Driving behavior scoring method, device, equipment and storage medium

Abstract

The present invention discloses a driving behavior scoring method, device, equipment and storage medium. The method comprises: determining at least two driving behavior categories corresponding to driving behavior data of a to-be-evaluated trip; for driving behavior scoring rules corresponding to different driving behavior categories, determining scoring values ​​corresponding to different driving behaviors under the corresponding driving behavior categories according to driving behavior data corresponding to the corresponding driving behavior categories; and determining the driving behavior score of the driving user corresponding to the to-be-evaluated trip according to at least one of the scoring values. The embodiment of the present application improves the accuracy of driving behavior scoring.

Description

Technical Field

[0001] The present invention relates to the field of vehicle networking technology, and in particular to a driving behavior scoring method, device, equipment and storage medium. Background Art

[0002] In recent years, the Internet of Vehicles technology has developed rapidly and has become an important manifestation of the automotive technology field. Driving behavior analysis or evaluation services have gradually become one of the main functions of Internet of Vehicles services.

[0003] In the prior art, usually only individual driving behaviors are scored, the scoring content is not comprehensive, and the scoring method of driving behaviors is not accurate enough, resulting in low accuracy of the scoring results. Summary of the invention

[0004] The present invention provides a driving behavior scoring method, device, equipment and storage medium to improve the accuracy of driving behavior scoring.

[0005] According to one aspect of the present invention, a driving behavior scoring method is provided, the method comprising:

[0006] Determine at least two driving behavior categories corresponding to the driving behavior data of the trip to be evaluated;

[0007] According to the driving behavior scoring rules corresponding to different driving behavior categories, the scoring values ​​corresponding to different driving behaviors under the corresponding driving behavior categories are determined according to the driving behavior data corresponding to the corresponding driving behavior categories;

[0008] A driving behavior score of the driving user corresponding to the trip to be evaluated is determined according to at least one of the scoring values.

[0009] According to another aspect of the present invention, a driving behavior scoring device is provided, the device comprising:

[0010] A driving behavior category determination module, used to determine at least two driving behavior categories corresponding to the driving behavior data of the trip to be evaluated;

[0011] A scoring value determination module is used to determine the scoring values ​​corresponding to different driving behaviors under the corresponding driving behavior categories according to the driving behavior scoring rules corresponding to different driving behavior categories and the driving behavior data corresponding to the corresponding driving behavior categories;

[0012] The driving behavior score determination module is used to determine the driving behavior score of the driving user corresponding to the to-be-evaluated trip according to at least one of the score values.

[0013] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0014] at least one processor; and

[0015] a memory communicatively connected to the at least one processor; wherein,

[0016] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the driving behavior scoring method described in any embodiment of the present invention.

[0017] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the driving behavior scoring method described in any embodiment of the present invention when executed.

[0018] The embodiment of the present invention determines at least two driving behavior categories corresponding to the driving behavior data of the trip to be evaluated; for the driving behavior scoring rules corresponding to different driving behavior categories, the scoring values ​​corresponding to different driving behaviors under the corresponding driving behavior categories are determined according to the driving behavior data corresponding to the corresponding driving behavior categories; and the driving behavior score of the driving user corresponding to the trip to be evaluated is determined according to at least one scoring value. The above scheme adopts the driving behavior scoring rules corresponding to different driving behavior categories to determine the scoring values ​​corresponding to each driving behavior under the corresponding driving behavior categories, thereby realizing the targeted determination of the scoring values ​​of driving behaviors according to different driving behavior scoring rules under the driving behavior categories determined according to the behavioral characteristics of the driving behaviors. Compared with the prior art in which the same driving behavior scoring rules are used to determine the scoring values ​​for different driving behaviors, the present invention has a higher accuracy in determining the scoring values ​​corresponding to the driving behaviors.

[0019] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0021] Figure 1 is a flow chart of a driving behavior scoring method provided according to Embodiment 1 of the present invention;

[0022] Figure 2is a flow chart of a driving behavior scoring method provided according to Embodiment 2 of the present invention;

[0023] Figure 3 is a flow chart of a driving behavior scoring method provided according to Embodiment 3 of the present invention;

[0024] Figure 4 is a structural schematic diagram of a driving behavior scoring device provided according to a fourth embodiment of the present invention;

[0025] Figure 5 Schematic diagram of the structure of an electronic device for implementing the driving behavior scoring method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0026] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0027] It should be noted that the terms "candidate", "target", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0028] Embodiment 1

[0029] Figure 1 A flowchart of a driving behavior scoring method is provided for the first embodiment of the present invention. This embodiment is applicable to the case of scoring the driving behavior of a user during a trip. The method can be executed by a driving behavior scoring device. The driving behavior scoring device can be implemented in the form of hardware and / or software. The driving behavior scoring device can be configured in an electronic device. Figure 1 As shown, the method includes:

[0030] S110: Determine at least two driving behavior categories corresponding to the driving behavior data of the trip to be evaluated.

[0031] Among them, the trip to be evaluated can be a trip for which the driving behavior is to be scored after the driving user completes a single trip. The driving behavior data can be the data generated by the driving user during the driving process that needs to be scored. For example, the driving behavior data can include acceleration, deceleration, steering, speeding, high-speed cornering, cornering braking, idling, driving prediction, AEB (Autonomous Emergency Braking, automatic braking system) triggering, FCW (Forward Collision Warning, front collision warning system), ESP (Electronic Stability Program, electronic stability system) triggering, LDW (Lane Departure Warning, lane departure warning) triggering, smooth acceleration, smooth deceleration, late night driving and fatigue driving, etc.

[0032] The driving behavior category may be a category pre-classified by relevant technical personnel for at least one driving behavior according to the driving behavior characteristics. For example, the driving behavior category may include an event-type driving behavior category, a continuous driving behavior category, and an indicative driving behavior category. Among them, the driving behavior in the event-type driving behavior category may be a driving behavior based on the frequency of events; the driving behavior in the continuous driving behavior category may be a driving behavior of a continuous or persistent event; and the driving behavior in the indicative driving behavior category may be a driving behavior with a binary classification characteristic based on whether the behavior occurs.

[0033] Among them, the event-type driving behavior category may include at least one of the driving behaviors such as acceleration, deceleration, steering, speeding, high-speed cornering, cornering braking, idling, driving prediction, AEB triggering, FCW, ESP triggering, LDW triggering, etc. The continuous driving behavior category may include at least one of the driving behaviors such as smooth driving and smooth deceleration. The indicative driving behavior category may include at least one of the driving behaviors such as late-night driving and fatigue driving.

