Active driving safety information push system based on vehicle-road cooperative technology

Abstract

The present invention relates to the field of vehicle safety technology, and specifically to a driving safety information active push system based on vehicle-road cooperative technology, including a braking analysis module, a risk positioning module and a push control module. The braking analysis module performs independent analysis on a single vehicle, and records the analyzed single vehicle as a target vehicle, analyzes the data affecting the braking ability of the target vehicle, and calculates a braking impact value reflecting the braking ability of the target vehicle. The braking impact value can be used to effectively judge the strength of the braking ability of the target vehicle. The risk positioning module includes an active upload unit, an on-board identification unit and a fixed identification unit. The active upload unit obtains the risk point data uploaded by the user and the administrator and analyzes and screens the uploaded data to determine the actual risk positioning coordinates. The on-board identification unit and the fixed identification unit respectively analyze the driving data monitored by the vehicle itself and the vehicle data monitored by the monitoring equipment to determine the actual risk positioning coordinates.

Description

Technical Field

[0001] The present invention relates to the field of vehicle safety technology, and in particular to a system for actively pushing driving safety information based on vehicle-road collaborative technology. Background Art

[0002] Vehicle-road collaboration technology is a technology that optimizes traffic flow and enables efficient operation of intelligent transportation systems through information exchange and interaction between vehicles and road infrastructure. This technology is based on information and communication technology and realizes real-time data sharing and communication between vehicles and road traffic management centers through interconnection with vehicle equipment. This technology uses on-board sensors, roadside sensors, and communication technologies to collect and transmit information such as vehicle driving status and road conditions in real time. Through data analysis and processing, it provides accurate traffic condition analysis and prediction for traffic management personnel, thereby quickly regulating traffic flow and improving traffic efficiency.

[0003] The active driving safety information push system in the existing technology can push safe driving warning information to vehicles passing through the area according to road congestion and accidents involving vehicles ahead, thereby helping drivers take appropriate measures to avoid risks. However, it is difficult to make targeted warnings based on the vehicle's own braking performance and the distance between vehicles, and it is unable to provide drivers with effective and diverse preventive measures recommendations, resulting in poor actual warning effects and certain defects. Summary of the invention

[0004] In view of the above-mentioned shortcomings of the prior art, the present invention provides an active driving safety information push system based on vehicle-road collaborative technology, which can effectively solve the problem in the prior art that it is difficult to provide vehicles with diversified and targeted warnings based on the vehicle's braking performance and distance.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0006] The present invention provides a driving safety information active push system based on vehicle-road cooperative technology, which at least includes: a braking analysis module, a risk positioning module and a push control module;

[0007] The braking analysis module performs independent analysis on a single vehicle, records the analyzed single vehicle as a target vehicle, performs differential analysis on the data affecting the braking capacity of the target vehicle according to the type of the target vehicle, and calculates the braking impact value reflecting the braking capacity of the target vehicle;

[0008] The risk location module includes an active upload unit, a vehicle identification unit and a fixed identification unit. The active upload unit obtains the risk point data uploaded by users and administrators and analyzes and screens the uploaded data to determine the actual risk location coordinates. The vehicle identification unit obtains the driving data monitored by the vehicle itself and records and analyzes it to identify the risk points and determine the actual risk location coordinates. The fixed identification unit is equipped with speed measuring equipment at both ends of the road to monitor the data of vehicles passing through the road and further analyze and calculate to determine the actual risk location coordinates. The location where the risk occurs on the road is determined by the actual risk location coordinates.

[0009] The push control module includes an early warning push unit and a differentiated push unit. The early warning push unit uniformly pushes early warning information to the vehicles around it according to the actual risk location coordinate position and the road to which it belongs. The differentiated push unit obtains the braking impact value of different vehicles and the distance from the actual risk location coordinate position, analyzes and obtains the early warning impact value used to judge the early warning level, and outputs different early warning recommended control instructions according to the selected early warning level.

