Vehicle operation state real-time monitoring and early warning system

Abstract

The invention relates to the field of vehicle operation monitoring, in particular to a vehicle operation state real-time monitoring and early warning system. According to the method, the specified speed limit of the road where the current position of the monitored vehicle is located is obtained, and the allowed speed limit is determined in combination with the road type and environmental parameters of the current position; if the current driving speed exceeds the allowed speed limit, it is judged that an overspeed behavior exists, and an early warning is given out; on the contrary, the running speed and the vehicle distance of the vehicles around the monitored vehicle are obtained, whether the running speed of the monitored vehicle is abnormal or not is judged by combining the current running speed of the monitored vehicle, and if the running speed is abnormal, the braking deceleration of each braking of the monitored vehicle in the recent historical time period and the vehicle distance of the front vehicle are obtained; and preliminarily judging whether the driving state of the monitored vehicle is abnormal or not, and analyzing and judging whether a prompt needs to be sent out or not according to the distance and the driving speed of the front vehicle of each braking recorded by the historical safe driving record of the driver. And the practicability and reliability of early warning are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vehicle operation monitoring, and relates to a vehicle operation state real-time monitoring and early warning system. BACKGROUND

[0003] The prior art such as Chinese patent publication CN117275235B discloses a vehicle monitoring method and system, which collects the speed, acceleration and steering angle data of the vehicle in real time, analyzes the driving state of the vehicle based on the basic vehicle data set, and uses a machine learning algorithm of support vector machine or decision tree to identify abnormal driving behavior and generate an abnormal driving report.

[0004] However, the prior art has the following problems: 1. Only the vehicle data set is analyzed, without considering adjusting the specified speed limit according to the road type and environmental parameters, resulting in a high speed threshold in the early warning determination, low adaptability to the actual situation, and ignoring the potential risk of low braking efficiency at high driving speed in bad weather.

[0005] 2. The existing technology mostly analyzes and determines abnormal driving behavior only according to vehicle driving data, without considering analyzing recent continuous driving behavior in combination with the driving habits of the driver to determine whether there is fatigue driving, which may cause misjudgment of normal driving and send false alarms. SUMMARY

[0006] The present application aims to solve the problems of the prior art and provides a vehicle operation state real-time monitoring and early warning system.

[0007] To achieve the above-mentioned purpose, the present application adopts the following technical solution: a vehicle operation state real-time monitoring and early warning system, comprising: a speed limit correction module, an overspeed risk determination module, a driving state abnormality determination module and a state early warning module. The connection relationship between the modules is: the speed limit correction module is connected with the overspeed risk determination module, and the driving state abnormality determination module is connected with the state early warning module and the overspeed risk determination module.

[0008] Speed limit correction module: obtain the specified speed limit of the road where the monitored vehicle is currently located, determine the safe driving speed in combination with the road type of the current location and the current location environmental parameters.

[0009] Overspeed risk determination module: real-time acquisition of the current driving speed of the monitored vehicle, if the current driving speed exceeds the safe driving speed, it is determined that the monitored vehicle has overspeed behavior and sends a warning reminder; otherwise, the driving speed and the distance of the vehicles around the monitored vehicle are obtained by the vehicle-mounted radar.

[0010] Driving state abnormality determination module: according to the monitoring vehicle current driving speed, combined with the driving speed of surrounding vehicles to determine whether the monitoring vehicle has driving speed abnormality, if there is driving speed abnormality, the monitoring vehicle braking deceleration and the front vehicle distance of each braking in the recent history period are obtained, and whether the monitoring vehicle has driving state abnormality is preliminarily determined.

[0011] State early warning module: if the monitoring vehicle has driving state abnormality, the front vehicle distance and driving speed of each braking in the historical safe driving record of the driver are analyzed to determine whether a reminder needs to be sent.

[0012] Compared with the prior art, the present application has the following beneficial effects: (1) the present application determines the safe driving speed by obtaining the specified speed limit of the road where the monitoring vehicle is located, combined with the road type of the current position and the current position environment parameter, realizes the correction of the speed limit according to the actual transportation situation and the weather condition, and makes the corrected speed limit more suitable for the safety boundary of the actual driving of the vehicle.

