CN109211575B - Unmanned vehicle and site testing method, device and readable medium thereof - Google Patents

Unmanned vehicle and site testing method, device and readable medium thereof Download PDF

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Publication number
CN109211575B
CN109211575B CN201710543930.5A CN201710543930A CN109211575B CN 109211575 B CN109211575 B CN 109211575B CN 201710543930 A CN201710543930 A CN 201710543930A CN 109211575 B CN109211575 B CN 109211575B
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target scene
unmanned
vehicle
road
output data
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CN109211575A (en
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胡太群
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Beijing Baidu Netcom Science and Technology Co Ltd
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Beijing Baidu Netcom Science and Technology Co Ltd
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    • GPHYSICS
    • G01MEASURING; TESTING
    • G01MTESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M17/00Testing of vehicles
    • G01M17/007Wheeled or endless-tracked vehicles

Abstract

The invention provides an unmanned automobile and a field test method, a device and a readable medium thereof; the method comprises the following steps: in field testing, acquiring output data of each analog sensor in a target scene, acquired in a real road by a manually driven data acquisition vehicle, from the outside, and assembling each analog sensor in the data acquisition vehicle according to the assembly position of each sensor in the unmanned vehicle so as to simulate the sensor at the corresponding position on the unmanned vehicle; controlling the unmanned automobile to run in a test field according to the output data of each analog sensor so as to simulate the unmanned automobile to run in a target scene in a real road; and testing the performance of the unmanned automobile in the target scene according to the driving behavior of the unmanned automobile in the target scene. According to the technical scheme, the accuracy of data of the site test of the unmanned automobile can be ensured, and further the site test efficiency of the unmanned automobile can be effectively improved.

Description

Unmanned vehicle and site testing method, device and readable medium thereof
[ technical field ] A method for producing a semiconductor device
The invention relates to the technical field of computer application, in particular to an unmanned automobile, a field test method and device thereof and a readable medium.
[ background of the invention ]
The unmanned automobile is an intelligent automobile, which can be called as a wheeled mobile robot, and mainly depends on an intelligent driver mainly comprising a computer system in the automobile to realize unmanned driving. The unmanned automobile integrates a plurality of technologies such as automatic control, a system structure, artificial intelligence, visual calculation and the like, is a product of high development of computer science, mode recognition and intelligent control technologies, is an important mark for measuring national scientific research strength and industrial level, and has wide application prospect in the fields of national defense and national economy.
At present, the unmanned vehicle is still in a continuous research and development and test stage, and because the danger of the road test is high, the field test is mainly carried out on the unmanned vehicle by sealing a test field at present. In site testing in the prior art, various facilities are deployed in a testing site to simulate a real road environment, such as building a traffic signal lamp device, a traffic sign board, placing a dummy or a dummy car and the like, and building a real road topological structure such as a bridge, an ascending slope, a descending slope, a multi-lane and the like. Various road conditions were then produced to test the performance of the unmanned vehicle.
In the prior art, when the unmanned automobile is tested by manufacturing various road conditions in a built test site, the manufactured road conditions are assumed subjectively by testers, and the accuracy is poor, so that the site test efficiency of the site test in the prior art is low.
[ summary of the invention ]
The invention provides an unmanned automobile, a field test method and device thereof and a readable medium, which are used for improving the field test efficiency of the unmanned automobile.
The invention provides a site testing method of an unmanned automobile, which comprises the following steps:
in a field test, acquiring output data of each analog sensor in a target scene, acquired in a real road by a manually driven data acquisition vehicle, from the outside, and assembling each analog sensor in the data acquisition vehicle according to the assembly position of each sensor in an unmanned vehicle to simulate the sensor at the corresponding position on the unmanned vehicle;
controlling the unmanned automobile to run in a test field according to the output data of each analog sensor so as to simulate the unmanned automobile to run under the target scene in a real road;
and testing the performance of the unmanned automobile in the target scene according to the driving behavior of the unmanned automobile in the target scene.
Further optionally, in the method, acquiring, from the outside, output data of each analog sensor in a target scene, acquired in a real road by a data acquisition vehicle driven by a human, specifically includes:
acquiring output data of each analog sensor in the target scene from the data acquisition vehicle; or
And acquiring output data of each analog sensor in the target scene from a cloud server, wherein the output data of each analog sensor in the target scene in the cloud server is acquired and uploaded by the data acquisition vehicle.
Further optionally, in the method as described above, after acquiring, from the outside, output data of each analog sensor in a target scene acquired in a real road by a data acquisition vehicle driven by a human, the method further includes:
and mapping the output data of each analog sensor in the target scene into a format suitable for the unmanned automobile.
Further optionally, in the method as described above, after acquiring, from the outside, output data of each analog sensor in a target scene acquired in a real road by a data acquisition vehicle driven by a human, the method further includes:
and modifying the output data of the part of the analog sensor in the target scene to obtain the output data of each analog sensor in different scenes.
Further optionally, in the method as described above, controlling the driving of the unmanned vehicle in a test field according to the output data of each of the simulation sensors to simulate driving under the target scene in a real road specifically includes:
acquiring front road condition information under the simulated target scene according to the output data of each simulated sensor under the target scene;
generating a control instruction according to the front road condition information under the target scene;
and controlling the unmanned automobile to run in the test field according to the control instruction so as to simulate the running in the target scene in a real road.