[0010] Furthermore, the analysis process of the braking analysis module is as follows:

[0011] Acquire multiple factory data of the target vehicle, including the friction coefficient μ of the brake lining cp , effective area of ​​brake lining S cp , tire rolling resistance level and tire wet road grip level, set a rolling resistance value Gd and a grip value Zd, assign values ​​to the rolling resistance value and the grip value according to the tire rolling resistance level and the tire wet road grip level, the larger the value, the higher the level, classify the target vehicles into types, classify the target vehicles into micro-light vehicles, medium-heavy vehicles, and perform differential analysis according to different types of target vehicles;

[0012] When the target vehicle is a light vehicle, obtain the vehicle's curb weight Number of seats NUM and full load weight Substitute into the formula Calculate the target vehicle’s usage judgment value Pd1, where is a preset weight coefficient, and a preset usage judgment threshold value Pd1′ is set. When the usage judgment value of the target vehicle is less than or equal to the usage judgment threshold value Pd1′, it is judged as a passenger vehicle, and its curb weight is Number of seats NUM, friction coefficient of brake lining μ cp , effective area of ​​brake lining S cp , rolling resistance Gd and grip value Zd are normalized and substituted into the formula Calculate the braking impact value Br of the target vehicle; when the use judgment value of the target vehicle is greater than the use judgment threshold Pd1′, it is judged as a cargo vehicle, and its full load weight Friction coefficient of brake lining μ cp , effective area of ​​brake lining S cp , rolling resistance Gd and grip value Zd are normalized and substituted into the formula Calculate in to obtain the braking impact value Br of the target vehicle, where λ1 and λ2 are both preset constant coefficients;

[0013] When the target vehicle is a medium or heavy vehicle, obtain the fully loaded weight of the target vehicle Fully loaded weight of the target vehicle Friction coefficient of brake lining μ cp , effective area of ​​brake lining S cp , rolling resistance Gd and grip value Zd are normalized and substituted into the formula Calculation is performed to obtain the braking influence value Br of the target vehicle, wherein λ3 is a preset constant coefficient and λ3=λ1+λ2.

[0014] Furthermore, the process of the active uploading unit determining the actual risk location coordinates is as follows:

[0015] Get the risk coordinates uploaded by all users. The risk coordinates are the positioning coordinates of the user's mobile terminal. Set a time range value Δt and a distance range value r0. Set the time when the user uploads the data as t0. Draw a regional circle with the risk coordinate as the center and the distance range value r0 as the radius. Get the number of risk coordinates uploaded within the time interval [t0-Δt, t0] within the regional circle as the risk judgment value n and mark all risk coordinates as judgment coordinates. Set a risk judgment threshold. When the risk judgment value is greater than or equal to the risk judgment threshold, calculate the longitude average a and latitude average b of all judgment coordinates to obtain the center coordinates (a, b). Get the route data of the uploading user when uploading each judgment coordinate and select the overlapping segment as the overlapping route. Determine the nearest point of the center coordinate on the overlapping route, and use the coordinate data of the nearest point as the actual risk positioning coordinates.

[0016] Get the risk coordinates uploaded by the administrator and record them as the actual risk location coordinates.

[0017] Furthermore, the vehicle-mounted identification unit is arranged inside the vehicle, and the risk identification process is as follows:

[0018] Obtain the vehicle's driving speed, vehicle acceleration, and the speed limit of the vehicle's current road section, set a speed limit threshold, record the current road section with a speed limit value greater than the speed limit threshold as a monitoring section, and record and analyze the vehicle's driving speed when the vehicle enters the monitoring section;

[0019] The vehicle speed is recorded regularly and a line graph of the speed change over time is drawn. A monitoring time range ΔT is set. When the vehicle speed is equal to 0, the current time is set as T0. The maximum value of the vehicle acceleration within the time interval [T0-ΔT, T0] is obtained and recorded as the acceleration peak value G. max , intercept the line graph of driving speed variation over time within the time interval [T0, T0-k*ΔT] and calculate the area of ​​the graph enclosed by the line and the time axis and record it as the moving distance S M , where k is the preset rate factor and satisfies k*ΔT greater than or equal to 10 minutes. max ≥G′, S M ≤S′, the vehicle positioning coordinates are marked as the actual risk positioning coordinates.

