which the vehicle is located, the real-time data including curve radius, visibility, road friction coefficient and slope;

[0007] The cloud platform receives the real-time data from the data acquisition module, analyzes and processes the real-time data through a preset speed limit logic module, and then generates a new speed limit instruction;

[0008] The adaptive speed limit control module receives new speed limit instructions and provides speed limit reminders or controls for the autonomous driving vehicle based on the new speed limit instructions.

[0009] A second object of the present invention is to provide an adaptive speed limit control method based on the Internet of Vehicles, comprising:

[0010] S1. Acquire real-time data of the road on which the vehicle is located, wherein the real-time data includes curve radius, visibility, road friction coefficient, and slope;

[0011] S2. Analyze and process the real-time data using the speed limit logic module, and then generate a new speed limit instruction;

[0012] S3. Provide speed limit reminders or control to the autonomous driving vehicle according to the new speed limit instruction.

[0013] Compared with the prior art, the present invention has the following beneficial effects:

[0014] The present invention first uses multiple high-precision sensors deployed on the vehicle and along the roadside to comprehensively monitor the specific road conditions of the vehicle, including but not limited to key parameters such as curve radius, visibility range, road friction coefficient, and road slope. These sensors accurately capture and transmit real-time data via the 5G network, ensuring data accuracy and timeliness. This monitored real-time data is then transmitted to the speed limit logic module in the cloud platform, which incorporates advanced logic analysis capabilities to perform in-depth and detailed logical processing and analysis of the data. Based on the results of this logic analysis, the cloud platform generates a new set of speed limit instructions that are scientifically sound and effectively address the safety requirements of the current road conditions. Ultimately, these new speed limit instructions are transmitted to the vehicle's autonomous driving system or directly fed back to the driver. The autonomous driving system automatically adjusts the vehicle's speed based on the instructions, while the driver manually decelerates according to the instructions. This ensures safe and stable operation of the vehicle in complex road conditions, significantly improving the vehicle's overall safety performance and effectively reducing the probability of traffic accidents. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 A system block diagram of a preferred embodiment of the present invention;

[0016] Figure 2 This is a first structural diagram of a preferred embodiment of the present invention;

[0017] Figure 3 A second structural diagram of a preferred embodiment of the present invention;

[0018] Figure 4 A third structural diagram of a preferred embodiment of the present invention;

[0019] Figure 5 This is a fourth structural diagram of a preferred embodiment of the present invention;

[0020] Figure 6 Flowchart of a preferred embodiment of the present invention. DETAILED DESCRIPTION

[0021] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0022] Example 1:

[0023] See also Figure 1 , an adaptive speed limit control system based on the Internet of Vehicles, comprising:

[0024] The data acquisition module is used to obtain real-time data on the road the vehicle is on, including curve radius, visibility, road friction coefficient, and slope. Different sections of the road have different curve radius, visibility, road friction coefficient, and slope during driving. Therefore, only by obtaining accurate and real-time curve radius, visibility, road friction coefficient, and slope can a more accurate speed limit be obtained.

[0025] The cloud platform receives the real-time data from the data acquisition module and analyzes and processes the real-time data through a preset speed limit logic module to generate new speed limit instructions. The speed limit logic module is one of the core functions of the cloud platform and is derived from a large number of experimental tests.

[0026] The adaptive speed limit control module receives new speed limit instructions and provides speed limit reminders or controls for the autonomous driving vehicle based on the new speed limit instructions.

[0027] The present invention first utilizes multiple high-precision sensors deployed on the vehicle and along the roadside to comprehensively monitor the specific road conditions, covering key parameters such as curve radius, visibility range, road friction coefficient, and road slope. These sensors accurately capture and transmit real-time data via the 5G network, ensuring data accuracy and timeliness. This real-time data is then transmitted to the speed limit logic module within the cloud platform. This module, equipped with advanced logic analysis capabilities, performs in-depth and detailed logical processing and analysis of the data. Based on the analysis results, the cloud platform generates a new set of scientifically sound speed limit instructions to effectively address the safety requirements of the current road conditions. Ultimately, these new speed limit instructions are transmitted to the vehicle's autonomous driving system or directly fed back to the driver. The autonomous driving system automatically adjusts the vehicle's speed based on the instructions, while the driver is required to manually decelerate according to the instructions. This ensures safe and stable operation of the vehicle in complex road conditions, significantly improving the vehicle's overall safety performance and effectively reducing the probability of traffic accidents.

