CN110356339B - Lane change blind area monitoring method and system and vehicle - Google Patents
Lane change blind area monitoring method and system and vehicle Download PDFInfo
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- CN110356339B CN110356339B CN201810250023.6A CN201810250023A CN110356339B CN 110356339 B CN110356339 B CN 110356339B CN 201810250023 A CN201810250023 A CN 201810250023A CN 110356339 B CN110356339 B CN 110356339B
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- B60R16/00—Electric or fluid circuits specially adapted for vehicles and not otherwise provided for; Arrangement of elements of electric or fluid circuits specially adapted for vehicles and not otherwise provided for
- B60R16/02—Electric or fluid circuits specially adapted for vehicles and not otherwise provided for; Arrangement of elements of electric or fluid circuits specially adapted for vehicles and not otherwise provided for electric constitutive elements
Abstract
The invention provides a lane change blind area monitoring method, which comprises the following steps: collecting position information of a vehicle and obstacle information of the side and the rear of the vehicle; loading a corresponding high-precision map data packet according to the acquired position information of the vehicle, and constructing a three-dimensional static scene model according to the loaded high-precision map data packet; marking the acquired position information of the vehicle and the obstacle information at the side and rear of the vehicle in a three-dimensional static scene model; and monitoring the marked three-dimensional static scene model. A three-dimensional static scene model is constructed through a high-precision map data packet, vehicle position information and obstacle information around the vehicle are fused, and the risk detection and prediction effects of lane-changing blind areas are remarkably improved. The invention also provides a lane change blind area monitoring system and a vehicle.
Description
Technical Field
The invention relates to the technical field of vehicle auxiliary driving, in particular to a lane change blind area monitoring method and system and a vehicle.
Background
In the prior art, a lane-changing blind area monitoring system mostly adopts a millimeter wave radar and/or a camera, the millimeter wave radar cannot identify information such as lane lines and road traffic signs, and the camera is easy to cause detection errors under the condition of poor illumination intensity or strong light reflection.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a lane change blind area monitoring method, aiming at solving the defects in the prior art to a certain extent.
In order to achieve the above object, an embodiment of the present invention provides a lane change blind area monitoring method, including the following steps:
collecting position information of a vehicle and obstacle information on the side and the rear of the vehicle;
loading a corresponding high-precision map data packet according to the acquired position information of the vehicle, and constructing a three-dimensional static scene model according to the loaded high-precision map data packet;
marking the collected position information of the vehicle and the obstacle information on the lateral and rear sides of the vehicle in the three-dimensional static scene model;
and monitoring the lane changing blind area according to the marked three-dimensional static scene model.
According to the lane change blind area monitoring method provided by the embodiment of the invention, the data of the high-precision map data packet is utilized, the three-dimensional static scene model is constructed through the data of the high-precision map data packet, and the vehicle position information and the obstacle information around the vehicle are marked in the three-dimensional static scene model, so that the three-dimensional static scene model containing the static road information and the dynamic obstacle information is generated in a fusion manner, the lane change risk of the vehicle is conveniently judged and predicted, the risk detection and prediction effects of the lane change blind area are obviously improved, and the detection error easily caused by a camera under the condition of poor illumination intensity or strong light reflection is avoided.
The obstacle information of the vehicle side rear part comprises an obstacle type or an obstacle type, an obstacle distance or an obstacle type, an obstacle speed or an obstacle type, an obstacle distance and an obstacle speed.
The lane change blind area monitoring method further comprises the step of predicting the distance and/or the speed of the next state of the obstacle.
Determining an alarm grade according to the predicted distance and/or speed of the next state of the obstacle, and carrying out alarm reminding on a driver according to the alarm grade; wherein, the first and the second end of the pipe are connected with each other,
the closer the obstacle is to the next state and/or the greater the speed, the higher the warning level.
When it is monitored that an obstacle enters an alarm area, and the type of the obstacle threatens lane changing of a vehicle, an alarm is given to a driver, and the alarm area is a certain distance range defined by the lateral rear side of the vehicle.
When the warning level is highest, the lane change operation of the driver is corrected and/or prevented.
