CN112100855A - Vehicle following capability evaluation method and device, electronic device and storage medium - Google Patents
Vehicle following capability evaluation method and device, electronic device and storage mediumDownload PDFInfo
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Abstract
Description
Technical Field
The embodiment of the invention relates to the technical field of computers, in particular to a vehicle following capacity evaluation method and device, electronic equipment and a storage medium.
Background
With the continuous development of automobile technology, the evaluation of automatic driving capability is a big difficulty faced by the current industry. The following test scene is one of the most common typical scenes in daily driving, and a great deal of work is also done for strategy development of the following scene at present, however, the existing automatic driving and following capability evaluation method is not systematic enough, the theoretical basis is not firm enough, and a consistent and effective evaluation method is not formed in the whole field.
Therefore, it is desirable to have a test method that can meet the capability evaluation requirements of current automated driving and following behaviors.
Disclosure of Invention
It is an object of embodiments of the present invention to address at least the above problems and/or disadvantages and to provide at least the advantages described hereinafter.
The embodiment of the invention provides a vehicle following capability evaluation method and device, electronic equipment and a storage medium, and can realize effective evaluation on the vehicle following capability.
In a first aspect, a vehicle following capability evaluation method is provided, and includes:
acquiring a running state of a test vehicle, a motion state of a reference object and an actual distance between the test vehicle and the reference object;
determining the optimal distance between the test vehicle and the reference object according to the running state of the test vehicle and the motion state of the reference object;
and determining the vehicle following capacity of the test vehicle according to the matching result between the actual distance and the optimal distance.
Optionally, the determining an optimal distance between the test vehicle and the reference object according to the driving state of the test vehicle and the motion state of the reference object includes:
and determining the optimal distance between the test vehicle and the reference object according to the running state of the test vehicle, the motion state of the reference object and the test scene.
Optionally, the acquiring the running state of the test vehicle, the motion state of the reference object, and the actual distance between the test vehicle and the reference object includes:
acquiring the running state of a test vehicle, the motion state of a reference object and the actual distance between the test vehicle and the reference object at each test time in a test time interval;
determining the optimal distance between the test vehicle and the reference object according to the running state of the test vehicle and the motion state of the reference object, wherein the method comprises the following steps:
determining the optimal distance between the test vehicle and the reference object at each test time according to the running state of the test vehicle and the motion state of the reference object at each test time in the test time interval;
determining the vehicle following capability of the test vehicle according to the matching result between the actual distance and the optimal distance, wherein the determining comprises the following steps:
and determining the following capacity of the test vehicle according to the matching result between the actual distance and the optimal distance of each test moment in the test time interval.
Optionally, the determining, according to a matching result between the actual distance and the optimal distance at each test time in the test time interval, the following capability of the test vehicle includes:
dividing the test time interval into a following efficiency evaluation interval and a following risk evaluation interval according to the relative size between the actual distance and the optimal distance of each test time in the test time interval, wherein the actual distance of each test time contained in the following efficiency evaluation interval is greater than or equal to the corresponding optimal distance, and the actual distance of each test time contained in the following risk evaluation interval is less than the corresponding optimal distance;
determining the following efficiency evaluation of the test vehicle according to the matching result between the actual distance and the corresponding optimal distance of each test moment in the following efficiency evaluation interval;
determining the following risk evaluation of the test vehicle according to the matching result between the actual distance and the corresponding optimal distance of each test time in the following risk evaluation interval;
determining the car following capacity of the test vehicle according to the car following efficiency evaluation and the car following risk evaluation of the test vehicle; wherein the following efficiency evaluation has a positive effect on the following capability, and the following risk evaluation has a negative effect on the following capability.
Optionally, the following efficiency assessment is expressed in the form of a following efficiency score; the following risk evaluation is expressed in the form of a following risk score.
Optionally, the determining, according to a matching result between an actual distance of each test time in the following efficiency evaluation interval and a corresponding optimal distance, a following efficiency evaluation of the test vehicle includes:
determining the following efficiency score of the test vehicle according to the average deviation degree of the actual distances of all test moments in the following efficiency evaluation interval relative to the corresponding optimal distances; and the average deviation degree of the actual distances at all the test moments in the following efficiency evaluation interval relative to the corresponding optimal distances and the following efficiency score of the test vehicle have a negative correlation relationship.
Optionally, the determining the following risk evaluation of the test vehicle according to the matching result between the actual distance of each test time in the following risk evaluation interval and the corresponding optimal distance includes:
determining the following risk score of the test vehicle according to the average deviation degree between the actual distance and the corresponding optimal distance at all the test moments in the following risk evaluation interval; and the average deviation degree between the actual distance and the corresponding optimal distance at all the test moments in the following vehicle risk evaluation interval has a positive correlation with the following vehicle risk score of the test vehicle.
Optionally, the determining the following capability of the test vehicle according to the following efficiency evaluation and the following risk evaluation of the test vehicle includes:
determining preset weights respectively corresponding to the car following efficiency score and the car following risk score;
and carrying out weighted calculation on the car following efficiency score and the car following risk score according to a weighted calculation method to obtain a car following capacity score of the weighted calculation.
Optionally, the determining the following capability of the test vehicle according to the following efficiency evaluation and the following risk evaluation of the test vehicle includes:
and when the car following risk score is larger than a preset risk score limit value, judging the car following ability score as an invalid score.
Optionally, the test vehicle is an autonomous vehicle.
In a second aspect, there is provided a vehicle following ability evaluation device including:
the device comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for acquiring the running state of a test vehicle, the motion state of a reference object and the actual distance between the test vehicle and the reference object;
the optimal distance determining module is used for determining the optimal distance between the test vehicle and the reference object according to the running state of the test vehicle and the motion state of the reference object;
and the vehicle following capacity determining module is used for determining the vehicle following capacity of the test vehicle according to the matching result between the actual distance and the optimal distance.
Optionally, the optimal distance determining module is specifically configured to:
and determining the optimal distance between the test vehicle and the reference object according to the running state of the test vehicle, the motion state of the reference object and the test scene.
