CN112735137A - Method, device, system and medium for quantitative traffic early warning based on millimeter wave signals - Google Patents
Method, device, system and medium for quantitative traffic early warning based on millimeter wave signals Download PDFInfo
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- CN112735137A CN112735137A CN202110018752.0A CN202110018752A CN112735137A CN 112735137 A CN112735137 A CN 112735137A CN 202110018752 A CN202110018752 A CN 202110018752A CN 112735137 A CN112735137 A CN 112735137A
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0635—Risk analysis of enterprise or organisation activities
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/26—Government or public services
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/052—Detecting movement of traffic to be counted or controlled with provision for determining speed or overspeed
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/056—Detecting movement of traffic to be counted or controlled with provision for distinguishing direction of travel
Abstract
The invention discloses a method, a device, a system and a storage medium for quantitative traffic early warning based on millimeter wave signals, wherein the method comprises the following steps: collecting vehicle information on a target lane through a millimeter wave radar module, wherein the vehicle information comprises a vehicle position, a vehicle speed and a vehicle running direction; according to the collected vehicle information, carrying out quantitative risk prediction calculation on the vehicles in the preset area on the target lane; and outputting corresponding early warning information according to the risk prediction calculation result. According to the embodiment of the invention, the vehicles on the target lane are detected through the millimeter wave radar module, the quantitative risk prediction calculation is carried out on the running vehicles after corresponding vehicle information is collected, the dangerous vehicles can be accurately identified according to the risk prediction calculation result, the early warning information is timely output, the current road surface risks of pedestrians and normal running vehicles are reminded, and the road surface safety is effectively improved.
Description
Technical Field
The invention relates to the technical field of intelligent traffic, in particular to a method, a device and a system for quantitative traffic early warning based on millimeter wave signals and a storage medium.
Background
Along with the continuous improvement of the living standard of people, the conservation quantity of motor vehicles is increased year by year, the contradiction among people, vehicles and roads is increasingly prominent, and the gradually complicated road traffic environment also prompts the intelligent traffic management system to develop towards intellectualization, comprehensiveness, accuracy and real-time, so that reliable and accurate detection data must be relied on to meet the requirement.
The millimeter wave radar has the characteristics of small volume, easy integration and high spatial resolution, and is increasingly applied to the field of intelligent transportation at present to help realize an intelligent traffic management system, however, in the existing intelligent traffic management, simple speed measurement, distance measurement, target tracking and the like are realized only through the millimeter wave radar, and accurate risk early warning cannot be carried out on running vehicles with potential risks on the road surface.
Accordingly, the prior art is yet to be improved and developed.
Disclosure of Invention
In view of the above-mentioned deficiencies of the prior art, the present invention aims to provide a method, an apparatus, a system and a storage medium for quantitative traffic warning based on millimeter wave signals, which aims to solve the problem that accurate numerical risk warning and prompting for vehicles running on a road surface cannot be realized in the prior art.
The technical scheme of the invention is as follows:
a quantitative traffic early warning method based on millimeter wave signals comprises the following steps:
collecting vehicle information on a target lane through a millimeter wave radar module, wherein the vehicle information comprises a vehicle position, a vehicle speed and a vehicle running direction;
according to the collected vehicle information, carrying out quantitative risk prediction calculation on the vehicles in the preset area on the target lane;
and outputting corresponding early warning information according to the risk prediction calculation result.
In the millimeter wave signal-based quantitative traffic early warning method, before the millimeter wave radar module collects the vehicle information on the target lane, the method further includes:
and constructing a risk mesh model for a preset area on the target lane.
In the millimeter wave signal-based quantitative traffic early warning method, the risk prediction calculation for quantifying the vehicles in the preset area on the target lane according to the acquired vehicle information includes:
judging whether the vehicle enters a preset area or not according to the collected vehicle position;
and when the vehicle enters a preset area, performing path risk analysis and speed risk analysis on the vehicle according to the vehicle information and the risk grid model.
In the millimeter wave signal-based quantitative traffic early warning method, when a vehicle enters a preset area, path risk analysis and speed risk analysis are performed according to the vehicle information and the risk grid model, and the method comprises the following steps:
when a vehicle enters a preset area, calculating a corresponding path risk value according to the vehicle position and the vehicle running direction and a risk grid model;
and acquiring the average speed or the real-time speed of the vehicle according to the position and the speed of the vehicle, and dividing the speed risk grade of the current vehicle according to the corresponding average speed threshold or the real-time speed threshold.