[0034] It should be noted that, since different driving behaviors have different behavioral characteristics, different driving behaviors can be classified in advance according to the behavioral characteristics of the driving behaviors, and the driving behavior categories corresponding to the different driving behaviors can be determined. Specifically, the different driving behaviors can be divided into at least two driving behavior categories, so as to determine the driving behavior category to which at least one driving behavior in the driving behavior data of the driving user in the itinerary to be evaluated belongs according to the driving behavior categories corresponding to the different driving behaviors.

[0035] S120. Determine, for each driving behavior scoring rule corresponding to each driving behavior category, scoring values ​​corresponding to different driving behaviors under the corresponding driving behavior category according to driving behavior data corresponding to the corresponding driving behavior category.

[0036] Among them, the driving behavior scoring rule may be a rule for scoring the driving behavior of the driving user. Different driving behavior categories correspond to different driving behavior scoring rules. It should be noted that at least one driving behavior under a driving behavior category has a corresponding scoring value. For example, if driving behavior category A includes driving behavior a1, driving behavior a2, and driving behavior a3, then driving behavior a1, driving behavior a2, and driving behavior a3 each correspond to a scoring value.

[0037] For example, if the driving behavior category includes driving behavior category A and driving behavior category B. For driving behavior under driving behavior category A, the driving behavior scoring rule may be to determine the number of times the driving behavior occurs in the trip to be evaluated, and determine the scoring value corresponding to the driving behavior under driving behavior category A based on the number of occurrences and the preset total score. For driving behavior under driving behavior category B, the driving behavior scoring rule may be to determine the duration of the driving behavior in the trip to be evaluated, and determine the scoring value corresponding to the driving behavior under driving behavior category B based on the total duration of the trip to be evaluated.

[0038] S130: Determine a driving behavior score of the driving user corresponding to the trip to be evaluated according to at least one scoring value.

[0039] The driving behavior score may be the sum of the scores corresponding to different driving behaviors under each driving behavior category. For example, if there are driving behavior category A and driving behavior category B, driving behavior category A includes driving behavior a1 and driving behavior a2; driving behavior category B includes driving behavior b1 and driving behavior b2, then the driving behavior score of the driving user corresponding to the trip to be evaluated is the sum of the scores corresponding to driving behavior a1, driving behavior a2, driving behavior b1, and driving behavior b2.

[0040] Relevant technicians may pre-set different weight values ​​for driving behaviors under different driving behavior categories. According to at least one score value, based on the preset weight value, the driving behavior score of the driving user corresponding to the trip to be evaluated is determined. Different weight values ​​may be set for different driving behavior categories, and the weight values ​​of driving behaviors under the same driving behavior category may be set the same or different.

[0041] The driving behavior score of the driver corresponding to the trip to be evaluated is determined as follows:

[0042]

[0043] Among them, s1, s2, …, sn are the scoring values ​​of driving behaviors; a1, a2, …, an are the weight values ​​corresponding to driving behaviors.

[0044] Exemplarily, if there are driving behavior categories A and B, driving behavior category A includes driving behavior a1 and driving behavior a2; driving behavior category B includes driving behavior b1 and driving behavior b2, the score corresponding to driving behavior a1 under driving behavior category A is 80 points, and the weight value is 0.1, and the score corresponding to driving behavior a2 under driving behavior category A is 85 points, and the weight value is 0.3; the score corresponding to driving behavior b1 under driving behavior category B is 80 points, and the weight value is 0.2, and the score corresponding to driving behavior b2 under driving behavior category B is 90 points, and the weight value is 0.4, then the driving behavior score S of the driving user corresponding to the trip to be evaluated is 85.5 points.

[0045] The embodiment of the present invention determines at least two driving behavior categories corresponding to the driving behavior data of the trip to be evaluated; for the driving behavior scoring rules corresponding to different driving behavior categories, the scoring values ​​corresponding to different driving behaviors under the corresponding driving behavior categories are determined according to the driving behavior data corresponding to the corresponding driving behavior categories; and the driving behavior score of the driving user corresponding to the trip to be evaluated is determined according to at least one scoring value. The above scheme adopts the driving behavior scoring rules corresponding to different driving behavior categories to determine the scoring values ​​corresponding to each driving behavior under the corresponding driving behavior categories, thereby realizing the targeted determination of the scoring values ​​of driving behaviors according to different driving behavior scoring rules under the driving behavior categories determined according to the behavioral characteristics of the driving behaviors. Compared with the prior art in which the same driving behavior scoring rules are used to determine the scoring values ​​for different driving behaviors, the present invention has a higher accuracy in determining the scoring values ​​corresponding to the driving behaviors.

[0046] Embodiment 2

[0047] Figure 2 This is a flow chart of a driving behavior scoring method provided in Embodiment 2 of the present invention. This embodiment is optimized and improved on the basis of the above technical solutions.

[0048] Furthermore, if the driving behavior category is an event-type category; accordingly, the step of "determining the scoring values ​​corresponding to different driving behaviors under the corresponding driving behavior category according to the driving behavior scoring rules corresponding to different driving behavior categories and the driving behavior data corresponding to the corresponding driving behavior categories" is refined into "obtaining the mileage value of the trip to be evaluated; determining the number of occurrences of the behavior corresponding to the driving behavior under the event-type category according to the driving behavior data and the current influencing factors; determining the scoring values ​​corresponding to each driving behavior under the event-type category based on the event-type scoring rules according to the mileage value and the number of occurrences of the behavior." to improve the determination of the scoring values ​​corresponding to each driving behavior under the event-type category.

[0049] like Figure 2 As shown, the method comprises the following specific steps:

[0050] S210: Determine at least two driving behavior categories corresponding to the driving behavior data of the trip to be evaluated.

[0051] S220: If the driving behavior category is an event-type category, obtain the mileage value of the trip to be evaluated.

[0052] The driving behavior under the event type category may be a driving behavior based on the frequency of the event; the event type category may include at least one of the driving behaviors of acceleration, deceleration, steering, speeding, high-speed cornering, cornering braking, idling, driving prediction, AEB triggering, FCW, ESP triggering, LDW triggering, etc. The mileage value of the trip to be evaluated may be the mileage value of the trip to be evaluated, for example, the mileage of the vehicle from the starting position to the end position.

[0053] S230: Determine the number of occurrences of the driving behavior corresponding to the event-type driving behavior according to the driving behavior data and the current influencing factors.

[0054] The current influencing factors may include at least one of a vehicle speed range, a road type, a traffic state, and a weather state. The vehicle speed range may include 0-30 km / h, 30-60 km / h, 60-80 km / h, and 80-120 km / h; the road type may include urban roads and rural roads; the traffic state may include smooth traffic and traffic congestion; and the weather state may include cloudy weather and sunny weather. The number of behavior occurrences may be the number of times each driving behavior under the event type category occurs in the trip to be evaluated.

