A vehicle operation state real-time monitoring and early warning system

Abstract

The present application relates to the field of vehicle operation monitoring, and relates to a real-time monitoring and early warning system for vehicle operation state. The present application determines the allowable speed limit by obtaining the prescribed speed limit of the road where the current position of the monitored vehicle is located, combining the road type and environmental parameters of the current position; if the current driving speed exceeds the allowable speed limit, it is determined that there is an overspeed behavior and a warning reminder is issued; otherwise, the driving speed and the distance of the vehicles around the monitored vehicle are obtained, the current driving speed of the monitored vehicle is combined to determine whether the monitored vehicle has an abnormal driving speed; if there is an abnormal driving speed, the braking deceleration and the distance of the preceding vehicle of each braking in the recent history period of the monitored vehicle are obtained to preliminarily determine whether the monitored vehicle has an abnormal driving state, and the distance of the preceding vehicle and the driving speed of each braking in the historical safe driving record of the driver are analyzed to determine whether a reminder is needed. The practicality and reliability of the early warning are improved.

Description

Technical Field

[0001] This invention relates to the field of vehicle operation monitoring technology, and specifically to a real-time monitoring and early warning system for vehicle operation status. Background Technology

[0002] Existing technologies, such as Chinese Patent Publication CN117275235B, disclose a vehicle monitoring method and system. This method collects vehicle speed, acceleration, and steering angle data in real time, and uses machine learning algorithms such as support vector machines or decision trees based on a basic vehicle dataset to analyze the vehicle's driving status, identify abnormal driving behaviors, and generate abnormal driving reports.

[0003] However, existing technologies have the following problems: 1. They only analyze vehicle datasets without considering the adjustment of speed limits based on road type and environmental parameters, resulting in high speed thresholds for warning judgments and low adaptability to actual conditions. They may also overlook the potential risks of low braking efficiency due to excessively high driving speeds in severe weather.

[0004] 2. Existing technologies mostly rely on vehicle driving data analysis to determine abnormal driving, without considering factors such as analyzing recent continuous driving behavior to determine if fatigue driving exists. This may lead to misjudgments of normal driving and the issuance of incorrect warnings. Summary of the Invention

[0005] The present invention aims to address the shortcomings of the prior art and provide a real-time monitoring and early warning system for vehicle operating status.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: a real-time monitoring and early warning system for vehicle operation status, comprising: a speed limit correction module, an overspeed risk determination module, a driving status anomaly determination module, and a status early warning module. The connection relationships between the modules are as follows: the speed limit correction module is connected to the overspeed risk determination module, and the driving status anomaly determination module is connected to both the status early warning module and the overspeed risk determination module.

[0007] Speed ​​limit correction module: Obtain the speed limit of the road where the monitored vehicle is currently located, and determine the safe driving speed by combining the road type and environmental parameters of the current location.

[0008] Speeding risk assessment module: Real-time collection 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 is speeding and a warning is issued. Otherwise, the speed and distance of the vehicles around the monitored vehicle are obtained based on the vehicle radar.

[0009] Driving Status Anomaly Determination Module: Based on the current driving speed of the monitored vehicle and the driving speed of surrounding vehicles, determine whether the monitored vehicle has an abnormal driving speed. If an abnormal driving speed is found, obtain the braking deceleration and distance to the vehicle in front of the monitored vehicle during each braking in recent historical periods to preliminarily determine whether the monitored vehicle has an abnormal driving status.

[0010] Status warning module: If the monitored vehicle has an abnormal driving status, it will analyze and determine whether an alert needs to be issued based on the distance to the vehicle in front and the driving speed during each braking in the driver's historical safe driving record.

[0011] Compared with the prior art, the present invention has the following beneficial effects: (1) The present invention obtains the prescribed speed limit of the road where the monitored vehicle is located, and determines the safe driving speed by combining the road type and environmental parameters of the current location. It realizes the correction of the speed limit according to the actual transportation situation and weather conditions, so that the corrected speed limit is more in line with the safety boundary of the actual driving of the vehicle.

[0012] (2) This invention monitors the current driving speed of a vehicle and combines it with the driving speed of surrounding vehicles to determine whether the monitored vehicle has an abnormal driving speed. It also uses the braking deceleration and distance to the vehicle in front of the monitored vehicle during each braking in recent historical periods to preliminarily determine whether the monitored vehicle has abnormal driving conditions such as fatigue. This avoids frequent warnings triggered by occasional and reasonable speed fluctuations and improves the practicality and accuracy of the warning system.