Further optionally, in the method as described above, the front road condition information includes a category and a relative position of an obstacle in the front road and a behavior of the obstacle.
Further optionally, in the method described above, before the output data of each analog sensor in the target scene, acquired in the real road by the data acquisition vehicle driven by a human being, is acquired from the outside, the method includes:
turning off each of the sensors on the unmanned vehicle.
Further optionally, in the method, testing the performance of the unmanned vehicle in the target scene according to the behavior of the unmanned vehicle in the target scene specifically includes:
if the driving behavior of the unmanned vehicle in the target scene is a braking process, judging whether the unmanned vehicle rolls a track line of the obstacle engraved on the road surface of the road in the test field in advance in the process from braking to stopping, and if so, determining that the braking performance of the unmanned vehicle in the target scene is not ideal; the trajectory line of the obstacle is previously marked on the road surface of the road according to the output data of each of the analog sensors.
The present invention provides an unmanned vehicle, comprising:
the system comprises an acquisition module, a data acquisition module and a data acquisition module, wherein the acquisition module is used for acquiring output data of each analog sensor in a target scene, which is acquired in a real road by a manually driven data acquisition vehicle, from the outside in a field test, and each analog sensor is assembled in the data acquisition vehicle according to the assembly position of each sensor in the unmanned vehicle so as to simulate the sensor at the corresponding position on the unmanned vehicle;
the control module is used for controlling the unmanned automobile to run in a test field according to the output data of each analog sensor so as to simulate the unmanned automobile to run in the target scene of a real road;
and the test module is used for testing the performance of the unmanned automobile in the target scene according to the driving behavior of the unmanned automobile in the target scene.
Further optionally, in the apparatus described above, the obtaining module is specifically configured to:
acquiring output data of each analog sensor in the target scene from the data acquisition vehicle; or
And acquiring output data of each analog sensor in the target scene from a cloud server, wherein the output data of each analog sensor in the target scene in the cloud server is acquired and uploaded by the data acquisition vehicle.
Further optionally, in the apparatus as described above, the unmanned vehicle further includes:
and the mapping module is used for mapping the output data of each analog sensor in the target scene into a format suitable for the unmanned automobile.
Further optionally, in the apparatus as described above, the unmanned vehicle further includes:
and the modification module is used for modifying the output data of the analog sensors in the part of the target scene to obtain the output data of the analog sensors in different scenes.
Further optionally, in the apparatus described above, the control module is specifically configured to:
acquiring front road condition information under the simulated target scene according to the output data of each simulated sensor under the target scene;
generating a control instruction according to the front road condition information under the target scene;
and controlling the unmanned automobile to run in the test field according to the control instruction so as to simulate the running in the target scene in a real road.
Further optionally, in the apparatus as described above, the front road condition information includes a category and a relative position of an obstacle in the front road and a behavior of the obstacle.
Further optionally, in the apparatus as described above, the control module is further configured to turn off each of the sensors on the unmanned vehicle.
Further optionally, in the apparatus described above, the test module is specifically configured to, if the behavior of the unmanned vehicle in traveling in the target scene is a braking process, determine whether a trajectory of the obstacle scribed in advance on the road surface of the road in the test site is crushed in the process from braking to stopping of the unmanned vehicle, and if so, determine that the braking performance of the unmanned vehicle in the target scene is not ideal; the trajectory line of the obstacle is previously marked on the road surface of the road according to the output data of each of the analog sensors.
The present invention also provides a control device of an unmanned vehicle, including:
one or more processors;
a memory for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the method for field testing of unmanned vehicles as described above.
The invention also provides a computer readable medium having stored thereon a computer program which, when executed by a processor, implements a method for field testing of an unmanned vehicle as described above.
According to the unmanned automobile and the field test method, device and readable medium thereof, output data of each analog sensor in a target scene, which is acquired in a real road by a manually driven data acquisition vehicle, is acquired from the outside in the field test, and each analog sensor is assembled in the data acquisition vehicle according to the assembly position of each sensor in the unmanned automobile so as to simulate the sensor at the corresponding position on the unmanned automobile; controlling the unmanned automobile to run in a test field according to the output data of each analog sensor so as to simulate the unmanned automobile to run in a target scene in a real road; and testing the performance of the unmanned automobile in the target scene according to the driving behavior of the unmanned automobile in the target scene. According to the technical scheme, the output data of each analog sensor under the target scene, which is acquired by a vehicle on a real road, is acquired according to the manually-driven data, so that the driving of the unmanned vehicle on the test site is controlled, and the road condition recorded in the output data of each analog sensor has authenticity and accuracy, so that the accuracy of the data tested by the unmanned vehicle site can be ensured, and the site test efficiency of the unmanned vehicle can be effectively improved.
[ description of the drawings ]
FIG. 1 is a flowchart of an embodiment of a method for field testing of an unmanned vehicle according to the present invention.
Fig. 2 is a block diagram of a first embodiment of the unmanned vehicle of the present invention.
Fig. 3 is a structural diagram of a second embodiment of the unmanned vehicle of the present invention.