[0013] (2) the present application preliminarily determines whether the monitoring vehicle has fatigue and other driving state abnormality by monitoring the current driving speed of the monitoring vehicle, combined with the driving speed of surrounding vehicles to determine whether the monitoring vehicle has driving speed abnormality, and the braking deceleration and the front vehicle distance of each braking of the monitoring vehicle with driving speed abnormality in the recent history period, avoids triggering frequent early warning due to occasional and reasonable speed fluctuation, and improves the practicability and accuracy of the early warning system.

[0014] (3) the present application analyzes whether a reminder needs to be sent by the front vehicle distance and driving speed of each braking in the historical safe driving record of the driver if the monitoring vehicle has driving state abnormality, improves the early warning accuracy by combining the historical driving record of the driver and fitting the individual driving habits of the driver, and avoids the interference of false early warning on driving. DETAILED DESCRIPTION

[0015] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiment description. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creating any creative labor.

[0016] Figure 1 It is a schematic diagram of the system module connection of the present application.

[0017] Figure 2 It is a specific step flowchart of the speed limit correction module in the present application.

[0018] Figure 3 It is a specific flowchart of preliminarily determining whether there is driving state abnormality in the present application.

[0019] Figure 4 The specific flowchart for correcting the preliminary determination result in the application. DETAILED DESCRIPTION

[0020] Various exemplary embodiments of the present application will now be described in detail with reference to the accompanying drawings. Note that the relative arrangement of the components and steps set forth in the examples, numerical expressions, and numerical values are not limiting of the scope of the present application unless specifically stated otherwise. Also, it should be understood that the dimensions of the various portions shown in the drawings are not drawn to scale for the sake of convenience in description.

[0021] The following description of at least one example embodiment is merely exemplary in nature and is in no way intended to limit the scope of the application its application or uses. Techniques, methods, and devices known to those of ordinary skill in the art can not be discussed in detail, but should be understood to be part of the specification, where appropriate.

[0022] In all examples shown and discussed herein, any specific values should be interpreted as merely exemplary, and not as a limitation. Thus, other examples of the example embodiments can have different values.

[0023] The application determines the safe driving speed by acquiring the specified speed limit of the road where the monitored vehicle is currently located, in combination with the road type and environmental parameters of the current location. If the current driving speed exceeds the safe driving speed, it is determined that there is an overspeed behavior and a warning is issued. Otherwise, the driving speed of the vehicle around the monitored vehicle is acquired by the vehicle-mounted radar, in combination with the current driving speed of the monitored vehicle, to determine whether the monitored vehicle has an abnormal driving speed. If there is an abnormal driving speed, the braking deceleration and the front vehicle distance of each braking in the recent historical period of the monitored vehicle are acquired, to preliminarily determine whether the monitored vehicle has an abnormal driving state. In addition, the front vehicle distance and driving speed of each braking in the historical safe driving record of the driver are analyzed to determine whether a warning is needed. The practicability and reliability of the warning are improved.

[0024] Referring to Figure 1 As shown in the figure, the application provides a vehicle operation state real-time monitoring and warning system, which comprises a speed limit correction module, an overspeed risk determination module, a driving state abnormality determination module, and a state warning module. The connection relationship between the modules is that the speed limit correction module is connected with the overspeed risk determination module, and the driving state abnormality determination module is connected with the state warning module and the overspeed risk determination module.

[0025] The speed limit correction module acquires the specified speed limit of the road where the monitored vehicle is currently located, in combination with the road type and the environmental parameters of the current location, to determine the safe driving speed.

[0026] Considering that in the long-distance transportation process, different road types such as slopes will affect the driving speed, the greater the slope, the more difficult the braking, and if the speed is high, the probability of accidents will increase, and the probability of accidents can be reduced by analyzing the excess kinetic energy under the influence of road characteristics to modify the specified speed limit, so as to keep the driving speed not higher than the specified speed limit in the process of descending by reducing the speed in the process of descending.

[0027] In addition, different weather types and visibility will also have different effects on vehicle driving, and the lower the visibility, the higher the probability of vehicle accidents, so the speed is reduced to ensure driving safety.

[0028] Based on this, as shown in the speed limit correction module, the specific content includes: S1, based on the current position of the monitored vehicle, the corresponding road type and its characteristic parameters are matched from the vehicle operation background database. Figure 2

[0029] S2, according to the characteristic parameters of the current position, the additional kinetic energy generated by the monitored vehicle under the influence of the corresponding road type is calculated.

