CN113837504B - Method, device and terminal equipment for evaluating driving danger level of driver based on operation data - Google Patents

Method, device and terminal equipment for evaluating driving danger level of driver based on operation data Download PDF

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CN113837504B
CN113837504B CN202010498464.5A CN202010498464A CN113837504B CN 113837504 B CN113837504 B CN 113837504B CN 202010498464 A CN202010498464 A CN 202010498464A CN 113837504 B CN113837504 B CN 113837504B
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许乐
周金明
韩晓春
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Nanjing Xingzheyi Intelligent Transportation Technology Co ltd
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Abstract

The invention discloses a method, a device and terminal equipment for evaluating driving danger level of a driver based on operation data, wherein the method comprises the following steps: step 1, acquiring the actual execution condition of a shift of a certain driver for n consecutive days and a driving schedule of the following day, wherein the actual execution condition of the shift comprises the shift executed by the driver and the start and stop time of the shift, and step 2, calculating a plurality of working strength parameters and dangerous behavior parameters of the driver, and determining the driving dangerous degree level of the driver. Through analysis of past operation data of a driver and a driving plan to be executed, the fatigue degree level of the driver and the driving behavior risk degree level of the driver are quantitatively represented, and the driving risk level of the driver is comprehensively and reasonably estimated. The method comprises the steps of carrying out key monitoring on a driver with higher risk level, adjusting a driving plan of the driver, carrying out early intervention in modes such as safe driving training and the like, and avoiding or reducing the possibility of dangerous driving behaviors of the driver, so that personal safety of the driver and passengers is guaranteed.

Description

Method, device and terminal equipment for evaluating driving danger level of driver based on operation data
Technical Field
The invention relates to intelligent transportation, in particular to the field of public transportation research, and particularly relates to a method, a device and terminal equipment for evaluating driving danger level of a driver based on operation data.
Background
The bus is taken as an important component of urban public transportation, a large number of passengers are transported every day, and the bus is selected to travel only 531 ten thousand times in 2019 of Nanjing as an example, and once the accident result of the bus is not envisaged, the safe driving work of the bus is finished, and the prevention and control of dangerous driving behaviors are particularly critical. In the process of implementing the present invention, the inventor finds that at least the following problems exist in the prior art: current solutions for monitoring the safe driving behavior of a bus driver, which are common in the industry, generally require that additional hardware devices be installed on the bus. If the real-time driving image of the driver is acquired through the camera, the real-time driving track of the driver is analyzed, and the like, the dangerous driving behavior of the driver is alarmed through a complex algorithm. The current implementation scheme of the method has higher cost and has high requirements on the reliability of the hardware reliability algorithm. In addition, the current monitoring method alarms dangerous driving behaviors in real time in the driving process of the driver, and lacks early warning of the driving risk of the high-risk driver, and the dangerous driving behaviors of the driver are often tracked and circulated, so that the early avoidance and early warning can be realized to a certain extent.
Disclosure of Invention
In order to overcome the defects of the prior art, the embodiment of the disclosure provides a method, a device and terminal equipment for evaluating the driving risk level of a driver based on operation data, and the driving risk level of the driver is comprehensively and reasonably evaluated. The technical proposal is as follows:
in a first aspect, there is provided a method of assessing driver driving risk level based on operational data, the method comprising:
step 1, obtaining the actual execution condition of a shift of a certain driver in the past of n continuous days and a driving schedule of the following day, wherein the actual execution condition of the shift comprises the shift executed by the driver and the start-stop time of the shift,
the bus shift types include: the double-shift, single-shift and sub-shift, wherein the double-shift is that a certain driver only executes the morning shift or the afternoon shift, the single-shift is that a certain driver executes the whole-day driving plan of a vehicle, and the sub-shift is that a certain driver only executes the shift in the morning and evening passenger flow peak.
Step 2, calculating a plurality of working intensity parameters and dangerous behavior parameters of the driver, and determining the driving danger degree level of the driver;
and according to a driving schedule of the following day, counting the maximum continuous driving duration CT of the driver when the day and the total rest time BT in the continuous driving time.
If CT is greater than or equal to CT max +α, and BT < BT min The driver's fatigue level is high,
if CT max ＜CT＜CT max +α, and BT < BT min The driver's fatigue level is high,
if CT is less than or equal to CT max The driver's fatigue level is low,
CT max for a given maximum continuous driving duration, BT min For a shortest rest period within a given maximum continuous driving period; alpha is a given constant.