In the millimeter wave signal-based quantitative traffic early warning method, the constructing a risk mesh model for a preset area on the target lane includes:
dividing a preset area on the target lane into a plurality of grids;
setting unit risk values of each adjacent grid when a vehicle runs between the adjacent grids;
and constructing a path equation for risk prediction and calculating a path risk value when the vehicle runs according to the unit risk value.
In the millimeter wave signal-based quantitative traffic early warning method, when a vehicle enters a preset area, a corresponding path risk value is calculated according to the vehicle position and the vehicle driving direction according to a risk grid model, and the method specifically includes:
and when the vehicle enters a preset area, calculating a path risk value when the vehicle runs according to the path equation at preset time intervals according to the position and the running direction of the vehicle.
In the millimeter wave signal-based quantitative traffic early warning method, outputting corresponding early warning information according to the risk prediction calculation result includes:
judging whether the vehicle meets a red light early warning condition or an out-of-control early warning condition according to the risk prediction calculation result;
when the early warning condition of the red light is met, controlling the pedestrian lane traffic light to light the red light and the lane traffic light to light the yellow light;
and when the out-of-control early warning condition is met, controlling the pedestrian lane traffic light to light the red light, controlling the lane traffic light to light the red light and outputting voice early warning information.
Another embodiment of the present invention further provides a device for quantitative traffic warning based on millimeter wave signals, the device comprising:
the millimeter wave radar module is used for collecting vehicle information on a target lane, wherein the vehicle information comprises a vehicle position, a vehicle speed and a vehicle running direction;
the risk calculation module is used for carrying out quantitative risk prediction calculation on the vehicles in the preset area on the target lane according to the acquired vehicle information;
and the early warning module is used for outputting corresponding early warning information according to the risk prediction calculation result.
The invention further provides a quantitative traffic early warning system based on millimeter wave signals, which comprises at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the above-described millimeter wave signal-based quantitative traffic warning method.
Another embodiment of the present invention also provides a non-transitory computer-readable storage medium storing computer-executable instructions, which, when executed by one or more processors, may cause the one or more processors to perform the above-mentioned method for quantitative traffic warning based on millimeter-wave signals.
Another embodiment of the present invention also provides a computer program product including a computer program stored on a non-volatile computer-readable storage medium, the computer program including program instructions that, when executed by a processor, cause the processor to execute the above-mentioned millimeter wave signal-based quantitative traffic warning method.
Has the advantages that: compared with the prior art, the method, the device, the system and the storage medium for quantitative traffic early warning based on millimeter wave signals detect vehicles on a target lane through a millimeter wave radar module, quantitative risk prediction calculation is carried out on running vehicles after corresponding vehicle information is collected, dangerous vehicles can be accurately identified according to risk prediction calculation results, early warning information is timely output, current road surface risks of pedestrians and normal running vehicles are reminded, and road surface safety is effectively improved.
Drawings
The invention will be further described with reference to the accompanying drawings and examples, in which:
FIG. 1 is a flowchart of a method for quantitative traffic warning based on millimeter wave signals according to a preferred embodiment of the present invention;
fig. 2 is a flowchart of step S20 in the preferred embodiment of the millimeter wave signal-based quantitative traffic warning method according to the present invention;
fig. 3 is a flowchart of step S22 in the preferred embodiment of the method for quantitatively early warning traffic based on millimeter wave signals according to the present invention;
fig. 4 is a flowchart of steps S101 to S103 in the preferred embodiment of the method for quantitatively early warning traffic based on millimeter wave signals according to the present invention;
FIG. 5 is a flowchart of step S30 in the preferred embodiment of the method for quantitative traffic warning based on millimeter wave signals according to the present invention;
fig. 6 is a schematic diagram of mesh division of a target road in an application embodiment of the millimeter wave signal-based quantitative traffic early warning method provided by the present invention;
fig. 7 is a schematic diagram of risk values of each adjacent grid unit in an application embodiment of the millimeter wave signal-based quantitative traffic early warning method provided by the present invention;
fig. 8 is a schematic functional block diagram of a quantized traffic warning device based on millimeter wave signals according to a preferred embodiment of the present invention;
fig. 9 is a schematic hardware structure diagram of a quantitative traffic warning system based on millimeter wave signals according to a preferred embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and effects of the present invention clearer and clearer, the present invention is described in further detail below. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. Embodiments of the present invention will be described below with reference to the accompanying drawings.
Referring to fig. 1, fig. 1 shows a preferred embodiment of a method for quantitative traffic warning based on millimeter wave signals according to the present invention, which includes the following steps:
and S10, collecting vehicle information on the target lane through the millimeter wave radar module, wherein the vehicle information comprises the vehicle position, the vehicle speed and the vehicle driving direction.