Optionally, the obtaining module is specifically configured to:
acquiring the running state of a test vehicle, the motion state of a reference object and the actual distance between the test vehicle and the reference object at each test time in a test time interval;
the optimal distance determination module is specifically configured to:
determining the optimal distance between the test vehicle and the reference object at each test time according to the running state of the test vehicle and the motion state of the reference object at each test time in the test time interval;
the car following capacity determining module is specifically used for:
and determining the following capacity of the test vehicle according to the matching result between the actual distance and the optimal distance of each test moment in the test time interval.
Optionally, the following capability determining module includes:
the test time interval dividing unit is used for dividing the test time interval into a following efficiency evaluation interval and a following risk evaluation interval according to the relative size between the actual distance and the optimal distance of each test time in the test time interval, wherein the actual distance of each test time contained in the following efficiency evaluation interval is greater than or equal to the corresponding optimal distance, and the actual distance of each test time contained in the following risk evaluation interval is less than the corresponding optimal distance;
the following efficiency evaluation determining unit is used for determining the following efficiency evaluation of the test vehicle according to the matching result between the actual distance of each test moment in the following efficiency evaluation interval and the corresponding optimal distance;
the following risk evaluation determining unit is used for determining the following risk evaluation of the test vehicle according to the matching result between the actual distance of each test time in the following risk evaluation interval and the corresponding optimal distance;
the following capacity determining unit is used for determining the following capacity of the test vehicle according to the following efficiency evaluation and the following risk evaluation of the test vehicle; wherein the following efficiency evaluation has a positive effect on the following capability, and the following risk evaluation has a negative effect on the following capability.
Optionally, the following efficiency assessment is expressed in the form of a following efficiency score; the following risk evaluation is expressed in the form of a following risk score.
Optionally, the following efficiency evaluation determining unit is specifically configured to:
determining the following efficiency score of the test vehicle according to the average deviation degree of the actual distances of all test moments in the following efficiency evaluation interval relative to the corresponding optimal distances; and the average deviation degree of the actual distances at all the test moments in the following efficiency evaluation interval relative to the corresponding optimal distances and the following efficiency score of the test vehicle have a negative correlation relationship.
Optionally, the following risk evaluation determining unit is specifically configured to:
determining the following risk score of the test vehicle according to the average deviation degree between the actual distance and the corresponding optimal distance at all the test moments in the following risk evaluation interval; and the average deviation degree between the actual distance and the corresponding optimal distance at all the test moments in the following vehicle risk evaluation interval has a positive correlation with the following vehicle risk score of the test vehicle.
Optionally, the following capability determining unit is specifically configured to:
determining preset weights respectively corresponding to the car following efficiency score and the car following risk score;
and carrying out weighted calculation on the car following efficiency score and the car following risk score according to a weighted calculation method to obtain a car following capacity score of the weighted calculation.
Optionally, the following capability determining unit is specifically configured to:
and when the car following risk score is larger than a preset risk score limit value, judging the car following ability score as an invalid score.
Optionally, the test vehicle is an autonomous vehicle.
In a third aspect, an electronic device is provided, including: at least one processor, and a memory communicatively coupled to the at least one processor, wherein the memory stores instructions executable by the at least one processor to cause the at least one processor to perform the method described above.
In a fourth aspect, a storage medium is provided, on which a computer program is stored which, when executed by a processor, implements the method described above.
The embodiment of the invention at least comprises the following beneficial effects:
according to the vehicle following capability evaluation method and device provided by the embodiment of the invention, the running state of the test vehicle, the motion state of the reference object and the actual distance between the test vehicle and the reference object are firstly obtained, then the optimal distance between the test vehicle and the reference object is determined according to the running state of the test vehicle and the motion state of the reference object, and finally the vehicle following capability of the test vehicle is determined according to the matching result between the actual distance and the optimal distance. Based on the method and the device, the effective evaluation of the vehicle following capacity can be realized.
Additional advantages, objects, and features of embodiments of the invention will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of embodiments of the invention.
Drawings
FIG. 1 is a schematic diagram of a system architecture provided by one embodiment of the present invention;
fig. 2 is a flowchart of a vehicle following capability evaluation method according to an embodiment of the present invention;
FIG. 3 is a schematic illustration of a test vehicle following a reference vehicle according to one embodiment of the present invention;
fig. 4 is a flowchart of a vehicle following capability evaluation method according to another embodiment of the present invention;
FIG. 5 is a flow chart of determining the following capability of a test vehicle according to another embodiment of the present invention;
FIG. 6 is a distribution curve of actual distances and optimal distances within a test time interval according to another embodiment of the present invention;
fig. 7 is a schematic structural diagram of a vehicle following capability evaluation device according to an embodiment of the present invention;
fig. 8 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
The embodiments of the present invention will be described in further detail with reference to the accompanying drawings so that those skilled in the art can implement the embodiments of the invention with reference to the description.
Fig. 1 shows an exemplary system architecture to which embodiments of a vehicle following ability evaluation method, apparatus, electronic device, and storage medium of the present invention can be applied. As shown in FIG. 1, the system architecture may includetest terminals network 130, and aserver 140. The user may control thetest terminal 110 and thetest terminal 120 to perform data interaction with theserver 140 through thenetwork 130, respectively, to receive commands or transmit data, etc.