According to the actual execution condition of the shifts of the driver in the past for n consecutive days, the driver connection is countedAverage driving duration AT for n days, and setting maximum average driving duration AT max Setting upIf k is less than 1, the driver fatigue level is low, if 1 is less than or equal to k is less than 1+ω, the driver fatigue level is high, if k is less than or equal to 1+ω, the driver fatigue level is high, ω is a constant less than 1.
According to the actual execution condition of the shift of the previous day of the driver, the rest time period RT of the driver on the same day and night is counted,
if RT is greater than or equal to RT min The driver fatigue level is low
If RT min -β＜RT＜RT min The driver is fatigued to a high degree
If RT is not more than RT min Beta, the driver fatigue is high
RT min For a given reasonable sleep period, β is a given constant.
If 1 item of the fatigue degree of the driver is high according to the maximum continuous driving time CT, the average driving time AT of continuous n days and the rest time RT of the day and night, the driving danger degree of the driver is high;
if 2 items in the fatigue degree of the driver are higher, the driving danger degree of the driver is higher;
if only 1 item in the fatigue degree of the driver is higher, the driving danger degree of the driver is lower;
if the fatigue degree of the driver is low, the driving danger degree of the driver is low, and the risk is avoided.
Preferably, in counting the continuous driving time period CT, if the interval time period of two shifts is BT min Within this, continuous driving is considered.
Preferably, the driver's night rest period RT may be replaced with a period of driver sleep monitored by a sleep monitoring device, such as a sport wristband.
Preferably, the method for evaluating the driving risk level of the driver can also work strongly for each driverSetting the fatigue degree of the driver in the degree parameter, and setting the value X of the fatigue degree of the driver according to the fatigue degree 1 、X 2 、X 3 … … (X is less than or equal to 1), and weighting lambda is set for working strength parameters of a plurality of drivers 1 、λ 2 、λ 3 … …, (wherein lambda) 1 +λ 2 +λ 3 + … … =1) according to the cumulative result Σ (λ i *X i ) And obtaining the fatigue driving risk level of the driver.
Preferably, if the driving risk level of the driver is low or low, further judging the risk behavior parameters of the driver, and further judging the driving risk level of the driver according to the risk behaviors, wherein the risk behaviors are as follows: overspeed, arrival of superpoints, station slipping, violation.
Preferably, the driving danger degree of the driver is further judged according to the dangerous behavior, specifically: according to the number or frequency of various dangerous behaviors of a driver for m consecutive days in the past: overspeed Y 1 Super point reaching Y 2 Station Y 3 Violation Y 4 Setting weight beta for various dangerous behaviors 1 、β 2 、β 3 、β 4 ，β 1 +β 2 +β 3 +β 4 =1, according to Σ (β i *Y i ) Further judging the driving danger degree of the driver.
Further, when counting the number or frequency of various dangerous behaviors in the past consecutive m days, the number or frequency of dangerous behaviors in the peak period of the passenger flow=the actual number or frequency of dangerous behaviors in the peak period of the passenger flow μ, μ > 1, because dangerous behaviors occur in the peak period of the passenger flow, the dangerous degree is more serious. When Sigma (. Beta.) i *Y i ) Above a certain threshold, the driver is considered to be driving at a higher or higher risk.
Preferably, the driving danger degree of the driver is further judged according to the dangerous behavior, specifically: overspeed behavior means that the road quasi time T of a certain period of a certain driver is obviously lower than the average road quasi time of the period
If it isThe driver's driving behavior is at a high risk,
if it isThe driver driving behavior is at a higher risk;
if it isThe driving behavior risk of the driver is low or low, 1 < eta 1 ＜η 2 ；
The super-point arrival refers to the phenomenon that the actual arrival time of the bus is earlier than the planned arrival time, and the super-point rate P of the driver is defined e Super-point arrival times C and total shift times C 0 P is then e ＝C/C 0 If P e ≥η 4 The driver is considered to have a high risk of driving behavior if eta 3 <P e <η 4 The driver is considered to have a higher risk of driving behavior if P e ≤η 3 The driver's driving behavior is low or low in risk; 1 < eta 3 ＜η 4 。
The bus stop is the behavior of bus stop without stop, defines the driver stop sliding rate Ps,if Ps is greater than or equal to eta 6 If η is high, the driving behavior of the driver is considered to be dangerous 5 ＜Ps＜η 6 The dangerous degree of the driving behavior of the driver is considered to be higher, if Ps is less than or equal to eta 5 The driver's driving behavior is at a low or low risk.