[0020] Furthermore, the fixed identification unit records the road without forks as the monitoring road, and sets speed measuring devices for monitoring vehicle license plates and speed at both ends of the monitoring road. Vehicles are distinguished according to the vehicle license plates and vehicles entering the monitoring road are recorded as entering vehicles. The speed of the entering vehicle when entering the monitoring road is calculated and recorded as v, which is substituted into the formula t SR =S JC / v is calculated to obtain the estimated time t of the vehicle entering SR , where S JC To monitor the length of the road, when the vehicle enters the road within the time range t SR +Δt SR If the vehicle does not leave the monitored road within 2 hours, the vehicle will be recorded as a problem vehicle, where Δt SR It is half of the average passing time of vehicles in the past 24 hours. When the number of problem vehicles is greater than or equal to 2, the vehicle position coordinates of the problem vehicle that first enters the monitored road are obtained as the actual risk positioning coordinates.

[0021] Furthermore, the warning push unit records all roads to which the actual risk positioning coordinates belong as risk roads, obtains the driving direction of each risk road, sets a warning distance L, and when the risk road is a two-way road, sends warning signals to vehicles within a road range of a distance of L on both sides of the risk road with the actual risk positioning coordinate position as the center point; when the risk road is a one-way road, sends warning signals to vehicles moving toward the actual risk positioning coordinate position and whose distance from the actual risk positioning coordinate position is less than or equal to L.

[0022] Furthermore, the difference push unit early warning control process is specifically as follows:

[0023] All vehicles receiving warning signals are recorded as push vehicles, the vehicle location information of all push vehicles is obtained, and the path distance from the vehicle location of the push vehicle to the actual risk positioning coordinate position is calculated and recorded as L jl , obtain the braking impact value Br of the pushed vehicle, and substitute it into the formula Calculate the warning impact value Where η is a preset constant coefficient, and there are three preset warning thresholds: When the warning impact value Less than or equal to When it is greater than or equal to 0, a level 4 warning signal is generated; when the warning impact value Less than or equal to Greater than or equal to When the warning impact value is Less than or equal to Greater than or equal to When the warning impact value is Greater than or equal to A first-level warning signal is generated.

[0024] Compared with the known prior art, the technical solution provided by the present invention has the following beneficial effects:

[0025] 1. The braking analysis module of the present invention can identify the purpose of a target vehicle as a micro-light vehicle for cargo or passenger transport, and selects different formulas to calculate its braking impact value according to different purposes. Compared with direct calculation without distinction, the result of the differentiated calculation is more in line with the use scenario of the target vehicle during daily use, and the braking impact value calculated by integrating multiple data of the target vehicle can be used to judge the braking ability of the target vehicle. Compared with the analysis of a single data, the braking performance of the vehicle can be more accurately evaluated from the side, and different constant coefficients are given for calculation, so as to facilitate the subsequent quantitative analysis of various types of vehicles.

[0026] 2. The risk location module of the present invention obtains the actual risk location coordinates through various means to realize multi-channel data uploading and intelligent identification. Compared with the fixed-point monitoring mode, it improves the ability to discover risk locations. The push control module can uniformly warn vehicles within a certain range to enhance the driver's vigilance. At the same time, it can send different levels of warning signals to different vehicles in layers according to the vehicle's own braking performance and the distance from the dangerous location, and remind the driver to adopt different degrees of response measures to reduce the overall speed of the traffic flow. Compared with the unified sending of the same instructions, it better reduces the probability of accidents during the unified implementation process, can effectively avoid and reduce accidents caused by sudden braking, so that vehicles passing through dangerous locations can safely and orderly slow down and pass. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0028] Figure 1 It is the overall module block diagram of the present invention. DETAILED DESCRIPTION

[0029] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are 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 creative work are within the scope of protection of the present invention.

[0030] The present invention will be further described below in conjunction with the embodiments.

[0031] See also Figure 1 The active driving safety information push system based on vehicle-road cooperative technology at least includes: a braking analysis module, a risk positioning module and a push control module.