[0055] For example, the threshold corresponding to the driving behavior under the event type category can be pre-set by relevant technical personnel. For example, for the acceleration driving behavior under the event type category, the acceleration threshold can be set to 0.35m / s 2 ; The acceleration during the driving process to be evaluated exceeds 0.35m / s 2 The number of times the steering angular velocity exceeds 200 deg / s in the driving process to be evaluated is taken as the number of occurrences of the behavior corresponding to the acceleration driving behavior. For example, for the turning behavior under the event type category, the turning threshold can be set to 200 deg / s; the number of times the steering angular velocity exceeds 200 deg / s in the driving process to be evaluated is taken as the number of occurrences of the behavior corresponding to the turning driving behavior.

[0056] It should be noted that the driving user may be affected by some internal or external factors during the driving process, such as weather conditions, roads and other factors. Therefore, the current influencing factors can be considered in the process of determining the number of behavior occurrences corresponding to the driving behavior under the event-type category to eliminate the influence of the current influencing factors on the number of behavior occurrences corresponding to the driving behavior, thereby improving the accuracy of the number of behavior occurrences, and then improving the accuracy of the scoring values ​​corresponding to each driving behavior under the event-type category.

[0057] In an optional embodiment, the number of behavior occurrences corresponding to the driving behavior under the event-type category is determined based on the driving behavior data and the current influencing factors, including: determining candidate behavior influencing factor groups and behavior influence thresholds corresponding to the candidate behavior influencing factor groups based on the driving behavior influence matrix and the historical driving behavior data; selecting a target behavior influencing factor group from the candidate behavior influencing factor groups based on the driving behavior data and the current influencing factors; and determining the number of behavior occurrences corresponding to the driving behavior under the event-type category based on the driving behavior data and the behavior influence thresholds corresponding to the target behavior influencing factor group.

[0058] The driving behavior influence matrix may be a matrix used to determine the correlation between driving behavior and influencing factors. The driving behavior influence matrix may be determined by relevant technicians based on actual experience values ​​or experimental values.

[0059] For example, if the influencing factors include vehicle speed range, road type, traffic conditions and weather conditions; and the driving behaviors under the event-type category include acceleration, deceleration, steering, speeding, high-speed cornering, cornering braking, idling, driving prediction, AEB triggering, FCW, ESP triggering, and LDW triggering, then the driving behavior influence matrix under the event-type category determined by relevant technical personnel based on actual experience values ​​or experimental values ​​can be as shown in Table 1.

[0060] Table 1

[0061] Factors affecting driving behavior Speed ​​range Road Type Traffic status Weather conditions accelerate 1 1 1 1 slow down 0 1 1 0 Steering 1 1 1 0 Speeding 0 1 1 1 High speed cornering 1 1 0 0 Cornering Braking 1 1 1 0 Idle 0 1 1 0 Driving prediction 0 0 1 0 AEB triggering 0 0 0 0 FCW trigger 0 1 1 1 ESP Trigger 0 0 0 0 LDW Trigger 0 1 1 0

[0062] Among them, "0" in Table 1 indicates that there is no correlation between driving behavior and influencing factors; "1" indicates that there is a correlation between driving behavior and influencing factors.

[0063] The candidate behavior influencing factor grouping can be determined based on the driving behavior influencing matrix, and the behavior influencing threshold corresponding to the driving behavior influencing factor grouping can be determined based on the historical behavior data. The current influencing factor can be an influencing factor that changes continuously with the changes in the road, weather, traffic and other environments during driving. The target behavior influencing factor grouping can be a behavior influencing factor grouping corresponding to the driving state during driving.

[0064] Taking the acceleration driving behavior as an example, as shown in Table 1, it can be determined according to the driving behavior influence matrix that the acceleration driving behavior is related to the speed range, road type, traffic status and weather status, and the candidate behavior influence grouping is determined according to the arrangement and combination of the speed range, road type, traffic status and weather status. For example, the candidate behavior influence grouping may include grouping 1: cloudy weather, traffic congestion, urban road, speed range of 0-30km / h; grouping 2: sunny weather, smooth traffic, urban road, speed range of 30-60km / h; grouping 3: sunny weather, smooth traffic, rural road, speed range of 0-30km / h; grouping 4: cloudy weather, traffic congestion, rural road, speed range of 30-60km / h; grouping 5: sunny weather, smooth traffic, urban road, speed range of 60-80km / h; grouping 6: sunny weather, traffic congestion, rural road, speed range of 30-60km / h, etc. The specific number of groups can be set according to actual needs, and this embodiment does not limit this.

[0065] Based on historical driving behavior data, determine the behavior impact threshold corresponding to each candidate behavior impact factor group. For example, group 1: cloudy weather, traffic congestion, urban roads, speed range of 0-30km / h, the corresponding behavior impact threshold is 3.5m / s 2 . Among them, the method for determining the behavior impact threshold can be predetermined by relevant technical personnel. For example, the behavior impact threshold corresponding to group one can be the median acceleration in the historical driving behavior data belonging to group one. If the current influencing factors during driving are sunny weather, smooth traffic, rural roads, and a speed of 11km / h, then the target behavior impact factor group corresponding to the current influencing factors can be determined to be group three. If the behavior impact threshold corresponding to group three is 3.0m / s 2 , then under this influencing factor, when the driving acceleration exceeds 3.0m / s 2 When the vehicle is in a state of acceleration, an acceleration driving behavior is recorded.

[0066] Among them, in the entire driving journey, the acquisition time period of the current influencing factor can be pre-set, and the occurrence of the driving behavior can be determined. For example, the current influencing factor can be set to be acquired once every 10 minutes. It can also be that when the current influencing factor changes, whether the driving behavior occurs is determined once. For example, the current influencing factors are cloudy weather, traffic congestion, and urban roads. When the road state changes to a rural road, whether the driving behavior occurs is determined again. Similarly, the above scheme is used to determine the number of occurrences of behaviors corresponding to other driving behaviors under the event type category. For example, in the sudden deceleration driving behavior, the behavior influence threshold of the deceleration of each candidate behavior influencing factor group is set; in the FCW trigger driving behavior, the threshold of the number of FCW function activations corresponding to each candidate behavior influencing factor group is set; in the steering driving behavior, the threshold of the steering wheel speed in each candidate behavior influencing factor group is set; in the high-speed cornering driving behavior, the threshold of the average yaw angular velocity in each candidate behavior influencing factor group is set; in the cornering braking driving behavior, the threshold of the maximum deceleration in each candidate behavior influencing factor group is set; in the idling driving behavior, the threshold of the idling time in each candidate behavior influencing factor group is set, etc. This embodiment will not be repeated. Among them, each candidate behavior influence group corresponding to each driving behavior is determined according to the driving behavior influence matrix.