In this embodiment, vehicle information of a target lane is collected by setting up the millimeter wave radar module, and specifically the millimeter wave radar module can include one or more millimeter wave radars and cameras, in order to realize vehicle information collection on the multilane, the millimeter wave radars have advantages such as small as the radar that works in millimeter wave band detection, easy integration and spatial resolution, and can realize accurate multi-target vehicle information tracking collection with the cooperation of high definition digtal camera, in this embodiment can set up the millimeter wave radar module at the intersection, carry out vehicle information collection to the road of four directions simultaneously, gather vehicle position on the target lane in the multi-direction in real time, vehicle speed and vehicle direction of travel, realize accurate, real-time vehicle information collection, provide the data basis of tamping for subsequent traffic early warning. Of course, in other embodiments, pedestrian information in the waiting area for pedestrians beside the target lane can be further collected to cooperate with the vehicle information to perform intelligent traffic scheduling and the like.
And S20, carrying out quantitative risk prediction calculation on the vehicles in the preset area on the target lane according to the collected vehicle information.
In this embodiment, a preset region is set on the target lane according to the detection range of the current millimeter wave radar module, for example, a zebra crossing 500m away from the target lane is set as the preset region, that is, the preset region is within the detection range, so that the millimeter wave radar module can accurately detect vehicle information in the preset region, false early warning caused by inaccurate detection data is avoided, and quantitative risk prediction calculation is performed on vehicles in the preset region according to the acquired vehicle information, so as to realize accurate numerical risk identification on the traveling vehicles, reduce the occurrence probability of traffic accidents as much as possible, and improve the safety of road driving.
Further, before the step S10, the method further includes the steps of:
s100, constructing a risk mesh model for a preset area on the target lane.
In this embodiment, a risk mesh model is constructed in advance for the preset area to be used for subsequent risk prediction calculation, that is, the risk prediction of quantification is performed on the running vehicles on the road surface through the risk mesh model, and the acquired vehicle information is synthesized to realize accurate risk calculation.
Referring to fig. 2, which is a flowchart of step S20 in the millimeter wave signal-based quantitative traffic warning method according to the present invention, as shown in fig. 2, the step S20 includes:
s21, judging whether the vehicle enters a preset area or not according to the collected vehicle position;
and S22, when the vehicle enters a preset area, performing path risk analysis and speed risk analysis on the vehicle according to the vehicle information and the risk grid model.
In this embodiment, when performing risk prediction calculation, it is first determined whether a vehicle enters a preset region according to a vehicle position, and when the vehicle enters the preset region, vehicle path risk analysis and speed risk analysis are respectively performed according to a preset risk grid model and acquired vehicle information, that is, the vehicle in the preset region is subjected to path and speed risk simulation calculation through the risk grid model, and its risk cost is estimated according to a traveling path and a traveling speed of the vehicle, so that the vehicle information acquired through millimeter wave signals is not limited to simple speed and distance measurement, and a traveling vehicle with a potential risk on a current road can be further simulated, calculated and identified, and objective risk information with an accurate value is obtained, but risk judgment by artificial subjective judgment is performed, and more accurate and intelligent traffic management is achieved.
Referring to fig. 3, which is a flowchart of step S22 in the millimeter wave signal-based quantitative traffic warning method according to the present invention, as shown in fig. 3, the step S22 includes:
s221, when the vehicle enters a preset area, calculating a corresponding path risk value according to the vehicle position and the vehicle running direction and a risk grid model;
s222, obtaining the average speed or the real-time speed of the vehicle according to the position and the speed of the vehicle, and dividing the speed risk level of the current vehicle according to the corresponding average speed threshold or the real-time speed threshold.
In the embodiment, after the vehicle enters the preset area, the corresponding path risk value is calculated according to the risk grid model by detecting the driving path of the vehicle, that is, different vehicles can calculate their corresponding path risk values under different driving paths, for example, if the vehicle normally drives along the current lane after entering the preset area, calculating to obtain a first path risk value, changing lanes for multiple times after the vehicle II enters a preset area to obtain a second path risk value, turning around and reversing the vehicle III after the vehicle III enters the preset area to obtain a third path risk value, wherein the first path risk value, the second path risk value and the third path risk value are successively higher, the potential risks of the three vehicles under the three driving paths are sequentially increased, the vehicles with higher path risk values are more prone to traffic accidents, and driving behaviors of the vehicles need to be pre-warned to reduce the accident probability as much as possible.