[0030] S3, the additional kinetic energy and the specified speed limit of the current position are substituted into the kinetic energy theorem transformation formula to calculate the initial safe driving speed, and the standard specified speed limit corresponding to the environmental parameters of the current position is analyzed and determined to determine the safe driving speed.

[0031] In one preferred example of the present application, the road type data is retrieved from the vehicle operation background database, including normal road sections, downhill road sections, uphill road sections, etc. When the road type is normal road section and uphill road section, no additional kinetic energy is generated due to the road characteristic parameters, so the initial safe driving speed is the specified speed limit. If the road type of the current position of the monitored vehicle is downhill, the characteristic parameters corresponding to each road type are extracted from the vehicle operation background database, including road slope angle, slope length, and the additional kinetic energy generated by the slope is calculated. The initial safe driving speed is obtained by substituting it into the kinetic energy theorem transformation formula.

[0032] The kinetic energy theorem transformation formula is as follows: .

[0033] Among them represents the additional kinetic energy generated by the slope, represents the total weight of the monitored vehicle, respectively represent the specified speed limit and the initial safe driving speed.

[0034] Among them .

[0035] represents the acceleration of gravity, ​representing the slope length, representing the slope angle.

[0036] In the specific example of the present application, the determination method of the safe driving speed comprises: according to the weather type and the visibility in the environmental parameters of the current position, matching the corresponding standard speed limit from the set standard speed limit corresponding to each weather type under each visibility.

[0037] The standard speed limit refers to the standard speed limit published by the traffic management department in real time according to the environmental parameters, for example, the speed limit is 30km / h when the visibility is less than 50m in snow.

[0038] The standard speed limit is compared with the initial safe driving speed, if the initial safe driving speed is greater than the standard speed limit, the standard speed limit is recorded as the safe driving speed, otherwise, the initial safe driving speed is recorded as the safe driving speed.

[0039] The present application determines the safe driving speed by acquiring the speed limit of the road where the monitoring vehicle is currently located, combining the road type of the current position and the environmental parameters of the current position, realizes the correction of the speed limit according to the actual transportation situation and the weather condition, and makes the corrected speed limit more suitable for the safety boundary of the actual driving of the vehicle.

[0040] The overspeed risk judgment module: the current driving speed of the monitoring vehicle is collected in real time, if the current driving speed exceeds the safe driving speed, it is judged that the monitoring vehicle has overspeed behavior and a warning is issued; otherwise, the driving speed and the distance of the surrounding vehicles of the monitoring vehicle are acquired based on the vehicle-mounted radar.

[0041] Specifically, based on the detection signal emitted by the vehicle-mounted radar and the echo signal reflected by the target vehicle, the signal propagation time difference is extracted, and the distance between the monitoring vehicle and the target vehicle is directly calculated by combining the electromagnetic wave propagation speed.

[0042] Based on the Doppler frequency shift characteristics of the echo signal, the relative radial speed of each surrounding vehicle is calculated through the signal frequency shift, wavelength and Doppler frequency shift speed formula , wherein represents the electromagnetic wave signal frequency shift, represents the electromagnetic wave wavelength. The lateral velocity is calculated by extracting the lateral position difference of the surrounding vehicles and the monitoring vehicle in adjacent frames, and calculating the ratio of the lateral position difference in adjacent frames to the frame time interval.

[0043] The radial speed of the monitoring vehicle is calculated by the product of the line-of-sight angle cosine value between the monitoring vehicle and each surrounding vehicle and the driving speed of the monitoring vehicle, the absolute radial speed of the surrounding vehicle is calculated according to the difference between the relative radial speed and the radial speed of the monitoring vehicle, and the driving speed of the surrounding vehicle is obtained according to the synthesis vector of the absolute radial speed and the lateral velocity.

[0044] The application realizes accurate determination and timely warning of overspeed behavior, and ensures vehicle driving safety.

[0045] The driving state abnormality determination module: according to the monitoring vehicle current driving speed, the driving speed of the surrounding vehicles is judged to determine whether the monitoring vehicle has driving speed abnormality, if the driving speed abnormality exists, the braking deceleration and the front vehicle distance of each braking of the monitoring vehicle in the recent history period are obtained, and the driving state abnormality of the monitoring vehicle is preliminarily determined.

[0046] The judgment method of whether the monitoring vehicle has driving speed abnormality includes: first, the vehicle type and driving speed of the surrounding vehicles in the radar monitoring range are obtained according to the vehicle-mounted radar of the monitoring vehicle.

