CN113997940B - Driving behavior monitoring method and device - Google Patents
Driving behavior monitoring method and device Download PDFInfo
- Publication number
- CN113997940B CN113997940B CN202111562976.4A CN202111562976A CN113997940B CN 113997940 B CN113997940 B CN 113997940B CN 202111562976 A CN202111562976 A CN 202111562976A CN 113997940 B CN113997940 B CN 113997940B
- Authority
- CN
- China
- Prior art keywords
- target vehicle
- driving
- information
- illegal
- time period
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/08—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to drivers or passengers
- B60W40/09—Driving style or behaviour
Abstract
The invention provides a driving behavior monitoring method and a driving behavior monitoring device, wherein the method comprises the following steps: acquiring driving information of a target vehicle, wherein the driving information comprises one or more of running information, position information, external environment information and in-vehicle environment information of the target vehicle; identifying one or more illegal driving scenes generated by the target vehicle in a preset time period according to the driving information of the target vehicle at different moments in the preset time period; generating a driving score according to each illegal driving scene generated by the target vehicle within a preset time period; and if the driving score is not qualified, sending a driving report to a target object associated with the target vehicle, wherein the driving report comprises a driving behavior improvement item, and the driving behavior improvement item is determined according to an illegal driving scene generated in a preset time period. The method and the device are beneficial to improving the driving habit of the target object, reducing the vehicle loss and improving the driving safety.
Description
Technical Field
The invention belongs to the technical field of driving safety, and particularly relates to a driving behavior monitoring method and device.
Background
At present, social economy is increased, driving and traveling become an important traffic mode in the current society, the kinetic energy of a vehicle is high, the speed is high, and safe driving is very important, but most drivers have some dangerous behaviors in the driving process more or less in daily driving, vehicle loss is caused slightly due to the existence of the dangerous behaviors, and car accidents are caused seriously due to the existence of the dangerous behaviors, but the dangerous behaviors of the drivers form habits and are not known by themselves, so that the fact that the drivers have good driving habits in the driving process of the vehicle is particularly important.
Disclosure of Invention
Therefore, aiming at the problems in the prior art, the invention provides a driving behavior monitoring method and device, which help users to improve driving habits and improve driving safety.
In a first aspect, the present invention provides a method of monitoring driving behaviour, the method comprising: acquiring driving information of a target vehicle, wherein the driving information comprises one or more of driving information, position information, external environment information and in-vehicle environment information of the target vehicle; identifying one or more illegal driving scenes generated by the target vehicle in a preset time period according to the driving information of the target vehicle at different moments in the preset time period; generating a driving score according to each illegal driving scene generated by the target vehicle within a preset time period; and if the driving score is not qualified, sending a driving report to a target object associated with the target vehicle, wherein the driving report comprises a driving behavior improvement item, and the driving behavior improvement item is determined according to an illegal driving scene generated in a preset time period.
Optionally, in the driving behavior monitoring method provided by the present invention, the driving information includes a vehicle speed, the illegal driving scenario includes speeding and sudden braking, and the identifying that the target vehicle generates the illegal driving scenario within the preset time period according to the driving information of the target vehicle at different times within the preset time period includes: determining a speed limit value of a road section where the target vehicle is located according to the position information of the target vehicle, and if the ratio of the speed of the target vehicle to the speed limit value is greater than a first preset value, judging that an illegal driving scene generated by the target vehicle is overspeed driving; and determining the speed reduction rate of the target vehicle in a set time period according to the speeds of the target vehicle at different moments, and if the speed reduction rate of the target vehicle in the set time period is greater than a second preset value, determining that the illegal driving scene generated by the target vehicle is sudden braking.
Optionally, in the driving behavior monitoring method provided by the present invention, the external environment information includes data of a panoramic looking-around system, the illegal driving scenario includes driving under line-pressing, yellow-light robbing, and emergency lane occupation, and the method identifies that the target vehicle generates the illegal driving scenario within the preset time period according to the driving information of the target vehicle within the preset time period at different times, and includes: determining whether the target vehicle is in a line pressing state or not according to the panoramic all-round looking system data of the target vehicle, and if the target vehicle is in the line pressing state, judging that the illegal driving scene generated by the target vehicle is line pressing driving; determining the color of a traffic light of the target vehicle when the target vehicle passes through the intersection according to the panoramic all-round system data of the target vehicle, and if the color of the traffic light of the target vehicle when the target vehicle passes through the intersection is yellow, judging that an illegal driving scene generated by the target vehicle is a yellow rush light; and determining whether the target vehicle is in an emergency lane according to the panoramic looking-around system data of the target vehicle, and if the target vehicle is in the emergency lane, judging that the illegal driving scene generated by the target vehicle is an emergency lane.
Optionally, in the driving behavior monitoring method provided by the present invention, the external environment information includes panoramic looking-around system data, the driving information includes a vehicle speed, the illegal driving scene includes a non-courtesy pedestrian, and the identifying, according to the driving information of the target vehicle at different times within the preset time period, that the target vehicle generates the illegal driving scene within the preset time period includes: determining whether a pedestrian passes through a set area in front of the target vehicle according to the panoramic all-around system data of the target vehicle; and if the pedestrians pass through the front set area of the target vehicle and the speed of the target vehicle is greater than the third preset value, judging that the illegal driving scene generated by the target vehicle is a non-courtesy pedestrian.