[0013] (3) If the monitored vehicle has an abnormal driving status, the present invention analyzes and judges whether a reminder needs to be issued based on the distance to the vehicle in front and the driving speed of each braking in the driver's historical safe driving record. By combining the driver's historical driving record with the individual driving habits of the driver, the accuracy of the warning is improved and the interference of false warnings on driving is avoided. Attached Figure Description

[0014] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0015] Figure 1 This is a schematic diagram of the system module connections of the present invention.

[0016] Figure 2 This is a schematic diagram illustrating the specific steps of the speed limit correction module in this invention.

[0017] Figure 3 This is a schematic diagram illustrating the specific process for initially determining whether there is an abnormal driving status in this invention.

[0018] Figure 4 This is a schematic diagram illustrating the specific process for correcting the preliminary judgment results in this invention. Detailed Implementation

[0019] Various exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps set forth in these embodiments do not limit the scope of the invention. Furthermore, it should be understood that, for ease of description, the dimensions of the various parts shown in the drawings are not drawn to actual scale.

[0020] The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the invention or its application or use. Techniques, methods, and apparatus known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and apparatus should be considered part of the specification.

[0021] In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values.

[0022] This invention determines a safe driving speed by acquiring the speed limit of the road where the monitored vehicle is currently located, combined with the road type and environmental parameters. If the current driving speed exceeds the safe speed, speeding is detected and a warning is issued. Conversely, by acquiring the driving speed and distance of surrounding vehicles from the vehicle-mounted radar, and combining this with the monitored vehicle's current speed, it is determined whether the monitored vehicle is experiencing abnormal speeding. If abnormal speeding is detected, the braking deceleration and distance to the vehicle in front are acquired from each braking instance in recent historical periods to preliminarily determine whether the monitored vehicle is experiencing abnormal driving conditions. Finally, based on the driver's historical safe driving records of each braking instance and the distance and speed to the vehicle in front, an analysis is conducted to determine whether a warning needs to be issued. This improves the practicality and reliability of the warning system.

[0023] Please see Figure 1 As shown, this invention provides a real-time monitoring and early warning system for vehicle operation status, including: a speed limit correction module, an overspeed risk determination module, a driving status anomaly determination module, and a status early warning module. The connections between the modules are as follows: the speed limit correction module is connected to the overspeed risk determination module, and the driving status anomaly determination module is connected to both the status early warning module and the overspeed risk determination module.

[0024] Speed ​​limit correction module: Obtain the speed limit of the road where the monitored vehicle is currently located, and determine the safe driving speed by combining the road type and environmental parameters of the current location.

[0025] Considering that different road types can affect driving speed during long-distance transportation, and that the steeper the slope, the more difficult it is to brake, and that a higher speed would increase the likelihood of an accident, the probability of accidents can be reduced by analyzing the excess kinetic energy under the influence of road characteristics and correcting the speed limit accordingly. Therefore, it is necessary to reduce the speed during the downhill process to keep the driving speed below the speed limit.

[0026] Furthermore, considering that different weather types and visibility levels will have different effects on vehicle operation, the lower the visibility, the higher the probability of vehicle accidents. Therefore, it is necessary to reduce vehicle speed to ensure driving safety.

[0027] Based on this, such as Figure 2 As shown, the specific content of the speed limit correction module includes: S1, matching the corresponding road type and its characteristic parameters from the vehicle operation backend database based on the current location of the monitored vehicle.

[0028] S2. 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.

[0029] S3. Substitute the additional kinetic energy and the speed limit specified at the current position into the modified formula of the kinetic energy theorem to calculate the initial safe driving speed. Combine this with the standard speed limit specified at the current position environmental parameters to analyze and determine the safe driving speed.

[0030] In a preferred embodiment of the present invention, road type data, including normal road sections, downhill road sections, and uphill road sections, is retrieved from the vehicle operation backend database. When the road type is a normal road section or an uphill road section, no additional kinetic energy is generated due to the road characteristic parameters, so its initial safe driving speed is the prescribed speed limit. If the road type at the current location of the monitored vehicle is downhill, the characteristic parameters corresponding to each road type, including road slope angle and slope length, are extracted from the vehicle operation backend database. The additional kinetic energy generated by the slope is calculated, and it is substituted into the modified formula of the kinetic energy theorem to obtain the initial safe driving speed.

[0031] The transformed formula of the kinetic energy theorem is as follows: .

[0032] in This represents the additional kinetic energy generated by the slope. Represents the total weight of the monitored vehicle. These represent the prescribed speed limit and the initial safe driving speed, respectively.

[0033] in .

[0034] Represents gravitational acceleration. Represents slope length, Represents the slope angle.

