CN115966100B - Driving safety control method and system - Google Patents
Driving safety control method and system Download PDFInfo
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Abstract
The invention discloses a driving safety control method and a driving safety control system, wherein the method comprises the following steps: acquiring the positioning coordinate of the current vehicle at the current moment, and determining whether the vehicle runs on a road or not according to the positioning coordinate and the road coordinate; if yes, acquiring a control strategy preset in the vehicle when the current vehicle speed is greater than a first preset threshold value; when the control strategy is an offline strategy, extracting image data of nearby vehicles from a vehicle data recorder to obtain a first score of the driving level of each nearby vehicle; requesting a driving level second score of each nearby vehicle from the internet of vehicles server according to the identification information when the control strategy is an online strategy; adding the first score and the second score into the score set, and judging whether any one score value is smaller than a second preset threshold value according to each score value in the score set; if yes, a prompt for disengaging from the current driving environment is sent to a driver of the current vehicle. By applying the embodiment of the invention, the running safety risk is reduced.
Description
Technical Field
The invention relates to the technical field of Internet of vehicles, in particular to a driving safety control method and system.
Background
With the popularization of automobiles, especially the continuous improvement of the permeability of new energy automobiles with excellent acceleration performance, more and more automobiles run on roads, the complexity of roads is also higher and higher, and the running safety becomes an important subject.
The invention patent application with the application number of 202011603122.1 discloses a personalized differentiated driving risk evaluation method based on a driving safety event, which comprises the steps of obtaining driving behavior data and obtaining driving risk evaluation scores through a risk evaluation model. Specifically, historical behavior data of other drivers are required to be extracted, driving safety events are extracted according to a preset threshold value, equivalent pairing samples are extracted from a database of normal driving states of the drivers according to the extracted sample capacity, statistical inspection is carried out on the driving behavior data of the drivers in the driving safety events and the behavior data of the normal driving states, the result with obvious statistical difference obtained through inspection is input into a clustering algorithm for classification, risk evaluation indexes are obtained, and driving risk weights of various driving safety events to the drivers are obtained according to the risk evaluation indexes. The method fully considers the individual differences of different drivers in the risks of various driving safety events.
In the prior art, only the driver is subjected to driving risk assessment, so that dangerous driving behaviors of the driver can be avoided, and the influence of dangerous driving behaviors of other vehicles cannot be avoided.
Disclosure of Invention
The invention aims to solve the technical problem of providing a driving safety control method and a driving safety control system so as to reduce the safety risk in the driving process of a vehicle.
The invention solves the technical problems through the following technical scheme:
the invention provides a driving safety control method, which comprises the following steps:
acquiring a positioning coordinate of a current vehicle at the current moment, and determining whether the vehicle runs on a road or not according to the positioning coordinate and the road coordinate; if yes, acquiring the current vehicle speed of the current vehicle at the current moment, and acquiring a preset control strategy in the vehicle when the current vehicle speed is greater than a first preset threshold value;
when the control strategy is an offline strategy, extracting image data of nearby vehicles from a vehicle data recorder, and respectively evaluating the driving level of each nearby vehicle according to the image data to obtain a first score of the driving level of each nearby vehicle;
identifying identification information of nearby vehicles when the control strategy is an online strategy, and requesting a driving level second score of each nearby vehicle from the internet of vehicles server according to the identification information;
adding the first score and the second score into the score set, and judging whether any one score value is smaller than a second preset threshold value according to each score value in the score set; if yes, a prompt for disengaging from the current driving environment is sent to a driver of the current vehicle.
Optionally, the determining whether the vehicle runs on the road according to the positioning coordinates and the road coordinates includes:
acquiring edge coordinates of two side edges of the road with the width larger than a third preset threshold value, and taking a connecting line between the edge coordinates on the same side of the road as an edge line of the road;
setting all coordinates between edge lines at two sides of a road as road coordinates;
judging whether the positioning coordinates are in the range of the road coordinates, if so, judging that the vehicle runs on the road; if not, judging that the vehicle is not running on the road, and returning to the step of acquiring the positioning coordinates of the current vehicle at the current moment.
Optionally, the extracting the image data of the nearby vehicle from the automobile data recorder includes:
identifying an object image in the travel vehicle recorder, and screening out a vehicle image from the object image;
for each vehicle image, determining the distance between the corresponding vehicle of the vehicle image and the current vehicle according to the size of the vehicle image;
and acquiring the maximum braking distance of the current vehicle, and extracting all image data corresponding to the vehicle image when the maximum braking distance is not smaller than the distance.