[0067] It should be noted that for driving behaviors whose corresponding influencing factor values ​​in the driving behavior influence matrix are all 0, the behavior influence threshold can be directly set. For example, for driving behavior AEB triggering, it can be determined through the driving behavior influence matrix that it is not related to the vehicle speed range, road type, traffic conditions and weather conditions. Therefore, the behavior influence threshold corresponding to the AEB triggering can be pre-set by relevant technicians. For example, the threshold of the number of AEB function activations can be set to 2 times.

[0068] This optional embodiment scheme determines the correlation between driving behavior and each influencing factor under the event type category through the driving behavior influence matrix, and determines the candidate behavior influencing factor grouping; according to the current influencing factors and driving behavior data, based on the behavior influence threshold corresponding to the candidate behavior influencing factor grouping, the number of behavior occurrences corresponding to the driving behavior under the event type category is determined, and the accurate determination of the number of behavior occurrences corresponding to each driving behavior is achieved, avoiding the situation where the number of behavior occurrences of the driving behavior is directly determined by the preset threshold method, resulting in inaccurate behavior number determination results, and improving the accuracy of the subsequent determination of the scoring values ​​corresponding to each driving behavior according to the number of behavior occurrences. It avoids using a unified judgment standard for the number of behavior occurrences to reduce the influence of environmental factors on the number of driving behavior occurrences, and improves the accuracy of the judgment of the behavior occurrence of driving behaviors.

[0069] S240: Determine the score corresponding to each driving behavior under the event type category according to the mileage value and the number of times the behavior occurs and based on the event type scoring rule.

[0070] The event-based scoring rules may be pre-set by relevant technical personnel, wherein the calculation formula corresponding to the event-based scoring rules may be as follows:

[0071]

[0072] Among them, S1 is the score of driving behavior under the event type category, N is the basic score, is the basic score adjustment coefficient, M is the number of times the behavior occurs, is the travel mileage adjustment coefficient, and D is the travel mileage value. and It can be preset by relevant technical personnel. For example, N can be 100, It can be 0.1, Can be -2.

[0073] It should be noted that in the event-based scoring rules, through logarithmic calculation, the indicators such as the number of driving behavior occurrences and mileage values ​​involved in the scoring calculation are non-linearly mapped to a specific value range to calculate the driving behavior score, so as to eliminate the impact caused by discrete changes in the indicators.

[0074] For different trips to be evaluated, when the mileage values ​​are the same, the one with fewer driving behaviors will have a higher driving behavior score; when the number of driving behaviors is the same, the one with a longer mileage value will have a higher score; when the mileage values ​​and the number of driving behaviors are different, the driving behavior scores will be different.

[0075] S250: Determine a driving behavior score of the driving user corresponding to the trip to be evaluated according to at least one scoring value.

[0076] This embodiment scheme obtains the mileage value of the trip to be evaluated; determines the number of occurrences of the behavior corresponding to the driving behavior under the event-type category according to the driving behavior data and the current influencing factors; and determines the score corresponding to each driving behavior under the event-type category based on the event-type scoring rules according to the mileage value and the number of occurrences of the behavior. The above scheme achieves accurate determination of the score of each driving behavior under the event-type category by determining the score corresponding to each driving behavior under the event-type category based on the event-type scoring rules according to the number of occurrences of the behavior corresponding to the driving behavior and the mileage value of the trip to be evaluated. This embodiment scheme comprehensively considers the influence of the mileage value and the influence of the number of occurrences of the driving behavior in the process of determining the driving behavior score, so as to determine the score corresponding to each driving behavior under the event-type category, thereby improving the accuracy of determining the score.

[0077] Embodiment 3

[0078] Figure 3 This is a flow chart of a driving behavior scoring method provided in Embodiment 3 of the present invention. This embodiment is optimized and improved on the basis of the above technical solutions.

[0079] Furthermore, if the driving behavior category is a continuous category; accordingly, the step of "determining the scoring values ​​corresponding to different driving behaviors under the corresponding driving behavior category according to the driving behavior scoring rules corresponding to different driving behavior categories and the driving behavior data corresponding to the corresponding driving behavior categories" is refined into "determining the behavior proportion corresponding to the driving behavior under the continuous category according to the driving behavior data and the current influencing factors; determining the scoring values ​​corresponding to each driving behavior under the continuous category based on the continuous scoring rules according to the behavior proportion." to improve the determination of the scoring values ​​corresponding to each driving behavior under the continuous category.

[0080] like Figure 3 As shown, the method comprises the following specific steps:

[0081] S310: Determine at least two driving behavior categories corresponding to the driving behavior data of the trip to be evaluated.

[0082] S320: If the driving behavior category is a continuous category, determine the behavior proportion corresponding to the driving behavior under the continuous category according to the driving behavior data and current influencing factors.

[0083] The driving behavior under the continuous category may be a driving behavior of continuity or a continuous event; the continuous category may include at least one of driving behaviors such as smooth driving and smooth deceleration.

[0084] The current influencing factors may include at least one of a vehicle speed range, a road type, a traffic state, and a weather state. The vehicle speed range may include 0-30 km / h, 30-60 km / h, 60-80 km / h, and 80-120 km / h; the road type may include urban roads and rural roads; the traffic state may include smooth traffic and traffic congestion; and the weather state may include cloudy weather and sunny weather. The number of behavior occurrences may be the number of times each driving behavior under the event type category occurs in the trip to be evaluated.

[0085] For example, the threshold corresponding to the continuous driving behavior can be pre-set by relevant technicians. For example, for the smooth acceleration driving behavior under the continuous category, the acceleration threshold can be set to 0.35m / s 2 ; The acceleration during the driving process to be evaluated is lower than 0.35m / s 2The duration of occurrence of the behavior is the ratio of the total duration of the trip to be evaluated as the behavior ratio corresponding to the smooth acceleration driving behavior. Alternatively, the acceleration during the trip to be evaluated is less than 0.35m / s 2 The ratio of the mileage of the trip to be evaluated to the total mileage of the trip to be evaluated is used as the behavior ratio corresponding to the smooth acceleration driving behavior.