[0035] In a specific embodiment of the present invention, the method for determining the safe driving speed includes: matching the corresponding standard speed limit from the set standard speed limits corresponding to each weather type and each visibility level based on the weather type and visibility parameters of the current location.

[0036] The speed limit specified in the standard refers to the speed limit specified by the traffic management department in real time according to environmental parameters, such as a speed limit of 30 km / h when visibility is less than 50 m in snowy weather.

[0037] 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.

[0038] This invention obtains the speed limit of the road where the monitored vehicle is located, and determines the safe driving speed by combining the road type and environmental parameters of the current location. It realizes the correction of the speed limit according to the actual transportation situation and weather conditions, so that the corrected speed limit is closer to the safety boundary of the actual driving of the vehicle.

[0039] Speeding risk assessment module: Real-time collection 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 is speeding and a warning is issued. Otherwise, the speed and distance of the vehicles around the monitored vehicle are obtained based on the vehicle radar.

[0040] 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 combined with the electromagnetic wave propagation speed, the distance between the monitored vehicle and the target vehicle is directly calculated.

[0041] Based on the Doppler frequency shift characteristics of the echo signal, the Doppler frequency shift velocity formula is obtained by substituting the signal frequency shift and wavelength. The relative radial velocities of the surrounding vehicles are calculated, where Represents the frequency shift of electromagnetic wave signals. This represents the wavelength of the electromagnetic wave. The lateral velocity is calculated by extracting the lateral position difference between adjacent frames of surrounding vehicles and the monitored vehicle, and then calculating the ratio of this lateral position difference to the frame time interval.

[0042] The radial velocity of the monitored vehicle is calculated by multiplying the cosine of the line-of-sight angle between the monitored vehicle and the surrounding vehicles by the speed of the monitored vehicle. The absolute radial velocity of the surrounding vehicles is calculated based on the difference between the relative radial velocity and the radial velocity of the monitored vehicle. The speed of the surrounding vehicles is obtained by combining the absolute radial velocity and the lateral velocity into a vector.

[0043] This invention enables accurate detection and timely warning of speeding behavior, ensuring vehicle driving safety.

[0044] Driving Status Anomaly Determination Module: Based on the current driving speed of the monitored vehicle and the driving speed of surrounding vehicles, determine whether the monitored vehicle has an abnormal driving speed. If an abnormal driving speed is found, obtain the braking deceleration and distance to the vehicle in front of the monitored vehicle during each braking in recent historical periods to preliminarily determine whether the monitored vehicle has an abnormal driving status.

[0045] The method for determining whether the monitored vehicle has an abnormal driving speed includes: firstly, obtaining the vehicle type and driving speed of surrounding vehicles within the radar monitoring range based on the vehicle's onboard radar.

[0046] Specifically, the vehicle radar extracts the outer contour images, height, and width of surrounding vehicles, compares and matches them with a vehicle type feature database, and determines the vehicle type of each surrounding vehicle.

[0047] Secondly, based on the vehicle type of the monitored vehicle, the driving speeds of all vehicles of the same type as the monitored vehicle are selected from the surrounding vehicles. Combined with the driving speeds of other surrounding vehicles, the normal maximum speed threshold and normal minimum speed threshold are obtained.

[0048] The method for obtaining the normal maximum speed threshold and the normal minimum speed threshold is as follows: filter out all vehicles in the same lane as the monitored vehicle currently traveling from the surrounding vehicles.

[0049] The driving rules and traffic density of different lanes may vary. The driving status of vehicles in the same lane can better reflect the normal driving environment of the lane where the monitored vehicle is located. Analyzing the driving speed of vehicles in the same lane is an important basis for determining the normal driving speed range of the monitored vehicle.

[0050] 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.

[0051] Different types of vehicles travel at different speeds, so analyzing the speeds of vehicles of the same type in the same lane can provide a more accurate and standardized way to monitor vehicle speeds.

[0052] The vehicle closest to the monitored vehicle in the same lane is designated as the preceding vehicle. The speed of the preceding vehicle is extracted from the speeds of surrounding vehicles and recorded as the second speed threshold.

[0053] The speed of the vehicle in front directly affects the monitoring vehicle. If the speed of the monitoring vehicle is consistently higher than that of the vehicle in front, it will cause a rear-end collision. Therefore, the speed of the vehicle in front is also an important basis for determining the normal driving speed range of the monitoring vehicle.

[0054] 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.

[0055] Among them, the closest vehicle of the same type in the adjacent lane may be a vehicle of the same type preparing to overtake. If the speed of the monitored vehicle is consistently higher than that of the overtaking vehicle, it may cause a traffic accident.