In this embodiment, not only is the risk calculation performed for the traveling path of the vehicle, but also the speed risk analysis is further performed according to the vehicle speed, specifically, the average speed or the real-time speed of the vehicle is calculated according to the difference of the vehicle positions, so that the speed risk under the position of the vehicle can be reflected, the speed of the vehicle must be obtained in real time to perform the risk analysis to ensure the accurate identification of the vehicle at risk due to the limited braking distance in the area closer to the pedestrian, and the average speed can reflect the overall traveling state better in the area farther from the pedestrian due to the large change in the vehicle speed, for example, taking a preset area as 500m away from the zebra crossing as an example, when the vehicle is detected to be within 100-300m away from the zebra crossing, the average speed of the vehicle is calculated according to the acquired vehicle speed and the vehicle position, and when the vehicle is located within 0-100m away from, the real-time speed of the vehicle is obtained according to the acquired vehicle speed, and the calculation ranges of the average speed and the real-time speed can be flexibly adjusted according to actual needs, which is not limited in the invention.
And an average speed threshold and a real-time speed threshold are correspondingly set for the average speed and the real-time speed, namely when the vehicle is positioned in an average speed area, the speed risk grade of the vehicle is divided after the average speed of the vehicle is compared with the average speed threshold, and when the vehicle is positioned in a real-time speed area, the speed risk grade of the vehicle is divided after the real-time speed of the vehicle is compared with the real-time speed threshold, so that the vehicle speeds at different positions are subjected to targeted speed risk analysis, and an accurate speed risk grade division result is obtained.
Further, please refer to fig. 4, which is a flowchart of step S100 in the millimeter wave signal-based quantitative traffic warning method according to the present invention, and as shown in fig. 4, the step S100 includes:
s101, dividing a preset area on the target lane into a plurality of grids;
s102, setting unit risk values of all adjacent grids when a vehicle runs between the adjacent grids;
s103, constructing a path equation for risk prediction and calculating a path risk value when the vehicle runs according to the unit risk value.
In this embodiment, the risk mesh model building process for path risk calculation is specifically that a preset area on the target lane is divided into a plurality of meshes, for example, the preset area is 500m away from the zebra crossing, the mesh division may be divided averagely, for example, every 50m on each lane in the preset area is a mesh, or may be divided according to distance, for example, every 100m on each lane in the range of 300m away from the zebra crossing is a mesh, every 50m on each lane in the range of 100m away from the zebra crossing is a mesh, every 25m on each lane in the range of 0-100m away from the zebra crossing is a mesh, that is, as the distance from the zebra crossing is closer, the mesh division distance is shorter, so as to adapt to path risk calculation at different distances.
Then, each grid on each lane is numbered to distinguish each area, and a unit risk value of each adjacent grid when the vehicle runs between the adjacent grids is set, specifically, one grid is taken as a starting point, the unit risk value is taken as an initial value, when the vehicle runs from the grid of the starting point to the surrounding adjacent grids, different running paths are represented, such as normal forward running of the same lane, reverse running of the same lane, left/right lane changing, continuous forward running after left/right lane changing, reverse running after left/right lane changing, U-turn, continuous forward running after U-turn, reverse running of cross lanes and the like, so that each adjacent grid has a corresponding unit risk value, the path risk of the vehicle is quantized to the unit risk value of each grid through grid division, and the path risk value when the vehicle runs is calculated according to the unit risk value of each adjacent grid after a path equation for risk prediction is constructed, the path risk estimation during vehicle running is converted into quantitative mathematical calculation through a risk grid model, and more accurate path risk analysis is realized.
Preferably, the step S221 specifically includes:
and when the vehicle enters a preset area, calculating a path risk value when the vehicle runs according to the path equation at preset time intervals according to the position and the running direction of the vehicle.
In this embodiment, when a specific path risk value is calculated after a vehicle enters a preset area, the vehicle entering the preset area is taken as initial time, and the path risk value of the vehicle at the current time can be calculated according to a path equation according to the position of the vehicle and the driving direction of the vehicle, so that the path risk value is updated once at each preset time to obtain the latest path risk analysis result, thereby realizing real-time risk analysis and providing the latest and reliable risk analysis data for intelligent traffic early warning.
And S30, outputting corresponding early warning information according to the risk prediction calculation result.
In the embodiment, after the path risk value and the speed risk level of the vehicle are obtained through risk prediction calculation, the early warning information of the corresponding level is output according to different values and levels to prompt pedestrians and the vehicle that the current road surface has the risk of the corresponding level, so that the pedestrians and the vehicle can take corresponding avoidance measures in advance, the accidents of people collision and vehicle collision are avoided, and the safety of people and vehicles traveling on the road surface is improved.