Thetest terminal 110 is a vehicle-mounted test terminal disposed on the test vehicle, and is configured to monitor a driving state of the test vehicle. Thetest terminal 120 is mounted on the reference object for monitoring the motion state of the reference object. Thetest terminals test terminals test terminal 110 may be a hardware device capable of communicating with a driving computer on the test vehicle and reading the driving speed of the test vehicle from the driving computer, and for other state information included in the driving state, thetest terminal 110 may provide a monitoring function of corresponding state information and may also provide a distance measuring function of an actual distance between the test vehicle and a reference object. Thetest terminal 110 may be a hardware device capable of monitoring all state information included in the driving state without depending on a driving computer of the test vehicle to acquire the driving speed of the test vehicle, or thetest terminal 110 may be a hardware device capable of communicating with the global satellite navigation system and acquiring all state information of the driving state of the test vehicle from the global satellite navigation system. Accordingly, when the reference object is a vehicle, thetest terminal 120 may be a hardware device capable of communicating with a driving computer on the reference vehicle and reading the driving speed of the reference vehicle from the driving computer, and thetest terminal 120 may provide a monitoring function of corresponding state information for other state information included in the motion state of the reference vehicle. Thetest terminal 120 may also be a hardware device that does not rely on the running computer of the reference vehicle to obtain the running speed of the reference vehicle, but has a capability of monitoring all the state information included in the motion state. When the reference object is not a vehicle (such as a pedestrian, an animal, etc.), thetest terminal 120 may be a hardware device having a corresponding monitoring function for all state information included in the motion state of the reference object, or thetest terminal 110 may be a hardware device capable of communicating with the global satellite navigation system and acquiring all state information of the running state of the test vehicle from the global satellite navigation system. Since the test vehicle runs along the reference object in the test scene, thetest terminal 110 may also be used to monitor the actual distance between the test vehicle and the reference object, for example, by using an infrared or ultrasonic ranging technique to test the actual distance between the test vehicle and the reference object. In this case, thetest terminal 110 may directly transmit actual distance information between the test vehicle and the reference object to the server through thenetwork 130. In addition, thetest terminal 110 may obtain the positioning information of the test vehicle by communicating with the global satellite navigation system, and accordingly, thetest terminal 120 may obtain the positioning information of the reference object by communicating with the global satellite navigation system, thetest terminals network 130, and the server analyzes the positioning information of the test vehicle and the positioning information of the reference object and determines the actual distance between the test vehicle and the reference object. When thetest terminal 110 is software, it may be installed in the electronic device listed above, it may be implemented as a plurality of software or software modules, and it may be implemented as a single software or software module. When thetest terminal 120 is software, it may be installed in the electronic device listed above, it may be implemented as a plurality of software or software modules, and it may be implemented as a single software or software module. The present invention is not particularly limited herein.
Thenetwork 130 is a medium for providing a communication link between thetest terminals server 140.Network 130 may include various types of connections, such as wired communication links, wireless communication links, or fiber optic cables, to name a few. The present invention is not particularly limited herein.
Theserver 140 may be a server providing various services, for example, receiving various pieces of state information of the running state of the test vehicle and the positioning information of the test vehicle transmitted from thetest terminal 110 through thenetwork 130, receiving various pieces of state information of the motion state of the reference object and the positioning information of the reference object transmitted from thetest terminal 120 through thenetwork 130, analyzing the running state of the test vehicle, the motion state of the reference object, and the positioning information of both through data analysis capability, determining an actual distance between the test vehicle and the reference object based on the positioning information of both, determining an optimal distance between the test vehicle and the reference object based on the running state of the test vehicle and the motion state of the reference object, and outputting an evaluation result of the vehicle following capability of the test vehicle according to a matching result of the actual distance and the optimal distance. Theserver 140 may be hardware or software. When theserver 140 is hardware, it may be implemented as a distributed server cluster composed of a plurality of servers, or may be implemented as a single server. When the server is software, it can be implemented as a plurality of software or software modules, or as a single software or software module. The present invention is not particularly limited herein.
The information such as the driving state of the test vehicle, the motion state of the reference object, and the actual distance between the test vehicle and the reference object may be pre-stored in theserver 140 by various means, or may be dynamically and remotely acquired from thetest terminals
In addition, the above steps of analyzing data and outputting the evaluation of the following capability of the test vehicle, which are generally performed by the server, can be completely performed by thetest terminal 110 installed on the test vehicle, on the premise of having the calculation capability satisfying the requirements. In this case, the vehicle following capability evaluation method may be executed by thetest terminal 110, and accordingly, the vehicle following capability evaluation device may be provided in thetest terminal 110. The system architecture may not include theserver 140 and thenetwork 130, however, a corresponding network needs to be provided between thetest terminal 110 and thetest terminal 120 to realize data interaction therebetween.
It should be understood that the number of test terminals, networks and servers in fig. 1 is only illustrative, and the number of test terminals, networks and servers can be selected according to actual needs. The present invention is not particularly limited in this regard.
Fig. 2 is a flowchart of a vehicle following capability evaluation method according to an embodiment of the present invention, where the method is executed by a system with processing capability, a server, or a vehicle following capability evaluation device. As shown in fig. 2, the method includes:
In the test process, the test vehicle runs along the reference object, the test terminal installed on the test vehicle can monitor the running state of the test vehicle and the positioning information of the test vehicle in real time, and the test terminal installed on the reference object can monitor the motion state of the reference object and the positioning information of the reference object in real time. The two test terminals can be provided with various sensors for monitoring different state information and positioning information, such as a speed sensor, an acceleration sensor, a GPS module, and the like.
The state information included in the running state of the test vehicle includes the running speed and acceleration state information of the test vehicle, and may include other state information. The state information included in the motion state of the reference object includes the travel speed and acceleration state information of the reference object, and may include other state information. The state information included in the running state of the test vehicle and the state information included in the motion state of the reference object may be selected according to the need of the calculation process of the optimal distance.
The test vehicle may be an autonomous vehicle, i.e., a vehicle equipped with an autonomous system, or may be a non-autonomous vehicle. In addition, the test vehicle can be a fuel vehicle or a new energy automobile. The reference object may be a motor vehicle, a non-motor vehicle, a pedestrian, a stock, or the like. By selecting different reference objects, the following capacity of the vehicle can be more comprehensively measured. When the reference object is also a vehicle, the motion state of the reference object refers to the traveling state of the vehicle.
And step 220, determining the optimal distance between the test vehicle and the reference object according to the running state of the test vehicle and the motion state of the reference object.
In some embodiments, the optimal distance may be derived based on theoretical derivation in combination with the running state of the test vehicle and the motion state of the reference object. The running state of the test vehicle and the motion state of the reference object can be combined and analyzed through big data.