Optionally, in the driving behavior monitoring method provided by the present invention, the in-vehicle environment information includes call information or voice information, the driving information includes a vehicle speed, the illegal driving scenario includes a vehicle call, and the identifying, according to the driving information of the target vehicle at different times within the preset time period, that the target vehicle generates the illegal driving scenario within the preset time period includes: determining whether the target vehicle is in a call state according to the call information or the voice information of the target vehicle, and determining whether the target vehicle is in a running state according to the speed of the target vehicle; and if the target vehicle is in a call state and the target vehicle is in a driving state, judging that the illegal driving scene generated by the target vehicle is driving and calling.
Optionally, in the driving behavior monitoring method provided by the present invention, the driving information includes a vehicle speed and a steering direction, the illegal driving scenario includes a complex road overtaking, and the identifying that the target vehicle generates the illegal driving scenario within the preset time period according to the driving information of the target vehicle at different times within the preset time period includes: judging whether the road section where the target vehicle is located is a complex road section or not according to the position information of the target vehicle; if the road condition of the road section where the target vehicle is located is a complex road section, judging whether the target vehicle is in a overtaking driving state or not according to the speed and the steering of the target vehicle; and if the target vehicle is in the overtaking driving state, judging that the illegal driving scene generated by the target vehicle is the overtaking of the complex road section.
Optionally, in the driving behavior monitoring method provided by the present invention, generating a driving score according to each illegal driving scenario generated by the target vehicle within a preset time period includes: determining scores and score coefficient ratios corresponding to the illegal driving scenes; and calculating the weighted sum of the scores according to the score and the score coefficient ratio corresponding to each illegal driving scene, and taking the weighted sum as the driving score.
In a second aspect, the present invention provides a driving behaviour monitoring apparatus comprising: the measuring module is used for acquiring the driving information of the target vehicle, wherein the driving information comprises one or more of the driving information, the position information, the external environment information and the in-vehicle environment information of the target vehicle; the identification module is used for identifying one or more illegal driving scenes generated by the target vehicle in the preset time period according to the driving information of the target vehicle at different moments in the preset time period; the driving scoring module is used for generating driving scoring according to various illegal driving scenes generated by the target vehicle in a preset time period; and the reporting module is used for judging whether the driving score is qualified or not, and if the driving score is unqualified, sending a driving report to a target object associated with the target vehicle, wherein the driving report comprises a driving behavior improvement item, and the driving behavior improvement item is determined according to an illegal driving scene generated in a preset time period.
In a third aspect, the present invention provides a computer-readable storage medium storing computer instructions for execution by a processor to implement a driving behavior monitoring method.
In a fourth aspect, the invention provides a computer apparatus comprising: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executable by the at least one processor to perform a driving behavior monitoring method.
The driving behavior monitoring method and the driving behavior monitoring device have the following advantages:
according to the driving behavior monitoring method and device, after the driving information of the target vehicle is obtained, the illegal driving scene generated by the target vehicle is identified according to the driving information of the target vehicle, the driving score is generated based on the illegal driving scene, when the driving score is unqualified, the driving behavior improvement item is determined according to the illegal driving scene, and the driving behavior improvement item is determined according to the illegal driving scene actually generated by the target vehicle in the driving process, so that the driving behavior improvement item can accurately indicate bad habits of the target object in the driving process, a driving report containing the driving behavior improvement item is sent to the target object, the driving habit of the target object is improved, the vehicle loss is reduced, and the driving safety is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a flowchart of a specific example of a driving behavior monitoring method in an embodiment of the present invention;
fig. 2 is a schematic structural view of a specific example of a driving behavior monitoring apparatus according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a specific example of a computer device in the embodiment of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it should be understood that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Unless the context clearly requires otherwise, throughout the description and the claims, the words "comprise", "comprising", and the like are to be construed in an inclusive sense as opposed to an exclusive or exhaustive sense; that is, what is meant is "including, but not limited to".
In the description of the present invention, it is to be understood that the terms "first," "second," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. In addition, in the description of the present invention, "a plurality" means two or more unless otherwise specified.
In addition, the technical features involved in the different embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
An embodiment of the present invention provides a driving behavior monitoring method, as shown in fig. 1, the method includes:
step S1: the method comprises the steps of obtaining driving information of a target vehicle, wherein the driving information comprises one or more of driving information, position information, external environment information and in-vehicle environment information of the target vehicle.
In an alternative embodiment, the driving information includes vehicle speed, steering or pedal force angle, and the like, wherein the vehicle speed can be obtained through a vehicle speed sensor, the steering can be obtained through a steering sensor, and the pedal force angle can be obtained through a pedal sensor.
In an alternative embodiment, the location information may be obtained by a GPS module.