[0032] The braking analysis module performs independent analysis on a single vehicle, records the analyzed single vehicle as the target vehicle, analyzes the data affecting the braking ability of the target vehicle, and calculates the braking impact value reflecting the braking ability of the target vehicle. The braking impact value can be used to effectively judge the strength of the braking ability of the target vehicle.

[0033] The analysis process of the brake analysis module is as follows:

[0034] Acquire multiple factory data of the target vehicle, including the friction coefficient μ of the brake lining cp , effective area of ​​brake lining S cp(a vehicle contains multiple brake pads, and the effective area refers to the sum of multiple brake pads), tire rolling resistance level (from A to G) and tire wet road grip level (from A to G), set a rolling resistance value Gd and a grip value Zd, assign values ​​to the rolling resistance value and the grip value according to the tire rolling resistance level and the tire wet road grip level, the assigned value corresponds to the level, the larger the assigned value, the higher the level (for example, when the tire rolling resistance level is A, the corresponding rolling resistance value is assigned to 7, and when the tire rolling resistance level is G, the corresponding rolling resistance value is assigned to 1), classify the target vehicles into micro-light vehicles and medium-heavy vehicles, and perform differential analysis according to different types of target vehicles. The specific analysis process is as follows:

[0035] When the target vehicle is a light vehicle, obtain the vehicle's curb weight Number of seats NUM and full load weight Substitute into the formula Calculate the target vehicle’s usage judgment value Pd1, where is the preset weight coefficient (average weight of an adult), and a preset usage judgment threshold Pd1′ is set. When the usage judgment value of the target vehicle is less than or equal to the usage judgment threshold Pd1′, it is judged as a passenger vehicle, and its curb weight is Number of seats NUM, friction coefficient of brake lining μ cp , effective area of ​​brake lining S cp , rolling resistance Gd and grip value Zd are normalized and substituted into the formula Calculate the braking impact value Br of the target vehicle; when the use judgment value of the target vehicle is greater than the use judgment threshold Pd1′, it is judged as a cargo vehicle, and its full load weight Friction coefficient of brake lining μ cp , effective area of ​​brake lining S cp , rolling resistance Gd and grip value Zd are normalized and substituted into the formula Calculation is performed to obtain the braking influence value Br of the target vehicle, wherein λ1 and λ2 are both preset constant coefficients. In a specific embodiment, λ1 and λ2 are respectively 1 and 0.5 (adjusting the constant coefficient can make the braking influence value calculation result adaptively adjusted according to the vehicle use, so as to facilitate a unified comparison of the braking performance of vehicles for different uses).

[0036] By identifying the target vehicle as a micro-light vehicle for cargo or passenger purposes, the purpose of the target vehicle can be distinguished, and different formulas are used to calculate its braking impact value according to different purposes. Compared with direct calculation without distinction, the result of differentiated calculation is more in line with the usage scenario of the target vehicle during daily use, because cargo vehicles often require a longer braking distance to stop the vehicle when moving at high speeds than passenger vehicles. Therefore, under the same parameters, a relatively low constant coefficient needs to be given to adjust the calculation results of the braking performance of cargo vehicles to meet the scenario restrictions when they are used.

[0037] It should be noted that the classification of vehicle types and the determination of the friction coefficient of brake linings are based on the GB5763-2008 standard for automobile brake linings. The classification of tire rolling resistance levels and tire wet road grip levels is based on the standardization of tires in the EU tire labeling regulations. Although the size of the effective area of ​​the brake lining will not have a direct impact on the friction, the size of the effective area of ​​the brake lining will affect the loss and heat dissipation of the brake lining during braking, thereby indirectly affecting the friction during continuous braking. The larger the effective area of ​​the brake lining, the better the braking effect.

[0038] When the target vehicle is a medium or heavy vehicle, obtain the fully loaded weight of the target vehicle (When the vehicle is a tractor truck or trailer truck, its tractor gross mass is its fully loaded weight). Friction coefficient of brake lining μ cp , effective area of ​​brake lining S cp , rolling resistance Gd and grip value Zd are normalized and substituted into the formula Calculation is performed to obtain the braking influence value Br of the target vehicle, wherein λ3 is a preset constant coefficient and λ3=λ1+λ2.