[0028] In order to better understand the concept of the present invention, the following non-limiting description is given:

[0029] The data acquisition module includes:

[0030] The curve radius acquisition module first obtains image information of the road, then analyzes the image information through image analysis software, and finally obtains the curve radius. The curve radius is one of the key factors affecting vehicle speed. The larger the curve radius, the greater the curvature, and in this case, it is necessary to slow down.

[0031] The visibility acquisition module obtains road visibility through the weather monitor. Visibility is one of the important indicators to ensure the safe operation of vehicles. The lower the visibility, the worse the safety, and vice versa.

[0032] The road friction coefficient acquisition module uses a ground friction coefficient sensor installed on the outer surface of the tire to obtain the road friction coefficient. The road friction coefficient is another important indicator to ensure the safe operation of the vehicle. If the road friction coefficient is too low, the vehicle is prone to slipping.

[0033] The slope acquisition module obtains the slope of the road through the slope sensor. The slope is also one of the key factors affecting the vehicle speed. The greater the slope, the slower the vehicle needs to be driven.

[0034] The curve radius acquisition module includes:

[0035] Roadside cameras, used to obtain two-dimensional images of the road;

[0036] Roadside LiDAR, used to obtain three-dimensional point cloud images of the road;

[0037] A curve radius calculation module is set up on the cloud platform. The cloud platform receives two-dimensional images and three-dimensional point cloud images through an edge computing unit, fuses the two, and calculates the curve radius through the fused data.

[0038] The curve radius acquisition module exchanges data with the cloud platform through the roadside RSU; the road friction coefficient acquisition module and the slope acquisition module exchange data with the cloud platform through the vehicle-mounted OBU; the visibility acquisition module exchanges data with the cloud platform through a wireless communication network or a wired communication network.

[0039] The speed limit logic module includes:

[0040] A first speed limit module generates a first speed limit value based on the curve radius according to the curve radius;

[0041] The second speed limit module generates a second speed limit value based on visibility according to the visibility;

[0042] A third speed limit module generates a third speed limit value based on the road friction coefficient according to the road friction coefficient;

[0043] The fourth speed limit module generates a fourth speed limit value based on the slope according to the slope;

[0044] The priority module is used to set the priority of the four speed limit modules. The higher the priority, the larger the corresponding speed limit value. The speed limit value is the speed at which the standard speed limit is reduced.

[0045] The priorities are from high to low: the second speed limiting module, the third speed limiting module, the first speed limiting module and the fourth speed limiting module.

[0046] The second speed limit is 60 kilometers per hour, the third speed limit is 40 kilometers per hour, the first speed limit is 30 kilometers per hour, and the fourth speed limit is 20 kilometers per hour.

[0047] Example 2: Please refer to Figures 2 to 5 Based on the first embodiment, the specific components of the present invention are described in detail below; wherein, Figure 2 The scene shown is on a straight road. Figure 3 It shows a scene on a winding road. Figure 4 It shows scenes on roads with different road friction coefficients. Figure 5 Shown are scenes on roads with different visibility levels;

[0048] Roadside camera 1 is placed above the roadside pole and uses a high-definition pixel image sensor with a 150° FOV range. It collects the road shape in real time and inputs the road image data to the edge computing unit for calculating the curve radius.

[0049] Roadside LiDAR 2, located above the roadside pole, uses dynamic LiDAR and 256-beam laser scanning to perform 3D scanning of road shape, curve radius, and other information on the roadside. The scanned point cloud data is input into the edge computing unit, which calculates the curve radius or sends it to the cloud platform for further calculation. The unit of curve radius is meter.

[0050] The edge computing unit 3 receives 2D data (road data, vehicle information) transmitted by the roadside camera and 3D road data transmitted by the roadside lidar, fuses the 2D data with the 3D data, constructs a road image model, calculates the curve radius of the road on which the autonomous driving vehicle is located based on the road image model, and transmits the curve radius to the cloud platform, or calculates the curve radius through the cloud platform for the cloud platform to display reminders and control the speed limit display screen and the vehicle 14 (autonomous driving vehicle or non-autonomous driving vehicle);

[0051] The cloud platform 4 receives road condition information transmitted by the data acquisition module, including 1) curve radius data of road curves, 2) road slope data transmitted by the slope sensor, 3) ground friction coefficient data of the current road conditions transmitted by the ground friction coefficient sensor; and 4) current road condition visibility data transmitted by the roadside meteorological device. Based on the comprehensive judgment of the road condition information, the cloud platform 4 adaptively adjusts the vehicle speed limit in real time according to the different road conditions, issues alarms and controls the autonomous vehicle, and better ensures the driving safety of the autonomous vehicle.