[0086] It should be noted that the driving user may be affected by some internal or external factors during the driving process, such as weather conditions, roads and other factors. Therefore, the current influencing factors can be considered in the process of determining the behavior proportion corresponding to the driving behavior under the continuous category to eliminate the influence of the current influencing factors on the behavior proportion corresponding to the driving behavior, thereby improving the accuracy of the behavior proportion of the driving behavior under the continuous category, and then improving the accuracy of the scoring values ​​corresponding to each driving behavior under the continuous category.

[0087] In an optional embodiment, the behavior proportion corresponding to the driving behavior under the continuous category is determined based on the driving behavior data and the current influencing factors, including: determining the candidate behavior influencing factor grouping and the behavior influence threshold corresponding to the candidate behavior influencing factor grouping based on the driving behavior influence matrix and the historical driving behavior data; selecting the target behavior influencing factor grouping from the candidate behavior influencing factor grouping based on the driving behavior data and the current influencing factors; and determining the behavior proportion corresponding to the driving behavior under the continuous category based on the driving behavior data and the behavior influence threshold corresponding to the target behavior influencing factor grouping.

[0088] The driving behavior influence matrix may be a matrix used to determine the correlation between driving behavior and influencing factors. The driving behavior influence matrix may be determined by relevant technicians based on actual experience values ​​or experimental values.

[0089] For example, if the influencing factors include vehicle speed range, road type, traffic conditions and weather conditions; and the driving behaviors under the continuous category include smooth acceleration and smooth deceleration, then the driving behavior influence matrix under the event category determined by relevant technical personnel based on actual experience values ​​or experimental values ​​can be as shown in Table 2.

[0090] Table 2

[0091] Factors affecting driving behavior Speed ​​range Road Type Traffic status Weather conditions Smooth acceleration 1 1 1 1 Smooth deceleration 0 1 1 0

[0092] Among them, "0" in Table 2 indicates that there is no correlation between driving behavior and influencing factors; "1" indicates that there is a correlation between driving behavior and influencing factors.

[0093] The candidate behavior influencing factor grouping can be determined based on the driving behavior influencing matrix, and the behavior influencing threshold corresponding to the driving behavior influencing factor grouping can be determined based on the historical behavior data. The current influencing factor can be an influencing factor that changes continuously with the changes in the road, weather, traffic and other environments during driving. The target behavior influencing factor grouping can be a behavior influencing factor grouping corresponding to the driving state during driving.

[0094] Taking the steady acceleration driving behavior as an example, as shown in Table 2, it can be determined according to the driving behavior influence matrix that the steady acceleration driving behavior is related to the speed range, road type, traffic status and weather status, and the candidate behavior influence grouping is determined according to the arrangement and combination of the speed range, road type, traffic status and weather status. For example, the candidate behavior influence grouping may include grouping one: cloudy weather, traffic congestion, urban road, speed range of 0-30km / h; grouping two: sunny weather, smooth traffic, urban road, speed range of 30-60km / h; grouping three: sunny weather, smooth traffic, rural road, speed range of 0-30km / h; grouping four: cloudy weather, traffic congestion, rural road, speed range of 30-60km / h; grouping five: sunny weather, smooth traffic, urban road, speed range of 60-80km / h; grouping six: sunny weather, traffic congestion, rural road, speed range of 30-60km / h, etc. The specific number of groups can be set according to actual needs, and this embodiment does not limit this.

[0095] Based on the historical driving behavior data, determine the behavior impact threshold corresponding to each candidate behavior impact factor group. For example, group 1: cloudy weather, traffic congestion, urban roads, speed range of 0-30km / h, the corresponding behavior impact threshold is 2.5m / s 2 The method for determining the behavior impact threshold may be predetermined by relevant technical personnel. For example, the behavior impact threshold corresponding to group one may be the acceleration of the 20% percentile value in the historical driving behavior data belonging to group one. For example, the historical driving behavior data corresponding to group one includes an acceleration value of 1.5 m / s 2 , 1.5m / s 2 , 2m / s 2 , 2.5m / s 2 and 3m / s 2 , then the acceleration of the 20% percentile is 1.8m / s 2 .

[0096] If the total driving time of the trip to be evaluated is 30 minutes, the current influencing factors during the driving process are sunny weather, smooth traffic, rural roads, and a speed of 11km / h, then the target behavior influencing factor group corresponding to the current influencing factors can be determined as group three. If the behavior impact threshold corresponding to group three is 1.5m / s2 , then under this influencing factor, when the driving acceleration is lower than 1.5m / s 2 When the acceleration is less than 1.5m / s under this influencing factor, 2 Determine the total duration of the trip to be evaluated that meets the behavior impact threshold condition. For example, if the total duration that meets the behavior impact threshold condition is 27 minutes, the behavior corresponding to the smooth acceleration behavior accounts for 90%.

[0097] Among them, during the entire driving journey, the acquisition time period of the current influencing factor can be pre-set, and within the acquisition time period, the duration of the driving behavior meeting the behavioral impact threshold is determined. For example, it can be set to be determined every 10 minutes. It can also be that when the current influencing factor changes, the duration of the driving behavior meeting the behavioral impact threshold is determined. For example, if the current influencing factor is cloudy weather, traffic congestion, and urban roads, and the speed range is 0-30km / h, it is determined that under the current influencing factor, the duration of the smooth acceleration driving behavior meeting the behavioral impact threshold is 20 minutes. When the current influencing factor changes to the road state, the weather is clear, the traffic is smooth, and the urban road, and the speed range is 30-60km / h, it is determined that under the current influencing factor, the duration of the smooth acceleration driving behavior meeting the behavioral impact threshold is 10 minutes. If the total driving time of the trip to be evaluated is 40 minutes, it can be determined that the proportion of smooth acceleration driving behavior is 75%.

[0098] This optional embodiment scheme determines the candidate behavior influence factor grouping by determining the correlation between the driving behavior and each influencing factor under the continuous category through the driving behavior influence matrix; determines the behavior proportion corresponding to the driving behavior under the continuous category based on the behavior influence threshold corresponding to the candidate behavior influence factor grouping according to the current influencing factor and driving behavior data, thereby achieving accurate determination of the behavior proportion corresponding to each driving behavior, and improving the accuracy of subsequent determination of the scoring score corresponding to each driving behavior under the continuous category according to the behavior proportion.

[0099] S330: Determine the score corresponding to each driving behavior under the continuous category according to the behavior proportion and based on the continuous scoring rule.

[0100] The continuous scoring rule may be preset by relevant technical personnel, wherein the calculation formula corresponding to the continuous scoring rule may be as follows:

[0101]

[0102] Among them, S2 is the score of driving behavior under the continuous category, is the lower limit of the score, is the upper limit of the score, for The corresponding indicator value, that is, the preset behavior ratio, for The corresponding indicator value is The proportion of driving behaviors.