[0047] Specifically, the outer contour image, height and width of each surrounding vehicle are extracted by the vehicle-mounted radar, which are compared and matched with the vehicle type feature library to determine the vehicle type of each surrounding vehicle.

[0048] Secondly, the driving speed of all same-type vehicles with the same type as the monitoring vehicle is screened from the surrounding vehicles according to the vehicle type of the monitoring vehicle, and the normal maximum speed threshold and the normal minimum speed threshold are obtained by combining the driving speed of other surrounding vehicles.

[0049] The acquisition method of the normal maximum speed threshold and the normal minimum speed threshold is: all same-lane vehicles with the same lane as the current driving lane of the monitoring vehicle are screened from the surrounding vehicles.

[0050] Wherein, the driving rules and traffic density of different lanes may be different, and the driving state of the same-lane vehicles can better reflect the normal driving environment of the lane where the monitoring vehicle is located, and the driving speed of the same-lane vehicles is an important basis for determining the normal driving speed range of the monitoring vehicle.

[0051] The driving speed of each same-lane same-type vehicle with the same type as the monitoring vehicle is obtained according to the type of each same-lane vehicle, and the mean value is recorded as the first speed threshold.

[0052] Wherein, the driving speed of vehicles of different types is different, so by analyzing the driving speed of the same-lane vehicles of the same type, the driving speed of the monitoring vehicle can be more accurately specified.

[0053] The vehicle with the closest distance to the monitoring vehicle among all same-lane vehicles is recorded as the front vehicle, and the driving speed of the front vehicle is extracted from the driving speed of the surrounding vehicles and recorded as the second speed threshold.

[0054] Wherein, the speed of the front vehicle directly affects the monitoring vehicle, if the speed of the monitoring vehicle is continuously higher than that of the front vehicle, it will cause a rear-end collision accident, so the speed of the front vehicle is also an important basis for determining the normal driving speed range of the monitoring vehicle.

[0055] extracting the same type of vehicle in the adjacent lane of the monitoring vehicle from all the same type of vehicles, obtaining the distance between the same type of vehicle in each adjacent lane and the monitoring vehicle, and recording the driving speed of the same type of vehicle in the adjacent lane with the smallest distance as a third speed threshold.

[0056] The same type of vehicle closest to the adjacent lane may be a same type of vehicle preparing to overtake, and at this time, if the driving speed of the monitoring vehicle continues to be higher than the same type of overtaking vehicle, a traffic accident may be caused.

[0057] The minimum value of the first speed threshold, the second speed threshold and the third speed threshold is recorded as a normal maximum speed threshold.

[0058] The minimum value of the driving speed of all the same type of vehicles is recorded as a normal minimum speed threshold, so as to avoid that the speed of the monitoring vehicle is too low to affect the road passing efficiency.

[0059] The normal maximum speed threshold and the normal minimum speed threshold form a normal driving speed range.

[0060] If the current driving speed of the monitoring vehicle is not in the normal driving speed range, it is determined that the driving speed of the monitoring vehicle is abnormal, otherwise it is determined that the driving speed of the monitoring vehicle is not abnormal.

[0061] Considering that only a single driving speed abnormality cannot directly determine that the driving state of the driver is abnormal, the braking deceleration in the historical setting driving time and the vehicle distance before braking can be comprehensively analyzed to determine whether the driver has a driving state abnormality such as inattention or fatigue driving.

[0062] Based on this, as shown in the preferred example of the present application, the specific method for preliminarily determining whether the monitoring vehicle has a driving state abnormality comprises: Figure 3 S31, obtaining the braking deceleration of each braking record of the monitoring vehicle in the recent history period from the vehicle operation background database, and the vehicle distance between the monitoring vehicle and the preceding vehicle at each time point in the setting time window before the braking start, which is recorded as the preceding vehicle distance.

[0063] In specific embodiments of the present application, the recent history period is set to be within 1 hour recently, and the implementer can also set other values, but the time effectiveness should not be reduced by too large; the setting time window can be within 5 minutes before braking, and the implementer can also set other specific values.

[0064] S32, comparing the braking deceleration of each braking behavior in the recent history period with the preset braking deceleration threshold corresponding to the emergency braking of the vehicle, and if the braking deceleration of a certain braking behavior is greater than the braking deceleration threshold, the braking behavior is recorded as an emergency braking behavior.