The violation behaviors are obtained from the traffic management system, the violation driver is positioned through the violation vehicle and the violation time, the driving behavior risk degree of the driver is high when the violation times are larger than a threshold value according to the number of the violations in the past continuous m days of the driver, the driving behavior risk degree of the driver is high when the violation times are larger than 0 and smaller than the threshold value, and the driving behavior risk degree of the driver is low when the violation times are 0.
If 1 item in the driving behavior risk degree of the driver is high, the driving risk degree of the driver is high;
if 2 items in the driving behavior risk degree of the driver are higher, the driving risk degree of the driver is higher;
if only 1 item in the driving behavior risk degree of the driver is higher, the driving risk degree of the driver is lower;
if the driving behaviors of the driver are low in risk level, the driving risk level of the driver is low.
Preferably, when dangerous behavior occurs in a peak traffic period, the value of η is smaller in the process of judging the dangerous degree of the driving behavior of the driver than when dangerous behavior occurs in a non-peak traffic period.
Further, if the overspeed behavior occurs during the peak period of the passenger flow when the risk level of the driving behavior of the driver of the overspeed behavior is judgedThe driver's driving behavior is at a high risk,
if it isThe driver driving behavior is at a higher risk;
if it isThe driver driving behavior has low risk degree or lower, 1 < eta' 1 ＜η’ 2 ，η’ 1 ＜η 1 ，η′ 2 ＜η 2 。
Further, if P is the case when the super-point arrival behavior occurs in the peak period of passenger flow when judging the dangerous degree of the driving behavior of the driver of the super-point arrival behavior e ≥η’ 4 The driver is considered to have high driving behavior risk degree if eta' 3 <P e <η’ 4 The driver is considered to have a higher risk of driving behavior if P e ≤η’ 3 Otherwise, the driver driving behavior is low or low in risk; 1 < eta' 3 ＜η’ 4 ，η’ 3 ＜η 3 ，η’ 4 ＜η 4 。
Further, if Ps is greater than or equal to eta 'when the stop-slip behavior occurs in the peak passenger flow period' 6 If η 'is high, the driving behavior of the driver is considered to be dangerous' 5 ＜Ps＜η’ 6 The dangerous degree of the driving behavior of the driver is considered to be higher, if Ps is less than or equal to eta' 5 The driver driving behavior has low or lower risk degree, 1 < eta' 5 ＜η’ 6 ，η’ 5 ＜η 5 ，η’ 6 ＜η 6 。
Further, if the offending behavior occurs during peak traffic hours, the value of the threshold value becomes relatively small.
Preferably, the method further comprises a step 3 of performing manual intervention on the driver with high or higher driving risk level in the scheduling process or the dispatching process, reasonably adjusting the executed shift, and/or performing safe driving training on the driver, and/or adjusting the driving plan, and/or performing important monitoring on the high-risk driver.
In a second aspect, there is provided an apparatus for evaluating a driving risk level of a driver based on operational data, the apparatus including an acquisition unit, an evaluation unit;
the obtaining unit is configured to perform the step 1 of the method for evaluating the driving risk level of the driver based on the operation data according to any one of all possible implementation manners;
the evaluation unit is configured to perform the step 2 of the method of evaluating a driver driving risk level based on operational data according to any one of all possible implementations.
Preferably, the device further comprises a processing unit for performing the step 3 of a method of assessing driver driving risk level based on operational data according to any one of all possible implementations.
In a third aspect, embodiments of the present disclosure provide a terminal device, which includes an apparatus for evaluating a driver driving risk level based on operational data according to any one of all possible implementations.
Compared with the prior art, one of the technical schemes has the following beneficial effects:
through analysis of past operation data of a driver and a driving plan to be executed, dangerous driving habits of the driver can be depicted, the working intensity of the driver is monitored, the fatigue degree level of the driver and the driving behavior dangerous degree level of the driver are quantitatively represented, and the driving dangerous level of the driver is comprehensively and reasonably estimated. The method comprises the steps of carrying out key monitoring on a driver with higher risk level, arranging the key driver to carry out early intervention in a safe driving training mode and the like by adjusting the driving plan of the driver, and avoiding or reducing the possibility of dangerous driving behaviors of the driver, so that the personal safety of the driver and passengers is ensured.