Specifically referring to fig. 5, which is a flowchart of step S30 in the millimeter wave signal-based quantitative traffic warning method according to the present invention, as shown in fig. 5, the step S30 includes:
s31, judging whether the vehicle meets a red light early warning condition or an out-of-control early warning condition according to the risk prediction calculation result;
s32, when the red light early warning condition is met, controlling the pedestrian lane traffic light to light a red light and the lane traffic light to light a yellow light;
and S33, controlling the pedestrian lane traffic light to light the red light and the lane traffic light to light the red light and outputting voice early warning information when the out-of-control early warning condition is met.
In the embodiment, two early warning systems, a red light early warning system and an out-of-control vehicle early warning system are established in advance, when the vehicle meets the red light early warning condition, the red light early warning system is started, the red light is controlled to be on by the pedestrian lane traffic lights, the yellow light is controlled by the lane traffic lights, and the red light early warning notice can be output to a traffic command center, so that a worker can pay attention to the payment condition of the current road section in real time, when the vehicle meets the out-of-control early warning condition, the red light is controlled to be on by the pedestrian lane traffic lights, the red light is controlled by the lane traffic lights, and voice early warning information is output.
When judging whether the vehicle has the corresponding early warning condition according to the risk prediction calculation result, specifically presetting a corresponding condition range, such as a first risk value, a second risk value, a first speed risk level and a second speed risk level, wherein the second risk value is greater than the second risk value, the second speed risk level is higher than the first speed risk level, and when the path risk value of the vehicle is greater than the first risk value and is less than the second risk value, or the speed risk level of the vehicle is greater than the first speed risk level and is less than the second speed risk level, judging that the red light early warning condition is met; when the path risk value of the vehicle is greater than the second risk value or the speed risk level of the vehicle is greater than the second speed risk level, the condition that the out-of-control early warning condition is met is judged, namely, if one of the path risk value and the speed risk level meets the early warning condition, a corresponding early warning system is started, so that pedestrians and vehicles can obtain reliable traffic early warning signals, processing such as avoidance or warning is carried out in time, vehicle information is acquired through millimeter wave signals, accurate and timely road surface risk early warning is achieved, and potential risks brought by the risky vehicles are eliminated as much as possible.
In order to better understand the processes of path risk analysis and speed risk analysis in the millimeter wave signal-based quantitative traffic early warning method provided by the present invention, the following describes the processes of path risk analysis and speed risk analysis in detail by referring to fig. 6 and 7.
As shown in fig. 6 and 7, firstly, performing mesh division processing on a preset area on a target road, and performing numbering modeling on both lanes and meshes, where in fig. 6, taking the preset area as 500m away from a zebra crossing, two lanes from the right to the left are marked as a1 and a2, and two lanes from the left to the right are marked as B1 and B2, dividing the preset area detectable by a millimeter wave radar module into 10 squares according to the distance close to the zebra crossing, and marking the zebra crossing as mesh 0, where every 100m within the range of 300 + 500m away from the zebra crossing on each lane is a mesh, and 2 meshes (numbers 9 and 10) are provided; every 50m is a grid within the range of 100-300m away from the zebra crossing, and the number of the grids is 4 (the number is 5-8); every 25m in the range of 0-100m from the zebra crossing is a grid, and the number of the grids is 4 (the number is 1-4).
Then, setting unit risk values of each adjacent grid when the vehicle runs among the grids, taking the nine-square grid in fig. 7 as an example, the unit risk values include roads in two running directions, taking the center grid as a starting point, and are 0, and when the vehicle normally runs in the same lane, the unit risk values are 5; when the vehicle runs in the reverse direction in the same lane, the unit risk value is 50; when the vehicle changes lane left/right (fig. 7 shows only the right lane change, i.e., lane change a2 to a1), the unit risk value is 20; when the vehicle continues to proceed after left/right lane change (fig. 7 shows only right lane change a2 to a1), the unit risk value is 25; when the vehicle reverses course left/right and then reverses course (fig. 7 shows only right lane change a2 to a1), the unit risk value is 75; when the vehicle turned around (a2 turned around to B1), the unit risk value was 50; when the vehicle continues to move forward after turning around, the unit risk value is 55; when the vehicle is driving in the wrong direction across the lane, the unit risk value is 100.