[0065] The braking deceleration threshold value can be set according to the relevant range stipulated by the traffic management department, and in the specific embodiment of the present application, the braking deceleration threshold value is set to 3 m / s 2 .

[0066] S33, extracting the front vehicle speed at each time point within the set time window before the braking of each emergency braking behavior of the monitored vehicle from the vehicle operation background database, and calculating the braking deceleration of the front vehicle at each time point according to the speed at adjacent time points. Specifically, the braking deceleration of the front vehicle is calculated by the ratio of the speed difference between adjacent time points and the time interval between adjacent time points.

[0067] S34, analyzing whether each emergency braking behavior of the monitored vehicle is reasonable according to the front vehicle distance and the front vehicle braking deceleration at each time point within the set time window before braking.

[0068] The analysis method of whether the emergency braking behavior of the monitored vehicle is reasonable includes: constructing a front vehicle distance change curve with each time point in the set time window as the x-axis and the corresponding front vehicle distance as the y-axis.

[0069] When the front vehicle distance at a certain time point in the front vehicle distance change curve is less than the specified safe distance, it is determined whether the front vehicle belongs to an emergency braking behavior according to the front vehicle braking deceleration at the time point.

[0070] It should be noted that the specified safe distance is the standard safe distance stipulated for different driving speeds on the highway. For example, when the driving speed is greater than 100 km / h, the specified safe distance is 100 m, and when the speed is less than 100 km / h, the specified distance is 50 m.

[0071] If the front vehicle belongs to an emergency braking behavior or the front vehicle distance change curve has an abnormal change in distance, it is determined that the emergency braking behavior of the monitored vehicle is reasonable.

[0072] It can be understood that if the front vehicle is in an emergency braking state, it can be explained that the emergency braking of the monitored vehicle is to avoid rear-end collision, which is a reasonable behavior. If the front vehicle distance change curve has an abnormal change in distance, it means that the object of the front vehicle has changed, and there may be a queue, so the emergency braking of the monitored vehicle is also a reasonable behavior.

[0073] The specific determination method of the front vehicle distance change curve having an abnormal change in distance is that the distance difference between each time point in the front vehicle distance change curve and the distance at the previous time point is recorded as the distance change amount.

[0074] The absolute difference value between the distance change amount at each time point and the distance change amount at the previous time point is recorded as the second-order forward difference.

[0075] If the time point corresponding to the maximum value of the second-order forward difference corresponds to a negative value of the vehicle distance change amount, and the vehicle distance of all time points after the time point is less than the vehicle distance of all time points before the time point, the vehicle distance change curve has a vehicle distance change anomaly. It can be judged that the vehicle distance of the time point changes obviously, and there is a situation of being jammed.

[0076] S35, record the unreasonable emergency braking behavior as an abnormal braking behavior, count the number of abnormal braking behaviors of the monitoring vehicle in the recent history period, and if the abnormal braking behaviors exceed the set number, it is preliminarily determined that there is a driving state anomaly.

[0077] In the specific examples of the present application, the specific method of setting the number of times can be achieved by collecting the number of abnormal braking behaviors of each driver in each hour within a year when there is a fatigue driving condition, and calculating the second average value as the set number. In the present example, if the abnormal braking behavior reaches 2 or more times, it is preliminarily determined that there is a driving state anomaly, and the implementer can also set other specific values.

[0078] The present application monitors the current driving speed of the vehicle, judges whether the monitoring vehicle has a driving speed anomaly in combination with the driving speed of the surrounding vehicles, preliminarily determines whether the monitoring vehicle has a fatigue driving state anomaly by monitoring the braking deceleration and the vehicle distance of each braking of the monitoring vehicle with driving speed anomaly in the recent history period, avoids triggering frequent early warning due to occasional and reasonable speed fluctuations, and improves the practicability and accuracy of the early warning system.

[0079] State early warning module: if the monitoring vehicle has a driving state anomaly, then according to the vehicle distance and driving speed of each braking in the historical safe driving record of the driver, analyze and determine whether to issue a reminder.

[0080] As shown in Figure 4 The specific method of analyzing whether to issue a reminder includes: W1, extracting the historical safe driving records of the driver with the same current environmental parameters from the vehicle operation background database, and screening the average driving speed in each historical time period with the same length as the recent history period.

