CN110414756B - Vehicle driving system evaluation method, device and computer equipment - Google Patents
Vehicle driving system evaluation method, device and computer equipment Download PDFInfo
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Abstract
The application relates to a vehicle driving system evaluation method, a device, a computer device and a storage medium, wherein a plurality of driving tasks of a vehicle are evaluated according to preset rules to obtain a plurality of driving task evaluation values; obtaining road scene evaluation values of all the road scenes according to the driving task evaluation values of the driving tasks contained in each road scene; then, according to the road scene evaluation value of the road scene contained in each driving scene, obtaining the driving scene evaluation value of each driving scene; and finally, summarizing the driving scene evaluation values, and determining the evaluation value of the vehicle driving system according to the summarizing result. The evaluation method is not limited to basic performance evaluation of the vehicle or single auxiliary performance evaluation, but is used for comprehensively evaluating the driving system by combining the driving environment of the vehicle in a layering way, providing visual evaluation results for users, and facilitating the users to know the applicable environment of the vehicle.
Description
Technical Field
The present application relates to the field of vehicle engineering technologies, and in particular, to a vehicle driving system evaluation method, a device, a computer device, and a storage medium.
Background
With the development of the automobile industry, automobiles become a main transportation means for people to travel. In the daily driving process, a driver mainly controls a driving system to achieve the purpose that the automobile runs according to own will. The driving system includes not only: the steering device also includes other auxiliary devices, such as positioning devices, etc. In the running process of the vehicle, not only basic performances such as braking, acceleration and the like are considered, but also factors such as the running environment of the vehicle are considered to realize that the vehicle can reach the destination quickly and smoothly.
The current evaluation of the driving system of the vehicle is still only at the basic performance level, and a method for comprehensively evaluating the driving system of the vehicle in the driving environment is lacked, so that a user is difficult to judge the applicable environment of the vehicle.
Disclosure of Invention
In view of the foregoing, it is desirable to provide a method, apparatus, computer device, and storage medium that can comprehensively evaluate the driving system of a vehicle such as a vehicle.
A vehicle driving system assessment method comprising the steps of:
evaluating a plurality of driving tasks of the vehicle according to a preset rule to obtain a plurality of driving task evaluation values;
Obtaining road scene evaluation values of all road scenes according to driving task evaluation values of driving tasks contained in each road scene;
obtaining driving scene evaluation values of all driving scenes according to the road scene evaluation values of the road scenes contained in each driving scene;
and summarizing the driving scene evaluation values, and determining the evaluation value of the vehicle driving system according to the summarizing result.
In one embodiment, the step of evaluating a plurality of driving tasks of the vehicle according to a preset rule to obtain the plurality of driving task evaluation values includes:
acquiring evaluation items contained in each driving task, and evaluating each evaluation item by using an evaluation standard of each evaluation item to obtain an evaluation value of each evaluation item;
and calculating the driving task evaluation value of each driving task by using the evaluation value of the evaluation item corresponding to each driving task.
In one embodiment, the step of obtaining the evaluation items included in each driving task and evaluating each evaluation item by using the evaluation criteria of each evaluation item to obtain the evaluation value of each evaluation item includes:
and if the driving task comprises a detection item, acquiring detection data corresponding to the detection item, and comparing the detection data with standard data to obtain an evaluation value of the detection item.
In one embodiment, the step of obtaining the evaluation items included in each driving task and evaluating each evaluation item by using the evaluation criteria of each evaluation item to obtain the evaluation value of each evaluation item includes:
and if the driving task comprises a performance evaluation item, acquiring performance related data of the performance evaluation item, and evaluating the performance related data according to an evaluation standard of the performance evaluation item to obtain an evaluation value of the performance evaluation item.
In one embodiment, the performance evaluation item comprises:
safety performance evaluation, efficiency performance evaluation, comfort performance evaluation, completion performance evaluation and illegal driving evaluation.
In one embodiment, the step of obtaining the road scene evaluation value of each road scene according to the driving task evaluation value of the driving task included in each road scene includes:
acquiring task weight of each driving task contained in a certain road scene;
and carrying out weighted calculation on the driving task evaluation values of all driving tasks contained in the certain road scene by using the task weight of each driving task to obtain the road scene evaluation value of the certain road scene.
In one embodiment, the step of obtaining the driving scene evaluation value of each driving scene according to the road scene evaluation value of the road scene included in each driving scene includes:
acquiring the road scene weight of each road scene contained in a certain driving scene;
and carrying out weighted calculation on the road scene evaluation values of all the road scenes contained in the certain driving scene by using the road scene weight of each road scene to obtain the driving scene evaluation value of the certain driving scene.
In one embodiment, the step of summarizing the driving scenario evaluation values and determining the evaluation value of the vehicle driving system according to the summarized result includes:
acquiring driving scene weight of each driving scene in the summarized driving scenes;
and carrying out weighted calculation on all the summarized driving scene evaluation values by using the driving scene weight of each driving scene to obtain an evaluation value of a vehicle driving system.
A vehicle driving system assessment device, the device comprising:
the driving task evaluation module is used for evaluating a plurality of driving tasks of the vehicle according to a preset rule to obtain a plurality of driving task evaluation values;
The road scene evaluation module is used for obtaining road scene evaluation values of all the road scenes according to the driving task evaluation values of the driving tasks contained in each road scene;
the driving scene evaluation module is used for obtaining driving scene evaluation values of all driving scenes according to the road scene evaluation values of the road scenes contained in each driving scene;
and the evaluation result generation module is used for summarizing the driving scene evaluation values and determining the evaluation value of the vehicle driving system according to the summarizing result.