Fig. 4 is a block diagram of an embodiment of a control device of an unmanned vehicle according to the present invention.
Fig. 5 is an exemplary diagram of a control device of an unmanned vehicle according to the present invention.
[ detailed description ] embodiments
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in detail with reference to the accompanying drawings and specific embodiments.
FIG. 1 is a flowchart of an embodiment of a method for field testing of an unmanned vehicle according to the present invention. As shown in fig. 1, the site testing method for the unmanned vehicle in this embodiment may specifically include the following steps:
100. in field testing, acquiring output data of each analog sensor in a target scene, acquired in a real road by a manually driven data acquisition vehicle, from the outside, and assembling each analog sensor in the data acquisition vehicle according to the assembly position of each sensor in the unmanned vehicle so as to simulate the sensor at the corresponding position on the unmanned vehicle;
101. controlling the unmanned automobile to run in a test field according to the output data of each analog sensor so as to simulate the unmanned automobile to run in a target scene in a real road;
102. and testing the performance of the unmanned automobile in the target scene according to the driving behavior of the unmanned automobile in the target scene.
The execution main body of the site testing method of the unmanned automobile in the embodiment is the unmanned automobile. In the field test of the unmanned automobile, in order to ensure the accuracy and the authenticity of data in the field test, the output data of each analog sensor in a target scene, which is acquired by a data acquisition vehicle driven manually in a real road, is acquired from the outside during the field test. The simulation sensors in the data acquisition vehicle are assembled in the data acquisition vehicle according to the assembly positions of the sensors in the unmanned vehicle so as to simulate the sensors at the corresponding positions on the unmanned vehicle.
That is, in order to avoid the danger of the driverless vehicle directly going to the road for testing, in this embodiment, the corresponding analog sensors may be mounted at the corresponding positions in one data collecting vehicle according to the positions of the sensors in the driverless vehicle, so as to simulate the driverless vehicle. The data collection vehicle is driven manually. In this way, the data acquisition vehicle driven manually has the sensors of the unmanned vehicle, which is equivalent to driving the unmanned vehicle to acquire the output data of the sensors in the target scene on the real road. The analog sensors on the data acquisition vehicle and the sensors in the unmanned vehicle of the present embodiment may include a laser radar, an image sensor, a millimeter wave radar, an ultrasonic radar, a Global Positioning System (GPS) module, an Inertial Measurement Unit (IMU), and the like. Correspondingly, where the lidar is mounted in an unmanned vehicle, a simulated lidar may be mounted in a corresponding location in the data-capturing vehicle. Similarly, the image sensor is mounted in the unmanned vehicle, a simulated image sensor can be mounted in the corresponding position of the data acquisition vehicle, and so on, and the simulated sensor having the same parameters as the sensor in the corresponding position of the unmanned vehicle can be mounted in the corresponding position of the data acquisition vehicle according to the positions of the sensors in the unmanned vehicle. Preferably, each analog sensor on the data collecting vehicle of the present embodiment has the same parameters as the sensor on the corresponding unmanned vehicle, the same parameters of the present embodiment include the same internal parameters and the same external parameters, for example, the external parameters may include the manufacturer and model of the sensor, and the internal parameters may include the selected operating parameters of each sensor when collecting data, such as the viewing angle, the wide angle, and the like.
The laser radar of the embodiment can detect the point cloud of obstacles around a data acquisition vehicle or an unmanned vehicle; the image sensor can collect data to collect traffic lights or pedestrian detection in front of a vehicle or an unmanned automobile; the millimeter wave radar and the ultrasonic radar can detect obstacles around a data acquisition vehicle or an unmanned vehicle so as to determine road conditions; the GPS module may provide Location Based Service (LBS) for the data-capturing vehicle or the unmanned vehicle, and the IMU may provide various attitude information such as a driving direction, an angular velocity, etc. of the data-capturing vehicle or the unmanned vehicle.
The data acquisition vehicle is driven manually to run on a real road, and output data of each assembled simulation sensor in a target scene is acquired. The target scene of this embodiment is various scenes that need to be tested when the test site is tested, for example, the target scene at least includes road conditions on a road, that is, road conditions that need to be tested in the test site. When no abnormity occurs, the unmanned automobile runs safely and does not need to pass more tests. When an abnormal condition occurs, the unmanned automobile needs to be safely avoided, and the driving safety is ensured. The target scenes of the present embodiment can be considered as some abnormal states, and it is necessary for the unmanned vehicle to be able to generate a control command to change the driving track or generate braking to realize safe driving. The target scene of the embodiment may include various road conditions, for example, a scene that traffic lights in a road change, a scene that pedestrians cross the road X meters ahead, a scene that vehicles travel at a speed of a meter/hour, a scene that vehicles at the rear speed overspeed, a scene that vehicles travel at a low speed M meters ahead, and the like may be included. Further, in order to further simulate more scenes, the target scene of the embodiment may further include types of roads, where the types of roads may include ordinary asphalt roads, wet roads, snow roads, muddy roads, uneven roads, gravel roads, and the like. The corresponding target scene at this time may include a scene of traffic light change in a snow road, or may also include a scene of pedestrians crossing the road X meters ahead on a rainy and slippery road surface, or may also include a scene of vehicles running at a speed of a meter/hour on a highway and speeding at the rear, or may also include a scene of vehicles running at a low speed M meters ahead on a gravel road; and so on. For each target scene, each sensor on the data acquisition vehicle can acquire all output data in the process from road condition discovery to road condition processing completion. That is, the output data of each analog sensor in this embodiment is specifically a set of data, or a data sequence, and may include output data at each time of a time period corresponding to the target scene.