Optionally, the obtaining the maximum braking distance of the current vehicle includes:
and calculating the maximum braking distance of the current vehicle according to the speed of the current vehicle and the corresponding braking acceleration of the current vehicle.
Optionally, the obtaining the maximum braking distance of the current vehicle includes:
according to the driving data of the current vehicle, calculating the braking distance when braking each time, and taking the maximum value of all the braking distances as the maximum braking distance, wherein the driving data comprises: vehicle positioning data, vehicle acceleration data, and time stamp data.
Optionally, the identifying information of the nearby vehicle includes:
and sending an inquiry request to the nearby vehicle so that the nearby vehicle returns the identification information of the nearby vehicle to the current vehicle as response information after receiving the inquiry request.
Optionally, the identifying information of the nearby vehicle includes:
the current vehicle sends the identification information of the current vehicle and the current coordinates of the current vehicle to the internet of vehicles server, so that the internet of vehicles server queries nearby vehicles within a set radius range by taking the current coordinates as a center point, and the identification information of the nearby vehicles is returned to the current vehicle.
The invention also provides a driving safety control method which is applied to the Internet of vehicles server and comprises the following steps:
receiving identification information of a nearby vehicle transmitted by a current vehicle performing the method as described above;
and inquiring a second score of the driving level of each nearby vehicle according to the identification information, and sending the second score to the current vehicle.
Optionally, the obtaining process of the second score is:
obtaining driving behaviors of other vehicles, wherein the driving behaviors comprise: one or a combination of maximum vehicle speed, acceleration and sudden braking times;
and calculating a second score of each other vehicle according to the weight of each driving behavior and the corresponding score value.
The invention also provides a driving safety control system, which comprises:
a current vehicle performing the method as described above;
and the Internet of vehicles server executes the method.
Compared with the prior art, the invention has the following advantages:
according to the method, the other vehicles around the current vehicle are identified, the driving level of the other vehicles is evaluated, the corresponding first score and second score are obtained, and then when one of the first score and the second score is lower, the fact that the safety risk possibly exists is indicated, the driver of the current vehicle is reminded of taking measures away from the current driving environment, and driving safety is further guaranteed.
Drawings
Fig. 1 is a schematic flow chart of a driving safety control method according to an embodiment of the present invention;
fig. 2 is a schematic diagram of a driving safety control method according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a driving safety control system according to an embodiment of the present invention.
Detailed Description
The following describes in detail the examples of the present invention, which are implemented on the premise of the technical solution of the present invention, and detailed embodiments and specific operation procedures are given, but the scope of protection of the present invention is not limited to the following examples.
The embodiment of the invention provides a driving safety control method and a driving safety control system, and the driving safety control method provided by the embodiment of the invention is firstly described below.
Example 1
Fig. 1 is a schematic flow chart of a driving safety control method according to an embodiment of the present invention, as shown in fig. 1, where the method includes:
s101: acquiring a positioning coordinate of a current vehicle at the current moment, and determining whether the vehicle runs on a road or not according to the positioning coordinate and the road coordinate; if yes, acquiring the current vehicle speed of the current vehicle at the current moment, and acquiring a preset control strategy in the vehicle when the current vehicle speed is greater than a first preset threshold value;
by way of example, the positioning coordinates of the current vehicle at the current moment are positioned by using a vehicle-mounted positioning terminal, such as a mobile phone, or an intelligent vehicle-mounted terminal installed on the vehicle, and the positioning coordinates of the current vehicle at the current moment are uploaded to the internet of vehicles server.
And the vehicle networking server compares the positioning coordinates of the current vehicle at the current moment with the coordinates of the road, and if the positioning coordinates and the coordinates are overlapped, the vehicle is indicated to run on the road.
When the vehicle runs on a road, the speed of the current vehicle at the current moment is read, and when the current speed is greater than 30km/h, a preset control strategy in the vehicle is obtained. For example, a safe control strategy may be preset in the control center of the vehicle for the driver of the current vehicle. The user worry that the network condition on the road is not good, the control strategy can be set to be an offline strategy, and when the network condition on the road is good, or other requirements are met by the driver, the control strategy can be set to be an online strategy. That is, the offline policy is suitable for low latency, bad network conditions, and the online policy is suitable for high accuracy, real-time monitoring requirements. According to the embodiment of the invention, two control strategies are set, so that a driver can set according to actual requirements, the system is more flexible, and the user experience is improved.
The embodiment of the invention does not limit the setting mode of the control strategy.