A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of:
evaluating a plurality of driving tasks of the vehicle according to a preset rule to obtain a plurality of driving task evaluation values;
obtaining road scene evaluation values of all road scenes according to driving task evaluation values of driving tasks contained in each road scene;
obtaining driving scene evaluation values of all driving scenes according to the road scene evaluation values of the road scenes contained in each driving scene;
and summarizing the driving scene evaluation values, and determining the evaluation value of the vehicle driving system according to the summarizing result.
A computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:
evaluating a plurality of driving tasks of the vehicle according to a preset rule to obtain a plurality of driving task evaluation values;
obtaining road scene evaluation values of all road scenes according to driving task evaluation values of driving tasks contained in each road scene;
obtaining driving scene evaluation values of all driving scenes according to the road scene evaluation values of the road scenes contained in each driving scene;
and summarizing the driving scene evaluation values, and determining the evaluation value of the vehicle driving system according to the summarizing result.
According to the vehicle driving system evaluation method, the vehicle driving system evaluation device, the computer equipment and the storage medium, firstly, a plurality of driving tasks of a vehicle are evaluated according to preset rules, and a plurality of driving task evaluation values are obtained; obtaining road scene evaluation values of all the road scenes according to the driving task evaluation values of the driving tasks contained in each road scene; then, according to the road scene evaluation value of the road scene contained in each driving scene, obtaining the driving scene evaluation value of each driving scene; and finally, summarizing the driving scene evaluation values, and determining the evaluation value of the vehicle driving system according to the summarizing result. The evaluation method is not limited to basic performance evaluation of the vehicle or single auxiliary performance evaluation, but is used for comprehensively evaluating the driving system by combining the driving environment of the vehicle in a layering way, providing visual evaluation results for users, and facilitating the users to know the applicable environment of the vehicle.
Drawings
FIG. 1 is a diagram of an application environment for a vehicle driving system assessment method in one embodiment;
FIG. 2 is a block diagram of an evaluation algorithm in one embodiment;
FIG. 3 is a flow chart illustrating steps of a vehicle driving system assessment method in one embodiment;
FIG. 4 is a flowchart showing steps for obtaining a driving task evaluation value in one embodiment;
FIG. 5 is a flowchart illustrating steps for obtaining a road scene assessment value for a road scene in one embodiment;
FIG. 6 is a flowchart illustrating steps for obtaining a driving scenario evaluation value for a driving scenario in one embodiment;
FIG. 7 is a flowchart illustrating steps for determining an evaluation value of a vehicle driving system based on a summary result in one embodiment;
FIG. 8 is a block diagram of a vehicle driving system evaluation device in one embodiment;
fig. 9 is an internal structural diagram of a computer device in one embodiment.
Detailed Description
The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
The vehicle driving system evaluation method provided by the application can be applied to an application scene shown in fig. 1. The vehicle in the application scenario is a vehicle 130. Alternatively, the driving system of the vehicle 130 may be a semi-automatic driving system of the vehicle or a full-automatic driving system of the vehicle. The information acquisition device 120 acquires the relevant evaluation information of the vehicle 130 in the application scene, and then transmits the acquired information to the processor 110. Optionally, a memory is provided on the processor 110. Optionally, the processor 110 further includes: an acquisition module, an evaluation module, an operation module, a control module and the like. The acquiring module may be a hardware module such as an I/O (Input/Output) interface, and the operation module and the control module are both hardware modules. Alternatively, the information collecting device 120 and the processor 110 may be provided independently of the vehicle 130, or may be an in-vehicle information collecting device, and/or an in-vehicle processor.
Optionally, the relevant evaluation information includes: information such as the position, speed, acceleration, wheel angle, lamp status, etc. of the vehicle, and information obtained by detecting the surrounding environment by the sensors of the vehicle. Alternatively, the information acquisition device may include a camera, a laser radar, a radar, an ultrasonic wave, or the like, and the sensor may detect the surrounding environment to obtain detection data.
Optionally, the memory has stored thereon an evaluation algorithm for performing an evaluation of the driving system of the vehicle. The evaluation algorithm is arranged according to an algorithm framework as shown in fig. 2. Namely: the method comprises the steps of obtaining an evaluation result of a driving system of an evaluation vehicle, determining a driving scene suitable for the vehicle, evaluating the driving system of the vehicle under each suitable driving scene, and obtaining the driving scene evaluation result according to the evaluation result of a road scene in the driving scene, wherein the road scene evaluation result is obtained according to the driving task evaluation result of the vehicle, and the driving task evaluation result is obtained according to the evaluation result of a basic evaluation item. Alternatively, the evaluation items corresponding to each driving task may be plural. Alternatively, the driving tasks corresponding to each road scene may be multiple. Alternatively, the road scene corresponding to each driving scene may be plural. Alternatively, the obtaining of the evaluation result of each driving system may require integrating the driving scenario evaluation results of a plurality of driving scenarios.
When the processor 110 evaluates the vehicle driving system, the processor 110 firstly obtains the evaluation algorithm from the memory, and then runs the evaluation algorithm to process corresponding data, so as to obtain an evaluation result of the vehicle driving system. Optionally, the memory may also cache other data information acquired by the acquisition module of the processor 110, such as related information when evaluating the evaluation item, or an evaluation result of the vehicle driving system, and so on.