In order to ensure that the acquired output data of each analog sensor is reused, the output data of each analog sensor acquired by the data acquisition vehicle can be stored according to each analog sensor when being stored, for example, each output data storage area corresponding to each analog sensor is provided with an identifier of the analog sensor, so that after being acquired by the unmanned vehicle, the output data of the part is determined to be used for deployment to which sensor.
Optionally, in step 100 "acquiring, from the outside, output data of each analog sensor in a target scene, acquired by a data acquisition vehicle driven by a human being in a real road", specifically, the following two ways may be included:
(a1) acquiring output data of each analog sensor in a target scene from a data acquisition vehicle;
(a2) the output data of each analog sensor in the target scene in the cloud server is acquired by the data acquisition vehicle and uploaded.
In the method (a1), the data collection vehicle collects the output data of each analog sensor in the target scene and stores the output data in the data collection vehicle, when the unmanned vehicle needs the data collection vehicle, the data collection vehicle may request the output data of each analog sensor, and the data collection vehicle receives the data request of the unmanned vehicle and sends the output data of each analog sensor to the unmanned vehicle. Wherein, the data acquisition vehicle and the unmanned vehicle can be provided with communication modules, and the data acquisition vehicle and the unmanned vehicle can be communicated in a wireless mode.
In the method (a2), the data acquisition vehicle directly uploads the output data of each analog sensor in the target scene to the cloud server after acquiring the output data of each analog sensor in the target scene, and the cloud server stores the output data of each analog sensor in the target scene. The storage mode of the cloud server can be stored according to the corresponding relation among the target scene, the identifiers of the analog sensors in the target scene and the output data of the analog sensors. At this time, when the unmanned vehicle needs data, the output data of each analog sensor can be requested to the cloud server, and the cloud server receives the data request of the unmanned vehicle and sends the output data of each analog sensor to the unmanned vehicle. The communication between the cloud server and the unmanned vehicle can also be in a wireless mode.
During field test, after the unmanned automobile acquires output data of each analog sensor in the target scene from the outside, the output data of each analog sensor is used as the output data of each sensor on the unmanned automobile, which is equivalent to the fact that the unmanned automobile detects the real road condition of the target scene in a real road, and then the controller of the unmanned automobile controls the unmanned automobile to run in the test field according to the output data of each analog sensor so as to simulate the running in the target scene in the real road; then, a test module can be arranged on the unmanned automobile to test the performance of the unmanned automobile in the target scene according to the driving behavior of the unmanned automobile in the target scene, and further, the test result can be displayed on a display screen of the unmanned automobile or sent to a test center for a tester to check.
Optionally, in the field test of this embodiment, the unmanned vehicle directly obtains the output data of each analog sensor from the outside, and each sensor mounted on the unmanned vehicle does not need to sense the surrounding environment, so the unmanned vehicle of this embodiment may only determine the position of each sensor on the unmanned vehicle, and may not need to install each sensor, and the cost of the test vehicle of the unmanned vehicle used in the test field may also be effectively saved.
Alternatively, if the field test is performed using a non-test vehicle, the non-test vehicle is a formal version of the unmanned vehicle equipped with sensors. At this time, before step 100 of this embodiment, the unmanned vehicle needs to turn off each sensor on the unmanned vehicle, so as to prevent the environmental data sensed by each sensor on the unmanned vehicle from affecting the field test of the unmanned vehicle.
In the site test method of the unmanned vehicle of the embodiment, output data of each analog sensor in a target scene, which is acquired by a manually driven data acquisition vehicle on a real road, is acquired from the outside in the site test, and each analog sensor is assembled in the data acquisition vehicle according to the assembly position of each sensor in the unmanned vehicle so as to simulate the sensor at the corresponding position on the unmanned vehicle; controlling the unmanned automobile to run in a test field according to the output data of each analog sensor so as to simulate the unmanned automobile to run in a target scene in a real road; and testing the performance of the unmanned automobile in the target scene according to the driving behavior of the unmanned automobile in the target scene. According to the technical scheme, the driving of the unmanned automobile in the test site is controlled by acquiring the output data of each analog sensor under the target scene, acquired by the automobile on the real road according to the manually driven data, and the road condition recorded in the output data of each analog sensor has authenticity and accuracy, so that the accuracy of the data tested in the unmanned automobile site can be ensured, and the site test efficiency of the unmanned automobile can be effectively improved.
Further optionally, after "acquiring, from the outside, output data of each analog sensor in the target scene acquired by the data acquisition vehicle driven by a human in the real road" in step 100 in the embodiment shown in fig. 1, the method may further include: and mapping the output data of each analog sensor in the target scene into a format suitable for the unmanned automobile. In some scenes, the format of the acquired output data of the analog sensors after being stored is not suitable for being directly used by the unmanned automobile, and at the moment, after the unmanned automobile acquires the output data of each analog sensor, the output data of each analog sensor in the target scene is mapped into the format suitable for being used by the unmanned automobile. For example, if the unit of the output data of the analog sensor does not match the unit required for use in the unmanned vehicle, the unit of the output data of each analog sensor in the target scene needs to be converted into a unit suitable for use in the unmanned vehicle.