[0052] The cloud platform receives the road condition data output parameters abcd and adjusts the speed of the autonomous driving vehicle on the highway on the speed limit display screen according to the road parameter range. The priority of the road parameters affecting the basic speed limit is from high to low, 1-5 levels:

[0053] Level 1: Parameter b (road visibility < set range);

[0054] Level 2: Parameter d (road adhesion coefficient < setting range);

[0055] Level 3: Parameter a (curve radius < setting range);

[0056] Level 4: Parameter c (slope parameter < setting range);

[0057] Level 5: Parameters abcd (parameters ≥ setting range), specifically displaying a logical parameter table; simultaneously issuing a display speed command to the autonomous vehicle controller or the display screen of a non-autonomous vehicle to control the vehicle speed.

[0058] The roadside RSU5 is arranged above the roadside pole, receives the slope information and ground friction coefficient information transmitted by the vehicle-mounted OBU, and transmits the information to the cloud platform. It also sends the command information from the cloud platform to the vehicle-mounted OBU, which is then passed to the vehicle controller for speed limit reminders and vehicle speed control;

[0059] The onboard OBU6 is placed in the cockpit of the autonomous vehicle, receives slope information and ground friction coefficient information, and transmits the information to the roadside RSU. At the same time, it receives command information from the cloud platform transmitted by the roadside RSU.

[0060] The slope sensor 7 is arranged at the bottom of the vehicle and collects the slope information of the road surface on which the vehicle is traveling in real time. A positive slope value represents an uphill road condition, and a negative slope value represents a downhill road condition, and transmits the information to the vehicle OBU;

[0061] The ground friction coefficient sensor 8 is arranged on the edge or outer surface of the tire to collect the friction coefficient between the tire and the road surface on which the autonomous driving vehicle is located in real time, which is used to determine whether the current road surface is dry, wet, or slippery, and transmit it to the on-board OBU;

[0062] The weather monitor 9 is placed above the roadside pole and collects real-time weather information in the area where the vehicle is located, including rain, snow, fog, etc. The main indicator is road visibility. The visibility information is transmitted to the cloud platform for logical judgment of the speed limit control of the autonomous vehicle;

[0063] The vehicle controller 10 is arranged at the bottom of the vehicle and receives the speed limit instruction information of the cloud platform transmitted by the on-board OBU. It compares the speed limit value instruction of the cloud platform with the current speed of the vehicle. If the current speed is greater than the speed limit, the alarm reminder will be sounded and the brake will be controlled to slow down to the speed limit. If the current speed is not greater than the speed limit, the instruction operation will not be performed.

[0064] The alarm reminder 11 is arranged at the front of the vehicle, connected to the vehicle controller, receives the control instruction of the vehicle controller, and issues an alarm to remind the vehicle to limit the speed;

[0065] The brake 12 is arranged at the bottom of the vehicle and is connected to the vehicle controller. It receives control instructions from the vehicle controller, brakes the vehicle, controls the vehicle speed, and limits the vehicle speed.

[0066] The speed limit display screen 13 is arranged above the roadside pole and receives speed limit instruction information from the cloud platform. It can adaptively adjust the speed limit according to the curve radius, slope, road visibility and road friction coefficient of different road conditions, thereby playing the role of displaying the vehicle speed limit.

[0067] The following table 1 and table 2 illustrate a speed limit logic;

[0068] Table 1 shows the speed limit levels and speed limit values for different parameters

[0069]

[0070] Table 2 shows the numerical parameters of different speed limit logics

[0071]

[0072]

[0073] See also Figure 6 , an adaptive speed limit control method based on the Internet of Vehicles, comprising:

[0074] S1. Acquire real-time data of the road on which the vehicle is located, wherein the real-time data includes curve radius, visibility, road friction coefficient, and slope;

[0075] S2. Analyze and process the real-time data using the speed limit logic module, and then generate a new speed limit instruction;

[0076] S3. Provide speed limit reminders or control to the autonomous driving vehicle according to the new speed limit instruction.

[0077] The speed limit logic module includes:

[0078] A first speed limit module generates a first speed limit value based on the curve radius according to the curve radius;

[0079] The second speed limit module generates a second speed limit value based on visibility according to the visibility;

[0080] A third speed limit module generates a third speed limit value based on the road friction coefficient according to the road friction coefficient;

[0081] The fourth speed limit module generates a fourth speed limit value based on the slope according to the slope;

[0082] The priority module is used to set the priority of the four speed limit modules. The higher the priority, the larger the corresponding speed limit value. The speed limit value is the speed at which the standard speed limit is reduced.