In one embodiment, as shown in fig. 3, a vehicle driving system evaluation method is provided, and the method is applied to the application scenario in fig. 1 for illustration, and the method includes the following steps:
step 310: and evaluating a plurality of driving tasks of the vehicle according to a preset rule to obtain a plurality of driving task evaluation values.
Specifically, the evaluation module of the processor 110 evaluates the driving task of the vehicle according to a preset rule to obtain a driving task evaluation value. Optionally, the processor 110 obtains, through the obtaining module thereof, related information of a driving task executed by the driving system, and an evaluation algorithm designed according to a preset rule and stored in the memory, and then the evaluation module of the processor 110 operates the evaluation algorithm to process the obtained related information of the driving task, so as to obtain a driving task evaluation value of the driving task executed by the driving system. Alternatively, the driving task described above may be generated by the navigation system according to the journey of the vehicle. Alternatively, the vehicle may be a vehicle. Alternatively, the driving task may be generated according to the current journey of the vehicle, and may be a driving task contained in the journey in the navigation system history. The driving tasks described above include various types of driving tasks, such as: straight, cornering, parking, etc.
Alternatively, the driving system may be a semi-automatic driving system of the vehicle or a full-automatic driving system of the vehicle. Alternatively, the semiautomatic driving system of the vehicle may acquire the above-described driving task and control the operation of the driving system of the vehicle according to the acquired driving task, or assist the driver in controlling the driving system of the vehicle. Alternatively, the automatic driving system of the vehicle may acquire the above-described driving task, and control the operation of the driving system of the vehicle according to the acquired driving task.
Alternatively, different rules are used when evaluating different types of driving tasks. For example: the driving task "park", the corresponding evaluation rule may include: evaluation of location, time, etc. parameters; whereas the evaluation rules corresponding to the driving task "straight" may include: evaluation of speed change, time, etc. Optionally, when evaluating the driving task of the vehicle, the processor 110 first determines the type of the driving task currently evaluated, then determines the applicable preset rule according to the type of the driving task, and finally evaluates the driving task currently evaluated by using the corresponding preset rule. Alternatively, the driving task evaluation value may be a specific score, for example: 50, etc.
Step 320: and obtaining the road scene evaluation value of each road scene according to the driving task evaluation value of the driving task contained in each road scene.
Specifically, the evaluation module of the processor 110 obtains the road scene evaluation value of each road scene according to the driving task evaluation value of the driving task included in each road scene. Optionally, the obtaining module of the processor 110 first determines which driving tasks are included in the currently estimated road scene, then the estimating module obtains the corresponding driving task estimated value according to the driving tasks included in the current driving task, and finally calculates the road scene estimated value of the currently estimated road scene according to the obtained driving task estimated value. Optionally, the evaluation module processes the obtained driving task evaluation value by using a weighted average algorithm to obtain a road scene evaluation value.
For example: the road scene "intersection scene" evaluated for the current driving system (e.g., fully automatic driving system) includes driving tasks including: stopping the line to stop, and reacting to the traffic light. When the processor 110 evaluates the road scene, it may first acquire, through the acquisition module, a driving task evaluation value a for stopping the stop-line parking and a driving task evaluation value B for reacting to the traffic light, and then the evaluation module calculates a road scene evaluation value for the intersection scene according to the evaluation value a and the evaluation value B.
Step 330: and obtaining driving scene evaluation values of all driving scenes according to the road scene evaluation values of the road scenes contained in each driving scene.
Specifically, the evaluation module of the processor 110 obtains driving scene evaluation values of the driving scenes according to the road scene evaluation values of the road scenes included in each driving scene. Optionally, the obtaining module of the processor 110 first determines which road scenes are included in the currently estimated driving scene, then the estimating module obtains the corresponding road scene estimated value according to the determined road scenes, and finally calculates the driving scene estimated value of the currently estimated driving scene according to the obtained road scene estimated value. Optionally, the evaluation module processes the obtained road scene evaluation value by using a weighted average algorithm to obtain a driving scene evaluation value.
For example: the driving scenario "city scenario" assessed for the current driving system (e.g., fully automatic driving system), includes: intersection scene, roundabout scene. When the processor 110 evaluates the driving scenario, the acquiring module may first acquire the road scenario evaluation value C of the intersection scenario and the road scenario evaluation value D of the roundabout scenario, and then the evaluating module calculates the driving scenario evaluation value of the urban scenario according to the evaluation value C and the evaluation value D.
Step 340: and summarizing the driving scene evaluation values, and determining the evaluation value of the vehicle driving system according to the summarizing result.
Specifically, the evaluation module of the processor 110 sums up the driving scenario evaluation values, and determines an evaluation value of the vehicle driving system according to the result of the summation. Optionally, the processor 110 first determines, through its acquisition module, which driving scenarios the evaluation module evaluates, then the evaluation module acquires corresponding driving scenario evaluation values according to the determined driving scenarios, and finally calculates the evaluation value of the vehicle driving system according to the acquired driving scenario evaluation values. Optionally, the evaluation module processes the obtained driving scene evaluation value by using a weighted average algorithm to obtain a vehicle driving system evaluation value.
For example: driving scenarios evaluated for current driving systems (e.g., fully automated driving systems) include city scenarios, highway scenarios. When the processor 110 obtains the evaluation value of the vehicle driving system according to the driving scene evaluation value, the obtaining module may first obtain the driving scene evaluation value E of the urban scene and the driving scene evaluation value F of the highway scene, and then the evaluating module calculates the evaluation value of the vehicle driving system according to the evaluation value E and the evaluation value F.