[0103] in, , , , It can be preset by relevant technical personnel. For example, is 60 points, 99 points. is 0, is 50%.

[0104] The larger the proportion of driving behaviors under the continuous category, the better the smooth driving condition during the trip to be evaluated, and the higher the score of the corresponding driving behavior; the smaller the proportion of driving behaviors under the continuous category, the worse the smooth driving condition during the trip to be evaluated, and the lower the score of the corresponding driving behavior.

[0105] S340: Determine a driving behavior score of the driving user corresponding to the trip to be evaluated according to at least one scoring value.

[0106] Optionally, if the driving behavior category is an indicative category, where the indicative category may be a driving behavior with binary characteristics based on whether the behavior occurs, and the driving behavior of the indicative category may include late night driving and fatigue driving, then the calculation formula of the indicative scoring rule corresponding to the indicative driving behavior is as follows:

[0107]

[0108] Among them, S3 is the score of the driving behavior under the indicative category. For the driving behavior under the indicative category, it is irrelevant to other influencing factors, such as weather conditions, road conditions, and traffic conditions. Therefore, the scoring value of the driving behavior under the indicative category in the trip to be evaluated can be determined by directly setting the behavior occurrence threshold.

[0109] For indicative driving behaviors such as fatigue driving and late-night travel, the driving behavior may only appear or not appear in the trip to be evaluated. For this binary behavior, once it appears once, the driving behavior score is 0, and if it never appears, the score is 100. Among them, the fatigue driving behavior threshold is the continuous driving time threshold. When the continuous driving time exceeds the preset behavior threshold, it can be considered as fatigue driving. Among them, the fatigue driving behavior threshold can be 6 hours. The behavior threshold for late-night travel can be a time threshold. For example, the range of the late-night travel time threshold can be 00:00-04:00.

[0110] This embodiment scheme determines the proportion of behaviors corresponding to driving behaviors under the continuous category based on driving behavior data and current influencing factors; and determines the scoring values ​​corresponding to each driving behavior under the continuous category based on the continuous scoring rules according to the proportion of behaviors. The above scheme achieves accurate determination of the scoring values ​​of each driving behavior under the continuity category by determining the scoring values ​​corresponding to each driving behavior under the continuous category based on the continuous scoring rules according to the proportion of behaviors corresponding to the driving behaviors. In the process of determining the driving behavior score, this embodiment scheme comprehensively considers the proportion of behaviors of continuous driving behaviors in the itinerary to be evaluated, so as to determine the scoring values ​​corresponding to each driving behavior under the continuous category, thereby improving the accuracy of determining the scoring values.

[0111] It should be noted that in order to improve the accuracy of the scoring values ​​corresponding to each driving behavior under each driving behavior category, the driving behavior influence matrix can be determined in the following manner.

[0112] In an optional embodiment, the driving behavior influence matrix may be determined by: determining a partial correlation analysis result between at least one driving behavior and a behavior influence factor based on historical driving behavior data; determining a correlation between at least one driving behavior and a behavior influence factor based on the partial correlation analysis result; and determining a driving behavior influence matrix based on the correlation between at least one driving behavior and a behavior influence factor.

[0113] The partial correlation analysis result may include a significance level between at least one driving behavior and a behavior influencing factor, and the correlation between at least one driving behavior and the behavior influencing factor may be determined through the significance level. The partial correlation analysis result may be obtained through SSPS (Statistical Product and Service Solutions) correlation analysis technology. Among them, the behavior influencing factors may include vehicle speed range, road type, traffic conditions, weather conditions, etc.

[0114] According to the significance level obtained from the partial correlation analysis, the results of the driving behavior influence matrix between 16 driving behaviors and behavior influencing factors can be obtained, as shown in Table 3.

[0115] Table 3

[0116] Factors affecting driving behavior Speed ​​range Road Type Traffic status Weather conditions accelerate 1 1 1 1 slow down 0 1 1 0 Smooth acceleration 1 1 1 1 Smooth deceleration 0 1 1 0 Steering 1 1 1 0 Speeding 0 1 1 1 High speed cornering 1 1 0 0 Cornering Braking 1 1 1 0 Idle 0 1 1 0 Driving prediction 0 0 1 0 AEB triggering 0 0 0 0 FCW trigger 0 1 1 1 ESP Trigger 0 0 0 0 LDW Trigger 0 1 1 0 Late night driving 0 0 0 0 Fatigue driving 0 0 0 0

[0117] Optionally, a linear regression algorithm may be used to determine the degree of correlation between the relevant driving behaviors and behavior influencing factors, and a driving behavior influence matrix may be determined based on the degree of correlation.

[0118] This optional embodiment improves the accuracy of the number of occurrences of the behavior corresponding to the driving behavior under the event-type category and the accuracy of the proportion of the behavior corresponding to the driving behavior under the continuous type category by determining the correlation between at least one driving behavior and the behavior influencing factor according to the significance level in the partial correlation analysis results between at least one driving behavior and the behavior influencing factor to obtain a driving behavior influence matrix, thereby improving the scoring value of the driving behavior under each driving behavior category, and further improving the driving behavior score of the driving user corresponding to the itinerary to be evaluated.

[0119] In a specific embodiment, the scoring values ​​of 16 types of driving behaviors under three categories, namely, event type, continuous type and indicative type, are determined. The driving behavior score of the trip to be evaluated is obtained according to the scoring values ​​corresponding to the 16 driving behaviors under the three categories. The driving behavior score S of the trip to be evaluated is determined as follows:

[0120]

[0121] Among them, A, B, C, D, E, F, G, H, I, J, K, L, M, N, O, P and Q are the scoring values ​​corresponding to the driving behaviors of acceleration, deceleration, steering, speeding, high-speed cornering, cornering braking, idling, driving prediction, AEB triggering, FCW triggering, ESP triggering, LDW triggering, smooth acceleration, smooth deceleration, late-night driving and fatigue driving. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p are the weight values ​​corresponding to the driving behaviors of acceleration, deceleration, steering, speeding, high-speed cornering, cornering braking, idling, driving prediction, AEB triggering, FCW triggering, ESP triggering, LDW triggering, smooth acceleration, smooth deceleration, late-night driving and fatigue driving.

[0122] Among them, for the driving behaviors of acceleration, deceleration, steering, speeding, high-speed cornering, cornering braking, idling, driving prediction, AEB triggering, FCW triggering, ESP triggering, and LDW triggering under the event category, the following calculation formula is used to determine the corresponding scoring value of the driving behavior:

[0123]

[0124] Among them, S1 is the score of driving behavior under the event type category, N is the basic score, is the basic score adjustment coefficient, M is the number of times the behavior occurs, is the travel mileage adjustment coefficient, and D is the travel mileage value. and It can be preset by relevant technical personnel. For example, N can be 100, It can be 0.1, Can be -2.

