CN111026106A - Unmanned vehicle outdoor driving system - Google Patents
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- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
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- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
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Abstract
The application discloses an unmanned vehicle outdoor driving system which is characterized by comprising a vehicle path generation module, a navigation information acquisition module, a vehicle path tracking module, an auxiliary driving module and a GUI (graphical user interface) visual interface, wherein the unmanned vehicle outdoor driving system is realized by combining track tracking with dynamic target detection; firstly, collecting corresponding GPS sequence information for different paths to generate path information corresponding to the different paths, selecting the corresponding path information according to the path needing to be driven by the unmanned vehicle, tracking the selected path information by combining a transverse control method, and realizing the adaptation of the unmanned vehicle to a dynamic scene by the aid of functions such as visual target detection and the like; the unmanned vehicle positioning system and the unmanned vehicle positioning method improve the positioning accuracy of the unmanned vehicle and the adaptability to the dynamic road environment, and therefore the unmanned driving requirements of the middle and low speed road conditions are met.
Description
Technical Field
The application relates to the technical field of unmanned vehicle driving, in particular to an outdoor driving system of an unmanned vehicle.
Background
Along with the vigorous development of artificial intelligence theory, sensor technology, computer technology and vehicle technology, the unmanned driving theory and technology have been developed considerably. At present, along with the improvement of living standard of people, the number of automobiles is gradually increased, and along with the increase of urban routes, the frequent occurrence of traffic accidents is caused. Furthermore, the complexity of industrial environments and tasks and the diversification of war situations have prompted countries and enterprises to develop unmanned technologies. The unmanned vehicle can comprehensively sense the road surface condition in real time through the vehicle-mounted sensor, so that the intelligent control of the path traffic flow is realized, the occurrence of traffic accidents is avoided, and the travel pressure of urban paths is reduced; and unmanned operation, intelligent production, intelligent weapons and the like are realized. At present, the unmanned technology has certain development, but still can not meet the practical requirement.
Disclosure of Invention
The application aims to provide a medium-low speed outdoor unmanned scheme, and solves the problems that the existing unmanned scheme is low in positioning accuracy, low in dynamic barrier recognition rate and the like.
In order to realize the task, the following technical scheme is adopted in the application:
the utility model provides an unmanned vehicle outdoor driving system, includes vehicle route generation module, navigation information acquisition module, vehicle route tracking module, driver assistance module and GUI visual interface, wherein:
the vehicle path generation module is used for storing path information from a plurality of starting points to a terminal point, the path information is collected by a collection vehicle in advance, and the collection process of the position information is as follows: acquiring a driving route planned by a vehicle from a starting point to a terminal point, and continuously acquiring GPS data in the process of acquiring the driving of the vehicle from the starting point to the terminal point with constant speed, thereby forming a GPS track sequence from the starting point to the terminal point; generating a csv format map by using the GPS track sequence and the path attribute as path information from a starting point to an end point;
the navigation information acquisition module comprises a base station system, a vehicle-mounted combined navigator positioned on the unmanned vehicle, a vehicle-mounted GPS antenna and a vehicle-mounted base station receiving radio station, wherein the base station system comprises a base station GPS antenna, a base station transmitting radio station and a base station positioning receiver; the vehicle-mounted GPS antenna receives a first GPS signal, the base station system receives a second GPS signal through the base station GPS antenna, then the second GPS signal is transmitted to the base station positioning receiver, after the solution is completed on the base station positioning receiver, the solution information is transmitted to the base station transmitting radio station, the base station transmitting radio station utilizes the solution information to issue an RTK message through the radio frequency antenna, after the vehicle-mounted base station receiving radio station receives the RTK message, the RTK message and the first GPS signal are simultaneously input into the vehicle-mounted combined navigator, and more accurate GPS positioning information is obtained through differential comparison and serves as the current GPS positioning information of the unmanned vehicle;