[0083] The priorities are from high to low: the second speed limiting module, the third speed limiting module, the first speed limiting module and the fourth speed limiting module.

[0084] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. An adaptive speed limit control system based on the Internet of Vehicles, characterized in that: include: A data acquisition module is used to obtain real-time data of the road on which the vehicle is located, the real-time data including curve radius, visibility, road friction coefficient and slope; The cloud platform receives the real-time data from the data acquisition module, analyzes and processes the real-time data through a preset speed limit logic module, and then generates a new speed limit instruction; The adaptive speed limit control module receives new speed limit instructions and provides speed limit reminders or controls to the autonomous driving vehicle according to the new speed limit instructions.

2. The adaptive speed limit control system based on the Internet of Vehicles according to claim 1 is characterized in that: The data acquisition module includes: A curve radius acquisition module acquires image information of the road and obtains the curve radius through the image information; Visibility acquisition module, which obtains road visibility through weather monitors; A road friction coefficient acquisition module obtains the road friction coefficient through a ground friction coefficient sensor installed on the outer surface of the tire; The slope acquisition module obtains the slope of the road through the slope sensor.

3. The adaptive speed limit control system based on the Internet of Vehicles according to claim 2, characterized in that: The curve radius acquisition module includes: Roadside cameras, used to obtain two-dimensional images of the road; Roadside LiDAR, used to obtain three-dimensional point cloud images of the road; A curve radius calculation module is set up on the cloud platform. The cloud platform receives two-dimensional images and three-dimensional point cloud images through an edge computing unit, fuses the two, and calculates the curve radius through the fused data.

4. The adaptive speed limit control system based on the Internet of Vehicles according to claim 1, characterized in that: The curve radius acquisition module exchanges data with the cloud platform through the roadside RSU; the road friction coefficient acquisition module and the slope acquisition module exchange data with the cloud platform through the vehicle-mounted OBU; the visibility acquisition module exchanges data with the cloud platform through a wireless communication network or a wired communication network.

5. The adaptive speed limit control system based on the Internet of Vehicles according to claim 1, characterized in that: The speed limit logic module includes: A first speed limit module generates a first speed limit value based on the curve radius according to the curve radius; The second speed limit module generates a second speed limit value based on visibility according to the visibility; A third speed limit module generates a third speed limit value based on the road friction coefficient according to the road friction coefficient; The fourth speed limit module generates a fourth speed limit value based on the slope according to the slope; The priority module is used to set the priority of the four speed limit modules. The higher the priority, the larger the corresponding speed limit value. The speed limit value is the speed at which the standard speed limit is reduced.

6. The adaptive speed limit control system based on the Internet of Vehicles according to claim 5, characterized in that: The priorities are from high to low: the second speed limiting module, the third speed limiting module, the first speed limiting module and the fourth speed limiting module.

7. The adaptive speed limit control system based on the Internet of Vehicles according to claim 5, characterized in that: The second speed limit is 60 kilometers per hour, the third speed limit is 40 kilometers per hour, the first speed limit is 30 kilometers per hour, and the fourth speed limit is 20 kilometers per hour.

8. An adaptive speed limit control method based on the Internet of Vehicles, characterized in that: include: S1. Acquire real-time data of the road on which the vehicle is located, wherein the real-time data includes curve radius, visibility, road friction coefficient, and slope; S2. Analyze and process the real-time data using the speed limit logic module, and then generate a new speed limit instruction; S3. Provide speed limit reminders or control to the autonomous driving vehicle according to the new speed limit instruction.

9. The method for adaptive speed limit control based on the Internet of Vehicles according to claim 8, characterized in that: The speed limit logic module includes: A first speed limit module generates a first speed limit value based on the curve radius according to the curve radius; The second speed limit module generates a second speed limit value based on visibility according to the visibility; A third speed limit module generates a third speed limit value based on the road friction coefficient according to the road friction coefficient; The fourth speed limit module generates a fourth speed limit value based on the slope according to the slope; The priority module is used to set the priority of the four speed limit modules. The higher the priority, the larger the corresponding speed limit value. The speed limit value is the speed at which the standard speed limit is reduced.

10. The method for adaptive speed limit control based on the Internet of Vehicles according to claim 9, characterized in that: The priorities are from high to low: the second speed limiting module, the third speed limiting module, the first speed limiting module and the fourth speed limiting module.

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