Then a corresponding path equation is established,
when entering a millimeter wave radar detection area, recording t as 0, wherein delta t as 0.5s, updating the data every 0.5s, and s is the actual movement risk of the motor vehicle moving at 0-500 m; p is the predicted movement risk for the current grid to move to grid 0 (i.e., zebra crossing); f is a path risk value, namely the sum of the actual movement risk and the predicted movement risk; g is a movement risk of the current grid moving to the next grid, if the square is not changed, G is 0, and the line pressing is a minimum value; h is the estimated cost risk from the current grid to grid 0 (i.e., zebra crossing), such as from grid 8 to grid 0 (i.e., zebra crossing), with an estimated cost risk of H8 x 5 x 40; and F, s and p are cleared when entering the zebra crossing or leaving the preset area.
Then tracking the vehicle in real time, acquiring the position and the driving direction of the vehicle, calculating a path risk value of the vehicle, and judging whether a corresponding early warning system needs to be started according to the obtained path risk value, wherein the minimum value of F is 50, namely, the vehicle enters a measurement range and leaves a normal one-way road, and when the F is more than 50 and less than or equal to 100, the vehicle at least changes the road and does not change the direction twice, or the vehicle enters B1 from A2 and continues to move forwards; when F is more than 100 and less than or equal to 120, entering an alarm preparation system, for example, the vehicle continuously changes lanes and does not change direction for 3 times; when F is larger than 120, entering a red light early warning system, such as a retrograde lane changing; when F is larger than or equal to 150, the vehicle enters an out-of-control early warning system, for example, at least two times of retrograde motion in the grid occur, or the vehicle moves from A2 lane change to B1 to continue to move forward, the driving direction is not changed, namely the vehicle crosses the lane and retrograde motion is performed, so that path risk analysis is realized through path detection of the vehicle, and the corresponding early warning system is started to remind pedestrians and other vehicles to avoid.
Further, aiming at speed risk analysis, when the vehicle is detected to be located within the range of 100-300m (grid 5-grid 8) away from the zebra crossing, the average speed of the vehicle is calculated according to the collected vehicle speed and the vehicle position, a first average speed threshold value of 25m/s and a second average speed threshold value of 30m/s are set, when the traffic lights of the lane are in a red light state, if the average speed of the vehicle within the range is greater than 25m/s, the vehicle enters a red light early warning system, and if the average speed of the vehicle within the range is greater than 30m/s, the vehicle enters an out-of-control early warning system; and when the vehicle is located in the range of 0-100m (grid 1 to grid 4) away from the zebra crossing, the real-time speed of the vehicle is acquired according to the acquired vehicle speed, the real-time speed threshold of the grid 3 to the grid 4 is set to be 20m/s, the real-time speed threshold of the grid 2 is set to be 15m/s, the real-time speed threshold of the grid 1 is set to be 10m/s, when the real-time speed threshold of the corresponding grid is exceeded by 3m/s (for example, the vehicle is located in the grid 4 and the real-time speed is 23m/s), the red light early warning system is entered, when the real-time speed threshold of the corresponding grid is exceeded by 5m/s, the red light early warning system is entered, the corresponding speed early warning threshold is set for different grids, and more.
Furthermore, the working states of pedestrian lane traffic lights and lane traffic lights can be flexibly controlled according to pedestrian information and risk prediction calculation results, for example, when the pedestrian red light is limited, the pedestrians in a pedestrian waiting area are collected, the vehicle states of 0-500m areas on two sides of a road are detected at the same time, if no vehicle exists in the 0-500m areas, the pedestrians enter the area with yellow light to flicker immediately, and then the green lights of the pedestrians are turned on; if vehicles exist in the area of 0-500 meters, the time of the vehicles driving to the zebra crossing is calculated, the red light of the pedestrians enters red light countdown according to the time of the vehicles driving to the zebra crossing, for example, the vehicles need 5s to reach the zebra crossing, and at the moment, the pedestrian red light countdown which is more than 5s is started, so that the pedestrians can cross the road in time after the vehicles normally pass through the zebra crossing, and the waiting time of the pedestrians is shortened; when the vehicle is limited by the red light, if the pedestrian information is not collected, the time of the vehicle entering the zebra crossing area is predicted according to the path prediction of the vehicle, the red light time of the vehicle is shortened according to the predicted time, or the green light of the vehicle is turned on immediately before the vehicle stops on the zebra crossing, so that the waiting time of the vehicle is shortened.
It should be noted that, a certain order does not necessarily exist between the above steps, and those skilled in the art can understand, according to the description of the embodiments of the present invention, that in different embodiments, the above steps may have different execution orders, that is, may be executed in parallel, may also be executed interchangeably, and the like.