the vehicle path tracking module is used for realizing the tracking of the unmanned vehicle on the selected path information, and comprises the following components: according to the starting point and the end point of the path to be traveled by the unmanned vehicle, traversing the path information stored in the vehicle path generating module, and selecting corresponding path information; the current GPS positioning information of the unmanned vehicle is acquired through a navigation information acquisition module, path tracking is started if the GPS positioning information of the current position is matched with the GPS positioning information of the starting point in the selected path information, the GPS positioning information of the unmanned vehicle is continuously acquired and compared with track points in a GPS track sequence in the selected path information, and a transverse control method is adopted to control the steering wheel of the unmanned vehicle to make an angle, so that the unmanned vehicle can track the selected path information;
the auxiliary driving module comprises an image acquisition module, a target detection module and a display decision module, wherein the image acquisition module acquires road information in front of the unmanned vehicle through a vehicle-mounted camera to acquire a driving road condition image; after acquiring the driving road condition image, the target detection module firstly preprocesses the driving road condition image, identifies the preprocessed driving road condition image by using a target detection algorithm, marks the obstacle through the display decision module when the obstacle is identified, and acquires the position information and the distance information of the obstacle; the display decision module is used for judging whether the obstacle can cause potential safety hazards to the driving of the unmanned vehicle or not by combining the position information and the distance information of the obstacle, the safe driving area of the unmanned vehicle and the control information of the transverse control method, and making decisions of deceleration, acceleration and braking of the unmanned vehicle according to the judgment result;
the GUI visual interface is used for displaying the information of the path selected by the unmanned vehicle, the current GPS positioning information of the unmanned vehicle, and the position information and the distance information of the obstacle detected by the target detection algorithm.
Further, the traversing the path information stored in the vehicle path generating module, selecting the corresponding path information, includes:
recording the current position of the unmanned vehicle as A, taking the current position as a starting point of a path required to be traveled by the unmanned vehicle, and recording the end point of the path required to be traveled by the unmanned vehicle as B; traversing the stored path information, firstly finding the path information with the end point B in all the path information, and then selecting the path information with the starting point of the path information closest to the position A from the path information as the selected path information;
and controlling the unmanned vehicle to travel to the starting point in the selected path information.
Furthermore, after making the deceleration, acceleration and braking decisions of the unmanned vehicle, the display decision module converts the decision information into a control signal, sends the control signal to the bottom layer electric control system of the unmanned vehicle through the communication system of the unmanned vehicle, and controls the executing mechanism of the unmanned vehicle to execute the corresponding control action through the bottom layer electric control system.
Further, the transverse control method adopts a Stanley control algorithm.
Further, the target detection algorithm adopts a YOLO V3 algorithm.
Further, after the target detection module acquires the driving road condition image, the preprocessing process includes image filtering and normalization, so that the detection accuracy is improved.
The application has the following technical characteristics:
according to the method, the combined navigation instrument is adopted to output the differential position signal, centimeter-level high-precision positioning is obtained, and accurate positioning of the unmanned vehicle is realized; meanwhile, the target detection algorithm is adopted to realize the identification of the dynamic barrier, and the adaptability of the unmanned vehicle to the dynamic road environment is greatly improved, so that the unmanned driving requirement of the medium and low speed road conditions is met.
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FIG. 1 is a schematic structural diagram of an unmanned vehicle outdoor driving system;
FIG. 2 is a schematic diagram of the present application;
FIG. 3 is a schematic flow chart of unmanned vehicle path tracking;
fig. 4 is a schematic diagram of the target detection process.
Detailed Description
The application provides an unmanned vehicle outdoor driving system, which comprises a vehicle path generation module, a navigation information acquisition module, a vehicle path tracking module, an auxiliary driving module and a GUI (graphical user interface) visual interface, wherein the vehicle path generation module, the navigation information acquisition module, the vehicle path tracking module, the auxiliary driving module and the GUI visual interface are arranged in the vehicle path generation module; as shown in fig. 2, the application realizes outdoor unmanned driving by combining trajectory tracking with dynamic target detection; the method comprises the steps of firstly collecting corresponding GPS sequence information for different paths to generate path information corresponding to the different paths, selecting the corresponding path information according to the paths needing to be driven by the unmanned vehicle, tracking the selected path information by combining a transverse control method, and realizing the adaptation of the unmanned vehicle to a dynamic scene by the aid of functions such as visual target detection and the like. The following describes each module of the present application in detail.