In an alternative embodiment, the external environment information includes traffic light information, traffic sign or vehicle surrounding information, and the external environment information may be acquired through a vehicle panoramic looking-around system or a traffic department.
In an alternative embodiment, the in-vehicle environment information includes call information or voice information. The call information is obtained through a call module in the car machine; the voice information is acquired through the voice recognition module.
Step S2: the method comprises the steps of identifying one or more illegal driving scenes generated by a target vehicle in a preset time period according to driving information of the target vehicle at different moments in the preset time period, and generating a driving score according to each illegal driving scene generated by the target vehicle in the preset time period.
The driving behavior monitoring method provided by the embodiment of the invention can acquire the driving information of the target vehicle in real time to obtain the driving information at different moments, and can determine a driving scene of the target vehicle according to the driving information acquired at one or more continuous moments.
In an optional embodiment, the preset time period is greater than the time interval for collecting the driving information, and the driving information at multiple moments can be acquired within the preset time period, so that multiple driving scenes can be determined.
Illustratively, the preset time period may be one day, and the time interval for collecting the driving information may be 1s, 1min, or the like.
And step S3: and if the driving score is not qualified, sending a driving report to a target object associated with the target vehicle, wherein the driving report comprises a driving behavior improvement item, and the driving behavior improvement item is determined according to an illegal driving scene generated in a preset time period.
In an optional embodiment, a qualified driving score is set, and if the driving score is smaller than the qualified driving score, the driving score is determined to be unqualified; and if the driving score is equal to or larger than the set driving score qualified number, judging that the driving score is qualified.
The driving scoring qualification number may be set according to an actual demand, and for example, the driving scoring qualification number may be set to 60.
In an optional embodiment, the illegal driving scenario is caused by a bad or bad behavior of the target object when driving the vehicle, such as a sudden stepping on an accelerator/brake pedal, a call receiving or a random overtaking when driving the target vehicle, and different driving behavior improvement items are established for different illegal driving scenarios, if the number of times of the target vehicle having the illegal driving scenario within the preset time exceeds a set number of times, the driving behavior improvement item is established for the illegal driving scenario, and exemplarily, if the number of times of identifying that the target vehicle having the speeding illegal driving scenario within one day exceeds 3 times, the driving behavior improvement item is established for the speeding illegal driving scenario, and the driving behavior improvement item may be a behavior of reducing the sudden stepping on the accelerator pedal when reminding the target object of needing to drive the target vehicle in a graph or a text form.
In an alternative embodiment, if the driving score is qualified, no driving report is generated.
According to the driving behavior monitoring method provided by the embodiment of the invention, after the driving information of the target vehicle is acquired, the illegal driving scene generated by the target vehicle is identified according to the driving information of the vehicle, the driving score is generated based on the illegal driving scene, when the driving score is unqualified, the driving behavior improvement item is determined according to the illegal driving scene, and the driving behavior improvement item is determined according to the illegal driving scene actually generated by the target vehicle in the driving process, so that the driving behavior improvement item can accurately indicate bad habits of the target object in the driving process, and the driving report containing the driving behavior improvement item is sent to the target object, so that the driving habit of the target object can be improved, the vehicle loss is reduced, and the driving safety is improved.
In an optional embodiment, the driving information includes vehicle speed, the illegal driving scene includes speeding, and the identifying that the target vehicle generates the illegal driving scene in the preset time period according to the driving information of the target vehicle at different moments in the preset time period includes:
and determining the speed limit value of the road section where the target vehicle is located according to the position information of the target vehicle, and if the ratio of the speed of the target vehicle to the speed limit value is greater than a first preset value, judging that the illegal driving scene generated by the target vehicle is overspeed driving.
In an alternative embodiment, the speed limit value of the road section can be obtained by a traffic department or recorded by machine learning.
In an optional embodiment, the first preset value may be set according to an actual requirement, for example, the first preset value may be 105%, if the speed limit value of the road section where the target vehicle is located is 20km/h, the vehicle speed of the target vehicle is 30km/h, and at this time, the ratio of the vehicle speed of the target vehicle to the speed limit value is 150%, and since the ratio of the vehicle speed of the target vehicle to the speed limit value is greater than 105%, it is determined that the illegal driving scene generated by the target vehicle is speeding.
In an optional embodiment, the driving information includes vehicle speed, the illegal driving scene includes sudden braking, and the identifying that the target vehicle generates the illegal driving scene in the preset time period according to the driving information of the target vehicle at different moments in the preset time period includes:
and determining the speed reduction rate of the target vehicle in a set time period according to the speeds of the target vehicle at different moments, and if the speed reduction rate of the target vehicle in the set time period is greater than a second preset value, determining that the illegal driving scene generated by the target vehicle is sudden braking.
In an optional embodiment, the set time period and the second preset value can be set according to actual requirements, for example, the set time period can be 3 seconds, the second preset value can be 50%, and if the speed of the target vehicle is reduced from 60km/h to 20km/h within 3 seconds, it is determined that the target vehicle generates a sudden braking violation driving scene.