Detailed Description
In order to clarify the technical scheme and working principle of the present invention, the following describes the embodiments of the present disclosure in further detail.
Any combination of the above-mentioned optional solutions may be adopted to form an optional embodiment of the present disclosure, which is not described herein in detail.
The terms "step 1," "step 2," "step 3," and the like in the description and in the claims are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that embodiments of the present application described herein may be capable of operation in sequences other than those described herein, for example.
In this embodiment, the drivers include, but are not limited to, drivers of buses, and drivers of buses and buses of enterprises that use similar operation modes as buses.
First aspect: the embodiment of the disclosure provides a method for evaluating driving danger level of a driver based on operation data, which mainly comprises the following steps:
step 1, acquiring actual execution conditions of shifts of a certain driver for 6 consecutive days and a driving schedule of the following day, dividing a sample range into seven natural days, and statistically evaluating dimension-related working intensity of consecutive working days; table 1 shows seven continuous natural day driving plans of a certain bus driver, 2019-12-24-2019-12-29 shows actual shift execution conditions of the past 6 continuous days, 2019-12-30 shows driving plans of the following day, wherein the shift types of 24 days and 26-28 days are double shifts, and the shift types of 29 and 30 days are divided shifts.
TABLE 1 actual execution of a driver's shifts over 6 consecutive days and the current day's trip schedule
Step 2, calculating a plurality of working intensity parameters and dangerous behavior parameters of the driver
(1) And (5) counting the continuous driving duration of the driver on the same day:
according to the rule of the sixty two regulations of the national road traffic safety law of the people's republic: driving a motor vehicle must have the following actions: (seventh) continuously driving the motor vehicle for more than 4 hours without stopping the motor vehicle or for less than 20 minutes; therefore, CT is preferred max =240 min, BT min The total duration of the morning shift is less than 4 hours and the interval between the morning shift and the afternoon shift is greater than 20 minutes according to the following day schedule, namely 2019-12-30 days, and the maximum continuous driving duration only needs to count the afternoon, and the detailed schedule is shown in table 2:
TABLE 2 2019-12-30 day time schedule for a driver
If the interval duration of two shifts is BT min Within this, considered as continuous driving, the maximum continuous driving duration of the driver on day 30 is ct=42+46+43+48+44+43+39=305 minutes > CT max +α=300 minutes, rest period bt=2+1+4+1+5+6=19 minutes<BT min =20 minutes, i.e. the driver fatigue is high.
(2) The average working time of the last week of the driver is counted, and according to the average working time AT= (516+343+413+510+513)/6=382.5 min of the drivers 2019-12-24-2019-12-30 shown in table 1, the working time of the worker per week is set to be not more than 44 hours, namely 2640 minutes, according to the labor rule, namely the corresponding average working time per day is 377 minutes, and the AT is set max When the driver is in the fatigue state of =37 and ω=0.2, the fatigue degree of the driver is higher when 1.ltoreq.k=382.5/377=1.015 times < 1.2.
(3) The rest time of the driver on the same day and night is counted:
the driver usually needs to arrive at the station half an hour in advance before departure, and the driver cooperates with the crew to carry out daily inspection before departure, so that the rest deadline of the driver is set to be one hour before departure time of the first class. The driver rest time was set at one hour after the end of the last shift. As shown in table 1, the night rest period from the previous day of work to the present day (30 days) of work for the driver is rt=463 (22:04:58-05:48:00) -120=343 minutes, given RT min 480 minutes, β=180 minutes, i.e. the sleeping time of the driver is preferably 8 hours, not less than 5 hours, 300 minutes<RT<480 minutes considered the driver to be fatigued to a higher degree.
In summary, since the driver fatigue level obtained from the continuous driving time period on the same day of the driver is high, the driving risk level is high.
Preferably, if the obtained driving risk level of the driver is low or lower according to the working strength parameter of the driver, further judging the risk behavior parameter of the driver, and further judging the driving risk level of the driver according to the risk behavior, wherein the risk behavior is as follows: overspeed, arrival of the superpoint, station slipping and violation;
the driving data of the last 30 days or weekends of the driver are summarized to describe the driving habit of the driver.