According to the vehicle driving system evaluation method provided by the embodiment, firstly, a plurality of driving tasks of a vehicle are evaluated according to a preset rule, and a plurality of driving task evaluation values are obtained; obtaining road scene evaluation values of all the road scenes according to the driving task evaluation values of the driving tasks contained in each road scene; then, according to the road scene evaluation value of the road scene contained in each driving scene, obtaining the driving scene evaluation value of each driving scene; and finally, summarizing the driving scene evaluation values, and determining the evaluation value of the vehicle driving system according to the summarizing result. The evaluation method is not limited to basic performance evaluation of the vehicle or single auxiliary performance evaluation, but is used for comprehensively evaluating the driving system by combining the driving environment of the vehicle in a layering way, providing visual evaluation results for users, and facilitating the users to know the applicable environment of the vehicle.
As an alternative embodiment, the step of evaluating a plurality of driving tasks of the vehicle according to a preset rule, and obtaining the plurality of driving task evaluation values includes the steps as shown in fig. 4:
step 311: and acquiring evaluation items contained in each driving task, and evaluating the evaluation items by using evaluation standards of the evaluation items to obtain evaluation values of the evaluation items.
Specifically, the processor 110 first determines the evaluation items included in each driving task and the evaluation criteria of each evaluation item, and then evaluates each evaluation item according to the evaluation criteria of each evaluation item to obtain the evaluation value of each evaluation item. Alternatively, the evaluation criteria of each evaluation item are set in advance. Alternatively, the evaluation item included in the driving task may be a performance evaluation item, for example: one or more of safety performance, efficiency performance, comfort performance, finish performance and driving frequency of violation. Alternatively, the evaluation item included in the driving task may be a detection item, such as a position of a vehicle, obstacle detection, or the like. Alternatively, the detection item may be an item related to the sensor detecting the surrounding environment, such as: information acquired by a camera, lidar, radar, ultrasound, positioning means, etc.
Step 312: and calculating the driving task evaluation value of each driving task by using the evaluation value of the evaluation item corresponding to each driving task.
Specifically, the evaluation module of the processor 110 calculates the driving task evaluation value for each driving task using the evaluation value of the evaluation item corresponding to each driving task. Alternatively, if a certain driving task involves using multiple evaluation items, each evaluation item may be evaluated according to the evaluation criterion of each evaluation item to obtain an evaluation value of each evaluation item, and finally the evaluation values of each evaluation item are integrated (for example, in a weighted average manner) to obtain a driving task evaluation value of the driving task.
For example, a driving task "park" performed by a full-automatic driving system of a vehicle includes an evaluation item: two evaluation items of parking position and parking time. And respectively evaluating the two evaluation items according to the evaluation standards of the two evaluation items to obtain an evaluation value A1 of the evaluation item of the parking position and an evaluation value A2 of the evaluation item of the parking time. And then calculating according to A1 and A2 to obtain a driving task evaluation value of the driving task parking.
As an alternative embodiment, the step of obtaining the evaluation items included in each driving task, and evaluating each evaluation item by using the evaluation criteria of each evaluation item, to obtain the evaluation value of each evaluation item includes: and if the driving task comprises a detection item, acquiring detection data corresponding to the detection item, and comparing the detection data with standard data to obtain an evaluation value of the detection item.
Specifically, the processor 110 firstly obtains the detection data corresponding to the detection item through the obtaining module thereof, then compares the detection data with the standard data through the evaluation module thereof, and obtains the evaluation value of the detection item according to the comparison result. Optionally, when evaluating the driving task, the processor 110 first determines the type of the currently evaluated evaluation item, and then evaluates the currently evaluated evaluation item. Optionally, when the probe data is compared with the standard data, the higher the matching degree of the probe data and the standard data is, the larger the evaluation value of the probe term is. Alternatively, the standard data may be acquired through a network.
For example: when the probe item "road surface information" is to be evaluated, information in a High-Definition Map (High-Definition Map) or a highly automated driving Map (Highly Automated Driving Map) may be used as standard data. When the processor evaluates the probe, the processor may first acquire the road surface information acquired by the vehicle through the information acquisition device 110 (for example, a camera, etc.), and then compare the acquired road surface information with the corresponding information in the High-Definition Map or the High-automatic driving Map (Highly Automated Driving Map), to obtain the evaluation value of the probe.
As an alternative embodiment, the step of obtaining the evaluation items included in each driving task, and evaluating each evaluation item by using the evaluation criteria of each evaluation item, to obtain the evaluation value of each evaluation item includes:
and if the driving task comprises a performance evaluation item, acquiring performance related data of the performance evaluation item, and evaluating the performance related data according to an evaluation standard of the performance evaluation item to obtain an evaluation value of the performance evaluation item.
Specifically, the processor 110 first determines, through the acquisition module thereof, a performance evaluation item included in the driving task, then acquires relevant data of the performance evaluation item according to the determined performance evaluation item, and finally, the evaluation module of the processor evaluates the acquired relevant data according to the evaluation standard of the performance evaluation item to obtain an evaluation value of the performance evaluation item.
As an alternative embodiment, the performance evaluation item may be a security performance.
Specifically, the processor firstly acquires related data of the safety performance, and then processes the related data of the safety performance according to a preset safety standard to obtain an evaluation value of the safety performance. Alternatively, the safety criteria may be set according to relevant vehicle safety criteria, such as vehicle braking distance, etc.