In an optional embodiment, the external environment information includes panoramic looking-around system data, the illegal driving scene includes line-pressing driving, and the identification of the illegal driving scene generated by the target vehicle in the preset time period according to the driving information of the target vehicle at different moments in the preset time period includes:
and determining whether the target vehicle is in a line pressing state or not according to the panoramic looking-around system data of the target vehicle, and if the target vehicle is in the line pressing state, judging that the illegal driving scene generated by the target vehicle is line pressing driving.
In this embodiment, the panoramic looking-around system data includes image data of a target vehicle and information of an environment around the target vehicle, the panoramic looking-around system data is acquired through the panoramic looking-around system, a lane line can be identified through the panoramic looking-around system data, the position of the target vehicle is determined, and if the position of the target vehicle is the lane line, the target vehicle is determined to be in a line pressing state.
In an optional embodiment, the external environment information includes panoramic looking-around system data, the illegal driving scene includes a yellow robber, and the identifying that the target vehicle generates the illegal driving scene within the preset time period according to the driving information of the target vehicle at different moments within the preset time period includes:
and determining the color of a traffic light of the target vehicle when the target vehicle passes through the intersection according to the panoramic all-round looking system data of the target vehicle, and if the color of the traffic light of the target vehicle when the target vehicle passes through the intersection is yellow, judging that the illegal driving scene generated by the target vehicle is a yellow rush light.
In this embodiment, the panoramic all-around system data includes image data of the surrounding environment information of the target vehicle, the panoramic all-around system data is acquired through the panoramic all-around system, when the target vehicle passes through the intersection, the color of the traffic light is identified according to the panoramic all-around system data, and if the color of the traffic light is yellow at the moment, it is determined that the illegal driving scene generated by the target vehicle is a yellow robber.
In an optional embodiment, the external environment information includes panoramic all-round system data, the illegal driving scenario includes an occupied emergency lane, and the recognizing, according to the driving information of the target vehicle at different times within a preset time period, that the target vehicle generates the illegal driving scenario within the preset time period includes:
and determining whether the target vehicle is in an emergency lane according to the panoramic all-round looking system data of the target vehicle, and if so, judging that the illegal driving scene generated by the target vehicle occupies the emergency lane.
In this embodiment, the panoramic all-around system data includes image data of the surrounding environment information of the target vehicle, the panoramic all-around system data is acquired through the panoramic all-around system, the traffic lane can be identified through the panoramic all-around system data, the lane where the target vehicle is located is determined, and if the traffic lane of the lane where the target vehicle is located is the mark of the emergency lane, the target vehicle is determined to be in the emergency lane.
In an optional embodiment, the external environment information includes panoramic looking-around system data, the driving information includes a vehicle speed, the illegal driving scene includes a non-courtesy pedestrian, and the identifying that the target vehicle generates the illegal driving scene within the preset time period according to the driving information of the target vehicle at different times within the preset time period includes:
determining whether a pedestrian passes through a set area in front of the target vehicle according to the panoramic all-around system data of the target vehicle; and if the pedestrians pass through the set area in front of the target vehicle and the speed of the target vehicle is greater than the third preset value, judging that the illegal driving scene generated by the target vehicle is a non-courtesy pedestrian.
In this embodiment, the range of the front setting area of the target vehicle and the third preset value may be set according to actual requirements, and the front setting area of the target vehicle may be a sector area with the head of the target vehicle as a center, a central angle of 160 ° and a radius of 1 meter. The third preset value may be set to 0.
In an optional embodiment, the in-vehicle environment information includes call information or voice information, the driving information includes a vehicle speed, the illegal driving scenario includes a vehicle calling, and the identifying that the target vehicle generates the illegal driving scenario within the preset time period according to the driving information of the target vehicle at different times within the preset time period includes:
determining whether the target vehicle is in a call state according to the telephone module data or the voice recognition module data of the target vehicle, and determining whether the target vehicle is in a running state according to the speed of the target vehicle; and if the target vehicle is in a call state and the target vehicle is in a driving state, judging that the illegal driving scene generated by the target vehicle is driving and making a call.
In an optional embodiment, the call information is obtained according to a call module in a vehicle machine of the target vehicle, and the driver can make and receive calls according to the call module, so that whether the driver is calling can be determined according to the call information obtained by the call module.
The voice recognition module has the functions of machine learning and self-updating, whether the target vehicle is in a call state or not can be accurately judged through the voice recognition data acquired by the voice recognition module, and the accuracy of the result obtained through the driving behavior monitoring method provided by the embodiment is improved.
In an optional embodiment, the driving information includes a vehicle speed and a steering, the illegal driving scenario includes a complex road overtaking, and the identifying that the target vehicle generates the illegal driving scenario within the preset time period according to the driving information of the target vehicle at different moments within the preset time period includes:
judging whether the road section where the target vehicle is located is a complex road section or not according to the position information of the target vehicle; if the road condition of the road section where the target vehicle is located is a complex road section, judging whether the target vehicle is in an overtaking driving state or not according to the speed and the steering of the target vehicle; and if the target vehicle is in the overtaking driving state, judging that the illegal driving scene generated by the target vehicle is the overtaking of the complex road section.