1. Vehicle route generation module
The vehicle path generation module is used for storing path information from a plurality of starting points to a terminal point, the path information is collected by a collection vehicle in advance, and the collection process of the position information is as follows: acquiring a driving route planned by a vehicle from a starting point to a terminal point, and continuously acquiring GPS data in the process of acquiring the driving of the vehicle from the starting point to the terminal point with constant speed, thereby forming a GPS track sequence from the starting point to the terminal point; a csv-format map is generated as route information from a start point to an end point using the GPS trajectory sequence and the route attributes.
The vehicle route generation module is used as a storage module of the route information and stores the preset route information. The collection vehicle can utilize other manned vehicles to collect path information to form a path information database, and each piece of path information stores a GPS track sequence from a starting point to an end point and other path attributes. The GPS track sequence is composed of a series of GPS data, and each GPS data corresponds to a waypoint on a path; then for a waypoint on the path, its GPS data and path attributes include: waypoint number, latitude, longitude, heading angle, distance from a point, curvature, velocity attribute, GPS status, etc. When the vehicle runs from the starting point to the terminal point, the GPS data of each road point is collected to form a GPS track sequence, and meanwhile, a csv format map can be generated and stored by utilizing the path attribute of the road point and the GPS track sequence to obtain path information corresponding to different starting points and terminal points.
2. Navigation information acquisition module
The navigation information acquisition module comprises a base station system, and a vehicle-mounted combined navigator, a vehicle-mounted GPS antenna and a vehicle-mounted base station receiving radio station which are positioned on the unmanned vehicle. The base station system comprises a base station GPS antenna, a base station transmitting radio station and a base station positioning receiver.
After the unmanned vehicle is started, the current GPS positioning information of the unmanned vehicle is uninterruptedly acquired through the navigation information acquisition module; wherein each process of acquiring GPS positioning information comprises:
the vehicle-mounted GPS antenna receives a first GPS signal, the base station system receives a second GPS signal through the base station GPS antenna, then the second GPS signal is transmitted to the base station positioning receiver, after the solution is completed on the base station positioning receiver, the solution information is transmitted to the base station transmitting radio station, the base station transmitting radio station utilizes the solution information to issue an RTK message through the radio frequency antenna, after the vehicle-mounted base station receiving radio station receives the RTK message, the RTK message and the first GPS signal are simultaneously input into the vehicle-mounted combined navigator, and after differential comparison, more accurate centimeter-level GPS positioning information is obtained and serves as the current GPS positioning information of the unmanned vehicle.
The vehicle-mounted combined navigator analyzes the received data frame into information such as longitude, latitude, course angle, inclination angle, roll angle, GPS state and the like. The GPS state is divided into 4 levels, and when the GPS state is 4 or 3, a GPS signal is available; when the GPS state is 1 or 2, the GPS signal is not good and is not usable due to the fact that buildings are shielded around.