(1) Overspeed behavior:
overspeed behavior does not mean that the driving real-time driving speed of the driver exceeds the speed specified by laws and regulations. And counting the average road standard time of each period of drivers of each line in a period of time as a time speed reference standard of each period of time of the line. If the driving time of a certain driver in a certain period is obviously lower than the average driving time of the period, the driving speed of the driver is obviously too fast, and a certain risk exists. By default, the driver's driving shift distribution averages, and the route average road-target time is calculated without regard to the extremes of driver overspray or underspray. Average route time of each period of the route driver
Taking a seven-day driving schedule of a certain driver as an example of a driving route of the driver, counting average route standard time T of each period of nearly 30 working days of the route:
TABLE 3 average route time for each period of a route
Sequence number Time period Average road time (minutes)
1 00:00:00～07:00:00 29.5
2 07:00:00～09:00:00 38.3
3 09:00:00～17:00:00 36.8
4 17:00:00～19:00:00 43.4
5 19:00:00～00:00:00 33.7
According to the actual situation, in the non-passenger flow peak period, eta is given 1 The value is 1.1, eta 2 The value is 1.2, if the driver is in off-peak time, if T/T is more than or equal to 1.2, the driving behavior risk degree of the driver is considered to be high. If it isThe driving behavior risk degree of the driver is considered to be higher, and if T/T is less than or equal to 1.1, the driving behavior risk degree of the driver is considered to be low;
in peak periods of 07:00:00-09:00:00 and 17:00:00-19:00:00, eta 'is given' 1 The value is 1.05, eta' 2 Take a value of 1.1 ifThe driver driving behavior is at a high risk if +.>The driver driving behavior is at a higher risk; if->The driver's driving behavior is less dangerous or less dangerous.
(2) Super point arrival:
the phenomenon that the actual arrival time of buses is earlier than the planned arrival time is called super-point arrival, the super-point arrival easily causes a phenomenon of vehicle-crossing in the peak time, and the arrival station time is set to be two minutes or more earlier than the planned arrival time. Given a given eta 3 The value is 1.1, eta 4 The value is 1.2, and the super point rate P of the driver is defined e Super-point arrival times C and total shift times C 0 P is then e ＝C/C 0 . If P e More than or equal to 1.2, the driving behavior of the driver is considered to have high risk degree, if 1.2>P e >1.1 the driver's driving behavior is considered to be moderately dangerous.
(3) And (3) sliding:
the bus stop-free behavior is called stop slip, and the GPS track is compared with the GPS coordinates of each stop of the line through the GPS track uploaded in the vehicle running process. By calculating the stay time of the running track near the GPS coordinates of the platform, whether the driver has the station sliding behavior or not can be judged. The driver slip rate Ps is defined,if Ps is greater than or equal to 1.2, the driver is considered to have a high risk of driving behavior, if 1.2>Ps>1.1 the driver's driving behaviour is considered to be at a high risk.
If the driving behavior risk level of the driver is high in 1 item of driving behavior risk levels, the driving risk level of the driver is high;
if 2 items in the driving behavior risk degree of the driver are higher, the driving risk degree of the driver is higher;
if only 1 item in the driving behavior risk degree of the driver is higher, the driving risk degree of the driver is lower;
if the driving behavior risk degree of the driver is low, the driving risk degree of the driver is low, and no risk exists;
preferably, the method further comprises a step 3 of manually intervening the driver with high or higher driving danger level in the scheduling process or the dispatching process, reducing the execution quantity of the shifts, and/or performing safety consciousness training and/or adjusting the driving plan. Evaluating the driving risk of the current driver according to the driving risk level, and reasonably adjusting the scheduling to avoid continuous driving of the driver with high fatigue level if necessary; arranging safe driving related training for drivers with dangerous driving behaviors, and taking whether the dangerous driving behaviors exist as driver assessment indexes; the method is characterized in that drivers with high fatigue degree and dangerous driving behaviors are monitored in a key mode, and necessary intervention is carried out through a dispatching means.