The process of determining the optimum distance will be described by taking a vehicle as a reference. FIG. 3 is a schematic diagram of a test vehicle following a reference vehicle according to an embodiment of the present invention. In the test process, thetest vehicle 310 runs along thereference vehicle 320, time synchronization between the two vehicles is set, and at a certain time t, the running states of the test vehicle and the reference vehicle at the current time and the actual distance between the test vehicle and the reference vehicle can be obtained, wherein the running states of the test vehicle and the reference vehicle comprise the current running speed and acceleration of the test vehicle, and the running states of the reference vehicle comprise the current running speed and acceleration of the reference vehicle. In conjunction with the acquired running states of the test vehicle and the reference vehicle at the present time, the theoretical derivation of the optimum distance can be achieved based on the following assumptions: 1) the front reference vehicle starts a braking action at a maximum deceleration at time t, and the test vehicle starts the braking action after a reaction time elapses. 2) During the reaction time, the test vehicle is traveling at maximum acceleration. 3) After the reaction, the deceleration operation is performed at the minimum deceleration. 4) If the two vehicles reach the standstill, the distance between the two vehicles is just 0. The distance between the test vehicle and the reference vehicle at time t calculated based on the above-described assumption conditions is taken as the optimum distance between the test vehicle and the reference vehicle. It should be understood that, in the derivation process, the parameters such as the maximum deceleration of the reference vehicle, the maximum acceleration and the minimum deceleration of the test vehicle are known parameters and can be obtained by referring to the relevant performance index files of the test vehicle and the reference vehicle, and the braking response time is an empirical value.
It should be noted that, during the test, the actual distance and the optimal distance between the test vehicle and the reference object are required to be obtained based on the same conditions, that is, the driving state of the test vehicle and the motion state of the reference object based on which the actual distance is based are the same as the driving state of the test vehicle and the motion state of the reference object based on which the optimal distance is based.
Further, the optimal distance between the test vehicle and the reference object is determined according to the running state of the test vehicle, the motion state of the reference object and the test scene.
When the optimal distance is theoretically deduced, in order to improve the accuracy of the deduction of the optimal distance and further improve the accuracy of the evaluation of the vehicle following capacity, the influence of a test scene can be considered besides the driving state of a test vehicle and the motion state of a reference object. The test scenario may include a road condition, which refers to a road characteristic that may have an effect on the maximum acceleration, the minimum deceleration, and the maximum deceleration of the test vehicle, a weather condition, which may have an effect on the reaction time, the maximum acceleration, the minimum deceleration, and the maximum deceleration of the reference vehicle, and the like. Therefore, according to different test scenarios, parameters such as the reaction time used in the theoretical derivation process, the maximum acceleration and the minimum deceleration of the test vehicle, and the maximum deceleration of the reference vehicle can be adjusted accordingly, or appropriate parameters corresponding to a certain test scenario can be directly selected from the performance data of the existing test vehicle and the existing reference vehicle.
It should be understood that when the reference is not a vehicle, the theoretical derivation of the optimal distance may also be based on the same assumed conditions as when the vehicle is used as the reference. For example, when the reference object is a pedestrian, the maximum deceleration of the pedestrian (i.e., the pedestrian suddenly stops walking) may also be empirically determined; alternatively, when the reference object is a bicycle, the maximum deceleration of the bicycle may be obtained empirically or statistically from large data.
And step 230, determining the vehicle following capability of the test vehicle according to the matching result between the actual distance and the optimal distance.
In some embodiments, the following matching process may be performed for the actual distance and the optimal distance, and the following ability of the test vehicle may be determined based on the matching result. That is, the actual distance obtained instep 210 is compared with the optimal distance obtained instep 220, if the actual distance is smaller than the optimal distance, the test vehicle is at risk of rear-end collision, and if the actual distance is greater than the optimal distance, the following efficiency of the test vehicle is not at the highest driving efficiency.
In summary, according to the vehicle following capability evaluation method provided by the embodiment of the present invention, the driving state of the test vehicle, the motion state of the reference object, and the actual distance between the test vehicle and the reference object are first obtained, then the optimal distance between the test vehicle and the reference object is determined according to the driving state of the test vehicle and the motion state of the reference object, and finally the vehicle following capability of the test vehicle is determined according to the matching result between the actual distance and the optimal distance. Based on the method, effective evaluation on the vehicle following capacity can be realized. The vehicle following capability evaluation method provided by the embodiment of the invention is timely and reliable, has the advantages of clear method and low cost, is particularly suitable for capability evaluation of an automatic driving vehicle following scene, is beneficial to high and low discrimination of the automatic driving vehicle following capability, and fills the blank of the current technology.
Fig. 4 is a flowchart of a vehicle following capability evaluation method according to another embodiment of the present invention, which is executed by a system having a processing capability, a server, or a vehicle following capability evaluation device. As shown in fig. 4, the method includes:
and step 410, acquiring the running state of the test vehicle, the motion state of the reference object and the actual distance between the test vehicle and the reference object at each test time in the test time interval.
In the test process, the test vehicle runs along with the reference object, so that the running state of the test vehicle, the motion state of the reference object and the actual distance between the test vehicle and the reference object at each test time in a test time interval can be acquired along with the test. That is, at any test time, the running state of the test vehicle, the motion state of the reference object, and the actual distance between the test vehicle and the reference object at that test time can be obtained, and the optimal distance between the test vehicle and the reference object at that test time can be determined based on the running state of the test vehicle and the motion state of the reference object obtained at that test time.
And step 420, determining the optimal distance between the test vehicle and the reference object at each test time according to the running state of the test vehicle and the motion state of the reference object at each test time in the test time interval.
The process of determining the optimum distance will be described by taking a vehicle as a reference. In the test process, the test vehicle runs along the reference vehicle, the two vehicle time synchronization is set, and at a certain time t, the running states of the test vehicle and the reference vehicle at the current time and the actual distance between the test vehicle and the reference vehicle can be obtained, wherein the test vehicle and the running states comprise the current running speed and acceleration of the test vehicle, and the running states of the reference vehicle comprise the current running speed and acceleration of the reference vehicle. As the test process proceeds, the running state of the test vehicle, the moving state of the reference vehicle, and the actual distance between the test vehicle and the reference vehicle at each test time within the test time interval may be continuously acquired.