The embodiment of the invention also provides a lane-changing blind area monitoring system, which comprises a positioning module, a blind area monitoring control unit and at least one blind area monitoring sensing module;
the positioning module is used for acquiring the position information of the vehicle; the blind area monitoring and sensing module is used for acquiring barrier information of the rear and side of the vehicle;
The blind area monitoring and controlling unit is used for loading a corresponding high-precision map data packet according to the position information of the vehicle and constructing a three-dimensional static scene model according to the loaded high-precision map data packet;
the blind area monitoring and controlling unit is further used for marking the position information of the vehicle and the obstacle information of the side rear part of the vehicle in the three-dimensional static scene model; and monitoring the marked three-dimensional static scene model.
The lane-changing blind area monitoring system provided by the embodiment of the invention is based on the road information of the high-precision map data packet, constructs a three-dimensional static scene model, marks the position information of the vehicle and the acquired barrier information in the three-dimensional static scene model, and further monitors the marked three-dimensional static scene model. The existing data information is utilized, the camera is not required to be used for on-site acquisition, the accuracy is higher, and the detection error easily caused by poor illumination intensity or strong light reflection of the camera in the prior art is effectively avoided.
The positioning module comprises a global navigation satellite positioning system or a global navigation satellite positioning system and an inertia measurement unit.
The lane changing blind area monitoring system further comprises an alarm unit, and the alarm unit is used for alarming and reminding a driver.
The embodiment of the invention also provides a vehicle which comprises the lane change blind area monitoring system.
The vehicle provided by the embodiment of the invention is characterized in that a three-dimensional static scene model is constructed based on the road information of the high-precision map data packet, the position information of the vehicle and the acquired obstacle information are marked in the three-dimensional static scene model, and the marked three-dimensional static scene model is monitored. Because the existing data information is utilized, the field acquisition of a camera is not needed, the accuracy is higher, and the detection error easily caused by the camera under the condition of poor illumination intensity or strong light reflection in the prior art is effectively avoided.
Drawings
FIG. 1 is a flow chart of a lane change blind area monitoring method according to an embodiment of the present invention;
fig. 2 is a block diagram of a lane change blind area monitoring system according to an embodiment of the present invention:
fig. 3 is a block diagram of a vehicle according to an embodiment of the invention.
Detailed Description
Reference will now be made in detail to the embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like reference numerals refer to the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are illustrative and intended to explain the present invention and should not be construed as limiting the present invention.
In the lane change blind area monitoring scheme in the prior art, most of the lane change blind area monitoring schemes adopt millimeter wave radars or ultrasonic radar detectors, and the lane change blind area monitoring schemes are characterized in that the barrier recognition effect is good, but lane lines and road traffic signs cannot be recognized. The lane-changing blind area monitoring scheme of the camera is adopted, so that the recognition effect is good under the condition of sufficient light, but the recognition effect is poor under the condition of insufficient light; if the ambient light is too strong, false recognition is easily caused due to reflection of other objects, and the performance of the lane-changing blind area monitoring system is obviously reduced.
Fig. 1 shows a flow chart of a lane change blind area monitoring method according to an embodiment of the present invention. The lane change blind area monitoring method comprises the following steps,
collecting position information of a vehicle and obstacle information on the side and the rear of the vehicle;
loading a corresponding high-precision map data packet according to the acquired position information of the vehicle, and constructing a three-dimensional static scene model according to the loaded high-precision map data packet;
marking the collected position information of the vehicle and the obstacle information on the lateral and rear sides of the vehicle in the three-dimensional static scene model;
and monitoring the lane changing blind area according to the marked three-dimensional static scene model.
In the embodiment of the invention, the high-precision map data packet can be stored locally or on a cloud server. When lane change blind areas need to be monitored, the corresponding high-precision map data packet is selected to be loaded from the local or downloaded from the cloud server according to the position information of the vehicle, the high-precision map data packet is analyzed or decoded, and the analyzed or decoded high-precision map data packet is used for building a three-dimensional scene model. The corresponding high-precision map data packet refers to a map data packet of the position of the vehicle, so that the phenomenon that the loaded data packet is too large and exceeds the requirement to cause redundancy or great waste of computing resources is avoided. The high-precision map is a map which has higher resolution than that of a common map and contains road traffic sign lines and other road traffic signals. In such a map, facility data such as lane lines, road traffic signs, isolation zones, and guard rails exist as a priori knowledge. Therefore, the camera is not needed to detect facilities such as lane lines, road traffic signs, isolation zones and guardrails in real time, and the problem that the performance of a lane changing blind area monitoring system adopting the camera scheme is sharply reduced at night or under the condition of weak light is effectively solved.