[0125] For smooth acceleration and smooth deceleration driving behaviors under the continuous category, the following calculation formula is used to determine the corresponding scoring value of the driving behavior:

[0126]

[0127] Among them, S2 is the score of driving behavior under the continuous category, is the lower limit of the score, is the upper limit of the score, for The corresponding indicator value, that is, the preset behavior ratio, for The corresponding indicator value is The proportion of driving behaviors.

[0128] in, , , , It can be preset by relevant technical personnel. For example, is 60 points, 99 points. is 0, is 50%.

[0129] For late night driving and fatigue driving behaviors under the indicative category, the following calculation formula is used to determine the corresponding scoring value of the driving behavior:

[0130]

[0131] Among them, S3 is the scoring value of driving behavior under the indicative category.

[0132] Based on the calculation formula of driving behavior scores of event-type categories, continuous categories and indicative categories, a score corresponding to at least one driving behavior is determined; according to the score corresponding to at least one driving behavior in the driving behaviors to be evaluated, based on the determination method of the driving behavior score of the trip to be evaluated, the driving behavior score of the driving user corresponding to the trip to be evaluated is determined.

[0133] Embodiment 4

[0134] Figure 4 This is a schematic diagram of the structure of a driving behavior scoring device provided in the fourth embodiment of the present invention. The driving behavior scoring device provided in the embodiment of the present invention can be applied to the situation of scoring the driving behavior of the user during the trip. The device can be implemented in software and / or hardware. Figure 4As shown, the device specifically includes: a driving behavior category determination module 401, a score determination module 402 and a driving behavior score determination module 403.

[0135] A driving behavior category determination module 401 is used to determine at least two driving behavior categories corresponding to the driving behavior data of the trip to be evaluated;

[0136] The scoring value determination module 402 is used to determine the scoring values ​​corresponding to different driving behaviors under the corresponding driving behavior categories according to the driving behavior data corresponding to the corresponding driving behavior categories according to the driving behavior scoring rules corresponding to the different driving behavior categories;

[0137] The driving behavior score determination module 403 is used to determine the driving behavior score of the driving user corresponding to the to-be-evaluated trip according to at least one of the score values.

[0138] The embodiment of the present invention determines at least two driving behavior categories corresponding to the driving behavior data of the trip to be evaluated; for the driving behavior scoring rules corresponding to different driving behavior categories, the scoring values ​​corresponding to different driving behaviors under the corresponding driving behavior categories are determined according to the driving behavior data corresponding to the corresponding driving behavior categories; and the driving behavior score of the driving user corresponding to the trip to be evaluated is determined according to at least one scoring value. The above scheme adopts the driving behavior scoring rules corresponding to different driving behavior categories to determine the scoring values ​​corresponding to each driving behavior under the corresponding driving behavior categories, thereby realizing the targeted determination of the scoring values ​​of driving behaviors according to different driving behavior scoring rules under the driving behavior categories determined according to the behavioral characteristics of the driving behaviors. Compared with the prior art in which the same driving behavior scoring rules are used to determine the scoring values ​​for different driving behaviors, the present invention has a higher accuracy in determining the scoring values ​​corresponding to the driving behaviors.

[0139] Optionally, different driving behavior categories correspond to different driving behavior scoring rules.

[0140] Optionally, if the driving behavior category is an event-type category, the scoring value determination module 402 includes:

[0141] A trip mileage value obtaining unit, used to obtain the trip mileage value of the trip to be evaluated;

[0142] A behavior occurrence number determination unit, used to determine the behavior occurrence number corresponding to the driving behavior under the event type category according to the driving behavior data and current influencing factors;

[0143] The scoring value determination unit is used to determine the scoring value corresponding to each driving behavior under the event type category based on the trip mileage value and the number of times the behavior occurs and based on the event type scoring rule.

[0144] Optionally, the behavior occurrence frequency determination unit includes:

[0145] A first group determination subunit is used to determine candidate behavior influencing factor groups and behavior influence thresholds corresponding to the candidate behavior influencing factor groups according to the driving behavior influence matrix and historical driving behavior data;

[0146] A first group selection subunit is used to select a target behavior influencing factor group from the candidate behavior influencing factor groups according to the driving behavior data and the current influencing factors;

[0147] The behavior occurrence count determination subunit is used to determine the behavior occurrence count corresponding to the driving behavior under the event type category according to the driving behavior data and the behavior influence threshold corresponding to the target behavior influence factor group.

[0148] Optionally, if the driving behavior category is a continuous category, the scoring value determination module 402 includes:

[0149] A behavior proportion determination unit, configured to determine a behavior proportion corresponding to the driving behavior under the continuous category according to the driving behavior data and the current influencing factors;

[0150] The scoring value determination unit is used to determine the scoring value corresponding to each driving behavior under the continuous category according to the behavior proportion and based on the continuous scoring rule.

[0151] Optional, behavior ratio determination unit, including:

[0152] A first group determination subunit is used to determine candidate behavior influencing factor groups and behavior influence thresholds corresponding to the candidate behavior influencing factor groups according to the driving behavior influence matrix and historical driving behavior data;

[0153] A second group selection subunit is used to select a target behavior influencing factor group from the candidate behavior influencing factor groups according to the driving behavior data and the current influencing factor;

[0154] The behavior proportion determination subunit is used to determine the behavior proportion corresponding to the driving behavior under the continuous category according to the driving behavior data and the behavior influence threshold corresponding to the target behavior influencing factor group.

[0155] Optionally, the device further comprises an influence matrix determination module, wherein the influence matrix determination module is used to determine a driving behavior influence matrix;

[0156] The impact matrix determination module includes:

[0157] A partial correlation analysis result determination unit, used to determine a partial correlation analysis result between at least one driving behavior and a behavior influencing factor based on historical driving behavior data;

[0158] a correlation determination unit, configured to determine the correlation between at least one driving behavior and a behavior influencing factor according to the partial correlation analysis result;

[0159] The influence matrix determination unit is used to determine the driving behavior influence matrix according to the correlation between at least one driving behavior and the behavior influence factor.

[0160] The above-mentioned driving behavior scoring device can execute the driving behavior scoring method provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing each driving behavior scoring method.