[0081] Specifically, in the specific embodiments of the present application, the historical safe driving records of the driver within a year are extracted, and the average driving speed of the driver within 1 hour is obtained.

[0082] W2, according to the average driving speed in the recent history period, screen all vehicle distances in each historical time period with the same average driving speed as the average driving speed in the recent history period, and form a historical vehicle distance group with all vehicle distances in each historical time period.

[0083] W3, monitoring the habitual driving headway range of the driver of the monitored vehicle at the corresponding average driving speed according to the headway distribution analysis of the historical headway group.

[0084] In specific examples of the present application, the specific method for obtaining the habitual driving headway range corresponding to each braking initial speed interval comprises: eliminating outliers of the headway of the historical headway group, fitting a kernel density curve corresponding to the historical headway group by using kernel density estimation method on the remaining headways after eliminating the outliers, and obtaining the peak value of the kernel density curve.

[0085] Specifically, the outliers in each historical headway group are eliminated by using the quartile method, the headways in each historical headway group are arranged in ascending order, the 25th percentile headway is recorded as the first quantile, the 75th percentile headway is recorded as the third quantile, the difference between the first quantile and the third quantile is calculated and recorded as the interquartile range, and the first quantile plus 1.5 times the interquartile range is recorded as the minimum boundary, wherein 1.5 is a set value in the existing quartile method.

[0086] In addition, it should be further pointed out that the specific steps for fitting the kernel density curve corresponding to the historical headway group are as follows: the remaining headways in the historical headway group are used as sample points, a Gaussian kernel function is used as the kernel function for kernel density estimation, the bandwidth is automatically determined by using Scott's rule, the bandwidth and the sample points are substituted into the kernel function to calculate the influence weight of each sample point, and the influence weight of each sample point, the bandwidth and the number of sample points are substituted into the kernel density estimation value calculation formula to obtain each kernel density estimation value.

[0087] The kernel density estimation curve is formed by connecting the points of each kernel density estimation value, and the headway corresponding to the maximum kernel density estimation value is recorded as the peak value. The Gaussian kernel function, Scott's rule and the kernel density estimation value calculation formula are all prior art, and the specific calculation formula will not be described herein.

[0088] The standard deviation of the historical headway group is calculated, the difference between the peak value and the standard deviation is taken as the minimum value of the habitual driving headway range, and the sum of the peak value and the standard deviation is taken as the maximum value of the habitual driving headway range.

[0089] The minimum value and the maximum value of the habitual driving headway range form the habitual driving headway range of the driver of the monitored vehicle at the corresponding average driving speed.

[0090] The headway corresponding to the peak value of the kernel density curve of each historical headway group is taken as the core, and the habitual driving headway range of the driver at the corresponding average driving speed is finally obtained by expanding the range through the standard deviation, which can reflect the headway control preference of the driver at the driving speed.

[0091] W4, if the preceding vehicle distance at the start of the abnormal braking behavior is less than the minimum value of the corresponding habitual driving distance range, a fatigue driving related reminder is issued.

[0092] W5, on the contrary, if the preceding vehicle distance at the start of each abnormal braking behavior is within the habitual driving distance range of the driver, it is determined that the corresponding preceding vehicle distance of each abnormal braking behavior is the driving habit of the driver, and no related reminder is issued.

[0093] The present application analyzes and determines whether a reminder needs to be issued according to the preceding vehicle distance and driving speed of each braking in the historical safe driving record of the driver when the monitored vehicle has a driving state abnormality, improves the warning accuracy by combining the historical driving record of the driver and fitting the individual driving habit of the driver, and avoids the interference of false warning on driving.

[0094] The above embodiments can be realized wholly or partially by software, hardware, firmware or any combination thereof. When realized by software, the above embodiments can be realized in the form of a computer program product, wholly or partially.

[0095] Those skilled in the art can realize that the modules and algorithm steps of the examples described in combination with the embodiments disclosed herein can be realized by electronic hardware or a combination of computer software and electronic hardware. Whether the functions are realized in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0096] In addition, the functional modules in each embodiment of the present application can be integrated in one processing module, or each module can exist physically alone, or two or more modules can be integrated in one module.

[0097] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any skilled person in the art can easily think of changes or replacements within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

[0098] Finally, the above is only a preferred embodiment of the present application and is not used to limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.