Further optionally, after "acquiring, from the outside, output data of each analog sensor in the target scene acquired by the data acquisition vehicle driven by a human in the real road" in step 100 in the embodiment shown in fig. 1, the method may further include: and modifying the output data of the part of the analog sensors in the target scene to obtain the output data of each analog sensor in different scenes.
For example, in a traffic light switching scene of various road types, output data of a part of analog sensors may be modified, for example, a red light in each analog sensor data may be changed to a green light, or a green light may be changed to a red light, so as to obtain different scenes, thereby obtaining more test data, so as to perform a test of more scenes on an unmanned vehicle in a test site, so as to improve the safety of the unmanned vehicle.
Further optionally, the step 101 in the embodiment shown in fig. 1 of "controlling the unmanned vehicle to run in the test site according to the output data of each simulation sensor to simulate running in a target scene in a real road" may specifically include the following steps:
(b1) acquiring front road condition information under a simulated target scene according to output data of each simulated sensor under the target scene;
(b2) generating a control instruction according to the front road condition information under the target scene;
(b3) and controlling the unmanned automobile to run in the test field according to the control instruction so as to simulate the running in a target scene in a real road.
For example, in this embodiment, according to the output data of each analog sensor in the target scene, the acquired front road condition information in the analog target scene may include the type and relative position of the obstacle in the front road and the behavior of the obstacle. For example, what obstacle is doing at X meters ahead. Therefore, the controller of the unmanned automobile can make a decision according to the road condition information in front and generate a control instruction, wherein the control instruction comprises the control instruction of each component involved in the decision, such as the control instruction of each component involved in braking, steering or the like. At the moment, each part of the unmanned automobile can control the unmanned automobile to run in the test field according to the corresponding control instruction so as to simulate the running in the target scene of the real road, and thus, the performance of the unmanned automobile can be tested according to the running of the unmanned automobile in the test field.
Optionally, when the target scene includes a preset road type, controlling the driverless vehicle to travel in the test site according to the output data of each simulation sensor to simulate the driverless vehicle before traveling under the target scene in the real road, the method may further include: and controlling the unmanned automobile to run to a road section corresponding to the road type preset in the test site according to the set destination of the tester.
That is to say, in the test site, road segments of various types of roads may be set, such as asphalt roads, wet and slippery roads, snow roads, muddy roads, concave and convex roads, and gravel roads, before the test, the type of the preset road in the test scene may be obtained from the outside, then the destination of the road corresponding to the road type in the test scene may be set in the unmanned vehicle by the tester, and then the unmanned vehicle may be started to run, and at this time, the unmanned vehicle may be controlled to run to the road segment corresponding to the road type preset in the test site according to the destination set by the tester.
Further optionally, on the basis of the technical solution of the above embodiment, the performance of the unmanned vehicle in the target scene is tested according to the driving behavior of the unmanned vehicle in the target scene, specifically including the test of the braking process.
Specifically, if the driving behavior of the unmanned vehicle in the target scene is a braking process, whether a track line of an obstacle previously engraved on the road surface of a road in the test field is rolled or not in the process from braking to stopping of the unmanned vehicle is judged, and if yes, it is determined that the braking performance of the unmanned vehicle in the target scene is not ideal; the trajectory of the obstacle is previously marked on the road surface of the road based on the output data of each analog sensor.
That is to say, in the test site of the embodiment, various obstacles, such as a test vehicle to be tested, a simulated test pedestrian, and the like, may not be built; meanwhile, other road facilities such as guard rails on the road side and the like are not required to be built, and the track lines of the static obstacles or the moving obstacles can be scribed on the road in advance through the acquired output data of each analog sensor. Therefore, whether the track line of the barrier carved on the road surface of the road in the test field in advance is rolled or not can be judged in the process from braking to stopping of the unmanned automobile, and if yes, it is determined that the braking performance of the unmanned automobile in the target scene is not ideal.
For example, if the driving behavior of the unmanned vehicle in the target scene is a braking process of avoiding pedestrians on a wet road surface, the driving behavior of the unmanned vehicle can be detected by installing a test module on the unmanned vehicle, for example, the test module may include an image sensor and can detect the condition of the road surface under the vehicle in the driving process of the unmanned vehicle; the test module can further judge whether the unmanned automobile rolls the track line of the pedestrian on the road surface of the road in the test field in advance in the process from braking to stopping according to the detected condition of the road surface under the unmanned automobile in the running process, and if so, the test module determines that the braking performance of the unmanned automobile in the target scene is not ideal. At the moment, a tester can adjust the control parameters of the unmanned automobile in driving on a wet and slippery road surface so as to adjust the safety of the unmanned automobile.
In a similar mode, the unmanned vehicle can be tested for various test scenes such as rear-end collision, overtaking, traffic light sudden change and the like on various road surfaces, so that the performance of the unmanned vehicle in various test scenes can be tested, and if the performance is not ideal, a tester can timely adjust the decision-making and control capacity of the unmanned vehicle on the test scenes, so that the safety of the unmanned vehicle is enhanced.