In an optional embodiment, the position information of the target vehicle is acquired through a GPS module, the GPS module has a GPS system and a map system, the GPS system can accurately acquire the position of the target vehicle, the map system can acquire road information of the position of the target vehicle according to the position of the target vehicle, and if the road information of the position of the target vehicle is an intersection, a curve, or a crosswalk, it is determined that the position of the target vehicle is a complex road segment.
In an optional embodiment, generating a driving score according to each illegal driving scene generated by the target vehicle within a preset time period includes: determining scores and score coefficient ratios corresponding to the illegal driving scenes; and calculating the weighted sum of the scores according to the score and the score coefficient ratio corresponding to each illegal driving scene, and taking the weighted sum as the driving score.
In an optional embodiment, the score and the score coefficient ratio corresponding to each illegal driving scenario may be determined according to an actual demand, and for example, the score coefficient ratio corresponding to each illegal driving scenario may be: the corresponding fraction coefficient ratio of overspeed driving is 25 percent; the coefficient ratio of the corresponding fraction of the sudden braking is 10 percent; the ratio of the corresponding fraction coefficient of the line pressing driving is 20 percent; the corresponding fraction coefficient ratio of the yellow robber lamp is 15 percent; the corresponding fraction coefficient ratio of the pedestrian is not suitable for being given 12%; the ratio of the fraction coefficient corresponding to the calling of the vehicle is 5 percent; the overtaking corresponding fraction coefficient ratio of the complex road section is 13%.
If the corresponding scores of the illegal driving scenes are as follows: the corresponding fraction of speeding is 80; the corresponding fraction of sudden braking is 80; the corresponding score of line pressing running is 70; the corresponding score of the yellow robbing lamp is 90; the corresponding score of the pedestrian is 90; the score corresponding to the calling in driving is 60; the overtaking corresponding score of the complex road section is 80.
The weighted sum of the scores is 80 × 25% +80 × 10% +70 × 20% +90 × 15% +90 × 12% +60 × 5% +80 × 13% =79.7, and the driving score is 79.7.
An embodiment of the present invention provides a driving behavior monitoring device, as shown in fig. 2, including:
the measuring module 1 is configured to obtain driving information of the target vehicle, where the driving information includes one or more of driving information, position information, external environment information, and in-vehicle environment information of the target vehicle, and details of the driving information refer to the description in the above embodiment and are not described herein again.
The identifying module 2 is configured to identify one or more illegal driving scenes generated by the target vehicle within the preset time period according to the driving information of the target vehicle within the preset time period at different times, for details, refer to the description in the above embodiment, and are not described herein again.
The driving scoring module 3 is configured to generate a driving score according to each illegal driving scenario generated by the target vehicle within a preset time period, and the detailed content refers to the description in the above embodiment, which is not described herein again.
And the reporting module 4 is configured to determine whether the driving score is qualified, and if the driving score is not qualified, send a driving report to a target object associated with the target vehicle, where the driving report includes a driving behavior improvement item, and the driving behavior improvement item is determined according to an illegal driving scene generated within a preset time period, and details of the driving behavior improvement item are described in the above embodiment, and are not described herein again.
For specific limitations and beneficial effects of a driving behavior monitoring device, reference may be made to the above limitations of the driving behavior monitoring method, which are not described herein again. The various modules in the driving behavior monitoring device described above may be implemented in whole or in part by software, hardware, and combinations thereof. The modules may be embedded in a hardware form or may be independent of a processor in the electronic device, or may be stored in a memory in the electronic device in a software form, so that the processor calls and executes operations corresponding to the modules.
An embodiment of the present invention further provides a non-transitory computer storage medium, where a computer executable instruction is stored in the computer storage medium, and the computer executable instruction may execute the driving behavior monitoring method in any of the above method embodiments. The storage medium may be a magnetic Disk, an optical Disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a Flash Memory (Flash Memory), a Hard Disk (Hard Disk Drive, abbreviated as HDD), a Solid State Drive (SSD), or the like; the storage medium may also comprise a combination of memories of the kind described above.
An embodiment of the present invention further provides a computer device, as shown in fig. 3, the computer device may include at least one processor 31, at least one communication interface 32, at least one communication bus 33, and at least one memory 34, where the communication interface 32 may include a Display screen (Display) and a Keyboard (Keyboard), and the optional communication interface 32 may also include a standard wired interface and a standard wireless interface. The Memory 34 may be a Random Access Memory (RAM) or a non-volatile Memory (non-volatile Memory), such as at least one disk Memory. The memory 34 may optionally be at least one memory device located remotely from the processor 31. An application program is stored in the memory 34 and the processor 31 invokes the program code stored in the memory 34 for performing the steps of any of the inventive embodiments described above.
The communication bus 33 may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The communication bus 33 may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in FIG. 3, but that does not indicate only one bus or one type of bus.
The memory 34 may include a volatile memory (RAM), such as a random-access memory (RAM); the memory may also include a non-volatile memory (english: flash memory), such as a Hard Disk Drive (HDD) or a solid-state drive (SSD); the memory 34 may also comprise a combination of the above kinds of memories.