[0039] The braking impact value calculated by integrating multiple data of the target vehicle can be used to judge the braking ability of the target vehicle. Compared with the analysis of single data, it can more accurately evaluate the vehicle's braking performance and give different constant coefficients for calculation, so as to facilitate the subsequent quantitative analysis of various types of vehicles.

[0040] The risk location module includes an active uploading unit, a vehicle-mounted identification unit and a fixed identification unit. The active uploading unit obtains the risk point data uploaded by users and administrators and analyzes and screens the uploaded data to determine the actual risk location coordinates. The vehicle-mounted identification unit and the fixed identification unit respectively calculate and analyze the driving data monitored by the vehicle itself and the data monitored by the probe equipment on both sides of the road, identify the risk points and determine the actual risk location coordinates. The actual risk location coordinates are used to determine the location where the risk occurs on the road.

[0041] The process of the active upload unit determining the actual risk location coordinates is as follows:

[0042] Get the risk coordinates uploaded by all users. The risk coordinates are the positioning coordinates of the user's mobile terminal (such as a mobile phone, a car computer, a car GPS positioning device, etc.). Set a time range value Δt and a distance range value r0. Set the time when the user uploads the data as t0. Draw a regional circle with the risk coordinate as the center and the distance range value r0 as the radius. Get the number of risk coordinates uploaded within the time interval [t0-Δt, t0] within the regional circle as the risk judgment value n and record all risk coordinates (including the risk coordinates at the center of the circle) as judgment coordinates. Set a risk judgment threshold. When the risk judgment value is greater than or equal to the risk judgment threshold, calculate the longitude average a and latitude average b of all judgment coordinates to obtain the center coordinates (a, b). Get the route data of the user who uploaded each judgment coordinate when uploading it and select the overlapping segment as the overlapping route. Determine the nearest point of the center coordinate on the overlapping route, and use the coordinate data of the nearest point as the actual risk positioning coordinate (the actual location of the danger on the road can be more accurately determined by calculating the latitude and longitude average values).

[0043] It should be noted that users can actively send risk coordinates to the control center through mobile terminals when a road hazard occurs or is discovered, so that the control center can determine the location of the hazard in a timely manner and send it to other users to reduce further losses;

[0044] Get the risk coordinates uploaded by the administrator and record them as the actual risk location coordinates.

[0045] The vehicle identification unit is installed inside the vehicle, and its risk identification process is as follows:

[0046] Obtain the vehicle's driving speed, vehicle acceleration (forward direction) and the speed limit of the vehicle's current road section, set a speed limit threshold (in a specific embodiment, the speed limit threshold is 60 kilometers per hour), record the current road section with a speed limit value greater than the speed limit threshold as a monitored road section, and record and analyze the vehicle's driving speed when the vehicle enters the monitored road section (by limiting the road section range of data monitoring, the data reliability of the monitored road section can be limited, and the interference of low-speed road driving can be reduced);

[0047] The vehicle speed is recorded regularly and a line graph of the speed change over time is drawn. A monitoring time range ΔT is set. When the vehicle speed is equal to 0, the current time is set as T0. The maximum value of the vehicle acceleration within the time interval [T0-ΔT, T0] is obtained and recorded as the acceleration peak value G. max , intercept the line graph of driving speed variation over time within the time interval [T0, T0-k*ΔT] and calculate the area of ​​the graph enclosed by the line and the time axis and record it as the moving distance S M, where k is the preset rate factor and satisfies k*ΔT greater than or equal to 10 minutes. max ≥G′, S M ≤S′, the vehicle positioning coordinates are marked as the actual risk positioning coordinates.

