Task scheduling method and device, electronic equipment and computer program product

Abstract

The invention provides a task scheduling method and device, electronic equipment and a computer program product, and the method comprises the steps: obtaining a to-be-executed first transportation task, a transportation time period of the first transportation task, and a risk level, and obtaining the driving information of each to-be-matched first driver; according to the driving information, idle target drivers in the transportation time period are determined in the first drivers; under the condition that the driving score contained in the driving information of the target driver is greater than or equal to the score corresponding to the risk level, predicting a target mental state score of the target driver in the transportation time period according to the current mental state score contained in the driving information of the target driver; and when the target mental state score is greater than or equal to a preset threshold value, sending a task work order corresponding to the first transportation task to a terminal device associated with the target driver. According to the invention, the execution security of the transportation task is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of testing, in particular to a task scheduling method and device, electronic equipment and computer program product. BACKGROUND

[0002] With the development of the transportation industry, the number of transportation tasks is increasing, and personnel need to be dispatched for each transportation task to perform the transportation task.

[0003] In the exemplary technology, when scheduling a transportation task, a vehicle is arranged for the transportation task, and the vehicle is bound to a driver, that is, a driver is dispatched for the transportation task by arranging a vehicle to perform the scheduling of the transportation task.

[0004] The above scheduling of the transportation task is performed by the vehicle, and the safety of performing the transportation task needs to be ensured, but based on the vehicle adapting to the transportation task, the safety of performing the transportation task is not improved, that is, the safety of performing the transportation task is low. SUMMARY

[0005] Based on the above technical status, the present application provides a task scheduling method, device, electronic equipment and computer program product to solve the problem of low safety of performing the transportation task.

[0006] In order to achieve the above technical purpose, the present application specifically proposes the following technical solutions:

[0007] In a first aspect, the present application provides a task scheduling method, comprising:

[0008] obtaining a first transportation task to be performed, a transportation time period and a risk level of the first transportation task, and obtaining driving information of each first driver to be matched;

[0009] According to the driving information, a target driver is determined among the first drivers who is idle in the transportation time period;

[0010] In the case that the driving score contained in the driving information of the target driver is greater than or equal to the score corresponding to the risk level, the target mental state score of the target driver in the transportation time period is predicted according to the current mental state score contained in the driving information of the target driver.

[0011] In the case that the target mental state score is greater than or equal to a preset threshold, a task order corresponding to the first transportation task is sent to a terminal device associated with the target driver.

[0012] In some embodiments, the driving information of each first driver to be matched is obtained, comprising:

[0013] acquire historical driving behaviors of the first driver in driving a vehicle, physiological information of the first driver when performing a second transportation task, completion information of the second transportation task, device information, and basic information of the first driver;

[0014] determine scores of the first driver on a plurality of scoring factors according to the historical driving behaviors, the physiological information, the completion information, the device information, and the basic information, the scores of the plurality of scoring factors including at least two of a mental state score, a driving behavior compliance score, a concentration score, a device health score, a driving smoothness score, and a work intensity score;

[0015] determine a driving score of the first driver according to the scores corresponding to the respective scoring factors and weights;

[0016] construct driving information of the first driver according to the scores of the respective scoring factors and the driving score.

[0017] In some embodiments, the determining, according to the driving information, a target driver who is idle in the transportation time period among the first drivers, includes:

[0018] determining, based on the driving information, a first driver corresponding to an idle time period including the transportation time period as a second driver;

[0019] determining a matching degree between the second driver and the first transportation task according to driving information of the second driver and task information of the first transportation task;

[0020] determining the second driver as the target driver in a case where the matching degree is greater than or equal to a set threshold.

[0021] In some embodiments, the determining the second driver as the target driver includes:

[0022] determining a first work intensity parameter required for performing the first transportation task according to task information of the first transportation task;

[0023] determining an execution completion time corresponding to a last time of performing a transportation task by the second driver and a second work intensity parameter according to driving information of the second driver;

[0024] predicting a target work intensity parameter of the second driver in performing the first transportation task according to the execution completion time, an execution start time of the first transportation task, and the first work intensity parameter;

[0025] In a case where the target working strength parameter is greater than or equal to the first working strength parameter, the second driver is determined as a target driver.

[0026] In some embodiments, the matching degree between the second driver and the first transportation task is determined according to the driving information of the second driver and the task information of the first transportation task, including:

[0027] A first transportation route to which the second driver is adapted is determined according to the driving information of the second driver.

[0028] A second transportation route is determined according to the task information of the first transportation task.

[0029] An overlapping route between the first transportation route and the second transportation route is determined, and the matching degree between the second driver and the first transportation task is determined according to a ratio between a route length of the overlapping route and a route length of the second transportation route.

[0030] In some embodiments, the task order corresponding to the first transportation task is sent to a terminal device associated with the target driver, including:

[0031] A first execution efficiency parameter of the target driver when performing a transportation task is determined according to the driving information of the target driver.

[0032] In a case where the first execution efficiency parameter is greater than or equal to a second execution efficiency parameter required by the first transportation task, the task order corresponding to the first transportation task is sent to the terminal device associated with the target driver.

[0033] In some embodiments, the first transportation task to be executed is obtained, including:

[0034] A plurality of unexecuted third transportation tasks are obtained, and a priority of each third transportation task is determined.

[0035] The third transportation task corresponding to the highest priority is determined as the first transportation task to be executed.

[0036] In a second aspect, the present application provides a task scheduling device, including:

[0037] An obtaining module is configured to obtain a first transportation task to be executed, a transportation time period and a risk level of the first transportation task, and obtain driving information of each first driver to be matched.

[0038] A determining module is configured to determine a target driver who is idle in the transportation time period from each first driver according to the driving information.

[0039] predicting, by the prediction module, a target mental state score of the target driver in the transportation time period according to a current mental state score included in the driving information of the target driver, in a case where the driving score included in the driving information of the target driver is greater than or equal to the score value corresponding to the risk level;

[0040] sending, by the sending module, a task order corresponding to the first transportation task to a terminal device associated with the target driver, in a case where the target mental state score is greater than or equal to a preset threshold.

[0041] In a third aspect, the present application provides an electronic device, including a memory and a processor, wherein,

[0042] The memory is connected with the processor, and is configured to store a program.

[0043] The processor is configured to realize the task scheduling method according to the first aspect or any implementation manner of the first aspect by running the program in the memory.