In a second aspect, there is provided an apparatus for evaluating a driving risk level of a driver based on operational data, the apparatus including an acquisition unit, an evaluation unit;
the obtaining unit is configured to perform the step 1 of the method for evaluating the driving risk level of the driver based on the operation data according to any one of all possible implementation manners;
the evaluation unit is configured to perform the step 2 of the method for evaluating a driving risk level of a driver based on operational data according to any one of all possible implementations;
preferably, the device further comprises a processing unit for performing the step 3 of a method of assessing driver driving risk level based on operational data according to any one of all possible implementations.
It should be noted that, when the apparatus for estimating the driving risk level of the driver based on the operation data provided in the above embodiment performs a method for estimating the driving risk level of the driver based on the operation data, only the division of the above functional modules is used for illustration, and in practical application, the above functional allocation may be performed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules, so as to complete all or part of the functions described above. In addition, the device for evaluating the driving risk level of the driver based on the operation data and the method for evaluating the driving risk level of the driver based on the operation data provided in the foregoing embodiments belong to the same concept, and detailed implementation processes of the device are detailed in the method and are not described herein.
In a third aspect, embodiments of the present disclosure provide a terminal device, which includes an apparatus for evaluating a driver driving risk level based on operational data according to any one of all possible implementations.
While the invention has been described above by way of example, it is evident that the invention is not limited to the particular embodiments described above, but rather, it is intended to provide various insubstantial modifications, both as to the method concepts and technical solutions of the invention; or the above conception and technical scheme of the invention are directly applied to other occasions without improvement and equivalent replacement, and all are within the protection scope of the invention.

Claims (10)

1. A method of assessing driver driving risk level based on operational data, the method comprising:
step 1, obtaining the actual execution condition of a shift of a certain driver in the past of n continuous days and a driving schedule of the following day, wherein the actual execution condition of the shift comprises the shift executed by the driver and the start-stop time of the shift,
step 2, calculating a plurality of driver intensity parameters, and determining the driving danger degree level of the driver;
according to the driving schedule of the following day, the maximum continuous driving duration CT of the driver and the total rest time BT in the continuous driving time are counted,
if CT is greater than or equal to CT max +α, and BT < BT min The driver's fatigue level is high,
if CT max ＜CT＜CT max +α, and BT < BT min The driver's fatigue level is high,
if CT is less than or equal to CT max The driver's fatigue level is low,
CT max for a given maximum continuous driving duration, BT min For the most part within a given maximum continuous driving durationShort rest time; alpha is a given constant;
according to the actual execution condition of the shifts of the driver for n continuous days, the average driving duration AT of the driver for n continuous days is counted, and the maximum average driving duration AT is set max Setting upIf k is less than 1, the fatigue degree of the driver is low, if k is less than or equal to 1+ω, the fatigue degree of the driver is higher, if k is less than or equal to 1+ω, the fatigue degree of the driver is high, and ω is a constant less than 1;
according to the actual execution condition of the shift of the previous day of the driver, the rest time period RT of the driver on the same day and night is counted,
if RT is greater than or equal to RT min The driver fatigue level is low
If RT min -β＜RT＜RT min The driver is fatigued to a high degree
If RT is not more than RT min Beta, the driver fatigue is high
RT min For a given reasonable sleep duration, β is a given constant;
if 1 item of the fatigue degree of the driver is high according to the maximum continuous driving time CT, the average driving time AT of continuous n days and the rest time RT of the day and night, the driving danger degree of the driver is high;
if 2 items in the fatigue degree of the driver are higher, the driving danger degree of the driver is higher;
if only 1 item in the fatigue degree of the driver is higher, the driving danger degree of the driver is lower;
if the fatigue degree of the driver is low, the driving danger degree of the driver is low.
2. The method for estimating a driving risk level of a driver based on operation data according to claim 1, wherein in counting the continuous driving time period CT, if the interval time period of two shifts is BT min Within this, continuous driving is considered.
3. A method of assessing a driver's driving risk level based on operational data according to claim 1 wherein the driver's rest period RT overnight on the day may be replaced by a driver's sleep period as monitored by the sleep monitoring device.
4. A method for estimating a driver's driving risk level based on operation data according to any one of claims 1-3, wherein the driver's driving risk level estimating method further comprises quantifying the driver fatigue level in each of the driver's operation strength parameters, and setting the driver fatigue level value X according to the magnitude of the fatigue level 1 、X 2 、X 3 … …, X is less than or equal to 1, and a weight lambda is set for the working strength parameters of a plurality of drivers 1 、λ 2 、λ 3 … …, where lambda 1 +λ 2 +λ 3 + … … =1, according to the cumulative result Σ (λ i *X i ) And obtaining the fatigue driving risk level of the driver.