3. Vehicle path tracking module
The vehicle path tracking module is used for tracking the selected path information by the unmanned vehicle, as shown in fig. 3, and includes: and traversing the path information stored in the vehicle path generating module according to the starting point and the end point of the path to be traveled by the unmanned vehicle, and selecting the corresponding path information. That is, after the unmanned vehicle is started, the current position of the unmanned vehicle is set as a starting point a, and the position where the unmanned vehicle is expected to reach is set as an ending point B. Firstly, stored path information needs to be inquired, and path information with a starting point and an end point A and B in the path information is found, and the specific process is as follows:
recording the current position of the unmanned vehicle as A, taking the current position as a starting point of a path required to be traveled by the unmanned vehicle, and recording the end point of the path required to be traveled by the unmanned vehicle as B; and traversing the stored path information, firstly finding a plurality of pieces of path information with the end points of B in all the path information, and then selecting the path information with the starting point of the path information closest to the position A from the path information as the selected path information. The selection method is adopted because the current position of the unmanned vehicle may not be strictly matched with the starting position of any one piece of route information in the stored route information, so that the route information with the closest starting position is selected as the selected route information, and the unmanned vehicle can be tracked according to the selected route information only by controlling to travel to the starting point in the selected route information, and the method comprises the following steps:
the current GPS positioning information of the unmanned vehicle is obtained through the navigation information acquisition module, if the GPS positioning information of the current position is matched with the GPS positioning information of the starting point in the selected path information (namely the current unmanned vehicle drives to the starting point position in the selected path information), path tracking is started, the GPS positioning information of the unmanned vehicle is continuously obtained and compared with the track point in the GPS track sequence in the selected path information, and the steering wheel of the unmanned vehicle is controlled to make an angle by adopting a transverse control method, so that the unmanned vehicle can track the selected path information. Optionally, in an embodiment of the present application, the lateral control method employs a Stanley control algorithm; in the tracking process, the assistant driving module can be started to carry out assistant decision of target detection.
4. Driving assistance module
The driving assistance module comprises an image acquisition module, a target detection module and a display decision module, as shown in fig. 4, wherein the image acquisition module acquires road information in front of the unmanned vehicle through a vehicle-mounted camera to acquire a driving road condition image; optionally, the vehicle-mounted camera is arranged in front of the cab, and in order to ensure the real-time performance and the integrity of image information, the camera adopts a 720P/30FPS acquisition mode. After the target detection module acquires the driving road condition image, preprocessing the driving road condition image, including image filtering, normalization and the like, is performed on the driving road condition image, so that the detection accuracy is improved, and the influence of noise and illumination factors in the acquisition and transmission processes is reduced.
The method comprises the steps that a preprocessed driving road condition image is recognized through a target detection algorithm, when an obstacle is recognized, the obstacle is marked through a display decision module, specifically, the position of the obstacle can be framed out through a target frame, and the position information and the distance information of the obstacle are obtained; and the display decision module is used for judging whether the barrier can cause potential safety hazards to the driving of the unmanned vehicle or not by combining the position information and the distance information of the barrier, the safety driving area of the unmanned vehicle and the control information of the Stanley control algorithm, and making the decision of deceleration, acceleration and braking of the unmanned vehicle according to the judgment result. For example, a certain obstacle is detected to be 20m away from the unmanned vehicle, the position of the obstacle is 30 degrees to the right in front of the unmanned vehicle, if the current road is straight, according to the current speed, the safety region where the unmanned vehicle runs is within +/-5 degrees from the left and right in front of the unmanned vehicle, and the unmanned vehicle does not need to turn according to the control information, so that the obstacle does not cause potential safety hazard to the unmanned vehicle in running and does not need to slow down; and if the influence on the driving of the unmanned vehicle is possible, the judgment result is deceleration, and then the steering wheel is controlled to make an angle through the Stanley control algorithm, and the unmanned vehicle is accelerated after avoiding the obstacle.
The decision information is converted into a control signal, the control signal is sent to a bottom layer electric control system of the unmanned vehicle through a communication system of the unmanned vehicle, and an executing mechanism (such as a brake pedal, an accelerator pedal and the like) of the unmanned vehicle is controlled by the bottom layer electric control system to execute corresponding control actions such as deceleration, acceleration, braking and the like.
GUI visual interface
The GUI visual interface is used for displaying the information of the path selected by the unmanned vehicle, the current GPS positioning information of the unmanned vehicle, the position information and the distance information of the obstacle detected by the target detection algorithm, namely the image information can be displayed through the GUI visual interface, so that the current driving condition of the unmanned vehicle can be intuitively known.