[0044] In a fourth aspect, the present application provides a computer program product, which realizes the task scheduling method according to the first aspect or any implementation manner of the first aspect when executed by a processor.

[0045] In a fifth aspect, the present application provides a computer readable storage medium, which stores a computer program, and the computer program realizes the task scheduling method according to the first aspect or any implementation manner of the first aspect when executed by a processor.

[0046] The task scheduling method, device, electronic device and computer program product provided by the embodiments of the present application obtain a transportation task to be executed, a transportation time period corresponding to the transportation task and a risk level, determine a target driver having an idle time in the transportation time period from the first drivers, predict a target mental state of the target driver in the transportation time period based on a current mental state score included in the driving information of the target driver, in a case where a driving score included in the driving information of the target driver is greater than or equal to a score value corresponding to the risk level, and distribute a task order of the transportation task to a terminal device associated with the target driver, in a case where the target mental state score is greater than or equal to a preset threshold. In the present application, a driver having a high driving score is arranged to the transportation task, so that the driver having a good driving behavior executes the transportation task, and the execution safety of the transportation task is improved. In addition, the target mental state score of the driver in executing the transportation task is greater than the preset threshold, so that the mental state of the driver in executing the transportation task is good, and the execution safety of the transportation task is further improved. BRIEF DESCRIPTION OF DRAWINGS

[0047] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the accompanying drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced. Obviously, the accompanying drawings in the following description only need to be drawn for the embodiments of the present application, and other drawings can be obtained by those skilled in the art without any creative effort on the basis of the provided drawings.

[0048] Figure 1 A scene schematic diagram of a task scheduling method provided by an embodiment of the present application

[0049] Figure 2 A flow of a task scheduling method provided by an embodiment of the present application Figure 1

[0050] Figure 3 A flow of a task scheduling method provided by an embodiment of the present application Figure 2

[0051] Figure 4 A flow of a task scheduling method provided by an embodiment of the present application Figure 3

[0052] Figure 4 A flow of a task scheduling method provided by an embodiment of the present application Figure 6

[0053] Figure 7 A module schematic diagram of a task scheduling device provided by an embodiment of the present application

[0054] Figure 1 A structure schematic diagram of an electronic device provided by an embodiment of the present application DETAILED DESCRIPTION

[0055] The technical solution provided by the embodiments of the present application is suitable for the test scene of display components, and aims to improve the test efficiency of display components. By using the technical solution described in the embodiments of the present application, the test system inputs the working current simulating the actual voltage fluctuation of the measured system in the running process to the measured system, so that the test system can test the reason causing the display component to appear black screen in normal operation, and the test effect of the display component is improved. In addition, the test system performs multiple rounds of tests on the total number of times of testing the display component, realizes long-time testing of the display component, and thus can find the hidden black screen problem of the display component under long-time work, and the test effect of the display component is improved.

[0056] ​​​​With reference to the drawings of the embodiments of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described. Obviously, the described embodiments are only a part of the embodiments of the present application, but not all the embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the scope of the present application.

[0057] It should be noted that the user information (including but not limited to user equipment information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in the present application are all information and data authorized by the user or authorized by all parties, and the collection, use and processing of related data need to comply with relevant laws, regulations and standards, and provide corresponding operation portal for user to choose authorization or refusal.

[0058] With the development of the transportation industry, the number of transportation tasks is increasing, and personnel need to be dispatched for each transportation task to perform the transportation task.

[0059] In the example technology, when scheduling a transportation task, a vehicle is arranged for the transportation task, and the vehicle is bound to a driver, that is, a driver is scheduled for the transportation task by arranging a vehicle to perform the scheduling of the transportation task.

[0060] The above scheduling of the transportation task is performed by the vehicle, and the safety of performing the transportation task needs to be ensured, but based on the vehicle adapting to the transportation task, the safety of performing the transportation task is not improved, that is, the safety of performing the transportation task is low.

[0061] Therefore, the embodiments of the present application are dedicated to providing a task scheduling method, device, electronic equipment and computer program product, by arranging a driver with a high driving score for a transportation task, so that a driver with good driving behavior performs the transportation task, and the safety of performing the transportation task is improved. In addition, the target mental state score of the driver performing the transportation task is greater than a preset threshold, so that the mental state of the driver performing the transportation task is good, and the safety of performing the transportation task is further improved.

[0062] Among them, the task scheduling method, device, electronic equipment and computer program product provided by the embodiments of the present application can be applied to the scheduling scene of the transportation task.

[0063] Reference Figure 1 , Exemplary methodA schematic diagram of a scene of the task scheduling method of the present application. The task scheduling device 100 obtains a transportation task to be executed, a transportation time period corresponding to the transportation task, and a risk level. The obtaining method can be input by a scheduling personnel to the task scheduling device 100. The task scheduling device 100 obtains the driving information of each first driver to be matched. The driving information can be stored in the task scheduling device 100. The task scheduling device 100 determines a target driver who is idle in the transportation time period among the first drivers based on the driving information. When the driving score contained in the driving information of the target driver is greater than or equal to the score corresponding to the risk level, the target mental state score of the target driver in the transportation time period is predicted based on the current mental state score contained in the driving information of the target driver. If the target mental state score is greater than or equal to a preset threshold, the task order corresponding to the transportation task is sent to the terminal device 200 associated with the target driver to complete the allocation of the transportation task.

[0064] Figure 2

[0065] Figure 1 A flow of a task scheduling method provided by an embodiment of the present application Figure 2 . As shown in Figure 3 , the task scheduling method provided by the embodiment includes:

[0066] Step S201, obtaining a first transportation task to be executed, a transportation time period of the first transportation task, and a risk level, and obtaining driving information of each first driver to be matched.

[0067] In the embodiment, the execution subject is a task scheduling device. The task scheduling device can be an entity device or a virtual device where a transportation task scheduling center is located. The task scheduling device can also be any terminal device with a transportation task scheduling function. For ease of description, the device is used to represent the task scheduling device hereinafter.

[0068] The device obtains a transportation task to be executed, which is defined as a first transportation task. In an example, a scheduling personnel inputs a transportation task to the device, and the device takes the input transportation task as the first transportation task to be executed.