The processor 31 may be a Central Processing Unit (CPU), a Network Processor (NP), or a combination of CPU and NP.
The processor 31 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a Programmable Logic Device (PLD), or a combination thereof. The PLD may be a Complex Programmable Logic Device (CPLD), a field-programmable gate array (FPGA), a General Array Logic (GAL), or any combination thereof.
Optionally, the memory 34 is also used to store program instructions. The processor 31 may invoke program instructions to implement the driving behavior monitoring method as shown in the embodiment of fig. 1 of the present invention.
Claims (8)
1. A driving behavior monitoring method, characterized in that the method comprises:
acquiring driving information of a target vehicle, wherein the driving information comprises one or more of driving information, position information, external environment information and in-vehicle environment information of the target vehicle;
identifying one or more illegal driving scenes generated by the target vehicle in a preset time period according to the driving information of the target vehicle at different moments in the preset time period;
generating a driving score according to each illegal driving scene generated by the target vehicle in the preset time period;
if the driving score is not qualified, sending a driving report to a target object associated with the target vehicle, wherein the driving report comprises a driving behavior improvement item, the driving behavior improvement item is determined according to an illegal driving scene generated in the preset time period, and if the number of times of the illegal driving scene of the target vehicle in the preset time exceeds the set number of times, establishing the driving behavior improvement item aiming at the illegal driving scene;
the illegal driving scenario includes not being a courtesy pedestrian,
according to the driving information of the target vehicle at different moments in a preset time period, recognizing that the target vehicle generates an illegal driving scene in the preset time period, wherein the recognizing comprises the following steps: the external environment information includes panoramic looking around system data, the driving information includes vehicle speed,
determining whether a pedestrian passes through a set area in front of the target vehicle according to the panoramic all-around system data of the target vehicle; the front set area of the target vehicle is a sector area taking the head of the target vehicle as the center of a circle;
if the pedestrian passes through the set area in front of the target vehicle and the speed of the target vehicle is greater than a third preset value, judging that the illegal driving scene generated by the target vehicle is a non-courtesy pedestrian;
the offending driving scenario includes a complex road segment cut-in,
according to the driving information of the target vehicle at different moments in a preset time period, recognizing that the target vehicle generates an illegal driving scene in the preset time period, wherein the recognizing comprises the following steps: the running information includes a vehicle speed, a steering,
judging whether the road section where the target vehicle is located is a complex road section according to the position information of the target vehicle;
if the road condition of the road section where the target vehicle is located is a complex road section,
judging whether the target vehicle is in a overtaking driving state or not according to the speed and the steering of the target vehicle;
if the target vehicle is in a overtaking driving state, judging that the illegal driving scene generated by the target vehicle is a complex road section overtaking;
the position information of the target vehicle is acquired through a GPS module, the GPS module is provided with a GPS system and a map system, the GPS system can accurately acquire the position of the target vehicle, the map system can acquire the road information of the position of the target vehicle according to the position of the target vehicle, and if the road information of the position of the target vehicle is an intersection, a curve or a crosswalk, the position of the target vehicle is judged to be a complex road section.
2. The driving behavior monitoring method according to claim 1, wherein the driving information includes vehicle speed, the illegal driving scenario includes speeding, hard braking,
according to the driving information of the target vehicle at different moments in a preset time period, recognizing that the target vehicle generates an illegal driving scene in the preset time period, wherein the recognizing comprises the following steps:
determining a speed limit value of a road section where the target vehicle is located according to the position information of the target vehicle, and if the ratio of the speed of the target vehicle to the speed limit value is greater than a first preset value, determining that an illegal driving scene generated by the target vehicle is overspeed driving;
and determining the speed reduction rate of the target vehicle in a set time period according to the speeds of the target vehicle at different moments, and if the speed reduction rate of the target vehicle in the set time period is greater than a second preset value, determining that the illegal driving scene generated by the target vehicle is sudden braking.
3. The driving behavior monitoring method according to claim 1, wherein the external environmental information includes panoramic looking around system data, the illegal driving scenario includes driving with a pressed line, robbing a yellow light, occupying an emergency lane,
according to the driving information of the target vehicle at different moments in a preset time period, recognizing that the target vehicle generates an illegal driving scene in the preset time period, wherein the recognizing comprises the following steps:
determining whether the target vehicle is in a line pressing state or not according to the panoramic all-round looking system data of the target vehicle, and if the target vehicle is in the line pressing state, judging that the illegal driving scene generated by the target vehicle is line pressing driving;
determining the color of a traffic light of the target vehicle when the target vehicle passes through the intersection according to the panoramic all-round system data of the target vehicle, and if the color of the traffic light of the target vehicle when the target vehicle passes through the intersection is yellow, judging that an illegal driving scene generated by the target vehicle is a yellow robber;
and determining whether the target vehicle is in an emergency lane according to the panoramic all-round looking system data of the target vehicle, and if so, judging that the illegal driving scene generated by the target vehicle occupies the emergency lane.