In the constructed three-dimensional static scene model, the collected vehicle position information and the obstacle information at the side and the rear of the vehicle are marked. Thus, a three-dimensional scene model including dynamic vehicle position information, obstacle information, and static lane lines, road traffic signs, and the like is formed in a fusion manner. The three-dimensional scene model is used to monitor and determine lane change risks of the vehicle.
According to the lane-changing blind area monitoring method, a three-dimensional static scene model is built by adopting a high-precision map with coordinate precision reaching centimeter level, the position of the vehicle in the three-dimensional static scene model is obtained by utilizing a high-precision positioning device, and then the acquired vehicle side and rear obstacle information is marked in the three-dimensional static scene model, so that a three-dimensional scene model with a static scene and a dynamic obstacle target fused is formed finally. And the lane change risk of the vehicle can be effectively monitored and judged conveniently in the next state. The judgment accuracy is high and is not influenced by other factors such as light rays and the like.
In the embodiment of the invention, the acquired obstacle information and the positioning information of the vehicle are cached in the respective FIFO data areas. The FIFO data area is a First Input First Output First in First out data area. Therefore, the storage and reading of the vehicle positioning information and the vehicle side and rear obstacle information are realized.
In the embodiment of the invention, the obstacle information on the side rear of the vehicle comprises the obstacle information on the side rear of the vehicle in the lane where the vehicle is located and/or the lane to be changed of the vehicle.
Through the barrier information of gathering vehicle side rear, effectively reduced the information redundancy, avoid the existence of too much noise data.
Specifically, in the embodiment of the present invention, vehicle lateral and rear information of a lane where the host vehicle is located and/or a lane-to-lane-change-ready lane of the host vehicle is collected. For example, the driver prepares to change the lane to the left, acquires the lane change information of the vehicle through the turn signal of the vehicle, and starts to acquire the obstacle information of the lane where the driver is located and the lane on the left. If the vehicle is ready to change lanes to the right side, at the moment, a steering signal of the vehicle is obtained through a steering lamp signal of the vehicle, and the obstacle information of the lane where the vehicle is located and the lane on the right side is collected. It should be noted that the left lane and the right lane include an adjacent left lane or an adjacent right lane and/or a plurality of adjacent left lanes and/or right lanes. For example, the existing road is a four-lane one-way lane, and the left lane is the first lane when the vehicle is in the second lane in the driving direction; the right lane may be a third lane, or may be a third and fourth lane.
The obstacle information of the vehicle side rear part comprises an obstacle type or an obstacle type, an obstacle distance or an obstacle type, an obstacle speed or an obstacle type, an obstacle distance and an obstacle speed.
Specifically, the obstacle speed may be the speed of the obstacle or the speed of the obstacle relative to the host vehicle. Obstacles include vehicles in motion, pedestrians, animals, and other solids, etc. Therefore, the comprehensive monitoring of the obstacles is realized, complete data are provided for judging the lane change risk of the vehicle, and the prediction is more accurate.
The lane change blind area monitoring method further comprises the step of tracking and monitoring obstacles behind and beside the vehicle.
The lane change blind area monitoring method further comprises the step of predicting the distance and/or the speed of the next state of the obstacle.
Specifically, the screening is to screen the detected obstacles and only reserve the obstacles on the lane where the vehicle is located and on the vehicle side and behind the lane where the vehicle is ready to change. And tracking and monitoring the screened obstacles and analyzing the obstacles so as to obtain the prediction results of the distance and the speed of the next state of the obstacles. Therefore, the monitoring range of the obstacles is further reduced, and the monitoring is more accurate.
Specifically, in the embodiment of the present invention, a kalman filter is used to analyze and predict the distance and/or the speed of the obstacle. Specifically, the distance and the speed of the current obstacle are input into the kalman filter algorithm, so that the distance and the speed of the next state of the obstacle can be derived, and the analysis and prediction of the distance and/or the speed of the next state of the obstacle can be realized. In order to improve the prediction accuracy, the distance and the speed of the obstacle collected at the next moment can be fed back, compared with the predicted distance and speed, and the correlation coefficient is corrected, so that the accuracy of analysis and prediction of the algorithm is improved.