Optionally, the safety standard may also contain other relevant data affecting the safety of the vehicle, such as: evaluate the time or distance, etc., that a certain potential threat object was detected. For example, the preset safety standard of the automatic driving system or the semiautomatic driving system includes a time (for example, not less than 3 s) for detecting an object that may collide with the vehicle, and the earlier the vehicle detects a corresponding object (for example, a pedestrian in front of the vehicle), the larger the evaluation value of the safety performance.
As an alternative embodiment, the performance assessment term may be an efficiency performance.
Specifically, the processor 110 first acquires data related to efficiency performance, and then evaluates the acquired data related to efficiency performance using a preset efficiency standard to obtain an evaluation value of efficiency performance. Optionally, according to the completion time and the preset time of the evaluation item, an evaluation value of the efficiency performance is obtained.
For example: the evaluation criteria for the efficiency performance "time spent in parking process" of an autopilot system or a semiautomatic driving system are: if the time period for the parking process is 50s, the evaluation value of the efficiency performance "time period for the parking process" is 50 points.
As an alternative embodiment, the performance assessment item may be a comfort performance.
Specifically, the processor 110 may first acquire the related data of the comfort level, and then evaluate the related data of the comfort level using a preset comfort level standard to obtain an evaluation value of the comfort level performance. Optionally, the comfort criterion is set according to whether there is an operation affecting comfort when the automated driving system or the semi-automated driving system performs the driving task. For example: sudden braking and/or sudden turning occurs when the driving task is preset to be executed, and the evaluation value of the comfort performance is reduced.
As an alternative embodiment, the performance evaluation item may be a completion performance.
Specifically, the processor 110 first acquires the related data of the completion degree, and then evaluates the related data of the completion degree using a preset completion degree standard to obtain an evaluation value of the completion degree performance.
Optionally, the completion level criterion is set according to the completion accuracy of the automated or semi-automated driving system performing the driving task. For example: when the processor evaluates the completion performance, the automatic driving system firstly obtains the actual parking position of the vehicle, then compares the actual parking position of the vehicle with the parking space A, obtains an evaluation value of 70 minutes if the vehicle is accurately parked in the range of the parking space A, and evaluates the evaluation value of 50 minutes if the vehicle is not accurately parked in the range of the parking space A.
As an alternative embodiment, when the performance evaluation item is the number of driving violations.
Specifically, the processor 110 first obtains relevant data of the driving violations, and then evaluates the relevant data of the driving violations by using preset driving violations standards to obtain an evaluation value of the number of driving violations. Optionally, the driving violation standard is set according to the number of times of violation in the driving task executed by the automatic driving system or the semi-automatic driving system. For example: the more times a violation (such as a line ball running) occurs, the smaller the evaluation value of the violation evaluation item is preset.
As an alternative embodiment, obtaining the road scene evaluation value of each road scene according to the driving task evaluation value of the driving task included in each road scene includes the steps as shown in fig. 5:
Step 321: and acquiring the task weight of each driving task contained in a certain road scene.
Step 322: and carrying out weighted calculation on the driving task evaluation values of all driving tasks contained in the certain road scene by using the task weight of each driving task to obtain the road scene evaluation value of the certain road scene.
Specifically, the processor 110 determines, through its acquisition module, which driving tasks are included in the road scene evaluated for the current driving system, and the task weights of all driving tasks included in the road scene. And then the evaluation module processes the driving task evaluation values of all driving tasks contained in the current road scene by using the corresponding task weights to obtain the road scene evaluation value of the current road scene. Alternatively, the weights of the driving tasks in the road scene may be equal or different. Optionally, the evaluation module of the processor 110 processes the driving task evaluation values of the driving tasks in each road scene using a weighted average algorithm.
For example: the estimated road scene "intersection scene" contains: the two driving tasks of reacting to traffic lights and stopping the line and stopping are respectively scored as follows: reacting to traffic lights for 80 minutes; stopping the line and stopping for 60 minutes.
At this time, when the processor 110 calculates the road scene evaluation value of the road scene, the task weights of the traffic light reaction and the stop line parking two driving tasks are firstly obtained through the obtaining module, and are respectively 0.5 for the traffic light reaction; stopping line parking, 0.5, and weighting 80 and 60 by using two weights of 0.5 and 0.5 by the processor to obtain the evaluation result of the road scene at the moment as 70.
Optionally, acquiring task weights of two driving tasks of reacting to traffic lights and stopping the line parking in an acquisition module, wherein the task weights are respectively reacting to the traffic lights and the task weights are 0.4; stopping line parking, 0.6; at this time, the processor performs a weighted calculation on the weights 80 and 60 using the weights 0.4 and 0.6, and the evaluation result of the road scene is 68 minutes.
As an alternative embodiment, obtaining driving scene evaluation values of driving scenes from road scene evaluation values of road scenes included in each driving scene includes the steps as shown in fig. 6:
step 331: and obtaining the road scene weight of each road scene contained in a certain driving scene.
Step 332: and carrying out weighted calculation on the road scene evaluation values of all the road scenes contained in the certain driving scene by using the road scene weight of each road scene to obtain the driving scene evaluation value of the certain driving scene.
Specifically, the processor 110 determines, through its acquisition module, which road scenes are included in the driving scenes evaluated for the current driving system, and the road scene weights of the road scenes included in the driving scenes. And then the evaluation module processes the road scene evaluation values of all the road scenes contained in the current driving scene by using the corresponding road scene weights to obtain the driving scene evaluation value of the current driving scene. Alternatively, the weights of the road scenes in the driving scene may be equal or different. Optionally, the evaluation module of the processor 110 processes the road scene evaluation value of the driving scene using a weighted average algorithm.