In conjunction with the above-obtained running states of the test vehicle and the reference vehicle at the current time t, theoretical derivation of the optimum distance can be achieved based on the following assumptions: 1) the front reference vehicle starts a braking action at a maximum deceleration at time t, and the test vehicle starts the braking action after a reaction time elapses. 2) During the reaction time, the test vehicle is traveling at maximum acceleration. 3) After the reaction, the deceleration operation is performed at the minimum deceleration. 4) If the two vehicles reach the standstill, the distance between the two vehicles is just 0. The distance between the test vehicle and the reference vehicle at time t calculated based on the above-described assumption conditions is taken as the optimum distance between the test vehicle and the reference vehicle. Based on the driving states of the test vehicle and the reference vehicle at the plurality of test times within the test time interval, the optimal distance between the test vehicle and the reference vehicle at the plurality of test times within the test time interval can be determined.
And 430, determining the following capacity of the test vehicle according to the matching result between the actual distance and the optimal distance of each test moment in the test time interval.
In some embodiments, the actual distance and the optimal distance at each test time in the test time interval can be matched, and the following capacity of the test vehicle can be comprehensively evaluated based on the matching result corresponding to the whole test time interval. For example, the actual distance of each test time in the test time interval is compared with the optimal distance, if the actual distance of a certain test time is smaller than the optimal distance, the test vehicle at the test time has a rear-end collision risk, if the actual distance of a certain test time is larger than the optimal distance, the vehicle following efficiency of the test vehicle at the test time is not at the highest driving efficiency, the number of times of the situation with the rear-end collision risk and the number of times of the situation with the vehicle following efficiency not at the highest driving efficiency are counted, and the vehicle following capability of the test vehicle is comprehensively evaluated based on the frequency of the two situations.
FIG. 5 is a flow chart of determining a following capability of a test vehicle according to further embodiments of the present invention. In other embodiments, step 430 further comprises:
and 510, dividing the test time interval into a following efficiency evaluation interval and a following risk evaluation interval according to the relative size between the actual distance and the optimal distance of each test time in the test time interval, wherein the actual distance of each test time in the following efficiency evaluation interval is greater than or equal to the corresponding optimal distance, and the actual distance of each test time in the following risk evaluation interval is less than the corresponding optimal distance.
Fig. 6 is a distribution curve of the actual distance and the optimal distance in the test time interval according to the embodiment of the present invention. The actual distance and the optimal distance of each test time in the test time interval are plotted in fig. 6, and the relative relationship between the actual distance and the optimal distance in the test time interval can be observed intuitively. Based on the relative size of the actual distance and the optimal distance of each test moment in the test time interval, the test time interval can be divided into a following efficiency evaluation interval and a following risk evaluation interval. In the following efficiency evaluation interval, the actual distances included in each test time are all greater than or equal to the corresponding optimal distances, that is, corresponding to the situation in fig. 6 where the actual distance distribution curve is located above the optimal distance distribution curve or intersects with the optimal distance distribution curve, an area between the actual distance distribution curve and the optimal distance distribution curve may be represented by a. For the following efficiency evaluation interval, the actual distance at any test moment is greater than the optimal distance, which indicates that no rear-end collision risk exists at the current test moment, and at the moment, the matching result of the actual distance and the optimal distance can be used as the judgment basis of the following efficiency. Accordingly, in the following risk evaluation section, the actual distance included in each test time is smaller than the corresponding optimal distance, that is, corresponding to the case where the actual distance distribution curve is located below the optimal distance distribution curve in fig. 6, the region between the actual distance distribution curve and the optimal distance distribution curve may be represented by B. For the following vehicle risk evaluation interval, the actual distance at any test time is greater than the optimal distance, which indicates that the risk of rear-end collision exists at the current test time, and at this time, the matching result of the actual distance and the optimal distance can be used as the judgment basis of the following vehicle risk. That is to say, this embodiment can follow two dimensions of efficiency and the risk of following the car and carry out more comprehensive measurement to the ability of following the car of vehicle to improve the comprehensiveness and the validity to the ability evaluation of following the car of vehicle.
And step 520, determining the following efficiency evaluation of the test vehicle according to the matching result between the actual distance and the corresponding optimal distance of each test moment in the following efficiency evaluation interval.
In fig. 6, the area a corresponds to the following efficiency evaluation section. In some embodiments, the area size of the region a between the actual distance distribution curve and the optimal distance distribution curve in the following efficiency evaluation interval may be used as an evaluation criterion for the following efficiency of the test vehicle. Specifically, the smaller the area of the region a is, the closer the actual distance distribution curve is to the optimal distance distribution curve in the following efficiency evaluation interval as a whole is, that is, the higher the following efficiency of the test vehicle is on the basis of safety. Conversely, the larger the area of the area A, the smaller the following efficiency of the test vehicle.
The area size of the region a actually reflects the overall deviation degree of the actual distance from the optimal distance at each test time in the following efficiency evaluation interval. In other embodiments, the following efficiency evaluation of the test vehicle may also be determined according to an average deviation degree of the actual distances at all test times in the following efficiency evaluation interval from the corresponding optimal distances. Specifically, the difference between the actual distance of each test time in the following efficiency evaluation interval and the corresponding optimal distance may be calculated first, then the difference is subjected to integral operation, so as to obtain the area of the area a corresponding to the following efficiency evaluation interval, then the area of the area a is divided by the time length of the following efficiency evaluation interval, and the obtained value reflects the average deviation degree of the actual distances of all test times in the following efficiency evaluation interval from the optimal distance. When the average deviation degree is smaller, the following efficiency of the test vehicle is higher on the basis of safety, and otherwise, the following efficiency of the test vehicle is smaller. Compared with the method that the area size of the area A is used as the evaluation basis of the vehicle following efficiency of the test vehicle, the method that the average deviation degree of the actual distance of all test moments in the vehicle following efficiency evaluation interval relative to the corresponding optimal distance is used as the evaluation basis is helpful for providing more accurate evaluation results.