5. The method for evaluating driving risk level of a driver based on operation data according to any one of claims 1 to 4, wherein if the driving risk level of the driver is low or low, further judging the risk behavior parameter of the driver, further judging the driving risk level of the driver based on the risk behavior, wherein the risk behavior is: overspeed, arrival of superpoints, station slipping, violation.
6. The method for evaluating driving risk level of a driver based on operational data of claim 5, further comprising determining the driving risk level of the driver based on the risk behavior, in particular: according to the number or frequency of various dangerous behaviors of a driver for m consecutive days in the past: overspeed Y 1 Super point reaching Y 2 Station Y 3 Violation Y 4 Setting weight beta for various dangerous behaviors 1 、β 2 、β 3 、β 4 ，β 1 +β 2 +β 3 +β 4 =1, according to Σ (β i *Y i ) Further judging the driving danger degree of the driver.
7. The method for evaluating driving risk level of a driver based on operational data of claim 5, further comprising determining the driving risk level of the driver based on the risk behavior, in particular:
overspeed behavior means that the road quasi time T of a certain period of a certain driver is obviously lower than the average road quasi time of the periodIf->The driver driving behavior is at a high risk if +.>The driver driving behavior is at a higher risk; if it isThe driving behavior risk of the driver is low or low, 1 < eta 1 ＜η 2 ；
The super-point arrival refers to the phenomenon that the actual arrival time of the bus is earlier than the planned arrival time, and the super-point rate P of the driver is defined e Super-point arrival times C and total shift times C 0 P is then e ＝C/C 0 If P e ≥η 4 The driver is considered to have a high risk of driving behavior if eta 3 <P e <η 4 The driver is considered to have a higher risk of driving behavior if P e ≤η 3 The driver's driving behavior is low or low in risk; 1 < eta 3 ＜η 4 ；
The bus stop is the behavior of bus stop without stop, defines the driver stop sliding rate Ps,if Ps is greater than or equal to eta 6 If η is high, the driving behavior of the driver is considered to be dangerous 5 ＜Ps＜η 6 The dangerous degree of the driving behavior of the driver is considered to be higher, if Ps is less than or equal to eta 5 The driver's driving behavior is low or low in risk;
the method comprises the steps that the violation behaviors are obtained from a traffic management system, a violation driver is positioned through a violation vehicle and violation time, the driving behavior risk degree of the driver is high when the violation number is greater than a threshold value according to the number of violations in the past continuous m days of the driver, the driving behavior risk degree of the driver is high when the violation number is greater than 0 and smaller than the threshold value, and the driving behavior risk degree of the driver is low when the violation number is 0;
if 1 item in the driving behavior risk degree of the driver is high, the driving risk degree of the driver is high;
if 2 items in the driving behavior risk degree of the driver are higher, the driving risk degree of the driver is higher;
if only 1 item in the driving behavior risk degree of the driver is higher, the driving risk degree of the driver is lower;
if the driving behavior risk degree of the driver is low, the driving risk degree of the driver is low;
when dangerous behavior occurs in the peak period of passenger flow, the value of eta is smaller than that of eta when dangerous behavior occurs in the non-peak period of passenger flow in the process of judging the dangerous degree of driving behavior of a driver.
8. A method of assessing a driver's driving risk level based on operational data according to any one of claims 1-3, 6-7 further comprising step 3 of manually intervening on drivers with a high or higher driving risk level during or during a scheduling, rationally adjusting the shifts they perform, and/or performing safe driving training on them, and/or adjusting the driving plan, and/or performing a high risk driver's critical monitoring.
9. An apparatus for evaluating driving danger level of a driver based on operation data, the apparatus comprising an acquisition unit, an evaluation unit;
the acquisition unit for performing the step of step 1 of a method of evaluating a driver driving risk level based on operational data according to any one of claims 1-8;
the evaluation unit for performing the step of step 2 of a method of evaluating a driver driving risk level based on operational data according to any one of claims 1-8.
10. A terminal device, characterized in that it comprises a device for evaluating the driving risk level of a driver based on operational data according to claim 9.
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