In addition, it should be noted that the test props in the test field of this embodiment are pre-drawn in the test road according to the output data of each analog sensor, so during the test, the relative position of the unmanned vehicle and the test props needs to be strictly controlled according to the output data of each analog sensor, so as to realize accurate test.
According to the site testing method of the unmanned automobile, the output data of each analog sensor under the target scene, which is acquired by the automobile on the real road, is acquired according to the data of the artificial driving, so that the unmanned automobile is controlled to run on the testing site. In the technical scheme of the embodiment, the track line of the barrier is carved on the road surface of the road in advance according to the output data of each analog sensor, so that the troubles of building a test scene and deploying test props in a test field can be saved, the construction time of the test field can be saved, the construction cost of the test field can be effectively saved, the test cost of the unmanned automobile is saved, and the field test efficiency of the unmanned automobile is improved.
Fig. 2 is a block diagram of a first embodiment of the unmanned vehicle of the present invention. The unmanned vehicle of the present embodiment mainly refers to a control portion of the unmanned vehicle, as shown in fig. 2, the unmanned vehicle of the present embodiment may specifically include: the device comprises an acquisition module 10, a control module 11 and a test module 12.
The acquisition module 10 is used for acquiring output data of each analog sensor in a target scene, which is acquired in a real road by a manually driven data acquisition vehicle, from the outside in a field test, and each analog sensor is assembled in the data acquisition vehicle according to the assembly position of each sensor in the unmanned vehicle so as to simulate the sensor at the corresponding position on the unmanned vehicle;
the control module 11 is configured to control the unmanned vehicle to run in the test site according to the output data of each analog sensor acquired by the acquisition module 10, so as to simulate the unmanned vehicle to run in a target scene in a real road;
the test module 12 is configured to test performance of the unmanned vehicle in the target scene according to a driving behavior of the unmanned vehicle in the target scene controlled by the control module 11.
The implementation principle and technical effect of the unmanned vehicle in this embodiment for implementing the site test of the unmanned vehicle by using the modules are the same as those of the related method embodiments, and the details of the related method embodiments may be referred to, and are not repeated herein.
Fig. 3 is a structural diagram of a second embodiment of the unmanned vehicle of the present invention. As shown in fig. 3, the unmanned vehicle of the present embodiment may further include the following technical solutions on the basis of the technical solution of the embodiment shown in fig. 2.
The obtaining module 10 in the unmanned vehicle of the present embodiment is specifically configured to:
acquiring output data of each analog sensor in a target scene from a data acquisition vehicle; or
The output data of each analog sensor in the target scene in the cloud server is acquired by the data acquisition vehicle and uploaded.
Further optionally, as shown in fig. 3, the unmanned vehicle of the embodiment further includes a mapping module 13.
The mapping module 13 is configured to map the output data of each analog sensor in the target scene acquired by the acquiring module 10 into a format suitable for use by the unmanned vehicle.
At this time, the control module 11 is configured to control the unmanned vehicle to run in the test site according to the output data of each simulated sensor mapped by the mapping module 13, so as to simulate the running in the target scene in the real road.
Further optionally, as shown in fig. 3, the unmanned vehicle of the embodiment further includes a modification module 14. The modifying module 14 is configured to modify the output data of the partial analog sensor in the target scene, acquired by the acquiring module 10, so as to obtain the output data of each analog sensor in different scenes.
At this time, the control module 11 is configured to control the unmanned vehicle to travel in the test site according to the output data of each of the simulation sensors modified by the modification module 14 so as to simulate traveling in a target scene in a real road.
Further optionally, the control module 11 in the unmanned vehicle of this embodiment is specifically configured to:
acquiring front road condition information under a simulated target scene according to output data of each simulated sensor under the target scene;
generating a control instruction according to the front road condition information under the target scene;
and controlling the unmanned automobile to run in the test field according to the control instruction so as to simulate the running in a target scene in a real road.
Further optionally, in the unmanned vehicle of this embodiment, the front road condition information includes a type and a relative position of an obstacle in the front road and a behavior of the obstacle.
Further optionally, in the unmanned vehicle of the embodiment, the control module 11 is further configured to turn off each sensor on the unmanned vehicle.
Further optionally, in the unmanned vehicle according to this embodiment, the test module 12 is specifically configured to, if the driving behavior of the unmanned vehicle in the target scene is a braking process, determine whether a trajectory line of an obstacle previously scribed on a road surface of a road in the test site is rolled in the process from braking to stopping of the unmanned vehicle, and if so, determine that the braking performance of the unmanned vehicle in the target scene is not ideal; the trajectory of the obstacle is previously marked on the road surface of the road based on the output data of each analog sensor.
The implementation principle and technical effect of the unmanned vehicle in this embodiment for implementing the site test of the unmanned vehicle by using the modules are the same as those of the related method embodiments, and the details of the related method embodiments may be referred to, and are not repeated herein.