In some examples, the following efficiency rating may be expressed in the form of a following efficiency score.
Further, the following efficiency score of the test vehicle can be determined according to the average deviation degree of the actual distances of all test moments in the following efficiency evaluation interval relative to the corresponding optimal distances; and the average deviation degree of the actual distances of all the test moments in the following efficiency evaluation interval relative to the corresponding optimal distances and the following efficiency score of the test vehicle have a negative correlation relationship. Specifically, when the average deviation degree of the actual distances at all the test moments in the following efficiency evaluation interval relative to the corresponding optimal distances is smaller, the following efficiency score is higher; accordingly, when the average deviation degree of the actual distances at all the test moments in the following efficiency evaluation interval from the corresponding optimal distances is larger, the following efficiency score is lower.
Specifically, a following efficiency score table may be pre-established, and the table provides a corresponding relationship between the average deviation degree of the actual distances at all test times in different following efficiency evaluation intervals relative to the corresponding optimal distances and different following efficiency scores. And searching the range of the average deviation degree of the actual distance of all the test moments in the calculated following efficiency evaluation interval relative to the corresponding optimal distance in the table according to the corresponding relation in the table, and further determining the following efficiency score.
And step 530, determining the following risk evaluation of the test vehicle according to the matching result between the actual distance and the corresponding optimal distance of each test time in the following risk evaluation interval.
In fig. 6, the area B corresponds to the following risk evaluation section. In some embodiments, the area size of the difference B between the actual distance distribution curve and the optimal distance distribution curve in the following risk evaluation interval may be used as an evaluation basis for the following risk of the test vehicle. Specifically, the smaller the area of the region B is, the closer the actual distance distribution curve is to the optimal distance distribution curve as a whole in the following vehicle risk evaluation section is, that is, the smaller the risk of rear-end collision of the test vehicle is, the higher the safety is. Conversely, the larger the area of the region B, the greater the risk of rear-end collision of the test vehicle, and the lower the safety.
The area size of the region B actually reflects the overall deviation degree of the actual distance from the optimal distance at each test time in the following risk evaluation interval. In other embodiments, the following risk evaluation of the test vehicle may also be determined according to the average deviation degree between the actual distances and the corresponding optimal distances at all test moments in the following risk evaluation interval. Specifically, the difference between the optimal distance and the corresponding actual distance at each test time in the following vehicle risk evaluation interval may be calculated first, then the difference is subjected to integral operation, so as to obtain the area of the region B corresponding to the following vehicle risk evaluation interval, then the area of the region B is divided by the time length of the following vehicle risk evaluation interval, and the obtained numerical value reflects the average deviation degree of the actual distances of all the test times in the following vehicle risk evaluation interval from the optimal distances. When the average deviation degree is smaller, the smaller the rear-end collision risk of the test vehicle is, the higher the safety is, and otherwise, the larger the rear-end collision risk of the test vehicle is, the worse the safety is. Compared with the method that the area size of the area B is used as an evaluation basis for testing the vehicle following risk of the vehicle, the method that the average deviation degree of the actual distance of all the test moments in the vehicle following risk evaluation interval relative to the corresponding optimal distance is used as the evaluation basis is beneficial to providing a more accurate evaluation result.
In some examples, the following risk assessment may also be expressed in the form of a following risk score.
Further, the following risk score of the test vehicle can be determined according to the average deviation degree between the actual distance and the corresponding optimal distance at all the test moments in the following risk evaluation interval; and the average deviation degree between the actual distance and the corresponding optimal distance at all the test moments in the following vehicle risk evaluation interval has a positive correlation with the following vehicle risk score of the test vehicle. Specifically, when the average deviation degree between the actual distance and the corresponding optimal distance at all the test moments in the following vehicle risk evaluation interval is larger, the rear-end collision risk is larger, and the following vehicle risk score is higher; correspondingly, the smaller the average deviation degree between the actual distance and the corresponding optimal distance at all the test moments in the following vehicle risk evaluation interval is, the smaller the rear-end collision risk is, and the lower the following vehicle risk score is.
Specifically, a following vehicle risk score table may be pre-established, and the table provides a corresponding relationship between the average deviation degree of the actual distances of all the test times in different following vehicle risk evaluation intervals relative to the corresponding optimal distances and different following vehicle risk scores. And searching the range of the average deviation degree of the actual distance of all the test moments in the calculated following vehicle risk evaluation interval relative to the corresponding optimal distance in the table according to the corresponding relation in the table, and further determining the following vehicle risk score.
In the step, the vehicle following efficiency evaluation and the vehicle following risk evaluation of the vehicle are comprehensively tested, and the vehicle following capacity of the tested vehicle is evaluated. For example, the following capability evaluation can be made based on the following principle: when the following efficiency is higher, the following risk is lower, and the following capacity of the test vehicle is better; when the following efficiency is lower and the following risk is smaller, the following capacity of the test vehicle is general; when the following efficiency is higher, the following risk is larger, and the following capacity of the test vehicle is poorer. The following efficiency evaluation can be divided into a plurality of grades (such as high, general and low), the following risk evaluation is divided into a plurality of grades (such as large, general and small), and then the following capacity comprehensive judgment is made according to different matching conditions between the following efficiency evaluation grade and the following risk evaluation grade.
It should be noted that the following efficiency evaluation has a positive influence on the following capability, and the following risk evaluation has a negative influence on the following capability, that is, it is emphasized that the following efficiency needs to be improved on the premise of ensuring safety as much as possible in the evaluation of the following capability.
In some embodiments, a score for following capability may be quantitatively calculated based on a following efficiency score and a following risk score. Specifically, determining preset weights corresponding to a car following efficiency score and a car following risk score respectively; weighting and calculating the car following efficiency score and the car following risk score according to a weighting calculation method to obtain a car following capacity score of the weighting calculation. The formula for the weighting calculation is: f ═ α × F1-β*F2Wherein F represents the car following ability score, F1For rating car following efficiency, F2And alpha and beta are respectively the weight values of the following vehicle efficiency score and the following vehicle risk score, alpha can be 1, and beta can be selected according to the importance of the following vehicle risk score. It should be noted that, since the following risk evaluation has an adverse effect on the evaluation of the following capability, the calculation symbol before the following risk score is set as a minus sign. The corresponding meaning is that the larger the car following risk score is, the smaller the total car following capacity score obtained through weighted calculation is.