For example: the estimated driving scenario includes: the road scenes of the intersection scene and the roundabout scene are respectively scored as follows: intersection, 80 minutes, roundabout road, 60 minutes.
When the processor calculates the driving scene evaluation value of the driving scene, firstly, the acquisition module acquires road scene weights corresponding to two road scenes of the intersection and the roundabout, wherein the road scene weights are respectively equal to the intersection and 0.5; and (3) carrying out weighted calculation on 80 minutes and 60 minutes by using two weight values of 0.5 and 0.5 by the processor on the roundabout road, and obtaining an evaluation value of 70 minutes of the driving scene.
Optionally, acquiring road scene weights of two road scenes of the intersection and the roundabout road at an acquisition module, wherein the road scene weights are respectively equal to the intersection and 0.4; a roundabout road, 0.6; the processor uses the weights of 0.4 and 0.6 to weight the weights 80 and 60 to obtain the evaluation value of the driving scene as 68 minutes.
As an alternative embodiment, the step of summarizing the driving scenario evaluation values and determining the evaluation value of the vehicle driving system according to the summarized result includes the steps as shown in fig. 7:
step 341: and obtaining the driving scene weight of each driving scene in the summarized driving scenes.
Step 342: and carrying out weighted calculation on all the summarized driving scene evaluation values by using the driving scene weight of each driving scene to obtain an evaluation value of a vehicle driving system.
Specifically, the processor 110 determines, through its acquisition module, the driving scenario evaluated for the current driving system, and the corresponding driving scenario weights. And then the evaluation module processes the driving scene evaluation value by using the corresponding driving scene weight, and finally the evaluation value of the current vehicle driving system is obtained according to the processing results of all driving scenes. Alternatively, the driving scene weights may be equal or different. Alternatively, the driving scenario may be the entire applicable driving scenario of the vehicle, or may be a partial applicable driving scenario.
For example: the applicable driving scene of a certain vehicle is a driving scene such as a city scene, a highway scene, a mountain road scene and the like. In evaluating the driving system of the vehicle, only driving scene evaluation values of driving scenes (e.g., city scenes, expressway scenes) common to the vehicle may be referred to; driving scene evaluation values of the vehicle in all driving scenes (e.g., city scene, highway scene, mountain road scene, etc.) can also be considered. Optionally, the evaluation module of the processor 110 processes the driving scenario evaluation value using a weighted average algorithm to obtain a vehicle driving system evaluation value. Alternatively, the driving scenario weight may be set according to the market demand of the vehicle, for example, the main market of a certain vehicle model is Beijing, and then the driving scenario weight of the urban scenario may be set to be greater than the driving scenario weight of the expressway scenario when the vehicle driving system is evaluated.
For example: the estimated driving scenario includes: the two driving scenes of the city scene and the expressway scene have the scores of: urban scene, 80 minutes, highway scene, 60 minutes.
When the processor calculates the driving system evaluation value of the vehicle, firstly, road scene weights corresponding to two driving scenes of the urban scene and the expressway scene are acquired through the acquisition module, wherein the road scene weights are respectively the urban scene and 0.5; and (3) weighting calculation is carried out on 80 minutes and 60 minutes by using two weight values of 0.5 and 0.5 by the processor in the expressway scene, so that the evaluation value of the vehicle driving system is 70 minutes.
Optionally, the driving scene weights of two driving scenes, namely the city scene and the expressway scene, are acquired by an acquisition module and are respectively 0.4; 0.6 of expressway scene; the processor uses the weight values of 0.4 and 0.6 to weight the 80 and 60 points, and the evaluation result of the vehicle driving system is 68 points.
It should be noted that, in the above embodiment, the score is only one representation of the evaluation value, and may be correspondingly replaced by other evaluation result forms such as a cost value calculated by using a cost function. The present invention is not limited to the form of the evaluation value.
It should be understood that, although the steps in the flowcharts of fig. 3 to 7 are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps of fig. 3-7 may include multiple sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, nor does the order in which the sub-steps or stages are performed necessarily occur in sequence, but may be performed alternately or alternately with at least a portion of other steps or sub-steps or stages of other steps.
In one embodiment, as shown in fig. 8, there is provided a vehicle driving system evaluation apparatus including:
the driving task evaluation module 810 is configured to evaluate a plurality of driving tasks of the vehicle according to a preset rule, and obtain a plurality of driving task evaluation values;
the road scene evaluation module 820 is configured to obtain a road scene evaluation value of each road scene according to the driving task evaluation value of the driving task included in each road scene;
the driving scene evaluation module 830 is configured to obtain driving scene evaluation values of the driving scenes according to the road scene evaluation values of the road scenes included in each driving scene;
and the evaluation result generation module 840 is configured to aggregate the driving scenario evaluation values, and determine an evaluation value of the vehicle driving system according to the aggregate result.
As an optional implementation manner, the driving task evaluation module 810 is further configured to obtain an evaluation item included in each driving task, and evaluate each evaluation item by using an evaluation criterion of each evaluation item to obtain an evaluation value of each evaluation item; and calculating the driving task evaluation value of each driving task by using the evaluation value of the evaluation item corresponding to each driving task.
As an alternative implementation manner, the driving task evaluation module 810 is further configured to, if the driving task includes a probe, obtain probe data corresponding to the probe, and compare the probe data with standard data to obtain an evaluation value of the probe.