Claims

1. A real-time monitoring and early warning system for vehicle operating status, characterized in that, include: The speed limit correction module obtains the speed limit of the road where the monitored vehicle is currently located, and determines the safe driving speed by combining the road type and environmental parameters of the current location. The speeding risk assessment module collects and monitors the current speed of the vehicle in real time. If the current speed exceeds the safe driving speed, it determines that the monitored vehicle is speeding and issues a warning. Conversely, the vehicle's radar can be used to obtain information on the speed and distance of vehicles around the monitored vehicle. The abnormal driving status determination module determines whether the monitored vehicle has an abnormal driving speed based on the current driving speed of the monitored vehicle and the driving speed of surrounding vehicles. If an abnormal driving speed is found, the module obtains the braking deceleration and distance to the vehicle in front of the monitored vehicle during each braking in the recent historical period to preliminarily determine whether the monitored vehicle has an abnormal driving status. The status warning module analyzes and determines whether to issue a warning if the monitored vehicle has an abnormal driving status, based on the distance to the vehicle in front and the driving speed during each braking in the driver's historical safe driving record.

2. The vehicle operation status real-time monitoring and early warning system according to claim 1, characterized in that, The specific contents of the speed limit correction module include: Based on the current location of the monitored vehicle, the system matches the corresponding road type and its characteristic parameters from the vehicle operation backend database. Calculate the additional kinetic energy generated by the monitored vehicle under the influence of the corresponding road type based on the characteristic parameters of the current location; Substitute the additional kinetic energy and the speed limit at the current location into the modified formula of the kinetic energy theorem to calculate the initial safe driving speed. Combine this with the standard speed limit corresponding to the environmental parameters at the current location to analyze and determine the safe driving speed.

3. The vehicle operation status real-time monitoring and early warning system according to claim 2, characterized in that, The method for determining the safe driving speed includes: Based on the weather type and visibility in the environmental parameters of the current location, match the corresponding standard speed limit from the set standard speed limits for each weather type and visibility level; The standard speed limit is compared with the initial safe driving speed. If the initial safe driving speed is greater than the standard speed limit, the standard speed limit is recorded as the safe driving speed; otherwise, the initial safe driving speed is recorded as the safe driving speed.

4. The vehicle operation status real-time monitoring and early warning system according to claim 1, characterized in that, The methods for determining whether the monitored vehicle has abnormal driving speed include: The vehicle type and speed of surrounding vehicles within the radar monitoring range are obtained from the vehicle's onboard radar. Based on the vehicle type of the monitored vehicle, the driving speed of all vehicles of the same type as the monitored vehicle is selected from the surrounding vehicles. Combined with the driving speed analysis of other surrounding vehicles, the normal maximum speed threshold and normal minimum speed threshold are obtained. The normal driving speed range is formed by combining the normal maximum speed threshold and the normal minimum speed threshold. If the current speed of the monitored vehicle is not within the normal driving speed range, the vehicle speed is determined to be abnormal; otherwise, the vehicle speed is determined to be normal.

5. A real-time monitoring and early warning system for vehicle operating status according to claim 4, characterized in that, The method for obtaining the normal maximum speed threshold and the normal minimum speed threshold is as follows: Select all vehicles in the same lane as the vehicle currently traveling in the surrounding area; Based on the vehicle type in each lane, obtain the driving speed of each vehicle of the same type in the same lane as the monitored vehicle type, and record the average value as the first speed threshold. The vehicle closest to the monitored vehicle among all vehicles in the same lane is recorded as the vehicle in front. The speed of the vehicle in front is extracted from the speed of the surrounding vehicles and recorded as the second speed threshold. Extract vehicles of the same type from the adjacent lanes of the monitored vehicle from all vehicles of the same type, obtain the distance between the vehicles of the same type in each adjacent lane and the monitored vehicle, and record the speed of the vehicles of the same type in the adjacent lane with the smallest distance as the third speed threshold. The minimum value among the first speed threshold, the second speed threshold, and the third speed threshold is recorded as the normal maximum speed threshold. The minimum speed of all vehicles of the same type is recorded as the normal minimum speed threshold.