Another embodiment of the present invention provides a quantized traffic early warning device based on millimeter wave signals, as shown in fig. 8, the device 1 includes:
the millimeter wave radar module 11 is configured to collect vehicle information on a target lane, where the vehicle information includes a vehicle position, a vehicle speed, and a vehicle traveling direction;
the risk calculation module 12 is configured to perform quantitative risk prediction calculation on vehicles in a preset area on the target lane according to the acquired vehicle information;
and the early warning module 13 is used for outputting corresponding early warning information according to the risk prediction calculation result.
The millimeter wave radar module 11, the risk calculation module 12, and the early warning module 13 are connected in sequence, and for the specific implementation, reference is made to the corresponding method embodiment described above, which is not described herein again.
Another embodiment of the present invention provides a quantitative traffic warning system based on millimeter wave signals, as shown in fig. 9, the system 10 includes:
one or more processors 110 and a memory 120, where one processor 110 is illustrated in fig. 9, the processor 110 and the memory 120 may be connected by a bus or other means, and fig. 9 illustrates a connection by a bus as an example.
The memory 120, which is a non-volatile computer-readable storage medium, may be used to store non-volatile software programs, non-volatile computer-executable programs, and modules, such as program instructions corresponding to the millimeter wave signal-based quantitative traffic warning method in the embodiment of the present invention. The processor 110 executes various functional applications and data processing of the system 10 by executing nonvolatile software programs, instructions and units stored in the memory 120, that is, implements the millimeter wave signal-based quantitative traffic warning method in the above method embodiments.
The memory 120 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the system 10, and the like. Further, the memory 120 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some embodiments, memory 120 optionally includes memory located remotely from processor 110, which may be connected to system 10 via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
One or more units are stored in the memory 120, and when executed by the one or more processors 110, perform the millimeter wave signal-based quantitative traffic warning method in any of the above-described method embodiments, for example, performing the above-described method steps S10 to S30 in fig. 1.
Embodiments of the present invention provide a non-transitory computer-readable storage medium storing computer-executable instructions for execution by one or more processors, for example, to perform method steps S10-S30 of fig. 1 described above.
By way of example, non-volatile storage media can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), electrically erasable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM), which acts as external cache memory. By way of illustration and not limitation, RAM is available in many forms such as Synchronous RAM (SRAM), dynamic RAM, (DRAM), Synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), Enhanced SDRAM (ESDRAM), Synchlink DRAM (SLDRAM), and Direct Rambus RAM (DRRAM). The disclosed memory components or memory of the operating environment described herein are intended to comprise one or more of these and/or any other suitable types of memory.
Another embodiment of the present invention provides a computer program product, which includes a computer program stored on a non-volatile computer-readable storage medium, the computer program including program instructions, which, when executed by a processor, cause the processor to execute the method for quantitative traffic warning based on millimeter wave signals of the above-mentioned method embodiment. For example, the method steps S10 to S30 in fig. 1 described above are performed.
In summary, in the millimeter wave signal-based quantitative traffic early warning method, apparatus, system and storage medium disclosed in the present invention, the method includes: collecting vehicle information on a target lane through a millimeter wave radar module, wherein the vehicle information comprises a vehicle position, a vehicle speed and a vehicle running direction; according to the collected vehicle information, carrying out quantitative risk prediction calculation on the vehicles in the preset area on the target lane; and outputting corresponding early warning information according to the risk prediction calculation result. According to the embodiment of the invention, the vehicles on the target lane are detected through the millimeter wave radar module, the quantitative risk prediction calculation is carried out on the running vehicles after corresponding vehicle information is collected, the dangerous vehicles can be accurately identified according to the risk prediction calculation result, the early warning information is timely output, the current road surface risks of pedestrians and normal running vehicles are reminded, and the road surface safety is effectively improved.
The above-described embodiments are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the scheme of the embodiment.
Through the above description of the embodiments, those skilled in the art will clearly understand that the embodiments may be implemented by software plus a general hardware platform, and may also be implemented by hardware. With this in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer electronic device (which may be a personal computer, a server, or a network electronic device, etc.) to execute the methods of the various embodiments or some parts of the embodiments.
Conditional language such as "can," "might," or "may" is generally intended to convey that a particular embodiment can include (yet other embodiments do not include) particular features, elements, and/or operations, among others, unless specifically stated otherwise or otherwise understood within the context as used. Thus, such conditional language is also generally intended to imply that features, elements, and/or operations are in any way required for one or more embodiments or that one or more embodiments must include logic for deciding, with or without input or prompting, whether such features, elements, and/or operations are included or are to be performed in any particular embodiment.