S102: when the control strategy is an offline strategy, extracting image data of nearby vehicles from a vehicle data recorder, and respectively evaluating the driving level of each nearby vehicle according to the image data to obtain a first score of the driving level of each nearby vehicle;
specifically, the control center of the current vehicle reads all video recordings of the left side, the right side, the front side and the rear side of the current vehicle from the automobile data recorder. And identifying object images in the travel recorder from the video recordings by using a preset neural network model, and identifying nearby vehicle image data from each object image.
Identification information of the vehicle is identified from the image data of the vehicle, for example, the identified nearby vehicle is: a nearby vehicle 1, a nearby vehicle 2, and a nearby vehicle 3.
For the nearby vehicle 1, each frame of image including the nearby vehicle 1 is identified, the corresponding time of the nearby vehicle 1 is identified according to the time stamp of each frame of image, the distance between the nearby vehicle 1 and the current vehicle is determined according to the size of the nearby vehicle 1 in the image, and the advancing speed of the other vehicle 1 is calculated according to the time interval between the adjacent time and the quotient of the change of the distance. Whether the other vehicle 1 is traveling overspeed is determined based on whether the forward speed is at the prescribed speed. The score corresponding to the speed is 0 when the vehicle is in overspeed running; the score for the speed when not speeding was 0.1.
Similarly, lane information of the nearby vehicle 1 can be identified from the image, so that the lane change times of the nearby vehicle 1 can be counted; and normalizing the variable pass number to obtain the variable pass number score of 0.2.
Similarly, whether other vehicles 1 have continuous lane change behavior can be identified, and when the continuous lane change behavior exists, the score corresponding to the continuous lane change is 0; the score for continuous lane change when no continuous lane change behavior exists is 0.1.
It is also possible to recognize from the image whether the nearby vehicle 1 turns on the turn signal lamp, and determine the on/off period of the turn signal lamp of the nearby vehicle 1 in combination with the time stamp of the image. According to the turn-on/off period of the turn signal lamp and the lane change time of the nearby vehicle 1, it is determined whether the nearby vehicle 1 turns on the turn signal lamp 5 seconds or more before lane change and whether the turn signal lamp on period exceeds 5 seconds. And a result of whether the turn signal is correctly turned on is identified from the image, for example, if the turn signal is turned on to the left lane, the turn signal is judged to be turned on incorrectly, and if the turn signal is turned on to the left lane, the turn signal is judged to be turned on correctly.
When turning on the turn signal lamp 5 seconds or more before lane change, the corresponding score is 0.1; when the turn signal lamp is not turned on 5 seconds or more before lane change, the corresponding score is 0.
Similarly, when the turn signal on period exceeds 5 seconds, the corresponding score is 0.1.
When the turn signal on period does not exceed 5 seconds, the corresponding score is 0.
When the turn signal lamp is correctly turned on, the corresponding score is 0.1; when the turn signal is turned on in error, the corresponding score is 0.
Then, a first score of the nearby vehicle 1 is calculated from the weight corresponding to whether the nearby vehicle 1 is traveling overspeed multiplied by the corresponding score. Similarly, the first scores of the nearby vehicles 2, 3 are also calculated according to the above-described method. In practice, the first score for a nearby vehicle may also be obtained using methods known in the art.
Further, for each vehicle image, determining the distance between the corresponding vehicle of the vehicle image and the current vehicle according to the size of the vehicle image; and acquiring the maximum braking distance of the current vehicle, and extracting all image data corresponding to the vehicle image when the maximum braking distance is not smaller than the distance.
Further, the maximum braking distance is the product of the maximum time length of the brake when the driver of the current vehicle drives the current vehicle and the speed of the current vehicle at the current moment. Or calculating the maximum braking distance of the current vehicle according to the speed of the current vehicle and the corresponding braking acceleration of the current vehicle. Or, according to the driving data of the current vehicle, calculating the braking distance when each time of braking, and taking the maximum value of all the braking distances as the maximum braking distance, wherein the driving data comprises: vehicle positioning data, vehicle acceleration data, and time stamp data. In the step, the maximum braking distance of the vehicle can be calculated in a plurality of modes, the vehicle can be flexibly configured by a driver, and the flexibility is high; and when the driver does not configure, taking the maximum value calculated by the method as the maximum braking distance so as to ensure the running safety of the current vehicle.
By applying the embodiment of the invention, the nearby vehicles with overlarge distance from the current vehicle are excluded, so that the calculated amount can be reduced, the reflecting speed of the system can be improved, and the user experience can be further improved.