The method comprises the steps of predicting the distance and/or the speed of the next state of the obstacle, determining the alarm grade according to the predicted distance and/or the predicted speed of the next state of the obstacle, and carrying out alarm reminding on a driver according to the alarm grade; in particular, the method comprises the following steps of,
different alarm levels are set according to different ranges of the distance and/or the speed, and the smaller the range of the distance and/or the speed is, the higher the alarm level is. The closer the distance between the obstacle and the vehicle is, or the faster the obstacle is, the higher the risk of collision when the vehicle changes lane is, and at this time, the higher the alarm level is.
For example, a dynamic target passes through an early warning area of the vehicle at a certain relative speed v, N warning reminding levels are divided according to the value of v, and each warning level corresponds to different forms of sound and light warning. Therefore, the all-dimensional monitoring of the barrier is realized, the multi-level alarm is carried out on the driver, and the lane changing blind area detection scheme is more perfect.
When it is monitored that the barrier enters an alarm area and the type of the barrier threatens lane changing of the vehicle, an alarm is given to a driver, and the alarm area defines a certain distance range for the lateral rear of the vehicle.
Specifically, an alarm area is defined within a certain distance range from the side rear of the vehicle, and when it is monitored that an obstacle enters the alarm area and the type of the obstacle threatens lane change of the vehicle, an alarm is given to a driver.
The division of the warning area may be determined in dependence on the risk of collision of the obstacle with the vehicle.
Therefore, the detection range is further reduced, and meanwhile, the blind area monitoring is more accurate.
Preferably, the warning area may be classified into different levels according to the distance between the warning area and the vehicle, and the closer the distance is, the higher the risk of collision with the driver is, and in this case, the higher the warning level is.
Therefore, the alarm grade is judged directly through two parameters of the type of the obstacle and the entrance of the obstacle into the alarm area without predicting the speed of the obstacle, and the judgment mode is simple.
Preferably, in the embodiment of the present invention, when the warning level reaches the maximum, the lane change operation of the driver is directly corrected or prevented.
When the alarm level reaches the highest level, the lane change risk of the driver also reaches the maximum, and at the moment, the lane change is forced, so that danger is easy to occur. At this time, the lane change operation of the driver is corrected or directly prevented, so that the danger of lane change of the driver can be effectively avoided.
The invention also provides a lane-changing blind area monitoring system, which comprises a positioning module, a blind area monitoring control unit and at least one blind area monitoring sensing module; and further includes high-precision map data packet, specifically,
the positioning module is used for acquiring the position information of the vehicle; the blind area monitoring and sensing module is used for acquiring barrier information of the side rear part of the vehicle;
the blind area monitoring control unit is used for loading a corresponding high-precision map data packet according to the position information of the vehicle and constructing a three-dimensional static scene model according to the loaded high-precision map data packet;
The blind area monitoring control unit is also used for marking the position information of the vehicle and the obstacle information of the side rear part of the vehicle in the three-dimensional static scene model;
the blind area monitoring control unit is also used for monitoring the marked three-dimensional static scene model.
Wherein, at least one blind area monitoring and sensing module can be the sensing module who constitutes jointly by left rear side blind area radar and right rear side blind area radar. The left rear side blind area radar and the right rear side blind area radar form a CAN subnet by using CAN interfaces, and finally the CAN interface on one of the blind area radars (which CAN be the left rear side blind area radar or the rear right side blind area radar) is connected to a 'blind area monitoring control unit'; the data of the high-precision map is stored in a hard disk after being encrypted, and the hard disk is connected to a blind area monitoring control unit through an SATA interface; the global navigation satellite positioning system and/or the inertial measurement unit realize high-precision positioning, and the positioning data is transmitted to the blind area monitoring control unit through a serial port; a wireless data module is connected to the blind area monitoring and controlling unit through an Ethernet interface, and meanwhile, the module carries out data interaction with a server at the cloud end in a wireless connection mode.
The blind area monitoring control unit is a core device for realizing the method for improving the performance of the lane change blind area monitoring system. The construction of the 3-dimensional scene model, the fusion of the dynamic target detection results, the corresponding software system, the corresponding software process and the like are completed in the blind area monitoring control unit. The blind area monitoring control unit is connected with a CAN network of the whole vehicle through a CAN interface and CAN send different types of control instructions to the CAN network of the whole vehicle according to the evaluation of a software system on the risk coefficient of implementing the lane change operation.