The above-described embodiments are merely examples illustrating the present system and are not to be construed as limiting the present patent. Those skilled in the art can now make numerous uses of the foregoing descriptions that will provide many alternative embodiments for practicing the invention. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the claims of the present invention.
Claims (6)
1. The unmanned vehicle outdoor driving system is characterized by comprising a vehicle path generation module, a navigation information acquisition module, a vehicle path tracking module, an auxiliary driving module and a GUI (graphical user interface) visual interface, wherein:
the vehicle path generation module is used for storing path information from a plurality of starting points to a terminal point, the path information is collected by a collection vehicle in advance, and the collection process of the position information is as follows: acquiring a driving route planned by a vehicle from a starting point to a terminal point, and continuously acquiring GPS data in the process of acquiring the driving of the vehicle from the starting point to the terminal point with constant speed, thereby forming a GPS track sequence from the starting point to the terminal point; generating a csv format map by using the GPS track sequence and the path attribute as path information from a starting point to an end point;
the navigation information acquisition module comprises a base station system, a vehicle-mounted combined navigator positioned on the unmanned vehicle, a vehicle-mounted GPS antenna and a vehicle-mounted base station receiving radio station, wherein the base station system comprises a base station GPS antenna, a base station transmitting radio station and a base station positioning receiver; the vehicle-mounted GPS antenna receives a first GPS signal, the base station system receives a second GPS signal through the base station GPS antenna, then the second GPS signal is transmitted to the base station positioning receiver, after the solution is completed on the base station positioning receiver, the solution information is transmitted to the base station transmitting radio station, the base station transmitting radio station utilizes the solution information to issue an RTK message through the radio frequency antenna, after the vehicle-mounted base station receiving radio station receives the RTK message, the RTK message and the first GPS signal are simultaneously input into the vehicle-mounted combined navigator, and more accurate GPS positioning information is obtained through differential comparison and serves as the current GPS positioning information of the unmanned vehicle;
the vehicle path tracking module is used for realizing the tracking of the unmanned vehicle on the selected path information, and comprises the following components: according to the starting point and the end point of the path to be traveled by the unmanned vehicle, traversing the path information stored in the vehicle path generating module, and selecting corresponding path information; the current GPS positioning information of the unmanned vehicle is acquired through a navigation information acquisition module, path tracking is started if the GPS positioning information of the current position is matched with the GPS positioning information of the starting point in the selected path information, the GPS positioning information of the unmanned vehicle is continuously acquired and compared with track points in a GPS track sequence in the selected path information, and a transverse control method is adopted to control the steering wheel of the unmanned vehicle to make an angle, so that the unmanned vehicle can track the selected path information;
the auxiliary driving module comprises an image acquisition module, a target detection module and a display decision module, wherein the image acquisition module acquires road information in front of the unmanned vehicle through a vehicle-mounted camera to acquire a driving road condition image; after acquiring the driving road condition image, the target detection module firstly preprocesses the driving road condition image, identifies the preprocessed driving road condition image by using a target detection algorithm, marks the obstacle through the display decision module when the obstacle is identified, and acquires the position information and the distance information of the obstacle; the display decision module is used for judging whether the obstacle can cause potential safety hazards to the driving of the unmanned vehicle or not by combining the position information and the distance information of the obstacle, the safe driving area of the unmanned vehicle and the control information of the transverse control method, and making decisions of deceleration, acceleration and braking of the unmanned vehicle according to the judgment result;
the GUI visual interface is used for displaying the information of the path selected by the unmanned vehicle, the current GPS positioning information of the unmanned vehicle, and the position information and the distance information of the obstacle detected by the target detection algorithm.
2. The unmanned vehicle driver's cabin exterior system of claim 1, wherein traversing the path information stored in the vehicle path generation module, selecting corresponding path information, comprises:
recording the current position of the unmanned vehicle as A, taking the current position as a starting point of a path required to be traveled by the unmanned vehicle, and recording the end point of the path required to be traveled by the unmanned vehicle as B; traversing the stored path information, firstly finding the path information with the end point B in all the path information, and then selecting the path information with the starting point of the path information closest to the position A from the path information as the selected path information;
and controlling the unmanned vehicle to travel to the starting point in the selected path information.