S103: identifying identification information of nearby vehicles when the control strategy is an online strategy, and requesting a driving level second score of each nearby vehicle from the internet of vehicles server according to the identification information;
specifically, an inquiry request may be issued to the nearby vehicle so that the nearby vehicle returns its own identification information as response information to the current vehicle after receiving the inquiry request. The responding nearby vehicles are: a nearby vehicle 4, a nearby vehicle 5, and a nearby vehicle 6. The current vehicle transmits three pieces of identification information of the nearby vehicle 4, the nearby vehicle 5, and the nearby vehicle 6 to the internet of vehicles server, and the internet of vehicles server returns the second scores corresponding to the nearby vehicle 4, the nearby vehicle 5, and the nearby vehicle 6, respectively, to the current vehicle.
In practical applications, the second score may be calculated by the internet of vehicles server by using the method of calculating the first score in step S102.
Or the current vehicle sends the identification information of the current vehicle and the current coordinates of the current vehicle to the internet of vehicles server, so that the internet of vehicles server queries the nearby vehicles in the set radius range by taking the current coordinates as a center point, and the identification information of the nearby vehicles is returned to the current vehicle.
And then, inquiring the second scores corresponding to the nearby vehicles 4, 5 and 6 according to the identification information, and returning to the current vehicle.
S104: adding the first score and the second score into the score set, and judging whether any one score value is smaller than a second preset threshold value according to each score value in the score set; if yes, a prompt for disengaging from the current driving environment is sent to a driver of the current vehicle.
The current vehicle adds the first score or the second score to the score when receiving the first score corresponding to the nearby vehicle 1, the nearby vehicle 2, the nearby vehicle 3, or the second score corresponding to the nearby vehicle 4, the nearby vehicle 5, the nearby vehicle 6.
When the current vehicle receives only the first score, only the first score is in the score set; when the current vehicle receives only the second score, there is only the second score in the scores.
For each score value in the score sets, judging whether any score value is smaller than a second preset threshold value; if so, indicating that a risk point exists, and seriously threatening the driving safety of the current vehicle, and sending a prompt for disengaging from the current driving environment to the driver of the current vehicle.
Further, a warning that the driver of the current vehicle is away from the current driving environment can be sent out in a visual mode, for example, an icon of the current vehicle is displayed in the center of a central control large screen of the vehicle, a red mark is displayed behind the icon of the current vehicle when a nearby vehicle with a score value smaller than a second threshold value preset is located behind the current vehicle, and a red mark is displayed in front of the icon of the current vehicle when the nearby vehicle with a score value smaller than the second threshold value preset is located in front of the current vehicle. When the nearby vehicle whose score value is smaller than the second threshold preset is located on the left side of the current vehicle, a red mark is displayed on the left side of the icon of the current vehicle, and when the nearby vehicle whose score value is smaller than the second threshold preset is located on the right side of the current vehicle, a red mark is displayed on the right side of the icon of the current vehicle.
Furthermore, a voice prompt can be sent to the driver of the current vehicle, the nearby vehicle with the reminding score value smaller than the second threshold value is located behind or in front of the current vehicle, or the nearby vehicle with the reminding score value smaller than the second threshold value is located on the left side or the right side of the current vehicle, the number of times that the driver looks over the central control large screen can be reduced, and driving safety is further improved.
According to the method, the other vehicles around the current vehicle are identified, the driving level of the other vehicles is evaluated, the corresponding first score and second score are obtained, and then when one of the first score and the second score is lower, the fact that the safety risk possibly exists is indicated, the driver of the current vehicle is reminded of taking measures away from the current driving environment, and driving safety is further guaranteed.
Example 2
Based on example 1, the method of example 2 includes:
s201 (not shown in the figure): acquiring a positioning coordinate of a current vehicle at the current moment, and determining whether the vehicle runs on a road or not according to the positioning coordinate and the road coordinate; if yes, acquiring the current vehicle speed of the current vehicle at the current moment, and acquiring a preset control strategy in the vehicle when the current vehicle speed is greater than a first preset threshold value;
by way of example, the positioning coordinates of the current vehicle at the current moment are positioned by using a vehicle-mounted positioning terminal, such as a mobile phone, or an intelligent vehicle-mounted terminal installed on the vehicle, and the positioning coordinates of the current vehicle at the current moment are uploaded to the internet of vehicles server.
And the vehicle networking server compares the positioning coordinates of the current vehicle at the current moment with the coordinates of the road, and if the positioning coordinates and the coordinates are overlapped, the vehicle is indicated to run on the road.