In the embodiment of the invention, the position information of the vehicle and the obstacle information at the side and the rear of the vehicle, which are transmitted through the CAN interface, are received in an intermittent mode and are cached in the respective FIFO data areas. And the blind area monitoring control unit reads the position information of the vehicle and the obstacle information of the side rear part of the vehicle from the FIFO data area, analyzes the information and loads a corresponding high-precision map data packet from hardware or a cloud server according to the positioning information. And after the blind area monitoring control unit loads the high-precision map data packet, decrypting the high-precision map data packet and constructing a three-dimensional static scene model, and marking the position information of the vehicle and the obstacle information of the lateral rear part of the vehicle in the 3-dimensional static scene model, so that a 3-dimensional scene model combining a static scene and a dynamic target is generated by fusion. The high-precision map data packet comprises data information of lane lines, road traffic signs, isolation zones and guardrails.
The positioning module comprises a global navigation satellite positioning system and/or an inertial measurement unit.
Specifically, the positioning module refers to a global navigation satellite positioning system, including GPS in the united states, GLANESS in russia, galileo in the european union, beidou in china, and the like. The positioning module can also comprise an inertial measurement unit, and the combination of the global navigation satellite positioning system and the inertial measurement unit can realize advantage complementation so as to realize all-weather high-precision positioning.
The high-precision map data packet includes at least one of a lane line, a road traffic sign, a median, and a guardrail.
Specifically, the high-precision map is a map which has higher resolution than a common map and contains road traffic sign lines and other road traffic signals. In such a map, facility data such as lane lines, road traffic signs, isolation zones, and guard rails exist as a priori knowledge.
In the embodiment of the invention, the map data updating system further comprises a wireless data module used for updating data of the high-precision map data packet, and the wireless data module comprises at least one of a 3G data module, a 4G data module, a 5G data module and a wireless network module.
In the embodiment of the invention, the software program CAN be used for realizing online updating by sending a data packet to the local wireless data module through the cloud server, and CAN also be used for realizing online updating by connecting the upper computer software with the CAN network of the vehicle body. Compared with the traditional mode of simply depending on a CAN network to update the software program on line, the method provided by the invention is more flexible and diversified. The method is very beneficial to the development and verification process of the product in the early stage and the maintenance of the product in the later stage.
The lane change blind area monitoring system further comprises an alarm unit, and the alarm unit is used for giving an alarm to a driver in the forms of sound, light, vibration and the like.
Specifically, the blind area monitoring and controlling unit is used for monitoring and analyzing lane change risks of the vehicle according to a three-dimensional static scene model marked with position information of the vehicle and obstacle information of the side rear part of the vehicle, and controlling the alarming unit to alarm and remind a driver of information such as sound, light and vibration according to an analysis result. When the alarm level is the highest, lane changing operation of a driver can be corrected or organized, and danger is effectively avoided.
The embodiment of the invention further provides a vehicle which comprises the lane changing blind area monitoring system in any technical scheme.
The vehicle provided by the invention can obviously improve the blind area monitoring accuracy rate when the vehicle changes lanes due to the lane changing blind area monitoring system.
In the present invention, unless otherwise explicitly stated or limited, the terms "connected" and the like are to be understood broadly, and may be, for example, fixedly connected, detachably connected, or integrated; can be mechanically or electrically connected; they may be directly connected or indirectly connected through intervening media, or may be connected through the use of two elements or the interaction of two elements. The specific meanings of the above terms in the present invention can be understood according to specific situations by those of ordinary skill in the art.
Any process or method descriptions in flow charts may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing steps of a custom logic function or process, and alternate implementations are included within the scope of the preferred embodiment of the present invention in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and those skilled in the art may make variations, modifications, substitutions and alterations to the above embodiment within the scope of the present invention.
Claims (10)
1. A lane change blind area monitoring method is characterized by comprising the following steps:
collecting position information of a vehicle and obstacle information of the side and the rear of the vehicle;
loading a corresponding high-precision map data packet according to the acquired position information of the vehicle, and constructing a three-dimensional static scene model according to the loaded high-precision map data packet;
marking the collected position information of the vehicle and the information of the obstacles behind and beside the vehicle in the three-dimensional static scene model;
And monitoring the lane changing blind area according to the marked three-dimensional static scene model.
2. The lane-changing blind area monitoring method according to claim 1, wherein the obstacle information of the vehicle rear-and-side direction includes an obstacle type or an obstacle type, an obstacle distance or an obstacle type, an obstacle speed or an obstacle type, an obstacle distance, an obstacle speed.