[0069] In another example, a plurality of unexecuted third transportation tasks are stored in the device. Each third transportation task has corresponding task information, and the task information contains the priority of the third transportation task. For example, the priority of the third transportation task A is high, the priority of the third transportation task B is medium, and the priority of the third transportation task C is low. The device determines the priority corresponding to each third transportation task, and determines the third transportation task corresponding to the highest priority as the first transportation task to be executed, that is, the third transportation task A with high priority as the first transportation task.

[0070] After obtaining the first transportation task, the device obtains a transportation time period and a risk level in the task information of the first transportation task. The transportation time period is, for example, 14:00-18:00. The risk level is, for example, high, medium, or low.

[0071] After obtaining the risk level, the device obtains driving information of each first driver to be matched. Each first driver can be all drivers, and each first driver is associated with driving information, which includes a driving score and a current mental state score.

[0072] For example, the driving score refers to a comprehensive score obtained by the driver in driving the vehicle, which is calculated based on driver behavior data, driver annual physical examination data, driver age, driver driving age, driver cumulative driving deduction data, driver education level, and driver cumulative transportation mileage. The driver behavior data includes: driver freight order data, loading and unloading time, daily order volume, order completion time, order span mileage, order receiving time, completion time, red light running, smoking, not wearing a seat belt, and not yielding to pedestrians during driving. The driving behavior score is determined based on the driver behavior data, the driving behavior of the driver represented by the driver behavior data is more standardized, and the greater the driving behavior score; the driver health score is determined based on the driver health examination data, the healthier the driver represented by the driver health examination data, the higher the health score; the age score is determined based on the driver age, the younger the driver, the greater the age score; the driving age score is determined based on the driver driving age, the greater the driving age, the greater the driving age score; the deduction score is determined based on the driving deduction data, the more deductions represented by the driving deduction data, the smaller the deduction score; the culture score is determined based on the driver education level, the higher the driver education level, the higher the culture score; and the mileage score is determined based on the driver cumulative transportation mileage, the longer the mileage, the greater the mileage score. The device can obtain the comprehensive score by superimposing or weighting calculating the above scores. The driving score represents the safety of the driver driving the vehicle, and the higher the driving score, the higher the safety of the driver driving the vehicle.

[0073] The mental state score can represent the concentration, stability, fatigue level, or a combination of the above of the driver driving the vehicle. The higher the mental state score, the higher the concentration, the higher the stability, and the lower the fatigue level.

[0074] In step S202, according to the driving information, a target driver who is idle in the transportation time period is determined from the first drivers.

[0075] The driving information further includes a state of the first driver, the state including an idle state and a task state. The task state is associated with a task time period, and the idle state is associated with an idle time period. The device determines, based on the idle time period in the driving information, a first driver who is idle during the transportation time period among the first drivers as the target driver. For example, if the idle time period includes the transportation time period, it can be determined that the first driver is idle during the transportation time period.

[0076] In step S203, in a case where the driving score included in the driving information of the target driver is greater than or equal to the score corresponding to the risk level, a target mental state score of the target driver during the transportation time period is predicted according to the current mental state score included in the driving information of the target driver.

[0077] The risk level of the transportation task is different, and the required driver is different. For example, if the risk level of the transportation task is high, a driver with a driving score of 90 or higher is required; if the risk level of the transportation task is medium, a driver with a driving score of 80 or higher is required; and if the risk level of the transportation task is low, a driver with a driving score of 70 or higher is required.

[0078] To this end, the device determines the score corresponding to the risk level corresponding to the transportation task, and determines whether the driving score of the target driver is greater than or equal to the score. If the driving score is greater than or equal to the score, it is preliminarily determined that the safety of the target driver in performing the first transportation task is high. However, the mental state factor of the driver also needs to be considered. The device obtains a target mental state score of the target driver during the transportation time period from a current mental state score included in the driving information based on the current mental state score. In an example, the device stores a regular parameter of the mental state recovery of the target driver. Based on the regular parameter and the current mental state score, the target mental state score can be determined. For example, the regular parameter is that the mental state score is increased by 2 points every hour of rest. The interval time length is determined based on the current time point and the start time point of the transportation time period. The product of the interval time length and 2 is added to the current mental state score to obtain the target mental state score. In another example, the current mental state score, the information of the vehicle driven by the target driver, the basic information, and the transportation time period are input into a prediction model to obtain the target mental state score output by the prediction model. The prediction model is trained based on each training sample. The training sample includes sample data and a label. The sample data includes the information of the vehicle driven by the other driver, the basic information, the transportation time period of the transportation task that has been performed, and the mental state score. The label refers to the mental state score of the other driver during the transportation time period of the transportation task that has been performed.

[0079] Step S204, in the case that the target mental state score is greater than or equal to the preset threshold, the task order corresponding to the first transportation task is sent to the terminal device associated with the target driver.

[0080] After obtaining the target mental state score, it is determined whether the target mental state score is greater than or equal to a preset threshold, for example, 80. In the case that the target mental state score is greater than or equal to the preset threshold, it can be determined that the target driver not only meets the safety requirement of the first transportation task in terms of driving score, but also meets the requirement of the first transportation task in terms of concentration and stability, etc., to ensure that the safety of the target driver performing the first transportation task is high. Therefore, the device generates a task order corresponding to the first transportation task, and sends the task order to the terminal device associated with the target driver to complete the dispatch of the first transportation task.

[0081] It should be noted that in the case that there are multiple target drivers available in the transportation time period, the task order is sent to the target driver whose driving score is greater than or equal to the score corresponding to the risk level and whose target mental state score is greater than the preset threshold.

[0082] In addition, after the dispatch of the first transportation task is completed, the first transportation task to be performed is determined in the remaining third transportation tasks, and the target driver is determined in the remaining first drivers, that is, the first transportation task to be performed is determined in the remaining third transportation tasks, and the step of returning to perform the transportation time period and the risk level of the first transportation task to be performed is performed.

[0083] In addition, after the target driver receives the task order based on the terminal device, the target driver can refuse the task order, that is, the target driver sends a refusal message based on the terminal device, and the device returns to perform steps S201 to S204 to select a driver suitable for the first transportation task.