When the vehicle runs on a road, the speed of the current vehicle at the current moment is read, and when the current speed is greater than 40km/h, a preset control strategy in the vehicle is obtained. For example, a safe control strategy may be preset in the control center of the vehicle for the driver of the current vehicle. The user worry that the network condition on the road is not good, the control strategy can be set to be an offline strategy, and when the network condition on the road is good, or other requirements are met by the driver, the control strategy can be set to be an online strategy. That is, the offline policy is suitable for low latency, bad network conditions, and the online policy is suitable for high accuracy, real-time monitoring requirements. According to the embodiment of the invention, two control strategies are set, so that a driver can set according to actual requirements, the system is more flexible, and the user experience is improved.
The embodiment of the invention does not limit the setting mode of the control strategy.
S202 (not shown in the figure): when the control strategy is an offline strategy, extracting image data of nearby vehicles from a vehicle data recorder, and respectively evaluating the driving level of each nearby vehicle according to the image data to obtain a first score of the driving level of each nearby vehicle;
specifically, the control center of the current vehicle reads all video recordings of the left side, the right side, the front side and the rear side of the current vehicle from the automobile data recorder. And identifying object images in the travel recorder from the video recordings by using a preset neural network model, and identifying nearby vehicle image data from each object image.
Identification information of the vehicle is identified from the image data of the vehicle, for example, the identified nearby vehicle is: a nearby vehicle 10, a nearby vehicle 20, a nearby vehicle 30.
For the nearby vehicle 10, each frame of image including the nearby vehicle 10 is identified, the time corresponding to the nearby vehicle 10 is identified according to the time stamp of each frame of image, the distance between the nearby vehicle 10 and the current vehicle is determined according to the size of the nearby vehicle 10 in the image, and the advancing speed of the other vehicle 1 is calculated according to the time interval between adjacent time and the quotient of the change of the distance. Whether the other vehicle 1 is traveling overspeed is determined based on whether the forward speed is at the prescribed speed. The score corresponding to the speed is 0 when the vehicle is in overspeed running; the score for the speed when not speeding was 0.1.
Similarly, lane information of the nearby vehicle 10 can be identified from the image, so that the number of variable passes of the nearby vehicle 10 is counted; and normalizing the variable pass number to obtain the variable pass number score of 0.2.
Similarly, whether other vehicles 1 have continuous lane change behavior can be identified, and when the continuous lane change behavior exists, the score corresponding to the continuous lane change is 0; the score for continuous lane change when no continuous lane change behavior exists is 0.1.
It is also possible to recognize from the image whether the nearby vehicle 10 turns on the turn signal lamp, and determine the on/off period of the turn signal lamp of the nearby vehicle 10 in combination with the time stamp of the image. Whether the nearby vehicle 10 turns on the turn lamp 5 seconds or more before lane change and whether the turn lamp on period exceeds 10 seconds are determined according to the on/off period of the turn lamp and the lane change time of the nearby vehicle 10. And a result of whether the turn signal is correctly turned on is identified from the image, for example, if the turn signal is turned on to the left lane, the turn signal is judged to be turned on incorrectly, and if the turn signal is turned on to the left lane, the turn signal is judged to be turned on correctly.
When turning on the turn signal lamp 5 seconds or more before lane change, the corresponding score is 0.1; when the turn signal lamp is not turned on 5 seconds or more before lane change, the corresponding score is 0.
Similarly, when the turn signal on period exceeds 5 seconds, the corresponding score is 0.1.
When the turn signal on period does not exceed 5 seconds, the corresponding score is 0.
When the turn signal lamp is correctly turned on, the corresponding score is 0.1; when the turn signal is turned on in error, the corresponding score is 0.
Then, a first score of the nearby vehicle 10 is calculated from the weight corresponding to whether the nearby vehicle 10 is traveling overspeed multiplied by the corresponding score. Similarly, the first scores of the nearby vehicles 20, 30 are also calculated according to the above-described method. In practice, the first score for a nearby vehicle may also be obtained using methods known in the art.
Further, for each vehicle image, determining the distance between the corresponding vehicle of the vehicle image and the current vehicle according to the size of the vehicle image; and acquiring the maximum braking distance of the current vehicle, and extracting all image data corresponding to the vehicle image when the maximum braking distance is not smaller than the distance.
S203 (not shown in the figure): identifying identification information of nearby vehicles when the control strategy is an online strategy, and requesting a driving level second score of each nearby vehicle from the internet of vehicles server according to the identification information;
specifically, an inquiry request may be issued to the nearby vehicle so that the nearby vehicle returns its own identification information as response information to the current vehicle after receiving the inquiry request. The responding nearby vehicles are: a nearby vehicle 40, a nearby vehicle 50, a nearby vehicle 60. The current vehicle transmits three pieces of identification information of the nearby vehicle 40, the nearby vehicle 50, and the nearby vehicle 60 to the internet of vehicles server, and the internet of vehicles server returns the second scores corresponding to the nearby vehicle 40, the nearby vehicle 50, and the nearby vehicle 60, respectively, to the current vehicle.