[0048] By monitoring, recording and analyzing vehicle driving data, vehicle danger situations can be discovered in a timely manner, especially when vehicle danger situations occur in locations without road monitoring. The on-board identification unit can determine whether the vehicle has an abnormal situation that causes it to be abnormally stationary based on the vehicle driving data, thereby avoiding potential risks for other vehicles. This is because no matter what the reason for the vehicle to be abnormally stationary, it will pose a threat to subsequent passing vehicles and need to be avoided.

[0049] The fixed identification unit records the road without forks as the monitoring road. Speed ​​measuring devices for monitoring vehicle license plates and speed are set at both ends of the monitoring road. Vehicles are distinguished according to the vehicle license plates and vehicles entering the monitoring road are recorded as entering vehicles. The speed of the entering vehicle when entering the monitoring road is calculated and recorded as v. Substitute it into the formula t SR =S JC / v is calculated to obtain the estimated time t of the vehicle entering SR , where S JC To monitor the length of the road, when the vehicle enters the road within the time range t SR +Δt SR If the vehicle does not leave the monitored road within 2 hours, the vehicle will be recorded as a problem vehicle, where Δt SR It is half of the average passing time of vehicles in the past 24 hours. When the number of problem vehicles is greater than or equal to 2, the vehicle position coordinates of the problem vehicle that first enters the monitored road are obtained as the actual risk positioning coordinates.

[0050] The push control module includes a warning push unit and a differentiation push unit. The warning push unit uniformly pushes warning information to the vehicles around it according to the actual risk positioning coordinate position, thereby enhancing the driver's vigilance and preventing accidents. The differentiation push unit selects to output different warning recommended control instructions according to the braking impact value of different vehicles and the distance from the actual risk positioning coordinate position, so that the driver can make better avoidance decisions.

[0051] The early warning push unit records all roads to which the actual risk positioning coordinates belong as risk roads, obtains the driving direction of each risk road, sets a warning distance L, and when the risk road is a two-way road, sends early warning signals to vehicles within the road range of a distance L on both sides of the risk road with the actual risk positioning coordinate position as the center point; when the risk road is a one-way road, sends early warning signals to vehicles moving toward the actual risk positioning coordinate position and whose distance from the actual risk positioning coordinate position is less than or equal to L.

[0052] By sending warning signals to vehicles, drivers can be informed of dangerous conditions on the road ahead, thereby increasing their vigilance and observing road conditions, so that they can be prepared to take braking measures at any time, thereby reducing the probability of accidents and avoiding the aggravation of dangerous conditions at the actual risk location coordinates.

[0053] The specific early warning control process of the push unit is as follows:

[0054] All vehicles receiving warning signals are recorded as push vehicles, the vehicle location information of all push vehicles is obtained, and the path distance from the vehicle location of the push vehicle to the actual risk positioning coordinate position is calculated and recorded as L jl , obtain the braking impact value Br of the pushed vehicle, and substitute it into the formula Calculate the warning impact value (The warning impact value decreases with the increase of path distance and increases with the increase of braking performance), where η is a preset constant coefficient, and there are three preset warning threshold values: When the warning impact value Less than or equal to When the warning impact value is greater than or equal to 0, a level 4 warning signal is generated and sent to the user's mobile terminal to remind the driver to prepare to slow down. Less than or equal to Greater than or equal to When the warning impact value is Less than or equal to Greater than or equal to When the warning impact value is Greater than or equal to When the vehicle speed is slow, a first-level warning signal is generated and sent to the user's mobile terminal to remind the driver to slow down immediately.

[0055] By sending different levels of warning signals to different vehicles in layers according to the braking performance of the pushing vehicle itself and the distance from the dangerous location, and reminding the driver to adopt different degrees of response measures to reduce the overall speed of the traffic flow, compared with sending the same command uniformly, such as sending a unified braking command, it can better reduce the probability of accidents during the unified implementation process. Because when multiple vehicles take emergency braking measures uniformly, it can easily cause vehicle rear-end collisions. When vehicles in the traffic flow adopt gradual deceleration, it can effectively avoid and reduce accidents caused by emergency braking, so that vehicles passing through dangerous locations can decelerate safely and orderly.

[0056] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements will not cause the essence of the corresponding technical solutions to deviate from the protection scope of the technical solutions of the embodiments of the present invention.