[0056] 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.

[0057] The minimum speed of all vehicles of the same type is recorded as the normal minimum speed threshold to avoid monitoring vehicles whose speeds are too low, which would affect road traffic efficiency.

[0058] The normal driving speed range is formed by combining the normal maximum speed threshold and the normal minimum speed threshold.

[0059] 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.

[0060] Considering that a single abnormal driving speed cannot directly determine whether the driver's driving status is abnormal, a comprehensive analysis can be conducted on the braking deceleration and the distance to the vehicle in front during the braking time within the historical set driving time to determine whether the driver has abnormal driving status such as inattention or fatigue.

[0061] Based on this, such as Figure 3 As shown, in a preferred embodiment of the present invention, the specific method for initially determining whether the monitored vehicle has an abnormal driving status includes: S31, retrieving from the vehicle operation background database the braking deceleration of each braking record of the monitored vehicle in recent historical periods, and the distance between the monitored vehicle and the vehicle in front at each time point within the set time window before braking begins, and recording it as the distance between the vehicles in front.

[0062] In a specific embodiment of the present invention, the recent historical period is set to the most recent 1 hour. The implementer may also set other values, but they should not be too large to reduce timeliness. The time window can be set to the 5 minutes before braking begins, and the implementer may also set other specific values.

[0063] S32. Compare the braking deceleration of each braking behavior in the recent historical period 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, then the braking behavior is recorded as an emergency braking behavior.

[0064] The braking deceleration threshold can be set according to the relevant range stipulated by the traffic management department. In a specific embodiment of the present invention, the braking deceleration threshold is set to 3 m / s. 2 .

[0065] S33. 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. Calculate the braking deceleration of the preceding vehicle at each time point based on the speed at adjacent time points. Specifically, the braking deceleration of the preceding vehicle is calculated as the ratio of the speed difference between adjacent time points to the time interval between adjacent time points.

[0066] S34. Analyze whether the emergency braking behavior of the monitored vehicle is reasonable based on the distance to the preceding vehicle and the braking deceleration of the preceding vehicle at each time point within the time window set before braking begins.

[0067] The method for analyzing whether the emergency braking behavior of the monitored vehicle is reasonable includes: constructing 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.

[0068] When the distance between the preceding vehicle and the vehicle in front 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.

[0069] It should be noted that the specified safe following distance refers to the standard safe following distance prescribed for different driving speeds on highways. For example, when the driving speed is greater than 100 km / h, the specified safe following distance is 100 m, and when the driving speed is less than 100 km / h, the specified following distance is 50 m.

[0070] 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.

[0071] Understandably, if the vehicle in front brakes suddenly, it indicates that the monitoring vehicle's emergency braking was to avoid a rear-end collision, which is a reasonable action. If the distance change curve of the vehicle in front shows abnormal changes, it indicates that the vehicle in front has changed, possibly due to cutting in. In this case, the monitoring vehicle's emergency braking is also a reasonable action.

[0072] The specific method for determining whether there is an abnormal change in the distance of the preceding vehicle in the curve is as follows: the difference between the distance of the preceding vehicle at each time point and the distance at the previous time point is recorded as the distance change.

[0073] 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.

[0074] If the change in vehicle distance corresponding to the time point where the second-order forward difference reaches its maximum value is negative, and the distance between vehicles ahead at all time points after that point is less than the distance between vehicles ahead at all time points before that point, then the distance change curve shows an anomaly. It can be determined that a significant change in the distance between vehicles ahead occurred at that time point, indicating that someone was cut off.

[0075] S35. Record unreasonable emergency braking behavior as abnormal braking behavior, count the number of abnormal braking behaviors of the monitored vehicle in recent historical periods, and if the number of abnormal braking behaviors exceeds the set number, it is preliminarily determined that there is an abnormal driving state.

[0076] In a specific embodiment of the present invention, the method for setting the number of times can be achieved by collecting the number of times each driver exhibited abnormal braking behavior under fatigue driving conditions in each hour over the past year, and calculating the average value as the set number. In this embodiment, two or more instances of abnormal braking behavior are preliminarily determined to indicate an abnormal driving state. However, the implementer may also set other specific values.

[0077] This invention monitors the current speed of a vehicle and combines this with the speeds of surrounding vehicles to determine if the monitored vehicle is experiencing abnormal speed. By analyzing the braking deceleration and distance to the vehicle in front of the monitored vehicle during recent historical periods, it preliminarily determines whether the monitored vehicle is experiencing fatigue or other abnormal driving conditions. This avoids frequent warnings triggered by occasional and reasonable speed fluctuations, thus improving the practicality and accuracy of the warning system.