Fig. 4 is a block diagram of an embodiment of a control device of an unmanned vehicle according to the present invention. As shown in fig. 4, the control device of the unmanned vehicle according to the present embodiment includes: one or more processors 30, and a memory 40, the memory 40 for storing one or more programs, when the one or more programs stored in the memory 40 are executed by the one or more processors 30, cause the one or more processors 30 to implement the method for field testing of unmanned vehicles as described above in the embodiments of fig. 1-3. The embodiment shown in fig. 4 is exemplified by including a plurality of processors 30.
For example, fig. 5 is an exemplary diagram of a control device of an unmanned vehicle according to the present invention. Fig. 5 shows a block diagram of a control device 12a of an exemplary unmanned vehicle suitable for use in implementing embodiments of the present invention. The control device 12a of the unmanned automobile shown in fig. 5 is only an example, and should not bring any limitation to the function and the range of use of the embodiment of the present invention.
As shown in fig. 5, the control device 12a of the unmanned vehicle is a core part of the unmanned vehicle, and implements decision making and control of the unmanned vehicle during driving, and corresponds to a computer device, so that the present embodiment is represented in the form of a general-purpose computing device. The components of the control device 12a of the unmanned vehicle may include, but are not limited to: one or more processors 16a, a system memory 28a, and a bus 18a that connects the various system components (including the system memory 28a and the processors 16 a).
Bus 18a represents one or more of any of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, and a processor or local bus using any of a variety of bus architectures. By way of example, such architectures include, but are not limited to, Industry Standard Architecture (ISA) bus, micro-channel architecture (MAC) bus, enhanced ISA bus, Video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus.
The control device 12a of the unmanned vehicle typically includes a variety of computer system readable media. These media may be any available media that can be accessed by the control device 12a of the unmanned vehicle and include both volatile and nonvolatile media, removable and non-removable media.
The system memory 28a may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM)30a and/or cache memory 32 a. The control device 12a of the unmanned vehicle may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 34a may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 5, commonly referred to as a "hard drive"). Although not shown in FIG. 5, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 18a by one or more data media interfaces. System memory 28a may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of the various embodiments of the invention described above in fig. 1-3.
A program/utility 40a having a set (at least one) of program modules 42a may be stored, for example, in system memory 28a, such program modules 42a including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which examples or some combination thereof may include an implementation of a network environment. Program modules 42a generally perform the functions and/or methodologies described above in connection with the various embodiments of fig. 1-3 of the present invention.
The control apparatus 12a of the unmanned vehicle may also be in communication with one or more external devices 14a (e.g., a keyboard, a pointing device, a display 24a, etc.), with one or more devices that enable a user to interact with the control apparatus 12a of the unmanned vehicle, and/or with any device (e.g., a network card, a modem, etc.) that enables the control apparatus 12a of the unmanned vehicle to communicate with one or more other computing devices. Such communication may be through an input/output (I/O) interface 22 a. Also, the control device 12a of the unmanned vehicle may also communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the internet) via the network adapter 20 a. As shown, the network adapter 20a communicates with the other modules of the control device 12a of the unmanned vehicle via the bus 18 a. It should be understood that although not shown in the figures, other hardware and/or software modules may be used in conjunction with the control device 12a of the unmanned vehicle, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
The processor 16a executes various functional applications and data processing, such as implementing the field test method for the unmanned vehicle shown in the above-described embodiment, by executing the program stored in the system memory 28 a.
The present invention also provides a computer-readable medium having stored thereon a computer program which, when executed by a processor, implements the field testing method of an unmanned vehicle as shown in the above embodiments.
The computer-readable media of this embodiment may include RAM30a, and/or cache memory 32a, and/or storage system 34a in system memory 28a in the embodiment illustrated in fig. 5 described above.
With the development of technology, the propagation path of computer programs is no longer limited to tangible media, and the computer programs can be directly downloaded from a network or acquired by other methods. Accordingly, the computer-readable medium in the present embodiment may include not only tangible media but also intangible media.
The computer-readable medium of the present embodiments may take any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
In the embodiments provided in the present invention, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. For example, the above-described device embodiments are merely illustrative, and for example, the division of the units is only one logical functional division, and other divisions may be realized in practice.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
The integrated unit implemented in the form of a software functional unit may be stored in a computer readable storage medium. The software functional unit is stored in a storage medium and includes several instructions to enable a computer device (which may be a personal computer, a server, or a network device) or a processor (processor) to execute some steps of the methods according to the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.

Claims (18)

1. A method for field testing of an unmanned vehicle, the method comprising:
in a field test, acquiring output data of each analog sensor in a target scene, acquired in a real road by a manually driven data acquisition vehicle, from the outside, and assembling each analog sensor in the data acquisition vehicle according to the assembly position of each sensor in an unmanned vehicle to simulate the sensor at the corresponding position on the unmanned vehicle;
controlling the unmanned automobile to run in a test field according to the output data of each analog sensor so as to simulate the unmanned automobile to run under the target scene in a real road;
testing the performance of the unmanned automobile in the target scene according to the driving behavior of the unmanned automobile in the target scene;
according to the driving behavior of the unmanned automobile in the target scene, testing the performance of the unmanned automobile in the target scene, wherein the testing comprises the following steps:
and if the running behavior of the unmanned vehicle in the target scene is a braking process, judging whether the track line of the obstacle pre-engraved on the road surface of the road in the test field is rolled or not in the process from braking to stopping of the unmanned vehicle.