What has been described herein in the specification and drawings includes examples of a method, apparatus, system, and storage medium capable of providing a quantitative traffic warning based on a millimeter wave signal. It will, of course, not be possible to describe every conceivable combination of components and/or methodologies for purposes of describing the various features of the disclosure, but it can be appreciated that many further combinations and permutations of the disclosed features are possible. It is therefore evident that various modifications can be made to the disclosure without departing from the scope or spirit thereof. In addition, or in the alternative, other embodiments of the disclosure may be apparent from consideration of the specification and drawings and from practice of the disclosure as presented herein. It is intended that the examples set forth in this specification and the drawings be considered in all respects as illustrative and not restrictive. Although specific terms are employed herein, they are used in a generic and descriptive sense only and not for purposes of limitation.
Claims (10)
1. A quantitative traffic early warning method based on millimeter wave signals is characterized by comprising the following steps:
collecting vehicle information on a target lane through a millimeter wave radar module, wherein the vehicle information comprises a vehicle position, a vehicle speed and a vehicle running direction;
according to the collected vehicle information, carrying out quantitative risk prediction calculation on the vehicles in the preset area on the target lane;
and outputting corresponding early warning information according to the risk prediction calculation result.
2. The millimeter wave signal-based quantitative traffic early warning method according to claim 1, wherein before the millimeter wave radar module collects the vehicle information on the target lane, the method further comprises:
and constructing a risk mesh model for a preset area on the target lane.
3. The millimeter wave signal-based quantitative traffic early warning method according to claim 2, wherein the risk prediction calculation for quantifying vehicles in a preset area on the target lane according to the collected vehicle information comprises:
judging whether the vehicle enters a preset area or not according to the collected vehicle position;
and when the vehicle enters a preset area, performing path risk analysis and speed risk analysis on the vehicle according to the vehicle information and the risk grid model.
4. The quantitative traffic early warning method based on millimeter wave signals according to claim 3, wherein when a vehicle enters a preset area, path risk analysis and speed risk analysis are performed according to the vehicle information and a risk mesh model, and the method comprises the following steps:
when a vehicle enters a preset area, calculating a corresponding path risk value according to the vehicle position and the vehicle running direction and a risk grid model;
and acquiring the average speed or the real-time speed of the vehicle according to the position and the speed of the vehicle, and dividing the speed risk grade of the current vehicle according to the corresponding average speed threshold or the real-time speed threshold.
5. The millimeter wave signal-based quantitative traffic early warning method according to claim 4, wherein the constructing a risk mesh model for a preset area on the target lane comprises:
dividing a preset area on the target lane into a plurality of grids;
setting unit risk values of each adjacent grid when a vehicle runs between the adjacent grids;
and constructing a path equation for risk prediction and calculating a path risk value when the vehicle runs according to the unit risk value.
6. The quantitative traffic early warning method based on millimeter wave signals according to claim 5, wherein when a vehicle enters a preset area, the corresponding path risk value is calculated according to the vehicle position and the vehicle driving direction according to a risk grid model, and the method specifically comprises the following steps:
and when the vehicle enters a preset area, calculating a path risk value when the vehicle runs according to the path equation at preset time intervals according to the position and the running direction of the vehicle.
7. The millimeter wave signal-based quantitative traffic early warning method according to claim 1, wherein the outputting of the corresponding early warning information according to the risk prediction calculation result comprises:
judging whether the vehicle meets a red light early warning condition or an out-of-control early warning condition according to the risk prediction calculation result;
when the early warning condition of the red light is met, controlling the pedestrian lane traffic light to light the red light and the lane traffic light to light the yellow light;
and when the out-of-control early warning condition is met, controlling the pedestrian lane traffic light to light the red light, controlling the lane traffic light to light the red light and outputting voice early warning information.
8. A quantized traffic early warning device based on millimeter wave signals, the device comprising:
the millimeter wave radar module is used for collecting vehicle information on a target lane, wherein the vehicle information comprises a vehicle position, a vehicle speed and a vehicle running direction;
the risk calculation module is used for carrying out quantitative risk prediction calculation on the vehicles in the preset area on the target lane according to the acquired vehicle information;
and the early warning module is used for outputting corresponding early warning information according to the risk prediction calculation result.
9. A quantized traffic early warning system based on millimeter wave signals, characterized in that the system comprises at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the millimeter wave signal based quantitative traffic warning method of any one of claims 1 to 7.
10. A non-transitory computer-readable storage medium storing computer-executable instructions that, when executed by one or more processors, cause the one or more processors to perform the millimeter wave signal based quantitative traffic warning method of any one of claims 1 to 7.
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