3. The lane-change blind area monitoring method according to claim 1, further comprising predicting a distance and/or a speed of a next state of the obstacle.
4. The lane-changing blind area monitoring method according to claim 3, characterized in that an alarm level is determined according to the predicted distance and/or speed of the next state of the obstacle, and a driver is warned according to the alarm level; wherein, the first and the second end of the pipe are connected with each other,
the closer the obstacle is to the next state and/or the greater the speed, the higher the warning level.
5. The lane-changing blind area monitoring method according to claim 1, wherein when an obstacle entering a warning area is monitored, and the type of the obstacle threatens lane changing of the vehicle, a warning is given to a driver, and the warning area defines a certain distance range for the lateral rear of the vehicle.
6. The lane-change blind zone monitoring method according to claim 4, wherein when the warning level is the highest, a lane-change operation by the driver is corrected and/or prevented.
7. A lane change blind area monitoring system is characterized by comprising a positioning module, a blind area monitoring control unit and at least one blind area monitoring sensing module;
the positioning module is used for acquiring the position information of the vehicle; the blind area monitoring and sensing module is used for acquiring barrier information of the rear and side of the vehicle;
the blind area monitoring and controlling unit is used for loading a corresponding high-precision map data packet according to the position information of the vehicle and constructing a three-dimensional static scene model according to the loaded high-precision map data packet;
the blind area monitoring and controlling unit is further used for marking the position information of the vehicle and the obstacle information of the side rear part of the vehicle in the three-dimensional static scene model; and monitoring the marked three-dimensional static scene model.
8. The lane-change blind area monitoring system of claim 7, wherein the positioning module comprises a global navigation satellite positioning system or a global navigation satellite positioning system, an inertial measurement unit.
9. The lane-changing blind area monitoring system according to claim 7, further comprising an alarm unit for giving an alarm to a driver.
10. A vehicle characterized by comprising the lane-change blind spot monitoring system of any one of claims 7 to 9.
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| CN110920525A (en) * | 2019-12-12 | 2020-03-27 | 合肥市智信汽车科技有限公司 | Vehicle blind area monitoring system based on panoramic image technology |
| CN113932820A (en) * | 2020-06-29 | 2022-01-14 | 杭州海康威视数字技术股份有限公司 | Object detection method and device |
| CN111959511B (en) * | 2020-08-26 | 2022-06-03 | 腾讯科技（深圳）有限公司 | Vehicle control method and device |
| CN113178025B (en) * | 2021-05-14 | 2023-02-03 | 南京领行科技股份有限公司 | Vehicle lane change detection method and device, electronic equipment and storage medium |
| CN114348023A (en) * | 2022-01-25 | 2022-04-15 | 北京三快在线科技有限公司 | Unmanned equipment control method and device based on blind area |
| CN115953917B (en) * | 2023-03-14 | 2023-05-30 | 西安科技大学 | Dangerous variable road segment identification and control method based on real-time track feature analysis |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103234547A (en) * | 2013-04-18 | 2013-08-07 | 易图通科技（北京）有限公司 | Method and device for displaying road scene in vacuum true three-dimensional navigation |
| CN206520542U (en) * | 2016-09-18 | 2017-09-26 | 郑州日产汽车有限公司 | Auto-panorama monitors image system |
| CN107554430A (en) * | 2017-09-20 | 2018-01-09 | 京东方科技集团股份有限公司 | Vehicle blind zone view method, apparatus, terminal, system and vehicle |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7630806B2 (en) * | 1994-05-23 | 2009-12-08 | Automotive Technologies International, Inc. | System and method for detecting and protecting pedestrians |
| KR20160107054A (en) * | 2015-03-03 | 2016-09-13 | 엘지전자 주식회사 | Vehicle control apparatus and method thereof, vehicle driving assistance apparatus and method thereof, mobile terminal and method thereof |
-
2018
- 2018-03-26 CN CN201810250023.6A patent/CN110356339B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103234547A (en) * | 2013-04-18 | 2013-08-07 | 易图通科技（北京）有限公司 | Method and device for displaying road scene in vacuum true three-dimensional navigation |
| CN206520542U (en) * | 2016-09-18 | 2017-09-26 | 郑州日产汽车有限公司 | Auto-panorama monitors image system |
| CN107554430A (en) * | 2017-09-20 | 2018-01-09 | 京东方科技集团股份有限公司 | Vehicle blind zone view method, apparatus, terminal, system and vehicle |
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