Claims

1. The driving safety information active push system based on vehicle-road cooperative technology is characterized by: include: Braking analysis module, risk location module and push control module; The braking analysis module performs independent analysis on a single vehicle, records the analyzed single vehicle as a target vehicle, performs differential analysis on the data affecting the braking capacity of the target vehicle according to the type of the target vehicle, and calculates the braking impact value reflecting the braking capacity of the target vehicle; The analysis process of the braking analysis module is as follows: Acquire multiple factory data of the target vehicle, including the friction coefficient μ of the brake lining cp , effective area of ​​brake lining S cp , tire rolling resistance level and tire wet road grip level, set a rolling resistance value Gd and a grip value Zd, assign values ​​to the rolling resistance value and the grip value according to the tire rolling resistance level and the tire wet road grip level, the larger the value, the higher the level, classify the target vehicles into types, classify the target vehicles into micro-light vehicles, medium-heavy vehicles, and perform differential analysis according to different types of target vehicles; When the target vehicle is a light vehicle, obtain the vehicle's curb weight Number of seats NUM and full load weight Substitute into the formula Calculate the target vehicle’s usage judgment value Pd1, where is a preset weight coefficient, and a preset usage judgment threshold value Pd1′ is set. When the usage judgment value of the target vehicle is less than or equal to the usage judgment threshold value Pd1′, it is judged as a passenger vehicle, and its curb weight is Number of seats NUM, friction coefficient of brake lining μ cp , effective area of ​​brake lining S cp , rolling resistance Gd and grip value Zd are normalized and substituted into the formula Calculate the braking impact value Br of the target vehicle; when the use judgment value of the target vehicle is greater than the use judgment threshold Pd1′, it is judged as a cargo vehicle, and its full load weight Friction coefficient of brake lining μ cp , effective area of ​​brake lining S cp , rolling resistance Gd and grip value Zd are normalized and substituted into the formula Calculate in to obtain the braking impact value Br of the target vehicle, where λ1 and λ2 are both preset constant coefficients; When the target vehicle is a medium or heavy vehicle, obtain the fully loaded weight of the target vehicle Fully loaded weight of the target vehicle Friction coefficient of brake lining μ cp , effective area of ​​brake lining S cp , rolling resistance Gd and grip value Zd are normalized and substituted into the formula Calculation is performed to obtain the braking influence value Br of the target vehicle, wherein λ3 is a preset constant coefficient and λ3=λ1+λ2; The risk location module includes an active upload unit, a vehicle identification unit and a fixed identification unit. The active upload unit obtains the risk point data uploaded by users and administrators and analyzes and screens the uploaded data to determine the actual risk location coordinates. The vehicle identification unit obtains the driving data monitored by the vehicle itself and records and analyzes it to identify the risk points and determine the actual risk location coordinates. The fixed identification unit is equipped with speed measuring equipment at both ends of the road to monitor the data of vehicles passing through the road and further analyze and calculate to determine the actual risk location coordinates. The location where the risk occurs on the road is determined by the actual risk location coordinates. The push control module includes an early warning push unit and a differentiated push unit. The early warning push unit uniformly pushes early warning information to the vehicles around it according to the actual risk location coordinate position and the road to which it belongs. The differentiated push unit obtains the braking impact value of different vehicles and the distance from the actual risk location coordinate position, analyzes and obtains the early warning impact value used to judge the early warning level, and outputs different early warning recommended control instructions according to the selected early warning level.

2. The driving safety information active push system based on vehicle-road cooperative technology according to claim 1 is characterized in that: The process of determining the actual risk location coordinates by the active uploading unit is as follows: Get the risk coordinates uploaded by all users. The risk coordinates are the positioning coordinates of the user's mobile terminal. Set a time range value Δt and a distance range value r0. Set the time when the user uploads the data as t0. Draw a regional circle with the risk coordinate as the center and the distance range value r0 as the radius. Get the number of risk coordinates uploaded within the time interval [t0-Δt, t0] within the regional circle as the risk judgment value n and mark all risk coordinates as judgment coordinates. Set a risk judgment threshold. When the risk judgment value is greater than or equal to the risk judgment threshold, calculate the longitude average a and latitude average b of all judgment coordinates to obtain the center coordinates (a, b). Get the route data of the uploading user when uploading each judgment coordinate and select the overlapping segment as the overlapping route. Determine the nearest point of the center coordinate on the overlapping route, and use the coordinate data of the nearest point as the actual risk positioning coordinates. Get the risk coordinates uploaded by the administrator and record them as the actual risk location coordinates.