2. The method according to claim 1, wherein the externally obtaining the output data of each analog sensor in the target scene, acquired by the manually driven data acquisition vehicle in the real road, specifically comprises:
acquiring output data of each analog sensor in the target scene from the data acquisition vehicle; or
And acquiring output data of each analog sensor in the target scene from a cloud server, wherein the output data of each analog sensor in the target scene in the cloud server is acquired and uploaded by the data acquisition vehicle.
3. The method of claim 1, wherein after externally acquiring output data of each analog sensor in a target scene acquired in a real road by a data acquisition vehicle driven by a human, further comprising:
and mapping the output data of each analog sensor in the target scene into a format suitable for the unmanned automobile.
4. The method of claim 1, wherein after externally acquiring output data of each analog sensor in a target scene acquired in a real road by a data acquisition vehicle driven by a human, further comprising:
and modifying the output data of the part of the analog sensor in the target scene to obtain the output data of each analog sensor in different scenes.
5. The method according to claim 1, wherein controlling the unmanned vehicle to travel in a test field according to the output data of each of the simulation sensors to simulate traveling in the target scene in a real road comprises:
acquiring front road condition information under the simulated target scene according to the output data of each simulated sensor under the target scene;
generating a control instruction according to the front road condition information under the target scene;
and controlling the unmanned automobile to run in the test field according to the control instruction so as to simulate the running in the target scene in a real road.
6. The method of claim 5, wherein the front road condition information comprises a category, a relative position of an obstacle in a front road, and a behavior of the obstacle.
7. The method according to claim 5, wherein before externally acquiring the output data of each of the simulated sensors in the target scene acquired in the real road by the data acquisition vehicle driven by a human, the method comprises:
turning off each of the sensors on the unmanned vehicle.
8. The method according to any one of claims 6-7, wherein testing the performance of the unmanned vehicle in the target scenario based on the behavior of the unmanned vehicle in traveling in the target scenario further comprises:
if the unmanned automobile is in the process from braking to stopping, rolling the track line of the obstacle engraved on the road surface of the road in the test field in advance, and determining that the braking performance of the unmanned automobile under the target scene is not ideal; the trajectory line of the obstacle is previously marked on the road surface of the road according to the output data of each of the analog sensors.
9. An unmanned vehicle, comprising:
the system comprises an acquisition module, a data acquisition module and a data acquisition module, wherein the acquisition module is used for acquiring output data of each analog sensor in a target scene, which is acquired in a real road by a manually driven data acquisition vehicle, from the outside in a field test, and each analog sensor is assembled in the data acquisition vehicle according to the assembly position of each sensor in the unmanned vehicle so as to simulate the sensor at the corresponding position on the unmanned vehicle;
the control module is used for controlling the unmanned automobile to run in a test field according to the output data of each analog sensor so as to simulate the unmanned automobile to run in the target scene of a real road;
the test module is used for testing the performance of the unmanned automobile in the target scene according to the driving behavior of the unmanned automobile in the target scene;
the test module is used for judging whether a track line of an obstacle pre-engraved on the road surface of the road in the test field is rolled or not in the process from braking to stopping of the unmanned vehicle if the running behavior of the unmanned vehicle in the target scene is the braking process.
10. The unmanned vehicle of claim 9, wherein the acquisition module is specifically configured to:
acquiring output data of each analog sensor in the target scene from the data acquisition vehicle; or
And acquiring output data of each analog sensor in the target scene from a cloud server, wherein the output data of each analog sensor in the target scene in the cloud server is acquired and uploaded by the data acquisition vehicle.
11. The unmanned vehicle of claim 9, further comprising:
and the mapping module is used for mapping the output data of each analog sensor in the target scene into a format suitable for the unmanned automobile.
12. The unmanned vehicle of claim 9, further comprising:
and the modification module is used for modifying the output data of the analog sensors in the part of the target scene to obtain the output data of the analog sensors in different scenes.
13. The unmanned vehicle of claim 9, wherein the control module is specifically configured to:
acquiring front road condition information under the simulated target scene according to the output data of each simulated sensor under the target scene;
generating a control instruction according to the front road condition information under the target scene;
and controlling the unmanned automobile to run in the test field according to the control instruction so as to simulate the running in the target scene in a real road.
14. The unmanned aerial vehicle of claim 13, wherein the forward road condition information comprises a category, a relative location of an obstacle in a forward road, and a behavior of the obstacle.
15. The unmanned aerial vehicle of claim 9, wherein the control module is further configured to turn off each of the sensors on the unmanned aerial vehicle.
16. The unmanned aerial vehicle of any one of claims 14-15, wherein the testing module is further configured to determine that braking performance of the unmanned aerial vehicle in the target scenario is not ideal if the unmanned aerial vehicle rolls a trajectory line of the obstacle pre-scored on a roadway surface of a road in the test yard during braking to a stop; the trajectory line of the obstacle is previously marked on the road surface of the road according to the output data of each of the analog sensors.
17. A control device of an unmanned automobile, comprising:
one or more processors;
a memory for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-8.
18. A computer-readable medium, on which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1-8.
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