As an alternative implementation manner, driving task evaluation module 810 is further configured to, if the driving task includes a performance evaluation item, obtain performance related data of the performance evaluation item, and evaluate the performance related data according to an evaluation criterion of the performance evaluation item to obtain an evaluation value of the performance evaluation item.
As an optional implementation manner, the road scene evaluation module 820 is further configured to obtain a task weight of each driving task included in a certain road scene; and carrying out weighted calculation on the road scene evaluation values of all the road scenes contained in the certain driving scene by using the road scene weight of each road scene, and obtaining the road scene evaluation value of the certain road scene according to the processing result of the driving task evaluation value.
As an optional implementation manner, the driving scenario evaluation module 830 is further configured to obtain a road scenario weight of each road scenario included in a certain driving scenario; and carrying out weighted calculation on all the summarized driving scene evaluation values by using the driving scene weight of each driving scene, and obtaining the driving scene evaluation value of a certain driving scene according to the processing result of the road scene evaluation value.
As an optional implementation manner, the evaluation result generating module 840 is further configured to obtain a driving scenario weight of each driving scenario in the aggregated driving scenarios; and processing the summarized driving scene evaluation values by using the corresponding driving scene weights, and obtaining an evaluation value of a vehicle driving system according to the processing result of the driving scene evaluation values.
The specific limitations regarding the vehicle driving system evaluation device can be found in the above limitations regarding the vehicle driving system evaluation method, and will not be described in detail herein. The respective modules in the above-described vehicle driving system evaluation device may be implemented in whole or in part by software, hardware, and a combination thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, which may be a terminal, and the internal structure thereof may be as shown in fig. 9. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a vehicle driving system assessment method. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, can also be keys, a track ball or a touch pad arranged on the shell of the computer equipment, and can also be an external keyboard, a touch pad or a mouse and the like.
It will be appreciated by persons skilled in the art that the architecture shown in fig. 9 is merely a block diagram of some of the architecture relevant to the present inventive arrangements and is not limiting of the computer device to which the present inventive arrangements are applicable, and that a computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
In one embodiment, a computer device is provided, comprising a memory and a processor, the memory having stored thereon a computer program executable on the processor, the processor executing the computer program to perform the steps of: evaluating a plurality of driving tasks of the vehicle according to a preset rule to obtain a plurality of driving task evaluation values; obtaining road scene evaluation values of all road scenes according to driving task evaluation values of driving tasks contained in each road scene; obtaining driving scene evaluation values of all driving scenes according to the road scene evaluation values of the road scenes contained in each driving scene; and summarizing the driving scene evaluation values, and determining the evaluation value of the vehicle driving system according to the summarizing result.
In one embodiment, the processor when executing the computer program further performs the steps of: acquiring evaluation items contained in each driving task, and evaluating each evaluation item by using an evaluation standard of each evaluation item to obtain an evaluation value of each evaluation item; and calculating the driving task evaluation value of each driving task by using the evaluation value of the evaluation item corresponding to each driving task.
In one embodiment, the processor when executing the computer program further performs the steps of: and if the driving task comprises a detection item, acquiring detection data corresponding to the detection item, and comparing the detection data with standard data to obtain an evaluation value of the detection item.
In one embodiment, the processor when executing the computer program further performs the steps of: and if the driving task comprises a performance evaluation item, acquiring performance related data of the performance evaluation item, and evaluating the performance related data according to an evaluation standard of the performance evaluation item to obtain an evaluation value of the performance evaluation item.
In one embodiment, the processor when executing the computer program further performs the steps of: acquiring task weight of each driving task contained in a certain road scene; and carrying out weighted calculation on the driving task evaluation values of all driving tasks contained in the certain road scene by using the task weight of each driving task to obtain the road scene evaluation value of the certain road scene.
In one embodiment, the processor when executing the computer program further performs the steps of: acquiring the road scene weight of each road scene contained in a certain driving scene; and carrying out weighted calculation on the road scene evaluation values of all the road scenes contained in the certain driving scene by using the road scene weight of each road scene to obtain the driving scene evaluation value of the certain driving scene.
In one embodiment, the processor when executing the computer program further performs the steps of: acquiring driving scene weight of each driving scene in the summarized driving scenes; and carrying out weighted calculation on all the summarized driving scene evaluation values by using the driving scene weight of each driving scene to obtain an evaluation value of a vehicle driving system.
In one embodiment, a computer readable storage medium is provided having a computer program stored thereon, which when executed by a processor, performs the steps of: evaluating a plurality of driving tasks of the vehicle according to a preset rule to obtain a plurality of driving task evaluation values; obtaining road scene evaluation values of all road scenes according to driving task evaluation values of driving tasks contained in each road scene; obtaining driving scene evaluation values of all driving scenes according to the road scene evaluation values of the road scenes contained in each driving scene; and summarizing the driving scene evaluation values, and determining the evaluation value of the vehicle driving system according to the summarizing result.
In one embodiment, the computer program when executed by the processor further performs the steps of: acquiring evaluation items contained in each driving task, and evaluating each evaluation item by using an evaluation standard of each evaluation item to obtain an evaluation value of each evaluation item; and calculating the driving task evaluation value of each driving task by using the evaluation value of the evaluation item corresponding to each driving task.
In one embodiment, the computer program when executed by the processor further performs the steps of: and if the driving task comprises a detection item, acquiring detection data corresponding to the detection item, and comparing the detection data with standard data to obtain an evaluation value of the detection item.