3. The unmanned vehicle outdoor driving system of claim 1, wherein the display decision module converts the decision information into a control signal after making the unmanned vehicle deceleration, acceleration and braking decisions, and sends the control signal to the unmanned vehicle bottom layer electric control system through the unmanned vehicle communication system, and the bottom layer electric control system controls an execution mechanism of the unmanned vehicle to execute corresponding control actions.
4. The unmanned vehicle outboard steering system of claim 1, wherein said lateral control method employs a Stanley control algorithm.
5. The unmanned vehicle outside driving system of claim 1, wherein the target detection algorithm employs the YOLOV3 algorithm.
6. The unmanned vehicle outdoor driving system of claim 1, wherein after the target detection module obtains the driving road condition image, the preprocessing process includes image filtering and normalization to improve detection accuracy.
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| PCT/CN2020/116098 WO2021088528A1 (en) | 2019-11-07 | 2020-09-18 | Outdoor driving system for unmanned vehicle |
| JP2020552241A JP2022502722A (en) | 2019-11-07 | 2020-09-18 | Outdoor driving system for autonomous vehicles |
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Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102621566A (en) * | 2012-02-20 | 2012-08-01 | 刘瑜 | Accurate positioning system for outdoor mobile robot |
| CN106548135A (en) * | 2016-10-17 | 2017-03-29 | 北海益生源农贸有限责任公司 | A kind of road barrier detection method |
| CN107894771A (en) * | 2017-12-01 | 2018-04-10 | 浙江力邦合信智能制动系统股份有限公司 | A kind of dolly Omni-mobile control system and method |
| CN108596058A (en) * | 2018-04-11 | 2018-09-28 | 西安电子科技大学 | Running disorder object distance measuring method based on computer vision |
| CN108594821A (en) * | 2018-05-08 | 2018-09-28 | 陕西同力重工股份有限公司 | Unmanned mine car positioning and autonomous tracing in intelligent vehicle |
| CN108711344A (en) * | 2018-08-01 | 2018-10-26 | 南京精智新信息科技有限公司 | Drive training Driving Test examination evaluation system |
| CN109101017A (en) * | 2018-07-27 | 2018-12-28 | 江苏盛海智能科技有限公司 | A kind of unmanned vehicle tracks route planning method and terminal |
| CN109814550A (en) * | 2018-12-29 | 2019-05-28 | 北京中云智车科技有限公司 | It is a kind of for closing the unmanned transport vehicle of garden |
| CN109895100A (en) * | 2019-03-29 | 2019-06-18 | 深兰科技（上海）有限公司 | A kind of generation method of navigation map, device and robot |
| CN109945882A (en) * | 2019-03-27 | 2019-06-28 | 上海交通大学 | A kind of automatic driving vehicle path planning and control system and method |
Family Cites Families (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN200979501Y (en) * | 2006-04-19 | 2007-11-21 | 吉林大学 | A complete auto moving state detecting system |
| CN105741595B (en) * | 2016-04-27 | 2018-02-27 | 常州加美科技有限公司 | A kind of automatic driving vehicle navigation travelling-crane method based on cloud database |
| WO2018008627A1 (en) * | 2016-07-05 | 2018-01-11 | 国立研究開発法人宇宙航空研究開発機構 | Satellite positioning system and satellite positioning method |
| US20180194344A1 (en) * | 2016-07-29 | 2018-07-12 | Faraday&Future Inc. | System and method for autonomous vehicle navigation |