In practical applications, the second score may be calculated by the internet of vehicles server by using the method of calculating the first score in step S202.
Or the current vehicle sends the identification information of the current vehicle and the current coordinates of the current vehicle to the internet of vehicles server, so that the internet of vehicles server queries the nearby vehicles in the set radius range by taking the current coordinates as a center point, and the identification information of the nearby vehicles is returned to the current vehicle.
And then, inquiring the second scores corresponding to the nearby vehicles 40, 50 and 60 according to the identification information, and returning to the current vehicle.
S204 (not shown): adding the first score and the second score into the score set, and judging whether any one score value is smaller than a second preset threshold value according to each score value in the score set; if yes, a prompt for disengaging from the current driving environment is sent to a driver of the current vehicle.
The current vehicle adds the first score or the second score to the score when receiving the first score corresponding to the nearby vehicle 10, the nearby vehicle 20, the nearby vehicle 30, or the second score corresponding to the nearby vehicle 40, the nearby vehicle 50, the nearby vehicle 60.
When the current vehicle receives only the first score, only the first score is in the score set; when the current vehicle receives only the second score, there is only the second score in the scores.
For each score value in the score sets, judging whether any score value is smaller than a second preset threshold value; if so, indicating that a risk point exists, and seriously threatening the driving safety of the current vehicle, and sending a prompt for disengaging from the current driving environment to the driver of the current vehicle.
Further, a warning that the driver of the current vehicle is away from the current driving environment can be sent out in a visual mode, for example, an icon of the current vehicle is displayed in the center of a central control large screen of the vehicle, a red mark is displayed behind the icon of the current vehicle when a nearby vehicle with a score value smaller than a second threshold value preset is located behind the current vehicle, and a red mark is displayed in front of the icon of the current vehicle when the nearby vehicle with a score value smaller than the second threshold value preset is located in front of the current vehicle. When the nearby vehicle whose score value is smaller than the second threshold preset is located on the left side of the current vehicle, a red mark is displayed on the left side of the icon of the current vehicle, and when the nearby vehicle whose score value is smaller than the second threshold preset is located on the right side of the current vehicle, a red mark is displayed on the right side of the icon of the current vehicle.
Furthermore, a voice prompt can be sent to the driver of the current vehicle, the nearby vehicle with the reminding score value smaller than the second threshold value is located behind or in front of the current vehicle, or the nearby vehicle with the reminding score value smaller than the second threshold value is located on the left side or the right side of the current vehicle, the number of times that the driver looks over the central control large screen can be reduced, and driving safety is further improved.
According to the method, the other vehicles around the current vehicle are identified, the driving level of the other vehicles is evaluated, the corresponding first score and second score are obtained, and then when one of the first score and the second score is lower, the fact that the safety risk possibly exists is indicated, the driver of the current vehicle is reminded of taking measures away from the current driving environment, and driving safety is further guaranteed.
Example 3
Based on embodiment 1 or embodiment 2 of the present invention, embodiment 3 of the present invention provides another driving safety control method.
Specifically, S101 may include the following steps:
a (not shown in the figure): acquiring edge coordinates of two side edges of the road with the width larger than a third preset threshold value, and taking a connecting line between the edge coordinates on the same side of the road as an edge line of the road; typically, the third preset threshold value is equal to the body width of the current vehicle.
B (not shown): setting all coordinates between edge lines at two sides of a road as road coordinates;
c (not shown): judging whether the positioning coordinates are in the range of the road coordinates, if so, judging that the vehicle runs on the road; if not, judging that the vehicle is not running on the road, and returning to the step of acquiring the positioning coordinates of the current vehicle at the current moment.
Acquiring a high-precision map of a current vehicle driving road section, extracting edge coordinates of the road edge in the high-precision map, and taking a connecting line between the edge coordinates on the same side of the road as an edge line of the road; the edge line of the road forms two parallel lines, and when the current coordinate of the current vehicle falls within the range between the parallel lines, the current vehicle is judged to run on the road.
By applying the embodiment of the invention, whether the vehicle runs on the road can be judged, so that the selective triggering of the methods of the embodiment 1 and the embodiment 2 of the invention is realized, the steps of the embodiment 1 and the embodiment 2 of the invention are prevented from being triggered too frequently, the operation amount is further reduced, and the user experience is improved.