6. The vehicle operation status real-time monitoring and early warning system according to claim 5, characterized in that, The specific methods for initially determining whether the monitored vehicle has an abnormal driving status include: Retrieve the braking deceleration of each braking behavior of the monitored vehicle in recent historical periods from the vehicle operation backend database, as well as the distance between the monitored vehicle and the vehicle in front at each time point within the set time window before braking begins, and record it as the distance to the vehicle in front. The braking deceleration of each braking behavior in the recent historical period is compared with the preset braking deceleration threshold corresponding to the vehicle during emergency braking. If the braking deceleration of a certain braking behavior is greater than the braking deceleration threshold, the braking behavior is recorded as an emergency braking behavior. Extract the speed of the preceding vehicle at each time point within a set time window before each emergency braking action from the vehicle operation backend database, and calculate the braking deceleration of the preceding vehicle at each time point based on the speed of the preceding vehicle at adjacent time points. Based on the distance to the preceding vehicle and the braking deceleration of the preceding vehicle at each time point within the set time window before braking begins, analyze and monitor whether each emergency braking behavior of the monitored vehicle is reasonable. Unreasonable emergency braking behavior is recorded as abnormal braking behavior. The number of abnormal braking behaviors of the monitored vehicle in recent historical periods is counted. If the number of abnormal braking behaviors exceeds the set number, it is preliminarily determined that there is an abnormal driving status.

7. A real-time monitoring and early warning system for vehicle operating status according to claim 6, characterized in that, The analysis methods for determining whether the emergency braking behavior of the monitored vehicle is reasonable include: Construct a curve showing the change in the distance to the vehicle in front, with each time point within a set time window as the x-axis and the corresponding distance to the vehicle in front as the y-axis. When the distance between the preceding vehicle and the preceding vehicle is less than the prescribed safe distance at a certain time point in the current vehicle distance change curve, the braking deceleration of the preceding vehicle at that time point is used to determine whether the preceding vehicle is engaging in emergency braking behavior. If the vehicle in front is braking suddenly or if the distance curve of the vehicle in front shows abnormal changes, then the emergency braking behavior of the monitored vehicle is deemed reasonable.

8. The vehicle operation status real-time monitoring and early warning system according to claim 7, characterized in that, The specific method for determining whether the distance change curve of the preceding vehicle shows abnormalities is as follows: The difference between the distance to the vehicle at each time point in the curve of the change in distance to the vehicle at the previous time point is recorded as the change in distance. The absolute difference between the change in vehicle distance at each time point and the change in vehicle distance at the previous time point is denoted as the second-order forward difference. If the vehicle distance change at the time point where the second-order forward difference maximum value is negative, and the vehicle distance at all time points after that time point is less than the vehicle distance at all time points before that time point, then the vehicle distance change curve shows an anomaly in vehicle distance change.

9. A real-time monitoring and early warning system for vehicle operating status according to claim 8, characterized in that, The specific methods for determining whether an alert needs to be issued during the analysis include: Extract historical safe driving records of drivers with the same environmental parameters as the current environment from the vehicle operation backend database, and then filter the average driving speed within each historical time period with the same duration as the recent historical time period. Based on the average driving speed in recent historical periods, select all the distances to the vehicles in front in each historical period that have the same average driving speed in recent historical periods, and form a historical distance group for all the distances to the vehicles in front in each historical period. Based on the historical preceding vehicle distance distribution, the monitoring vehicle driver's habitual driving distance range at the corresponding average driving speed is analyzed. If an abnormal braking behavior occurs when the distance to the vehicle in front is less than the minimum value of the corresponding habitual driving distance range at the start of braking, a fatigue driving-related warning will be issued. Conversely, if the distance to the vehicle in front at the start of each abnormal braking action is within the driver's habitual driving distance, then the distance to the vehicle in front corresponding to each abnormal braking action is determined to be the driver's driving habit, and no relevant warning is issued.

10. A real-time monitoring and early warning system for vehicle operating status according to claim 9, characterized in that, The specific method for obtaining the habitual driving distance range of the monitored vehicle driver at the corresponding average driving speed includes: Remove outliers in the historical preceding vehicle distance group, and then use the kernel density estimation method to fit the kernel density curve corresponding to the historical preceding vehicle distance group to obtain the peak value of the kernel density curve. Calculate the standard deviation of the historical preceding vehicle distance group, take the difference between the peak value and the standard deviation as the minimum value of the habitual driving distance range, and take the sum of the peak value and the standard deviation as the maximum value of the habitual driving distance range. The minimum and maximum values ​​of the habitual driving distance range are used to form the habitual driving distance range of the monitored vehicle driver at the corresponding average driving speed.

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