Further, when the vehicle following capability of the test vehicle is determined according to the vehicle following efficiency evaluation and the vehicle following risk evaluation of the test vehicle, when the vehicle following risk score is larger than a preset risk score limit value, the vehicle following capability score is determined as an invalid score. That is, when the following risk is too large, it is considered that the following ability cannot be effectively evaluated, and at this time, the following ability score is determined as an invalid score regardless of the actual score of the following ability score.
In summary, according to the vehicle following capability evaluation method provided by the embodiment of the present invention, the driving state of the test vehicle, the motion state of the reference object, and the actual distance between the test vehicle and the reference object at each test time in the test time interval are first obtained, then the optimal distance between the test vehicle and the reference object at each test time is determined according to the driving state of the test vehicle and the motion state of the reference object at each test time in the test time interval, and finally the vehicle following capability of the test vehicle is determined according to the matching result between the actual distance and the optimal distance at each test time in the test time interval. Based on the method, effective evaluation on the vehicle following capacity can be realized. The vehicle following capability evaluation method provided by the embodiment of the invention is timely and reliable, has the advantages of clear method and low cost, is particularly suitable for capability evaluation of an automatic driving vehicle following scene, is beneficial to high and low discrimination of the automatic driving vehicle following capability, and fills the blank of the current technology.
Fig. 7 is a schematic structural diagram of a vehicle following capability evaluation device provided in an embodiment of the present invention. As shown in fig. 7, the vehicle following ability evaluation device 700 includes: an obtainingmodule 710, configured to obtain a driving state of the test vehicle, a motion state of the reference object, and an actual distance between the test vehicle and the reference object; an optimaldistance determining module 720, configured to determine an optimal distance between the test vehicle and the reference object according to the driving state of the test vehicle and the motion state of the reference object; and the vehicle followingcapability determining module 730 is used for determining the vehicle following capability of the test vehicle according to the matching result between the actual distance and the optimal distance.
In some embodiments, the optimaldistance determining module 720 is specifically configured to: and determining the optimal distance between the test vehicle and the reference object according to the running state of the test vehicle, the motion state of the reference object and the test scene.
In some embodiments, the obtainingmodule 710 is specifically configured to: acquiring the running state of a test vehicle, the motion state of a reference object and the actual distance between the test vehicle and the reference object at each test time in a test time interval; the optimaldistance determining module 720 is specifically configured to: determining the optimal distance between the test vehicle and the reference object at each test time according to the running state of the test vehicle and the motion state of the reference object at each test time in the test time interval; the followingcapability determining module 730 is specifically configured to: and determining the vehicle following capability of the test vehicle according to the matching result between the actual distance and the optimal distance of each test moment in the test time interval.
In some embodiments, the following capability determination module 730 includes: the test time interval dividing unit is used for dividing the test time interval into a following efficiency evaluation interval and a following risk evaluation interval according to the relative size between the actual distance and the optimal distance of each test time in the test time interval, wherein the actual distance of each test time contained in the following efficiency evaluation interval is greater than or equal to the corresponding optimal distance, and the actual distance of each test time contained in the following risk evaluation interval is less than the corresponding optimal distance; the following efficiency evaluation determining unit is used for determining the following efficiency evaluation of the test vehicle according to the matching result between the actual distance and the corresponding optimal distance at each test moment in the following efficiency evaluation interval; the following risk evaluation determining unit is used for determining the following risk evaluation of the test vehicle according to the matching result between the actual distance and the corresponding optimal distance of each test time in the following risk evaluation interval; the following capacity determining unit is used for determining the following capacity of the test vehicle according to the following efficiency evaluation and the following risk evaluation of the test vehicle; the following efficiency evaluation has a positive influence on the following capacity, and the following risk evaluation has a negative influence on the following capacity.
In some embodiments, the following efficiency rating is expressed in the form of a following efficiency score; the following risk evaluation is expressed in the form of a following risk score.
In some embodiments, the following efficiency evaluation determining unit is specifically configured to: determining the following efficiency score of the test vehicle according to the average deviation degree of the actual distances of all test moments in the following efficiency evaluation interval relative to the corresponding optimal distances; and the average deviation degree of the actual distances of all the test moments in the following efficiency evaluation interval relative to the corresponding optimal distances and the following efficiency score of the test vehicle have a negative correlation relationship.
In some embodiments, the following risk evaluation determination unit is specifically configured to: determining the following risk score of the test vehicle according to the average deviation degree between the actual distance and the corresponding optimal distance at all the test moments in the following risk evaluation interval; and the average deviation degree between the actual distance and the corresponding optimal distance at all the test moments in the following vehicle risk evaluation interval has a positive correlation with the following vehicle risk score of the test vehicle.
In some embodiments, the following capability determination unit is specifically configured to: determining preset weights corresponding to the car following efficiency score and the car following risk score respectively; and carrying out weighted calculation on the car following efficiency score and the car following risk score according to a weighted calculation method to obtain a car following capacity score of the weighted calculation.
In some embodiments, the following capability determination unit is specifically configured to: and when the following risk score is larger than a preset risk score limit value, judging the following ability score as an invalid score.
In some embodiments, the test vehicle is an autonomous vehicle.
Fig. 8 shows an electronic device of an embodiment of the invention. As shown in fig. 8, theelectronic device 800 includes: at least oneprocessor 810, and amemory 820 communicatively coupled to the at least oneprocessor 810, wherein the memory stores instructions executable by the at least one processor for causing the at least one processor to perform the method.
Specifically, thememory 820 and theprocessor 810 are connected together via thebus 830, and can be general-purpose memory and processor, which are not specifically limited herein, and when theprocessor 810 executes the computer program stored in thememory 820, the operations and functions described in the embodiments of the present invention in conjunction with fig. 1 to 6 can be performed.