Example 4
Corresponding to embodiments 1-3 of the present invention, fig. 2 is a schematic diagram of a driving safety control method provided by the embodiment of the present invention, as shown in fig. 2, applied to a server of the internet of vehicles, where the method includes:
s301: receiving identification information of a nearby vehicle transmitted by a current vehicle performing the method described in embodiment 1-embodiment 3;
s302: and inquiring a second score of the driving level of each nearby vehicle according to the identification information, and sending the second score to the current vehicle.
Specifically, the current vehicle sends the identification information of the current vehicle and the current coordinates of the current vehicle to the internet of vehicles server, so that the internet of vehicles server queries the nearby vehicles within the set radius range by taking the current coordinates as the center point, and the identification information of the nearby vehicles is returned to the current vehicle.
And then, inquiring the second scores corresponding to the nearby vehicles 4, 5 and 6 according to the identification information, and returning to the current vehicle.
By applying the method and the device, the query of the second score can be realized based on the Internet of vehicles server, and compared with the first score under the offline strategy, the evaluation data of the driving level of the nearby vehicle stored in the Internet of vehicles server are more, so that the evaluation is more accurate, and therefore, the second score can better evaluate the driving level of the driver of the nearby vehicle relative to the first score, so that the driving safety control is more accurately performed.
In a specific implementation manner of the embodiment of the present invention, the process of obtaining the second score is:
obtaining driving behaviors of other vehicles, wherein the driving behaviors comprise: one or a combination of maximum vehicle speed, acceleration and sudden braking times;
and calculating a second score of each other vehicle according to the weight of each driving behavior and the corresponding score value.
The principle of calculating the second score in this step is basically the same as that of calculating the first score in step S102 in embodiment 1, and the embodiment of the present invention will not be described here again.
Example 5
Fig. 3 is a schematic structural diagram of a driving safety control system provided by the embodiment of the present invention, and as shown in fig. 3, based on any one of embodiments 1 to 4 of the present invention, embodiment 5 of the present invention provides a driving safety control system, where the system includes:
a current vehicle 401 performing the method as described in embodiment 1-embodiment 3;
the internet of vehicles server 402 performing the method of embodiment 4.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, and alternatives falling within the spirit and principles of the invention.
Claims (9)
1. A driving safety control method, characterized in that the method comprises:
acquiring a positioning coordinate of a current vehicle at the current moment, and determining whether the vehicle runs on a road or not according to the positioning coordinate and the road coordinate; if yes, acquiring the current vehicle speed of the current vehicle at the current moment, and acquiring a preset control strategy in the vehicle when the current vehicle speed is greater than a first preset threshold value; the determining whether the vehicle runs on the road according to the positioning coordinates and the road coordinates comprises the following steps: acquiring edge coordinates of two side edges of the road with the width larger than a third preset threshold value, and taking a connecting line between the edge coordinates on the same side of the road as an edge line of the road; setting all coordinates between edge lines at two sides of a road as road coordinates; judging whether the positioning coordinates are in the range of the road coordinates, if so, judging that the vehicle runs on the road; if not, judging that the vehicle does not run on the road, and returning to the step of acquiring the positioning coordinates of the current vehicle at the current moment;
when the control strategy is an offline strategy, extracting image data of nearby vehicles from a vehicle data recorder, and respectively evaluating the driving level of each nearby vehicle according to the image data to obtain a first score of the driving level of each nearby vehicle;
identifying identification information of nearby vehicles when the control strategy is an online strategy, and requesting a driving level second score of each nearby vehicle from the internet of vehicles server according to the identification information;
adding the first score and the second score into the score set, and judging whether any one score value is smaller than a second preset threshold value according to each score value in the score set; if yes, a prompt for disengaging from the current driving environment is sent to a driver of the current vehicle.
2. The driving safety control method according to claim 1, wherein the extracting the image data of the nearby vehicle from the driving recorder comprises:
identifying an object image in the travel vehicle recorder, and screening out a vehicle image from the object image;
for each vehicle image, determining the distance between the corresponding vehicle of the vehicle image and the current vehicle according to the size of the vehicle image;
and acquiring the maximum braking distance of the current vehicle, and extracting all image data corresponding to the vehicle image when the maximum braking distance is not smaller than the distance.
3. The driving safety control method according to claim 2, wherein the obtaining the maximum braking distance of the current vehicle comprises:
and calculating the maximum braking distance of the current vehicle according to the speed of the current vehicle and the corresponding braking acceleration of the current vehicle.