| US10089872B1 (en) * | 2017-05-11 | 2018-10-02 | Here Global B.V. | Vehicle communication system for vehicle boarding area |
| CN109765887B (en) * | 2018-12-21 | 2020-08-14 | 杭州翱朝科技有限公司 | Automatic driving control method |
| CN111026106A (en) * | 2019-11-07 | 2020-04-17 | 广东工业大学 | Unmanned vehicle outdoor driving system |
-
2019
- 2019-11-07 CN CN201911079884.3A patent/CN111026106A/en active Pending
-
2020
- 2020-09-18 JP JP2020552241A patent/JP2022502722A/en active Pending
- 2020-09-18 WO PCT/CN2020/116098 patent/WO2021088528A1/en active Application Filing
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102621566A (en) * | 2012-02-20 | 2012-08-01 | 刘瑜 | Accurate positioning system for outdoor mobile robot |
| CN106548135A (en) * | 2016-10-17 | 2017-03-29 | 北海益生源农贸有限责任公司 | A kind of road barrier detection method |
| CN107894771A (en) * | 2017-12-01 | 2018-04-10 | 浙江力邦合信智能制动系统股份有限公司 | A kind of dolly Omni-mobile control system and method |
| CN108596058A (en) * | 2018-04-11 | 2018-09-28 | 西安电子科技大学 | Running disorder object distance measuring method based on computer vision |
| CN108594821A (en) * | 2018-05-08 | 2018-09-28 | 陕西同力重工股份有限公司 | Unmanned mine car positioning and autonomous tracing in intelligent vehicle |
| CN109101017A (en) * | 2018-07-27 | 2018-12-28 | 江苏盛海智能科技有限公司 | A kind of unmanned vehicle tracks route planning method and terminal |
| CN108711344A (en) * | 2018-08-01 | 2018-10-26 | 南京精智新信息科技有限公司 | Drive training Driving Test examination evaluation system |
| CN109814550A (en) * | 2018-12-29 | 2019-05-28 | 北京中云智车科技有限公司 | It is a kind of for closing the unmanned transport vehicle of garden |
| CN109945882A (en) * | 2019-03-27 | 2019-06-28 | 上海交通大学 | A kind of automatic driving vehicle path planning and control system and method |
| CN109895100A (en) * | 2019-03-29 | 2019-06-18 | 深兰科技（上海）有限公司 | A kind of generation method of navigation map, device and robot |
Non-Patent Citations (2)
| Title |
|---|
| 徐红宾: ""基于单目视觉的无人车障碍物识别技术研究"", 《中国优秀硕士学位论文数据库》 * |
| 林俊杰: ""基于FPGA立体视觉的无人车障碍检测算法研究与实现"", 《中国优秀硕士学位论文数据库》 * |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2021088528A1 (en) * | 2019-11-07 | 2021-05-14 | 广东工业大学 | Outdoor driving system for unmanned vehicle |
| CN111459172A (en) * | 2020-05-20 | 2020-07-28 | 中国北方车辆研究所 | Autonomous navigation system of boundary security unmanned patrol car |
| CN111459172B (en) * | 2020-05-20 | 2023-10-31 | 中国北方车辆研究所 | Surrounding security unmanned patrol car autonomous navigation system |
| CN114112421A (en) * | 2021-09-30 | 2022-03-01 | 东风汽车集团股份有限公司 | Automatic driving test method and device, electronic equipment and storage medium |
| CN114112421B (en) * | 2021-09-30 | 2023-06-20 | 东风汽车集团股份有限公司 | Automatic driving test method and device, electronic equipment and storage medium |
| CN114379584A (en) * | 2021-12-17 | 2022-04-22 | 阿波罗智联(北京)科技有限公司 | Vehicle control method, device, vehicle, equipment and storage medium |
| CN114379584B (en) * | 2021-12-17 | 2023-12-22 | 阿波罗智联(北京)科技有限公司 | Vehicle control method, device, vehicle, equipment and storage medium |
| CN114489056A (en) * | 2021-12-31 | 2022-05-13 | 深圳华侨城卡乐技术有限公司 | Trackless vehicle route control method, device, system and storage medium |
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| JP2022502722A (en) | 2022-01-11 |
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