An embodiment of the present invention further provides a storage medium, on which a computer program is stored, which, when executed by a processor, implements the method. For specific implementation, reference may be made to the method embodiment, which is not described herein again.
While embodiments of the present invention have been disclosed above, it is not limited to the applications listed in the description and the embodiments. It is fully applicable to a variety of fields in which embodiments of the present invention are suitable. Additional modifications will readily occur to those skilled in the art. Therefore, the embodiments of the invention are not to be limited to the specific details and illustrations shown and described herein, without departing from the general concept defined by the claims and their equivalents.
Claims (13)
1. A vehicle following ability evaluation method is characterized by comprising the following steps:
acquiring a running state of a test vehicle, a motion state of a reference object and an actual distance between the test vehicle and the reference object;
determining the optimal distance between the test vehicle and the reference object according to the running state of the test vehicle and the motion state of the reference object;
and determining the vehicle following capacity of the test vehicle according to the matching result between the actual distance and the optimal distance.
2. The vehicle following ability evaluation method according to claim 1, wherein the determining an optimal distance between the test vehicle and the reference object based on the running state of the test vehicle and the movement state of the reference object includes:
and determining the optimal distance between the test vehicle and the reference object according to the running state of the test vehicle, the motion state of the reference object and the test scene.
3. The vehicle following ability evaluation method according to claim 1, wherein the acquiring of the running state of the test vehicle, the movement state of the reference object, and the actual distance between the test vehicle and the reference object includes:
acquiring the running state of a test vehicle, the motion state of a reference object and the actual distance between the test vehicle and the reference object at each test time in a test time interval;
determining the optimal distance between the test vehicle and the reference object according to the running state of the test vehicle and the motion state of the reference object, wherein the method comprises the following steps:
determining the optimal distance between the test vehicle and the reference object at each test time according to the running state of the test vehicle and the motion state of the reference object at each test time in the test time interval;
determining the vehicle following capability of the test vehicle according to the matching result between the actual distance and the optimal distance, wherein the determining comprises the following steps:
and determining the following capacity of the test vehicle according to the matching result between the actual distance and the optimal distance of each test moment in the test time interval.
4. The vehicle following ability evaluation method according to claim 3, wherein the determining the vehicle following ability of the test vehicle according to the matching result between the actual distance and the optimal distance at each test time within the test time interval comprises:
dividing the test time interval into a following efficiency evaluation interval and a following risk evaluation interval according to the relative size between the actual distance and the optimal distance of each test time in the test time interval, wherein the actual distance of each test time contained in the following efficiency evaluation interval is greater than or equal to the corresponding optimal distance, and the actual distance of each test time contained in the following risk evaluation interval is less than the corresponding optimal distance;
determining the following efficiency evaluation of the test vehicle according to the matching result between the actual distance and the corresponding optimal distance of each test moment in the following efficiency evaluation interval;
determining the following risk evaluation of the test vehicle according to the matching result between the actual distance and the corresponding optimal distance of each test time in the following risk evaluation interval;
determining the car following capacity of the test vehicle according to the car following efficiency evaluation and the car following risk evaluation of the test vehicle; wherein the following efficiency evaluation has a positive effect on the following capability, and the following risk evaluation has a negative effect on the following capability.
5. The vehicle following ability evaluation method according to claim 4, wherein the following efficiency evaluation is expressed in the form of a following efficiency score; the following risk evaluation is expressed in the form of a following risk score.
6. The vehicle following ability evaluation method according to claim 5, wherein the determining of the following efficiency evaluation of the test vehicle according to the matching result between the actual distance and the corresponding optimal distance at each test time in the following efficiency evaluation interval comprises:
determining the following efficiency score of the test vehicle according to the average deviation degree of the actual distances of all test moments in the following efficiency evaluation interval relative to the corresponding optimal distances; and the average deviation degree of the actual distances at all the test moments in the following efficiency evaluation interval relative to the corresponding optimal distances and the following efficiency score of the test vehicle have a negative correlation relationship.
7. The vehicle following ability evaluation method according to claim 5, wherein the determining the vehicle following risk evaluation of the test vehicle according to the matching result between the actual distance and the corresponding optimal distance at each test time in the vehicle following risk evaluation interval comprises:
determining the following risk score of the test vehicle according to the average deviation degree between the actual distance and the corresponding optimal distance at all the test moments in the following risk evaluation interval; and the average deviation degree between the actual distance and the corresponding optimal distance at all the test moments in the following vehicle risk evaluation interval has a positive correlation with the following vehicle risk score of the test vehicle.
8. The vehicle following ability evaluation method according to claim 5, wherein the determining the following ability of the test vehicle based on the following efficiency evaluation and the following risk evaluation of the test vehicle comprises:
determining preset weights respectively corresponding to the car following efficiency score and the car following risk score;
and carrying out weighted calculation on the car following efficiency score and the car following risk score according to a weighted calculation method to obtain a car following capacity score of the weighted calculation.
9. The vehicle following ability evaluation method according to claim 5, wherein the determining the following ability of the test vehicle based on the following efficiency evaluation and the following risk evaluation of the test vehicle comprises:
and when the car following risk score is larger than a preset risk score limit value, judging the car following ability score as an invalid score.
10. The vehicle following ability evaluation method according to claim 1, wherein the test vehicle is an autonomous vehicle.
11. A vehicle following ability evaluation device characterized by comprising:
the device comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for acquiring the running state of a test vehicle, the motion state of a reference object and the actual distance between the test vehicle and the reference object;
the optimal distance determining module is used for determining the optimal distance between the test vehicle and the reference object according to the running state of the test vehicle and the motion state of the reference object;
and the vehicle following capacity determining module is used for determining the vehicle following capacity of the test vehicle according to the matching result between the actual distance and the optimal distance.
12. An electronic device, comprising: at least one processor, and a memory communicatively coupled to the at least one processor, wherein the memory stores instructions executable by the at least one processor to cause the at least one processor to perform the method of any of claims 1-10.
13. A storage medium on which a computer program is stored, which program, when being executed by a processor, is adapted to carry out the method of any one of claims 1-10.
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