3. The driving safety information active push system based on vehicle-road cooperative technology according to claim 1 is characterized in that: The vehicle identification unit is set inside the vehicle, and its risk identification process is as follows: Obtain the vehicle's driving speed, vehicle acceleration, and the speed limit of the vehicle's current road section, set a speed limit threshold, record the current road section with a speed limit value greater than the speed limit threshold as a monitoring section, and record and analyze the vehicle's driving speed when the vehicle enters the monitoring section; The vehicle speed is recorded regularly and a line graph of the speed change over time is drawn. A monitoring time range ΔT is set. When the vehicle speed is equal to 0, the current time is set as T0. The maximum value of the vehicle acceleration within the time interval [T0-ΔT, T0] is obtained and recorded as the acceleration peak value G. max , intercept the line graph of driving speed variation over time within the time interval [T0, T0-k*ΔT] and calculate the area of ​​the graph enclosed by the line and the time axis and record it as the moving distance S M , where k is the preset rate factor and satisfies k*ΔT greater than or equal to 10 minutes. max ≥G′, S M ≤S′, the vehicle positioning coordinates are marked as the actual risk positioning coordinates.

4. The driving safety information active push system based on vehicle-road cooperative technology according to claim 1 is characterized in that: The fixed identification unit records a road without a fork as a monitoring road. Speed ​​measuring devices for monitoring vehicle license plates and speeds are set at both ends of the monitoring road. Vehicles are distinguished according to the vehicle license plates and vehicles entering the monitoring road are recorded as entering vehicles. The speed of the entering vehicle when entering the monitoring road is calculated and recorded as v, which is substituted into the formula t SR =S JC / v is calculated to obtain the estimated time t of the vehicle entering SR , where S JC To monitor the length of the road, when the vehicle enters the road within the time range t SR +Δt SR If the vehicle does not leave the monitored road within 2 hours, the vehicle will be recorded as a problem vehicle, where Δt SR It is half of the average passing time of vehicles in the past 24 hours. When the number of problem vehicles is greater than or equal to 2, the vehicle position coordinates of the problem vehicle that first enters the monitored road are obtained as the actual risk positioning coordinates.

5. The driving safety information active push system based on vehicle-road cooperative technology according to claim 1 is characterized in that: The warning push unit records all roads to which the actual risk positioning coordinates belong as risk roads, obtains the driving direction of each risk road, sets a warning distance L, and when the risk road is a two-way road, sends warning signals to vehicles within a road range of a distance L on both sides of the risk road with the actual risk positioning coordinate position as the center point; when the risk road is a one-way road, sends warning signals to vehicles moving toward the actual risk positioning coordinate position and whose distance from the actual risk positioning coordinate position is less than or equal to L.

6. The driving safety information active push system based on vehicle-road cooperative technology according to claim 5 is characterized in that: The difference push unit early warning control process is as follows: All vehicles receiving warning signals are recorded as push vehicles, the vehicle location information of all push vehicles is obtained, and the path distance from the vehicle location of the push vehicle to the actual risk positioning coordinate position is calculated and recorded as L jl , obtain the braking impact value Br of the pushed vehicle, and substitute it into the formula Calculate the warning impact value Where η is a preset constant coefficient, and there are three preset warning thresholds: When the warning impact value Less than or equal to When it is greater than or equal to 0, a level 4 warning signal is generated; when the warning impact value Less than or equal to Greater than or equal to When the warning impact value is Less than or equal to Greater than or equal to When the warning impact value is Greater than or equal to A first-level warning signal is generated.

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