[0161] Embodiment 5

[0162] Figure 5 A schematic diagram of an electronic device 50 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0163] like Figure 5 As shown, the electronic device 50 includes at least one processor 51, and a memory connected to the at least one processor 51 in communication, such as a read-only memory (ROM) 52, a random access memory (RAM) 53, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 51 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 52 or the computer program loaded from the storage unit 58 to the random access memory (RAM) 53. In the RAM 53, various programs and data required for the operation of the electronic device 50 can also be stored. The processor 51, the ROM 52, and the RAM 53 are connected to each other through a bus 54. An input / output (I / O) interface 55 is also connected to the bus 54.

[0164] A number of components in the electronic device 50 are connected to the I / O interface 55, including: an input unit 56, such as a keyboard, a mouse, etc.; an output unit 57, such as various types of displays, speakers, etc.; a storage unit 58, such as a disk, an optical disk, etc.; and a communication unit 59, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 59 allows the electronic device 50 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0165] The processor 51 may be a variety of general and / or dedicated processing components with processing and computing capabilities. Some examples of the processor 51 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 51 executes the various methods and processes described above, such as the driving behavior scoring method.

[0166] In some embodiments, the driving behavior scoring method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 58. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 50 via the ROM 52 and / or the communication unit 59. When the computer program is loaded into the RAM 53 and executed by the processor 51, one or more steps of the driving behavior scoring method described above may be performed. Alternatively, in other embodiments, the processor 51 may be configured to execute the driving behavior scoring method in any other appropriate manner (e.g., by means of firmware).

[0167] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0168] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0169] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, device, or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0170] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0171] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0172] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0173] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0174] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A driving behavior scoring method, characterized in that: include: Determine at least two driving behavior categories corresponding to the driving behavior data of the trip to be evaluated; According to the driving behavior scoring rules corresponding to different driving behavior categories, the scoring values ​​corresponding to different driving behaviors under the corresponding driving behavior categories are determined according to the driving behavior data corresponding to the corresponding driving behavior categories; Determine, according to at least one of the rating scores, a driving behavior score of the driving user corresponding to the trip to be evaluated; Among them, different driving behavior categories correspond to different driving behavior scoring rules; If the driving behavior category is an event-type category, the driving behavior scoring rules corresponding to different driving behavior categories determine the scoring values ​​corresponding to different driving behaviors under the corresponding driving behavior category according to the driving behavior data corresponding to the corresponding driving behavior category, including: Obtaining the mileage value of the trip to be evaluated; Determine the number of occurrences of the driving behavior corresponding to the event-type category according to the driving behavior data and current influencing factors; wherein the current influencing factors include at least one of a vehicle speed range, a road type, a traffic condition, and a weather condition; According to the mileage value and the number of occurrences of the behavior, based on the event-type scoring rule, determine the scoring value corresponding to each driving behavior under the event-type category; and / or, If the driving behavior category is a continuous category, the driving behavior scoring rules corresponding to different driving behavior categories determine the scoring values ​​corresponding to different driving behaviors under the corresponding driving behavior category according to the driving behavior data corresponding to the corresponding driving behavior category, including: Determine the behavior proportion corresponding to the driving behavior under the continuous category according to the driving behavior data and the current influencing factors; wherein the current influencing factors include at least one of a vehicle speed range, a road type, a traffic condition, and a weather condition; According to the behavior proportions and based on continuous scoring rules, the scoring values ​​corresponding to the various driving behaviors under the continuous category are determined.

2. The method according to claim 1, characterized in that The determining, based on the driving behavior data and the current influencing factors, the number of occurrences of the behavior corresponding to the driving behavior under the event type category includes: Determine, according to the driving behavior influence matrix and the historical driving behavior data, candidate behavior influence factor groups and behavior influence thresholds corresponding to the candidate behavior influence factor groups; Selecting a target behavior influencing factor group from the candidate behavior influencing factor groups according to the driving behavior data and the current influencing factors; The number of behavior occurrences corresponding to the driving behavior under the event type category is determined according to the driving behavior data and the behavior influence threshold corresponding to the target behavior influence factor group.

3. The method according to claim 1, characterized in that Determining the behavior proportion corresponding to the driving behavior under the continuous category according to the driving behavior data and the current influencing factors includes: Determine, according to the driving behavior influence matrix and the historical driving behavior data, candidate behavior influence factor groups and behavior influence thresholds corresponding to the candidate behavior influence factor groups; Selecting a target behavior influencing factor group from the candidate behavior influencing factor groups according to the driving behavior data and the current influencing factors; The behavior proportion corresponding to the driving behavior under the continuous category is determined according to the driving behavior data and the behavior influence threshold corresponding to the target behavior influence factor grouping.

4. The method according to claim 2 or 3, characterized in that: The driving behavior influence matrix is ​​determined as follows: Determine, based on historical driving behavior data, a partial correlation analysis result between at least one driving behavior and a behavior influencing factor; Determining the correlation between at least one driving behavior and a behavior influencing factor according to the partial correlation analysis result; A driving behavior influence matrix is ​​determined according to a correlation between at least one driving behavior and a behavior influence factor.

5. A driving behavior scoring device, characterized in that: include: A driving behavior category determination module, used to determine at least two driving behavior categories corresponding to the driving behavior data of the trip to be evaluated; A scoring value determination module is used to determine the scoring values ​​corresponding to different driving behaviors under the corresponding driving behavior categories according to the driving behavior scoring rules corresponding to different driving behavior categories and the driving behavior data corresponding to the corresponding driving behavior categories; A driving behavior score determination module, used to determine the driving behavior score of the driving user corresponding to the to-be-evaluated trip according to at least one of the score values; Among them, different driving behavior categories correspond to different driving behavior scoring rules; If the driving behavior category is an event-type category, the scoring value determination module includes: A trip mileage value obtaining unit, used to obtain the trip mileage value of the trip to be evaluated; a behavior occurrence number determination unit, configured to determine the behavior occurrence number corresponding to the driving behavior under the event type category according to the driving behavior data and current influencing factors; wherein the current influencing factors include at least one of a vehicle speed range, a road type, a traffic condition, and a weather condition; A scoring value determination unit, configured to determine the scoring value corresponding to each driving behavior under the event type category according to the mileage value and the number of occurrences of the behavior and based on an event type scoring rule; and / or, If the driving behavior category is a continuous category, the scoring value determination module includes: a behavior proportion determination unit, configured to determine the behavior proportion corresponding to the driving behavior under the continuous category according to the driving behavior data and the current influencing factors; wherein the current influencing factors include at least one of a vehicle speed range, a road type, a traffic condition, and a weather condition; The scoring value determination unit is used to determine the scoring value corresponding to each driving behavior under the continuous category according to the behavior proportion and based on the continuous scoring rule.

6. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the driving behavior scoring method according to any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the driving behavior scoring method according to any one of claims 1 to 4 when executed.

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