[0078] Status warning module: If the monitored vehicle has an abnormal driving status, it will analyze and determine whether an alert needs to be issued based on the distance to the vehicle in front and the driving speed during each braking in the driver's historical safe driving record.

[0079] like Figure 4 As shown, the specific method for analyzing whether an alert needs to be issued includes: W1, extracting the driver's historical safe driving records with the same environmental parameters as the current environment from the vehicle operation backend database, and filtering the average driving speed within each historical time period with the same duration as the recent historical time period.

[0080] Specifically, in a specific embodiment of the present invention, the driver's historical safe driving records within the past year and the driver's average driving speed within the past hour are extracted.

[0081] W2. Based on the average driving speed in recent historical periods, filter 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.

[0082] W3. Analyze the range of habitual driving distances of drivers of monitored vehicles at the corresponding average driving speed based on the distribution of the preceding vehicle distance group in the historical preceding vehicle distance group.

[0083] In a specific embodiment of the present invention, the method for obtaining the habitual driving distance range corresponding to each braking initial speed range includes: removing outlier values ​​of the preceding vehicle distance from the historical preceding vehicle distance group, fitting the kernel density curve corresponding to the historical preceding vehicle distance group to the remaining preceding vehicle distance after removing the outlier values ​​using the kernel density estimation method, and obtaining the peak value of the kernel density curve.

[0084] Specifically, the quartile method is used to remove outliers in each historical preceding vehicle distance group. The preceding vehicle distances in each historical preceding vehicle distance group are arranged in ascending order. The 25th preceding vehicle distance is recorded as the first quartile, and the 75th preceding vehicle distance is recorded as the third quartile. The difference between the first quartile and the third quartile is calculated and recorded as the quartile distance. The difference between the first quartile and 1.5 times the quartile distance is recorded as the minimum boundary, where 1.5 is the set value in the existing quartile method.

[0085] Furthermore, it should be noted that the specific steps for fitting the kernel density curve corresponding to the historical preceding vehicle distance group are as follows: take the remaining preceding vehicle distances in the historical preceding vehicle distance group as each sample point, use the Gaussian kernel function as the kernel function for kernel density estimation, use the Scott rule to automatically determine the bandwidth, substitute the bandwidth and each sample point into the kernel function to calculate the influence weight of each sample point, and substitute the influence weight of each sample point, the bandwidth, and the number of sample points into the kernel density estimation formula to obtain each kernel density estimate.

[0086] A kernel density estimation curve is constructed by connecting the points of each kernel density estimate, and the distance to the preceding vehicle corresponding to the maximum kernel density estimate is recorded as the desired peak value. The Gaussian kernel function, Scott's rule, and the kernel density estimation formula are all existing technologies, and the specific calculation formulas will not be elaborated upon in this invention.

[0087] 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.

[0088] 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.

[0089] Using the distance to the vehicle ahead corresponding to the peak value of the kernel density curve of each historical distance to the vehicle ahead as the core, and expanding the range through standard deviation, we can finally obtain the driver's habitual driving distance range at the corresponding average driving speed, which can reflect the driver's distance control preference at that driving speed.

[0090] W4. 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.

[0091] W5. Conversely, if the distance to the vehicle in front at the start of each abnormal braking behavior is within the driver's habitual driving distance, then the distance to the vehicle in front corresponding to each abnormal braking behavior is determined to be the driver's driving habit, and no relevant warning is issued.

[0092] This invention analyzes and determines whether a warning needs to be issued when the monitored vehicle exhibits abnormal driving conditions, based on the distance to the preceding vehicle and the driving speed during each braking instance in the driver's historical safe driving record. By combining the driver's historical driving record with individual driving habits, the accuracy of the warning is improved, and false warnings are avoided from interfering with driving.

[0093] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, in the form of a computer program product.

[0094] Those skilled in the art will recognize that the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented 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 implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0095] In addition, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0096] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0097] Finally, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

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 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. 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. 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 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.

5. The vehicle operation status real-time monitoring and early warning system according to claim 4, 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.

6. The vehicle operation status real-time monitoring and early warning system according to claim 5, characterized in that, The specific method for determining whether the preceding vehicle distance change curve shows abnormal distance changes is as follows: The difference between the distance to the vehicle at each time point in the curve of the 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.

7. A real-time monitoring and early warning system for vehicle operating status according to claim 6, 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.

8. The vehicle operation status real-time monitoring and early warning system according to claim 7, 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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