4. The driving behavior monitoring method according to claim 1, wherein the in-vehicle environment information includes call information or voice information, the travel information includes a vehicle speed, the illegal driving scenario includes a vehicle making a call,
according to the driving information of the target vehicle at different moments in a preset time period, recognizing that the target vehicle generates an illegal driving scene in the preset time period, wherein the recognizing comprises the following steps:
determining whether the target vehicle is in a call state according to the call information or the voice information of the target vehicle, and determining whether the target vehicle is in a running state according to the speed of the target vehicle;
and if the target vehicle is in a call state and the target vehicle is in a driving state, judging that the illegal driving scene generated by the target vehicle is driving and making a call.
5. The driving behavior monitoring method according to claim 1, wherein generating a driving score according to each illegal driving scene generated by the target vehicle within the preset time period comprises:
determining scores and score coefficient ratios corresponding to the illegal driving scenes;
and calculating the weighted sum of all scores according to the scores corresponding to all illegal driving scenes and the score coefficient ratio, and taking the weighted sum as the driving score.
6. A driving behavior monitoring device, comprising:
the measuring module is used for acquiring the driving information of the target vehicle, wherein the driving information comprises one or more of the driving information, the position information, the external environment information and the in-vehicle environment information of the target vehicle;
the identification module is used for identifying one or more illegal driving scenes generated by the target vehicle in a preset time period according to the driving information of the target vehicle at different moments in the preset time period;
the driving scoring module is used for generating driving scores according to various illegal driving scenes generated by the target vehicle in the preset time period;
the reporting module is used for judging whether the driving score is qualified or not, if the driving score is unqualified, sending a driving report to a target object associated with the target vehicle, wherein the driving report comprises a driving behavior improvement item, the driving behavior improvement item is determined according to an illegal driving scene generated in the preset time period, and if the number of times of the illegal driving scene of the target vehicle in the preset time exceeds the set number of times, establishing the driving behavior improvement item aiming at the illegal driving scene;
the illegal driving scenario includes not being a courtesy pedestrian,
according to the driving information of the target vehicle at different moments in a preset time period, recognizing that the target vehicle generates an illegal driving scene in the preset time period, wherein the recognizing comprises the following steps: the external environment information includes panoramic looking around system data, the driving information includes vehicle speed,
determining whether a pedestrian passes through a set area in front of the target vehicle according to the panoramic all-around system data of the target vehicle; the front set area of the target vehicle is a fan-shaped area taking the head of the target vehicle as the center of a circle;
if a pedestrian passes through a set area in front of the target vehicle and the speed of the target vehicle is greater than a third preset value, judging that the illegal driving scene generated by the target vehicle is a nonprofitable pedestrian;
the illegal driving scenario includes a complex road segment overtaking,
according to the driving information of the target vehicle at different moments in a preset time period, recognizing that the target vehicle generates an illegal driving scene in the preset time period, wherein the recognizing comprises the following steps: the running information includes a vehicle speed, a steering,
judging whether the road section where the target vehicle is located is a complex road section according to the position information of the target vehicle;
if the road condition of the road section where the target vehicle is located is a complex road section,
judging whether the target vehicle is in a overtaking driving state or not according to the speed and the steering of the target vehicle;
if the target vehicle is in a overtaking driving state, judging that the illegal driving scene generated by the target vehicle is a complex road section overtaking;
the position information of the target vehicle is acquired through a GPS module, the GPS module is provided with a GPS system and a map system, the GPS system can accurately acquire the position of the target vehicle, the map system can acquire the road information of the position of the target vehicle according to the position of the target vehicle, and if the road information of the position of the target vehicle is an intersection, a curve or a crosswalk, the position of the target vehicle is judged to be a complex road section.
7. A computer-readable storage medium storing computer instructions which, when executed by a processor, implement a driving behavior monitoring method as claimed in any one of claims 1-5.