In one embodiment, the computer program when executed by the processor further performs the steps of: and if the driving task comprises a performance evaluation item, acquiring performance related data of the performance evaluation item, and evaluating the performance related data according to an evaluation standard of the performance evaluation item to obtain an evaluation value of the performance evaluation item.
In one embodiment, the computer program when executed by the processor further performs the steps of: acquiring task weight of each driving task contained in a certain road scene; and carrying out weighted calculation on the driving task evaluation values of all driving tasks contained in the certain road scene by using the task weight of each driving task to obtain the road scene evaluation value of the certain road scene.
In one embodiment, the computer program when executed by the processor further performs the steps of: acquiring the road scene weight of each road scene contained in a certain driving scene; and carrying out weighted calculation on the road scene evaluation values of all the road scenes contained in the certain driving scene by using the road scene weight of each road scene to obtain the driving scene evaluation value of the certain driving scene.
In one embodiment, the computer program when executed by the processor further performs the steps of: acquiring driving scene weight of each driving scene in the summarized driving scenes; and carrying out weighted calculation on all the summarized driving scene evaluation values by using the driving scene weight of each driving scene to obtain an evaluation value of a vehicle driving system.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples illustrate only a few embodiments of the application, which are described in detail and are not to be construed as limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of protection of the present application is to be determined by the appended claims.
Claims (11)
1. A vehicle driving system evaluation method, characterized by comprising the steps of:
evaluating a plurality of driving tasks of the vehicle according to a preset rule to obtain a plurality of driving task evaluation values;
obtaining road scene evaluation values of all road scenes according to driving task evaluation values of driving tasks contained in each road scene;
obtaining driving scene evaluation values of all driving scenes according to the road scene evaluation values of the road scenes contained in each driving scene;
Summarizing the driving scene evaluation values, determining the evaluation value of the driving system of the vehicle according to the summarizing result,
the driving system is a semi-automatic driving system of the vehicle or a full-automatic driving system of the vehicle.
2. The method of claim 1, wherein the step of evaluating a plurality of driving tasks of the vehicle according to a preset rule to obtain the plurality of driving task evaluation values comprises:
acquiring evaluation items contained in each driving task, and evaluating each evaluation item by using an evaluation standard of each evaluation item to obtain an evaluation value of each evaluation item;
and calculating the driving task evaluation value of each driving task by using the evaluation value of the evaluation item corresponding to each driving task.
3. The method according to claim 2, wherein the step of obtaining the evaluation items included in each driving task and evaluating each evaluation item using the evaluation criteria of each evaluation item to obtain the evaluation value of each evaluation item comprises:
and if the driving task comprises a detection item, acquiring detection data corresponding to the detection item, and comparing the detection data with standard data to obtain an evaluation value of the detection item.
4. The method according to claim 2, wherein the step of obtaining the evaluation items included in each driving task and evaluating each evaluation item using the evaluation criteria of each evaluation item to obtain the evaluation value of each evaluation item comprises:
and if the driving task comprises a performance evaluation item, acquiring performance related data of the performance evaluation item, and evaluating the performance related data according to an evaluation standard of the performance evaluation item to obtain an evaluation value of the performance evaluation item.
5. The method of claim 4, wherein the performance assessment term comprises:
one or more of safety performance, efficiency performance, comfort performance, finish performance and driving frequency of violation.
6. The method according to claim 1, wherein the step of obtaining the road scene evaluation value of each road scene from the driving task evaluation value of the driving task included in each road scene comprises:
acquiring task weight of each driving task contained in a certain road scene;
and carrying out weighted calculation on the driving task evaluation values of all driving tasks contained in the certain road scene by using the task weight of each driving task to obtain the road scene evaluation value of the certain road scene.
7. The method according to claim 1, wherein the step of obtaining driving scene evaluation values for each driving scene from road scene evaluation values for road scenes included in each driving scene comprises:
acquiring the road scene weight of each road scene contained in a certain driving scene;
and carrying out weighted calculation on the road scene evaluation values of all the road scenes contained in the certain driving scene by using the road scene weight of each road scene to obtain the driving scene evaluation value of the certain driving scene.
8. The method of claim 1, wherein the step of summarizing the driving scenario evaluation values and determining an evaluation value of a vehicle driving system based on the result of the summarizing comprises:
acquiring driving scene weight of each driving scene in the summarized driving scenes;
and carrying out weighted calculation on all the summarized driving scene evaluation values by using the driving scene weight of each driving scene to obtain an evaluation value of a vehicle driving system.
9. A vehicle driving system evaluation device, characterized in that the device comprises:
the driving task evaluation module is used for evaluating a plurality of driving tasks of the vehicle according to a preset rule to obtain a plurality of driving task evaluation values;
The road scene evaluation module is used for obtaining road scene evaluation values of all the road scenes according to the driving task evaluation values of the driving tasks contained in each road scene;
the driving scene evaluation module is used for obtaining driving scene evaluation values of all driving scenes according to the road scene evaluation values of the road scenes contained in each driving scene;
an evaluation result generation module for summarizing the driving scene evaluation values and determining the evaluation value of the driving system of the vehicle according to the summarizing result,
the driving system is a semi-automatic driving system of the vehicle or a full-automatic driving system of the vehicle.
10. A computer device, a memory and a processor, the memory having stored thereon a computer program executable on the processor, characterized in that the processor implements the steps of the method according to any of claims 1 to 8 when the computer program is executed.
11. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 8.
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