4. The driving safety control method according to claim 2, wherein the obtaining the maximum braking distance of the current vehicle comprises:
according to the driving data of the current vehicle, calculating the braking distance when braking each time, and taking the maximum value of all the braking distances as the maximum braking distance, wherein the driving data comprises: vehicle positioning data, vehicle acceleration data, and time stamp data.
5. The traffic safety control method according to claim 1, wherein the identifying information of the nearby vehicle includes:
and sending an inquiry request to the nearby vehicle so that the nearby vehicle returns the identification information of the nearby vehicle to the current vehicle as response information after receiving the inquiry request.
6. The traffic safety control method according to claim 1, wherein the identifying information of the nearby vehicle includes:
the current vehicle sends the identification information of the current vehicle and the current coordinates of the current vehicle to the internet of vehicles server, so that the internet of vehicles server queries nearby vehicles within a set radius range by taking the current coordinates as a center point, and the identification information of the nearby vehicles is returned to the current vehicle.
7. A traffic safety control method, characterized by being applied to a server of the internet of vehicles, comprising:
receiving identification information of a nearby vehicle transmitted by a current vehicle performing the method of any one of claims 1-6;
and inquiring a second score of the driving level of each nearby vehicle according to the identification information, and sending the second score to the current vehicle.
8. The driving safety control method according to claim 7, wherein the second score obtaining process is:
obtaining driving behaviors of other vehicles, wherein the driving behaviors comprise: one or a combination of maximum vehicle speed, acceleration and sudden braking times;
and calculating a second score of each other vehicle according to the weight of each driving behavior and the corresponding score value.
9. A traffic safety control system, the system comprising:
a current vehicle performing the method of any one of claims 1-6;
an internet of vehicles server performing the method of claim 7 or 8.
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103198685A (en) * | 2013-03-15 | 2013-07-10 | Tcl集团股份有限公司 | Method and system for achieving driving safety early warning |
| CN104077819A (en) * | 2014-06-17 | 2014-10-01 | 深圳前向启创数码技术有限公司 | Remote monitoring method and system based on driving safety |
| CN108288312A (en) * | 2017-03-06 | 2018-07-17 | 腾讯科技（深圳）有限公司 | Driving behavior determines method and device |
| CN109389863A (en) * | 2017-08-02 | 2019-02-26 | 华为技术有限公司 | Reminding method and relevant device |
| CN109466444A (en) * | 2018-10-31 | 2019-03-15 | 广州小鹏汽车科技有限公司 | Hazardous vehicles detect method for early warning and system |
| CN114495511A (en) * | 2020-11-13 | 2022-05-13 | 上海博泰悦臻网络技术服务有限公司 | Method, system, medium, and apparatus for reminding vehicle owner of paying attention to vehicle traveling in the same direction |
| CN114834474A (en) * | 2022-06-07 | 2022-08-02 | 公安部第三研究所 | Active safety auxiliary driving system based on real-time state monitoring of driver |
| JP2022130889A (en) * | 2021-02-26 | 2022-09-07 | 株式会社日立ビルシステム | Driving evaluation device and driving evaluation method |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| TWI525009B (en) * | 2013-11-11 | 2016-03-11 | 緯創資通股份有限公司 | Vehicle early warning system and vehicle early warning method |
-
2022
- 2022-12-19 CN CN202211630363.4A patent/CN115966100B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103198685A (en) * | 2013-03-15 | 2013-07-10 | Tcl集团股份有限公司 | Method and system for achieving driving safety early warning |
| CN104077819A (en) * | 2014-06-17 | 2014-10-01 | 深圳前向启创数码技术有限公司 | Remote monitoring method and system based on driving safety |
| CN108288312A (en) * | 2017-03-06 | 2018-07-17 | 腾讯科技（深圳）有限公司 | Driving behavior determines method and device |
| CN109389863A (en) * | 2017-08-02 | 2019-02-26 | 华为技术有限公司 | Reminding method and relevant device |
| CN109466444A (en) * | 2018-10-31 | 2019-03-15 | 广州小鹏汽车科技有限公司 | Hazardous vehicles detect method for early warning and system |
| CN114495511A (en) * | 2020-11-13 | 2022-05-13 | 上海博泰悦臻网络技术服务有限公司 | Method, system, medium, and apparatus for reminding vehicle owner of paying attention to vehicle traveling in the same direction |
| JP2022130889A (en) * | 2021-02-26 | 2022-09-07 | 株式会社日立ビルシステム | Driving evaluation device and driving evaluation method |
| CN114834474A (en) * | 2022-06-07 | 2022-08-02 | 公安部第三研究所 | Active safety auxiliary driving system based on real-time state monitoring of driver |
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