[0084] In the embodiment, the transportation task to be executed, the transportation time period corresponding to the transportation task, and the risk level are acquired, a target driver having an idle time in the transportation time period is determined among the first drivers, in a case where the driving score contained in the driving information of the target driver is greater than or equal to the score value corresponding to the risk level, the target mental state of the target driver in the transportation time period is predicted based on the current mental state score contained in the driving information of the target driver, and in a case where the target mental state score is greater than or equal to a preset threshold, the task order of the transportation task is dispatched to the terminal device associated with the target driver. In the embodiment, a driver with a high driving score is arranged for the transportation task, so that the driver with good driving behavior executes the transportation task, and the execution safety of the transportation task is improved. In addition, the target mental state score of the driver in executing the transportation task is greater than the preset threshold, so that the mental state of the driver in executing the transportation task is good, and the execution safety of the transportation task is further improved.

[0085] Figure 2 A task scheduling method provided in the embodiment of the application Figure 4 , based on Figure 3 As shown in the embodiment, step S201 includes:

[0086] In step S301, the historical driving behavior of the first driver in driving the vehicle, the physiological information of the first driver in executing the second transportation task, the completion information of the second transportation task, the equipment information, and the basic information of the first driver are acquired.

[0087] In the embodiment, the device acquires the historical driving behavior of the first driver in driving the vehicle, the physiological information of the first driver in executing the second transportation task, the completion information of the second transportation task, the equipment information, and the basic information of the first driver.

[0088] For example, an image acquisition component is arranged in the vehicle, and the image acquisition component is, for example, a camera. When the first driver executes the transportation task, the image acquisition component performs driving behavior scanning, fixed-point positioning face and upper body scanning on the driver on the driver's seat, and the fixed-point positioning face and upper body scanning can be used to acquire the physiological information of the driver. When the driver's non-standard driving behavior is scanned, voice broadcast is performed, and the voice broadcast is used to correct the driving behavior of the driver. For example, the driver does not wear a safety belt, the driver dozes off during driving, the driver smokes in the vehicle compartment during driving, and the like. In addition, the voice broadcast does not affect the driving of the driver. For example, the volume of the voice broadcast is moderate, the frequency of the voice broadcast is moderate, and the frequency and the volume of the voice broadcast are increased when the driver does not correct. It can be understood that the historical driving behavior of the first driver in driving the vehicle, the physiological information of the first driver in executing the second transportation task, and the second transportation task executed by the first driver can be acquired by this way.

[0089] Further, the terminal device associated with the first driver is provided with an application program for performing the transportation task, and the first driver opens the application program on the terminal device, and performs a clock-in and clock-out based on the application program, collects the working time of the first driver, and the completion information of the second transportation task, and the completion information includes the completion time of the second transportation task, the length of the transportation route, etc. In addition, the device also needs to obtain the device information of the terminal device, and the device information refers to the running information in the terminal device corresponding to the second transportation task performed by the first driver, and the running information represents the device health of the terminal device.

[0090] The device obtains the basic information of the first driver, and the basic information includes the education level of the first driver, the driving age of the first driver, and the age of the first driver.

[0091] In step S302, the score of the first driver on a plurality of scoring factors is determined according to the historical driving behavior, the physiological information, the completion information, the device information and the basic information, and the score of the plurality of scoring factors includes at least two of the mental state score, the driving behavior compliance score, the concentration score, the device health score, the driving stability score and the work intensity score.

[0092] The device determines the score of the first driver on a plurality of scoring factors based on the historical driving behavior, the physiological information, the completion information, the device information and the basic information, and the score of the plurality of scoring factors includes at least two of the mental state score, the driving behavior compliance score, the concentration score, the device health score, the driving stability score and the work intensity score. For example, the driving scores of three drivers D1, D2 and D3 are shown in Table-1:

[0093] Table-1

[0094]

[0095] For example, the mental state score can be determined based on the physiological information. For example, based on the physiological information, it is determined that the first driver is in a fatigue state, and the mental state score is low.

[0096] The compliance score can be determined by the historical driving behavior. When there is an irregular driving behavior in the historical driving behavior, a numerical value is deducted from the total compliance score, and when the total compliance score is deducted from all the numerical values of the irregular driving behaviors, the compliance score is obtained.

[0097] The concentration score can be determined by the physiological information. For example, the physiological information includes the state of the face collected by the image acquisition component, and the face state includes the detection of the eyes of the first driver. The ratio between the length of the eyes staring forward and the total length of the second transportation task is converted into the concentration score. The larger the ratio is, the larger the concentration score is.

[0098] The device health score is determined by device information, which represents the stability of the application program executed by the terminal device for running the transportation task. For example, the greater the remaining computing resources in the device information, the higher the device health score.

[0099] The stability score is determined by completion information. The completion information contains data collected when the vehicle executes the second transportation task, including the vehicle speed during the execution of the second transportation task, and the cumulative duration of vehicle jolting collected by the direction sensor. The higher the vehicle speed and the greater the cumulative duration of jolting, the lower the stability score.

[0100] The work intensity is determined by the basic information and the completion information. The total duration of continuous work (driving) of the first driver is determined by the basic information, and the duration of continuous work lost by the first driver is determined by the completion information. The difference duration is obtained by subtracting the lost duration from the total duration, and the difference duration is converted into work intensity. The greater the difference duration, the greater the work intensity score. For example, based on the basic information, it can be determined that the first driver can work continuously for 6 hours, but the duration of the first driver's last execution of the transportation task is 4 hours, and 0.5 hours of duration is lost per hour. Therefore, the difference duration of the first driver is 4 hours, and 4 / 6 is converted into a work intensity score of 66.6.

[0101] In step S303, the driving score of the first driver is determined according to the scores corresponding to each score factor and the weights.

[0102] After obtaining the above-mentioned score factors, the driving score of the first driver can be obtained by weighted calculation based on each score factor and the corresponding weight. The weight can be set artificially or as needed.

[0103] In step S304, the driving information of the first driver is constructed according to the scores of each score factor and the driving score.

[0104] After obtaining the driving score of the first driver, the driving information of the first driver can be constructed based on the scores of the score factors and the driving score. The driving information is each score in the above table.

[0105] When the target driver executes the first transportation task, the non-standard driving behavior of the target driver is reported by voice, and the physiological information of the target driver is collected by an infrared scanning device. In addition, the relevant data of the target driver executing the first transportation task is also displayed in the form of a chart.

[0106] The driving behavior image of each driver, the comprehensive score ranking of each driver, the daily driver attendance data, the daily driver vehicle positioning data, the daily order quantity / total order quantity, the driver scheduling data, the driver driving behavior non-standard warning data, etc. are comprehensively displayed in the form of charts.

[0107] In the embodiment, by adding the mobile phone for obtaining the driving behavior data of the driver on the vehicle through the application, the driving information such as the driving behavior data and the health comprehensive score value of the driver can be obtained through analysis of the data, so that the driver is automatically scheduled, the driver's willingness for scheduling is collected offline without manual operation, the labor cost for scheduling is reduced, and more accurate scheduling is realized, and the expertise and previous transportation experience of each driver are fully utilized.

[0108] In the embodiment, the device accurately obtains the driving information of the first driver based on the historical driving behavior of the first driver, the physiological information when the second transportation task is performed, the completion information of the second transportation task, the equipment information, and the basic information of the first driver.

[0109] Figure 2 The flow of the task scheduling method provided in the embodiment Figure 3 Based on the embodiments shown in Figure 5 or Figure 4 , step S202 includes:

[0110] In step S401, based on the driving information, the first driver corresponding to the idle time period containing the transportation time period is determined as the second driver.

[0111] In the embodiment, based on the driving information of each first driver, the first driver corresponding to the idle time period containing the transportation time period is determined as the second driver, that is, the first driver capable of performing the first transportation task is determined as the second driver among each first driver.

[0112] In step S402, the matching degree between the second driver and the first transportation task is determined according to the driving information of the second driver and the task information of the first transportation task.

[0113] After the second driver is determined, the matching degree between the second driver and the first transportation task is determined based on the driving information of the second driver and the task information of the first transportation task.

[0114] In an example, refer to Table-2, Table-2 is the task information of each transportation task, which is as follows:

[0115]

[0116] The driving skill of the second driver A is advanced, the driving skill of the second driver B is intermediate, and the driving skill of the second driver C is low, so the matching degree between the second driver A and the second transport task J1 is 100%, the driving skill of the second drivers B and C is not advanced, so the matching degree between the second drivers B and C and the second transport task J1 is 0; the driving skill of the second driver B is intermediate, and the required skill of the second transport task J2 is intermediate matching, so the matching degree between the second driver B and J2 is 100%, the driving skill of the second driver C is low, which does not meet the required intermediate skill of J2, so the matching degree between the second driver C and J2 is 0, and the driving skill of the second driver A is advanced, which meets the required intermediate skill of J2, but the driving skill of the second driver A is higher than the required intermediate skill of J2, so the matching degree between the second driver A and J2 is 75%; the driving skill of the second driver C is low, and the required skill of the second transport task J3 is low matching, so the matching degree between the second driver C and J3 is 100%, the driving skill of the second drivers A and B is higher than low, which meets the required low skill of J3, but the driving skill of the second drivers A and B is higher than the required low skill of J3, so the matching degree between the second driver A and J3 is 50%, and the matching degree between the second driver B and J3 is 75%. It can be understood that when the driving skill of the second driver is equal to the required skill of the transport task, the matching degree between the two is 100%; when the driving skill of the second driver is higher than the required skill of the transport task, the matching degree between the two is less than 100%, and the greater the difference between the driving skill of the second driver and the required skill of the transport task, the smaller the matching degree; when the driving skill of the second driver is lower than the required skill of the transport task, the matching degree between the two is 0. In this way, the driver with a high comprehensive score is avoided from being matched to a low requirement transport task, the transport task can be dispatched to a suitable driver, and resource waste is avoided.

[0117] In another example, the device determines a first transport route to which the second driver is adapted based on driving information of the second driver. For example, the driving information includes a transport route of a transport task that the second driver has historically performed, so that a familiar transport route of the second driver can be determined, for example, the number of times the second driver travels on the transport route exceeds a set number of times. The device determines a second transport route based on task information of the first transport task. The device determines an overlapping route between the first transport route and the second transport route, and determines a matching degree between the second driver and the first transport task based on a ratio between a route length of the overlapping route and a route length of the second transport route, and determines the matching degree based on the ratio. The greater the ratio, the greater the matching degree.

[0118] In step S403, the second driver is determined as the target driver when the matching degree is greater than or equal to a set threshold.

[0119] In an example, after determining the matching degree, it is judged whether the matching degree is greater than or equal to a set threshold, for example, 90%. When the matching degree of the second driver is greater than or equal to the set threshold, it can be determined that the second driver can be the target driver.

[0120] In another example, the device is further provided with a constraint condition, for example, the working strength of the driver in performing the transportation task needs to be greater than the working strength required by the transportation task. In this regard, the device determines a first working strength parameter required by the transportation task based on the task information of the first transportation task. The first working strength parameter is a numerical value, for example, the first working strength parameter is 80 minutes.

[0121] The device determines the execution completion time of the second driver in the last time of performing the transportation task and a second working strength parameter based on the driving information of the second driver, for example, the working strength score in Table-1.

[0122] The device predicts the target working strength of the second driver in performing the first transportation task by the execution completion time, the execution start time of the first transportation task and the first working strength parameter. For example, the device determines the interval time between the execution completion time and the execution start time as a target time, and the target time is the time length of the rest of the second driver. The working strength of the second driver is restored by a numerical value unit every time the second driver rests for a time length unit. The first number of the time length unit is determined based on the target time, and the product between the first number and the numerical value unit is determined. The product + the first working strength parameter is the target working strength parameter, and the target working strength cannot exceed the maximum value.

[0123] The device determines whether the target working strength parameter is greater than or equal to the working strength parameter after obtaining the target working strength parameter. If the target working strength parameter is greater than or equal to the first working strength parameter, the working strength of the second driver in performing the first transportation task meets the working strength required by the first transportation task, and thus the second driver can be determined as the target driver.

[0124] In this embodiment, the device first preliminarily determines the idle second driver in the first driver, and then determines the target driver suitable for the first transportation task from the first driver based on the matching degree between the second driver and the first transportation task.

[0125] Figures 2 to 4 A task scheduling method provided in the embodiment of the present application Exemplary apparatus Based on any one of the embodiments shown in Figure 6 Step S204 includes:

[0126] In step S501, a first execution efficiency parameter of the target driver when performing the transportation task is determined according to the driving information of the target driver.

[0127] In this embodiment, when performing the transportation task, the primary goal is to ensure the safety of performing the transportation task, and the secondary goal is to ensure the execution efficiency of the transportation task.

[0128] To this end, the device first determines the execution efficiency parameter of the target driver when performing the first transportation task based on the driving information of the target driver, and the execution efficiency parameter is defined as the first execution efficiency parameter.

[0129] For example, the driving information also includes the total duration of the target driver's historical execution of the transportation task, and the ratio between the total duration and the maximum duration required for the transportation task is the execution efficiency. The average of the execution efficiency of each historical execution of the transportation task can be used as the first execution efficiency parameter. Further, the device increases the average of the execution efficiency of the historical execution of the transportation task to obtain the first execution efficiency parameter if the familiarity of the target driver with the transportation route of the first transportation task is greater than a preset threshold, and decreases the average of the execution efficiency of the historical execution of the transportation task to obtain the first execution efficiency parameter if the familiarity is less than the preset threshold.

[0130] In step S502, if the first execution efficiency parameter is greater than or equal to a second execution efficiency parameter required for the first transportation task, a task order corresponding to the first transportation task is sent to a terminal device associated with the target driver.

[0131] The task information of the first transportation task includes an execution efficiency parameter, which is defined as the second execution efficiency parameter, and the second execution efficiency parameter is the execution efficiency parameter required for the execution of the first transportation task.

[0132] The device determines whether the first execution efficiency parameter is greater than or equal to the second execution efficiency parameter after obtaining the first execution efficiency parameter. If the first execution efficiency parameter is greater than or equal to the second execution efficiency parameter, it can be determined that the target driver has a high safety and high execution efficiency when performing the first transportation task.

[0133] In this embodiment, the device screens the drivers who can meet the safety and efficiency of the transportation task, so that the transportation task is adapted to the appropriate driver.

[0134] Figure 6

[0135] Corresponding to the above-mentioned task scheduling method, the present embodiment also provides a task scheduling device. Exemplary electronic device is a module schematic diagram of a task scheduling device provided by the present embodiment. As shown in Figure 7As shown, the task scheduling device 600 provided by the embodiments of the present application includes:

[0136] The acquisition module 610 is configured to acquire a first transportation task to be executed, a transportation time period of the first transportation task, and a risk level, and acquire driving information of each first driver to be matched;

[0137] The determination module 620 is configured to determine, according to the driving information, a target driver who is idle in the transportation time period from among the first drivers.

[0138] The prediction module 630 is configured to, in a case where a driving score contained in the driving information of the target driver is greater than or equal to a score corresponding to the risk level, predict a target mental state score of the target driver in the transportation time period according to a current mental state score contained in the driving information of the target driver.

[0139] The sending module 640 is configured to, in a case where the target mental state score is greater than or equal to a preset threshold, send a task order corresponding to the first transportation task to a terminal device associated with the target driver.

[0140] In some implementations, the task scheduling device 600 is configured to:

[0141] acquire historical driving behavior of the first driver in driving a vehicle, physiological information of the first driver when performing a second transportation task, completion information of the second transportation task, device information, and basic information of the first driver;

[0142] determine, according to the historical driving behavior, the physiological information, the completion information, the device information, and the basic information, a score of the first driver on a plurality of scoring factors, the scores of the plurality of scoring factors including at least two of a mental state score, a driving behavior compliance score, a concentration score, a device health score, a driving stability score, and a work intensity score;

[0143] determine, according to the scores corresponding to the respective scoring factors and weights, a driving score of the first driver;

[0144] construct, according to the scores of the respective scoring factors and the driving score, the driving information of the first driver.

[0145] In some implementations, the task scheduling device 600 is configured to:

[0146] determine, based on the driving information, a first driver corresponding to an idle time period of the transportation time period as a second driver;

[0147] determine, according to the driving information of the second driver and task information of the first transportation task, a matching degree between the second driver and the first transportation task;

[0148] In a case where the matching degree is greater than or equal to a set threshold, the second driver is determined as the target driver.

[0149] In some implementations, the task scheduling apparatus 600 is configured to:

[0150] According to the task information of the first transportation task, a first work intensity parameter required for performing the first transportation task is determined;

[0151] According to the driving information of the second driver, an execution completion time corresponding to a last time of performing a transportation task by the second driver and a second work intensity parameter are determined;

[0152] According to the execution completion time, an execution start time of the first transportation task, and the first work intensity parameter, a target work intensity parameter of the second driver performing the first transportation task is predicted;

[0153] In a case where the target work intensity parameter is greater than or equal to the first work intensity parameter, the second driver is determined as the target driver.

[0154] In some implementations, the task scheduling apparatus 600 is configured to:

[0155] According to the driving information of the second driver, a first transportation route to which the second driver is adapted is determined;

[0156] According to the task information of the first transportation task, a second transportation route is determined;

[0157] An overlapping route between the first transportation route and the second transportation route is determined, and according to a ratio between a route length of the overlapping route and a route length of the second transportation route, a matching degree between the second driver and the first transportation task is determined.

[0158] In some implementations, the task scheduling apparatus 600 is configured to:

[0159] According to the driving information of the target driver, a first execution efficiency parameter of the target driver performing a transportation task is determined;

[0160] In a case where the first execution efficiency parameter is greater than or equal to a second execution efficiency parameter required for the first transportation task, a task order corresponding to the first transportation task is sent to a terminal device associated with the target driver.

[0161] In some implementations, the task scheduling apparatus 600 is configured to:

[0162] A plurality of unexecuted third transportation tasks are obtained, and a priority of each third transportation task is determined;

[0163] A third transportation task corresponding to the highest priority is determined as a first transportation task to be executed.

[0164] The task scheduling device provided by the embodiment belongs to the same application concept as the task scheduling method provided by the embodiments of the present application, can execute the task scheduling method provided by any of the embodiments of the present application, and has the corresponding function modules and beneficial effects of executing the task scheduling method. Technical details not described in detail in the embodiment can be seen from the specific processing content of the task scheduling method provided by the embodiments of the present application, which will not be described here.

[0165] The functions implemented by each module in the task scheduling device can be implemented by the same or different processors, which is not limited in the embodiments of the present application.

[0166] It should be understood that the modules in the above system can be implemented in the form of processor calling software. For example, the system includes a processor connected with a memory, the memory stores instructions, and the processor calls the instructions stored in the memory to implement any of the above methods or the functions of the modules of the device, wherein the processor can be a general processor such as CPU or microprocessor, and the memory can be a memory in the device or a memory outside the system. Alternatively, the modules in the system can be implemented in the form of hardware circuit, and the functions of part or all of the modules can be implemented by designing the hardware circuit, which can be understood as one or more processors; for example, in one implementation, the hardware circuit is ASIC, and the functions of part or all of the modules are implemented by designing the logical relationship of elements in the circuit; for example, in another implementation, the hardware circuit can be implemented by PLD, and taking FPGA as an example, it can include a large number of logic gate circuits, and the connection relationship between the logic gate circuits is configured by a configuration file, so as to implement the functions of part or all of the modules. All modules of the above system can be implemented in the form of processor calling software, or implemented in the form of hardware circuit, or partially implemented in the form of processor calling software and the remaining part implemented in the form of hardware circuit.

[0167] In the embodiments of the present application, the processor is a circuit with signal processing capability, which can be a circuit with instruction reading and running capability in one implementation, such as CPU, microprocessor, GPU, or DSP, etc.; in another implementation, the processor can implement certain functions through the logical relationship of hardware circuit, which is fixed or can be reconfigured, such as ASIC or PLD implemented hardware circuit, such as FPGA, etc. In the reconfigurable hardware circuit, the process of the processor loading the configuration document to implement the hardware circuit configuration can be understood as the process of the processor loading the instructions to implement the functions of part or all of the modules. In addition, it can also be a hardware circuit designed for artificial intelligence, which can be understood as a kind of ASIC, such as NPU, TPU, DPU, etc.

[0168] It can be seen that each module in the above system can be one or more processors (or processing circuits) configured to implement the above method, for example: CPU, GPU, NPU, TPU, DPU, microprocessor, DSP, ASIC, FPGA, or a combination of at least two of these processor forms.

[0169] In addition, each module in the above system can be integrated together or can be implemented independently. In one implementation, the modules are integrated together to implement a SOC. The SOC can include at least one processor for implementing any of the above methods or functions of the modules of the device, and the at least one processor can be different, for example, including CPU and FPGA, CPU and artificial intelligence processor, CPU and GPU, etc.

[0170] Exemplary computer program product and storage medium

[0171] The embodiment of the present application further provides another structural diagram of an electronic device, as shown in ​ The electronic device includes a memory 700 and a processor 710; wherein the memory 700 is connected with the processor 710, and is used for storing programs; the processor 710 is used for realizing the task scheduling method disclosed in any of the above embodiments by running the programs stored in the memory 700.

[0172] Specifically, the above electronic device can further include a bus, a communication interface 720, an input device 730, and an output device 740. The electronic device can further include a data transceiving module, an image monitoring module, and a signal monitoring module.

[0173] The processor 710, the memory 700, the communication interface 720, the input device 730, the output device 740, the switch component 750, and the power supply module 760 are connected with each other through the bus. Wherein:

[0174] The bus can include a channel for transmitting information between various components in the electronic device.

[0175] The processor 710 can be a general-purpose processor, such as a general-purpose central processing unit (CPU), a microprocessor, etc., or can be an application-specific integrated circuit (ASIC), or one or more integrated circuits for controlling the execution of programs of the present application. It can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a ready-to-use programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component.

[0176] The processor 710 can include a main processor, and can further include a baseband chip, a modem, etc.

[0177] The memory 700 stores programs for implementing the technical solutions of the present application, and can also store operating systems and other key services. Specifically, the programs can include program codes, and the program codes include computer operation instructions. More specifically, the memory 700 can include a read-only memory (ROM), other types of static storage devices that can store static information and instructions, a random access memory (RAM), other types of dynamic storage devices that can store information and instructions, a disk memory, a flash memory, and the like.

[0178] The input device 730 can include devices that receive data and information input by a user, such as a keyboard, a mouse, a camera, a scanner, a light pen, a voice input device, a touch screen, a pedometer, a gravity sensor, and the like.

[0179] The output device 740 can include devices that allow information to be output to a user, such as a display screen, a printer, a speaker, and the like.

[0180] The communication interface 720 can include devices of the transceiver type or the like for communicating with other devices or communication networks, such as an Ethernet, a radio access network (RAN), a wireless local area network (WLAN), and the like.

[0181] The processor 710 executes the programs stored in the memory 700 and invokes other devices, which can be used to implement each step of any of the task scheduling methods provided by the above-described embodiments of the present application.

[0182] The embodiments of the present application also propose a chip including a processor and a data interface, the processor reading and running programs stored on a memory through the data interface to execute the task scheduling methods described in any of the above-described embodiments. The specific processing process and benefits thereof can be referred to the above-described embodiments of the task scheduling methods.

[0183] ​

[0184] In addition to the above methods and devices, the embodiments of the present application can also be computer program products that include computer program instructions, which, when executed by a processor, cause the processor to perform the steps of the task scheduling methods according to various embodiments of the present application described in any of the above-described embodiments.

[0185] The computer program product can be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C++ or the like, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code can execute entirely on the user's computing device, partly on the user's computing device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device or entirely on the remote computing device or server.

[0186] In addition, an embodiment of the present application can also be a storage medium, which stores the computer program, and the computer program is executed by the processor to perform the steps of the task scheduling method according to various embodiments of the present application described in any embodiment of the present specification. Specifically, the steps of the task scheduling method can be implemented as described above.

[0187] For each method embodiment described above, in order to simply describe, it is expressed as a series of action combinations, but those skilled in the art should know that the present application is not limited by the order of the described actions, because according to the present application, some steps can be performed in other order or simultaneously. Secondly, those skilled in the art should know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present application.

[0188] It should be noted that each embodiment in the specification is described in a progressive manner, and each embodiment focuses on the difference from other embodiments. The same and similar parts between each embodiment can be referred to each other. For device embodiments, since they are basically similar to method embodiments, they are described more simply, and the relevant parts can be referred to the part of the description of the method embodiment.

[0189] The steps in the method of each embodiment of the present application can be adjusted, combined and reduced in sequence according to actual needs, and the technical features recorded in each embodiment can be replaced or combined.

[0190] The units of the device in each embodiment of the present application can be combined, divided and reduced according to actual needs.

[0191] It should be understood that the disclosed terminal, device and method can be implemented in other ways. For example, the terminal embodiments described above are merely illustrative. For example, the division of modules or sub-modules is merely a logical function division. In actual implementation, another division manner can be used. For example, a plurality of sub-modules or modules can be combined or integrated into another module, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the displayed or discussed modules can be indirect coupling or communication connection through some interfaces, devices or modules, and can be electrical, mechanical or other forms.

[0192] The modules or sub-modules described as separate components can or can not be physically separate, and the components of the modules or sub-modules can or can not be physical modules or sub-modules, i.e., can be located in one place or distributed on a plurality of network modules or sub-modules. Some or all of the modules or sub-modules can be selected according to actual needs to achieve the purpose of the embodiment.

[0193] In addition, the functional modules or sub-modules in each embodiment of the present application can be integrated into a processing module, or each module or sub-module can exist physically, or two or more modules or sub-modules can be integrated into one module. The integrated module or sub-module can be realized in the form of hardware or software functional module or sub-module.

[0194] The skilled person can further realize that the units and algorithm steps of the examples described in conjunction with the embodiments disclosed herein can be realized in electronic hardware, computer software or a combination of both. In order to clearly illustrate the interchangeability of hardware and software, the components and steps of the examples have been described in general terms in the above description. Whether the functions are realized in hardware or software depends on the specific application and design constraints of the technical solution. The skilled person can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0195] The steps of the method or algorithm described in conjunction with the embodiments disclosed herein can be directly implemented by hardware, software units executed by a processor, or a combination of both. The software units can be placed in a random access memory (RAM), a memory, a read-only memory (ROM), an electrically programmable ROM, an electrically erasable programmable ROM, a register, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

[0196] Finally, it should be noted that, in this document, the term "only" is used simply to set off from one element to another, not to necessarily require or imply any such actual relationship or order between the elements. Also, the terms "comprises", "comprising", or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can also include other elements not expressly listed or inherent to such process, method, article, or apparatus. An element proceeded by "comprises... a" does not, without more constraints, exclude the existence of additional identical elements in the process, method, article, or apparatus that comprises the element.

[0197] The above description of disclosed embodiments provides enabling teaching for making or using the application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein can be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A task scheduling method, characterized in that: include: Obtaining a first transport task to be executed, a transport time period and a risk level of the first transport task, and obtaining driving information of each first driver to be matched; determining, based on the driving information, a target driver among the first drivers who is available during the transport time period; If the driving score included in the driving information of the target driver is greater than or equal to the score corresponding to the risk level, predicting a target mental state score of the target driver during the transportation time period based on the current mental state score included in the driving information of the target driver; When the target mental state score is greater than or equal to a preset threshold, the task work order corresponding to the first transport task is sent to the terminal device associated with the target driver.

2. The task scheduling method according to claim 1, characterized in that: The obtaining of driving information of each first driver to be matched includes: Acquiring the first driver's historical driving behavior, physiological information when performing the second transport task, completion information of the second transport task, equipment information, and basic information of the first driver; Determining scores of the first driver on a plurality of scoring factors based on the historical driving behavior, the physiological information, the completion information, the device information, and the basic information, where the scores of the plurality of scoring factors include scores of at least two of a mental state score, a driving behavior compliance score, a concentration score, a device health score, a driving smoothness score, and a work intensity score; Determining a driving score of the first driver according to the scores and weights of the respective scoring factors; Driving information of the first driver is constructed according to the scores of the respective scoring factors and the driving score.

3. The task scheduling method according to claim 1, characterized in that: Determining, based on the driving information, a target driver who is idle during the transportation time period among the first drivers includes: Based on the driving information, determining the first driver corresponding to the idle time period including the transport time period as the second driver; determining a matching degree between the second driver and the first transport task based on the driving information of the second driver and the task information of the first transport task; When the matching degree is greater than or equal to a set threshold, the second driver is determined as a target driver.

4. The task scheduling method according to claim 3, characterized in that: Determining the second driver as a target driver includes: determining, based on the task information of the first transport task, a first work intensity parameter required to perform the first transport task; determining, based on the driving information of the second driver, a completion time and a second work intensity parameter corresponding to the second driver's last transport task; predicting a target work intensity parameter for the second driver to perform the first transport task based on the execution completion time, the execution start time of the first transport task, and the first work intensity parameter; When the target work intensity parameter is greater than or equal to the first work intensity parameter, the second driver is determined as the target driver.

5. The task scheduling method according to claim 3, characterized in that: The determining, based on the driving information of the second driver and the task information of the first transport task, a matching degree between the second driver and the first transport task includes: determining a first transport route adapted for the second driver based on the driving information of the second driver; determining a second transport route according to the task information of the first transport task; An overlapping route between the first transport route and the second transport route is determined, and a matching degree between the second driver and the first transport task is determined based on a ratio of a route length of the overlapping route to a route length of the second transport route.

6. The task scheduling method according to claim 1, characterized in that: The step of sending the task work order corresponding to the first transport task to the terminal device associated with the target driver includes: determining a first execution efficiency parameter of the target driver when performing the transport task according to the driving information of the target driver; When the first execution efficiency parameter is greater than or equal to the second execution efficiency parameter required by the first transport task, the task work order corresponding to the first transport task is sent to the terminal device associated with the target driver.

7. The task scheduling method according to any one of claims 1 to 6, characterized in that: The obtaining of the first transport task to be executed includes: Acquire a plurality of unexecuted third transport tasks, and determine a priority of each of the third transport tasks; The third transport task corresponding to the highest priority is determined as the first transport task to be executed.

8. A task scheduling device, characterized in that: include: an acquisition module, configured to acquire a first transport task to be executed, a transport time period and a risk level of the first transport task, and to acquire driving information of each first driver to be matched; a determination module, configured to determine, from among the first drivers, a target driver who is available during the transportation time period based on the driving information; a prediction module configured to predict a target mental state score of the target driver during the transportation time period based on a current mental state score included in the driving information of the target driver, if the driving score included in the driving information of the target driver is greater than or equal to the score corresponding to the risk level; A sending module is used to send the task work order corresponding to the first transport task to the terminal device associated with the target driver when the target mental state score is greater than or equal to a preset threshold.

9. An electronic device, characterized in that: comprising a memory and a processor, wherein, The memory is connected to the processor and is used to store programs; The processor is configured to implement the task scheduling method according to any one of claims 1 to 7 by running the program in the memory.

10. A computer program product, characterized in that The method comprises a computer program, which, when executed by a processor, implements the task scheduling method according to any one of claims 1 to 7.

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