8. A computer device, comprising: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to perform the driving behavior monitoring method of any of claims 1-5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111562976.4A CN113997940B (en) | 2021-12-20 | 2021-12-20 | Driving behavior monitoring method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111562976.4A CN113997940B (en) | 2021-12-20 | 2021-12-20 | Driving behavior monitoring method and device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113997940A CN113997940A (en) | 2022-02-01 |
| CN113997940B true CN113997940B (en) | 2022-12-16 |
Family
ID=79931888
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111562976.4A Active CN113997940B (en) | 2021-12-20 | 2021-12-20 | Driving behavior monitoring method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113997940B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114782926B (en) * | 2022-06-17 | 2022-08-26 | 清华大学 | Driving scene recognition method, device, equipment, storage medium and program product |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106297290A (en) * | 2016-08-27 | 2017-01-04 | 时空链（北京）科技有限公司 | A kind of driving behavior processing method, mobile unit and cloud server |
| CN110276953A (en) * | 2019-06-28 | 2019-09-24 | 青岛无车承运服务中心有限公司 | Rule-breaking vehicle travel risk analysis method based on BEI-DOU position system |
| CN113291313A (en) * | 2021-06-30 | 2021-08-24 | 三一专用汽车有限责任公司 | Driving behavior early warning method and device and operation machine |
Family Cites Families (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105730370A (en) * | 2014-12-11 | 2016-07-06 | 鸿富锦精密工业（深圳）有限公司 | Automobile driving system and control method |
| CN105894609A (en) * | 2015-11-11 | 2016-08-24 | 乐卡汽车智能科技（北京）有限公司 | Data processing method and device and car insurance system |
| CN106004883B (en) * | 2016-05-24 | 2018-12-11 | 北京小米移动软件有限公司 | The method and device that rule-breaking vehicle is reminded |
| CN107563931A (en) * | 2017-08-16 | 2018-01-09 | 上海经达信息科技股份有限公司 | A kind of real-time driving behavior quality appraisal procedure of vehicle based on the Big Dipper or gps data |
| CN108482382B (en) * | 2018-03-27 | 2020-08-04 | 斑马网络技术有限公司 | Driving technology scoring method, device, storage medium and vehicle |
| CN108647708A (en) * | 2018-04-28 | 2018-10-12 | 清华-伯克利深圳学院筹备办公室 | Driver evaluation's method, apparatus, equipment and storage medium |
| CN111833480B (en) * | 2019-04-12 | 2022-04-15 | 比亚迪股份有限公司 | Driving behavior detection method and device and vehicle |
| CN110276954A (en) * | 2019-06-28 | 2019-09-24 | 青岛无车承运服务中心有限公司 | Vehicle driving behavior integration methods of marking based on BEI-DOU position system |
| CN111062240A (en) * | 2019-10-16 | 2020-04-24 | 中国平安财产保险股份有限公司 | Method and device for monitoring automobile driving safety, computer equipment and storage medium |
| CN113085871A (en) * | 2019-12-23 | 2021-07-09 | 祥云平台信息技术盐城有限公司 | Driving behavior safety assessment system |
| CN111361568A (en) * | 2020-03-10 | 2020-07-03 | 广州通达汽车电气股份有限公司 | Driver driving behavior evaluation method, device, equipment and storage medium |
| CN111353471A (en) * | 2020-03-17 | 2020-06-30 | 北京百度网讯科技有限公司 | Safe driving monitoring method, device, equipment and readable storage medium |
| CN112150668A (en) * | 2020-09-25 | 2020-12-29 | 深圳市元征科技股份有限公司 | Driving behavior reminding method and device |
-
2021
- 2021-12-20 CN CN202111562976.4A patent/CN113997940B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106297290A (en) * | 2016-08-27 | 2017-01-04 | 时空链（北京）科技有限公司 | A kind of driving behavior processing method, mobile unit and cloud server |
| CN110276953A (en) * | 2019-06-28 | 2019-09-24 | 青岛无车承运服务中心有限公司 | Rule-breaking vehicle travel risk analysis method based on BEI-DOU position system |
| CN113291313A (en) * | 2021-06-30 | 2021-08-24 | 三一专用汽车有限责任公司 | Driving behavior early warning method and device and operation machine |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113997940A (en) | 2022-02-01 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| EP3533681B1 (en) | Method for detecting safety of driving behavior, apparatus and storage medium | |
| CN108022450B (en) | Auxiliary driving method based on cellular network and traffic control unit | |
| CN110164130B (en) | Traffic incident detection method, device, equipment and storage medium | |
| US9870708B2 (en) | Methods for enabling safe tailgating by a vehicle and devices thereof | |
| CN107220583B (en) | Method and device for recognizing traffic signs | |
| CN112885145B (en) | Crossing risk early warning method and device | |
| CN101612925B (en) | Method for determining driving demand value | |
| CN111291916B (en) | Driving behavior safety prediction method and device, electronic equipment and storage medium | |
| US10755565B2 (en) | Prioritized vehicle messaging | |
| US20220266842A1 (en) | Method and device for monitoring driving behavior risk degree | |
| CN113256974A (en) | Vehicle violation early warning method, device, equipment and storage medium | |
| CN113997940B (en) | Driving behavior monitoring method and device | |
| EP2913239B1 (en) | Method and unit for managing following space | |
| WO2021104833A1 (en) | Method and device for promoting driving safety of vehicle | |
| CN110634324A (en) | Vehicle-mounted terminal based reminding method and system for courtesy pedestrians and vehicle-mounted terminal | |
| CN108682174B (en) | Driving early warning method and device and electronic equipment | |
| CN111145554B (en) | Scene positioning method and device based on automatic driving AEB | |
| CN112017456A (en) | Early warning method, vehicle-mounted terminal and computer readable storage medium | |
| CN114664085A (en) | Dangerous road section reminding method and device, electronic equipment and medium | |
| CN115188191A (en) | Vehicle safe driving control method and device and vehicle | |
| CN114162129A (en) | Vehicle collision responsibility determination method, device and system | |
| CN115966100B (en) | Driving safety control method and system | |
| CN117037544A (en) | Pedestrian traffic early warning method and device, vehicle-mounted terminal and storage medium | |
| CN116106839B (en) | Vehicle-mounted radar reliability detection method, device, equipment and storage medium | |
| CN112185106B (en) | Unreasonable speed limit sign screening method and device, storage medium and terminal |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |