CN111413692A - Camera transverse position estimation self-calibration method based on roadside stationary object - Google Patents
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Abstract
Description
技术领域technical field
本发明涉及汽车控制技术领域，具体地指一种基于路旁静止物体的摄像头横向位置估测自标定方法。The invention relates to the technical field of automobile control, in particular to a self-calibration method for estimating the lateral position of a camera based on a roadside stationary object.
背景技术Background technique
高级辅助驾驶系统(ADAS)的紧急制动功能对近处目标的横向位置估测精度极为敏感。通常摄像头的视野中心距离估测较准确，视野边缘由于畸变大，距离估测存在较大误差。近处相临车道目标，通常处于视野边缘，因此横向距离估测误差较大。会引起高级辅助驾驶系统(ADAS)误报警和漏报警的现象，极大的影响了的用户的驾乘体验。The emergency braking function of advanced driver assistance systems (ADAS) is extremely sensitive to the accuracy of lateral position estimation of nearby targets. Usually, the distance estimation of the center of the field of view of the camera is more accurate, and the distance estimation has a large error due to the large distortion of the edge of the field of view. The nearby lane targets are usually at the edge of the field of view, so the lateral distance estimation error is large. It will cause false alarms and missed alarms in the Advanced Assisted Driving System (ADAS), which greatly affects the user's driving experience.
发明内容SUMMARY OF THE INVENTION
本发明的目的就是要解决上述背景技术提到的技术问题，提供一种基于路旁静止物体的摄像头横向位置估测自标定方法。The purpose of the present invention is to solve the technical problems mentioned in the above background art, and to provide a self-calibration method for estimating the lateral position of a camera based on a roadside stationary object.
本发明的技术方案为：一种基于路旁静止物体的摄像头横向位置估测自标定方法，其特征在于：通过智能摄像头识别路边的静止物体，记录静止物体在摄像头中距离车辆本身的观测横向距离和观测纵向距离，摄像头通过通信连接传递数据至车辆的控制系统，控制系统计算获得车辆行驶过程中观测横向距离与实际横向距离的补偿系数，形成补偿系数与观测纵向距离的查找表，当汽车再次遇到近处目标时，控制系统通过查找表和近处目标距离车辆的观测纵向距离得出补偿系数，然后通过该补偿系数对近处目标的观测横向距离进行自动补偿获得近处目标的实际横向距离，确定该近处目标的横向位置。The technical scheme of the present invention is: a method for estimating and self-calibrating the lateral position of a camera based on a roadside stationary object, which is characterized in that: the stationary object on the roadside is identified by an intelligent camera, and the observation transverse direction of the stationary object in the camera from the vehicle itself is recorded. Distance and observed longitudinal distance. The camera transmits data to the vehicle's control system through a communication connection. The control system calculates and obtains the compensation coefficient between the observed lateral distance and the actual lateral distance during the driving process of the vehicle, and forms a look-up table between the compensation coefficient and the observed longitudinal distance. When encountering a near target again, the control system obtains the compensation coefficient through the lookup table and the observed longitudinal distance between the near target and the vehicle, and then automatically compensates the observed lateral distance of the near target through the compensation coefficient to obtain the actual near target. Lateral distance, to determine the lateral position of the near target.
进一步的所述通过智能摄像头识别路边静止物体的方法为：智能摄像头识别路边的路灯或是树木作为静止物体。Further, the method for recognizing a roadside stationary object by a smart camera is: the smart camera recognizes a streetlight or a tree on the roadside as a stationary object.
进一步的所述控制系统计算获得车辆行驶过程中观测横向距离与实际横向距离的补偿系数的方法为：当控制系统判断车辆处于直行状态时，根据车辆处于直行状态时静止物体距离车辆的实际横向距离是不变的这一原理，可以得到在智能摄像头中静止物体距离车辆的观测横向距离与实际横向距离的关系，从而获得观测横向距离与实际横向距离的补偿系数。Further, the control system calculates and obtains the compensation coefficient between the observed lateral distance and the actual lateral distance during the running of the vehicle as follows: when the control system judges that the vehicle is in a straight state, according to the actual lateral distance between the stationary object and the vehicle when the vehicle is in the straight state This principle is unchanged, and the relationship between the observed lateral distance between the stationary object and the vehicle in the smart camera and the actual lateral distance can be obtained, so as to obtain the compensation coefficient between the observed lateral distance and the actual lateral distance.
进一步的所述控制系统判断车辆处于直行状态的方法为：通过带有车道识别功能的智能摄像头判断车辆当前行驶车道是否处于直道，控制系统采集车辆行驶运动过程中的航向角速度，从而判断车辆是否处于直行状态。Further, the method for the control system to determine that the vehicle is in a straight state is as follows: using an intelligent camera with a lane recognition function to determine whether the current driving lane of the vehicle is in a straight road, and the control system collects the heading angular velocity during the driving motion of the vehicle, so as to determine whether the vehicle is in a straight road. straight state.
进一步的所述的近处目标为静止目标或是运动目标。Further, the near target is a stationary target or a moving target.
进一步的当车辆已经获得补偿系数与观测纵向距离的查找表以后，车辆再次遇到近处目标时，此时车辆可以处于直行状态也可以处于非直行状态，都可以通过查找表以及观测纵向距离获取近处目标的实际横向距离。Further, after the vehicle has obtained the look-up table of the compensation coefficient and the observed longitudinal distance, when the vehicle encounters a near target again, the vehicle can be in a straight-forward state or a non-straight-forward state, which can be obtained through the look-up table and the observed longitudinal distance. The actual lateral distance of the near target.
本发明的优点有：1、本发明通过预先对智能摄像头观测静止目标的横向距离进行标定，即通过观测横向距离和实际横向距离之间的关系进行补偿，从而形成摄像头观测纵向距离与补偿系数之间的查找表，然后基于查找表即可获得在下一次的近处目标的实际横向位置，从而消除由于摄像头横向距离估测误差偏大以及摄像头两侧视角畸变的问题，提高控制系统对汽车行驶过程中道路两侧目标的观测精度，避免出现高级辅助驾驶系统(ADAS)误报警和漏报警的现象，极大的提高了的用户的驾乘体验；The advantages of the present invention are as follows: 1. The present invention calibrates the horizontal distance of the stationary target observed by the smart camera in advance, that is, compensates by observing the relationship between the horizontal distance and the actual horizontal distance, thereby forming the relationship between the vertical distance observed by the camera and the compensation coefficient. Then, based on the look-up table, the actual lateral position of the next near target can be obtained, so as to eliminate the problem of large lateral distance estimation error of the camera and the distortion of the viewing angle on both sides of the camera, and improve the control system's ability to understand the driving process of the car. The observation accuracy of the targets on both sides of the middle road avoids the occurrence of false alarms and missed alarms of the Advanced Assisted Driving System (ADAS), which greatly improves the user's driving experience;
2、本发明通过智能摄像头识别路边的路灯或是树木作为静止物体，这类识别方式比较简单，且样本充足，识别的精度更高，方便后续的数据处理；2. The present invention recognizes street lamps or trees on the roadside as stationary objects through intelligent cameras. This kind of recognition method is relatively simple, and the samples are sufficient, and the recognition accuracy is higher, which is convenient for subsequent data processing;
3、本发明确定补偿系数是基于车辆在直行状态过程中，静止物体距离汽车的横向距离始终是不变的，但摄像头因为在移动过程中，静止物体从摄像头视角的中间位置向视角的两侧边缘移动，观测的横向距离会随着汽车纵向距离的变化而产生变化，这样就可以找出观测横向距离和实际横向距离时间的变化关系，从而获得补偿系数，该方法简单可行，极大方便了获得补偿系数的计算方法；3. The present invention determines the compensation coefficient based on the fact that when the vehicle is in a straight state, the lateral distance between the stationary object and the vehicle is always constant, but the camera moves from the middle position of the camera's view angle to the two sides of the view angle because the camera is moving. When the edge moves, the observed lateral distance will change with the change of the longitudinal distance of the car. In this way, the relationship between the observed lateral distance and the actual lateral distance can be found out, and the compensation coefficient can be obtained. This method is simple, feasible and extremely convenient. Obtain the calculation method of the compensation coefficient;
4、本发明判断车辆是否直行通过两个步骤，一是通过智能摄像头判断车辆是否处于直行车道中，二是通过控制系统观察车辆的行驶信号，判断车辆是否为直行状态，通过两个步骤能够准确判断车辆的直行状态，方法极为简单高效，且逻辑判断方式合理，判断结果也极为准确；4. The present invention judges whether the vehicle is going straight through two steps, one is to judge whether the vehicle is in the straight lane through the intelligent camera, and the other is to observe the driving signal of the vehicle through the control system to judge whether the vehicle is in a straight state, and the two steps can accurately The method of judging the straight-ahead state of the vehicle is extremely simple and efficient, and the logical judgment method is reasonable, and the judgment result is also extremely accurate;
5、本发明获得查找表以后，对于再次判断近处目标的横向距离就无需考虑该近处目标是否处于静止状态或是车辆是否处于直行状态，这样的使用状态能够大幅度提高车辆判断模式范围，能够应对各种实际行驶过程中出现的状况，极大程度拓展了本方法的应用场景。5. After the present invention obtains the look-up table, it is not necessary to consider whether the near target is in a stationary state or whether the vehicle is in a straight state for judging the lateral distance of the near target again. Such a use state can greatly improve the range of vehicle judgment modes. It can cope with various situations in the actual driving process, which greatly expands the application scenarios of this method.
本发明的方法极为简单，通过获得补偿系数与纵向距离的查找表，能够消除摄像头在观测近处目标时视角的畸变，准确得出近处目标的横向位置，避免出现高级辅助驾驶系统(ADAS)误报警和漏报警的现象，极大的提高了的用户的驾乘体验，具有极大的推广价值和广泛的应用场景。The method of the invention is extremely simple. By obtaining the lookup table of the compensation coefficient and the longitudinal distance, the distortion of the viewing angle of the camera when observing the near target can be eliminated, the lateral position of the near target can be accurately obtained, and the occurrence of the Advanced Driving Assistant System (ADAS) can be avoided. The phenomenon of false alarms and missed alarms greatly improves the user's driving experience, and has great promotion value and a wide range of application scenarios.
附图说明Description of drawings
图1：本发明的车辆行驶示意图。Fig. 1: Schematic diagram of the vehicle running of the present invention.
具体实施方式Detailed ways
下面结合附图和具体实施例对本发明作进一步的详细说明。The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.
本实施例首先对智能摄像头(Mobileye Q3前向摄像头)进行标定，获得智能摄像头观测横向距离与实际横向距离之间的补偿系数。本实施例的智能摄像头具有车道识别功能，智能摄像头通过车道识别功能判断车辆是否处于直行车道中，当判定车辆确实处于直行车道中，控制系统接收车辆的行驶信号，比如航向角速度等能够判断车辆是否偏转的行驶信号，当控制系统接收的行驶信号判定车辆处于直行状态时，此时可以开始对智能摄像头进行标定，即计算摄像头观测横向距离与实际横向距离的补偿系数。In this embodiment, the smart camera (Mobileye Q3 forward-facing camera) is calibrated first, and the compensation coefficient between the observed lateral distance and the actual lateral distance of the smart camera is obtained. The smart camera of this embodiment has a lane recognition function. The smart camera uses the lane recognition function to determine whether the vehicle is in the straight lane. When it is determined that the vehicle is indeed in the straight lane, the control system receives the vehicle's driving signals, such as the heading angular velocity, etc. to determine whether the vehicle is in the straight lane. The deflection of the driving signal, when the driving signal received by the control system determines that the vehicle is in a straight state, the smart camera can be calibrated at this time, that is, the compensation coefficient between the lateral distance observed by the camera and the actual lateral distance can be calculated.
当车辆处于直行状态时，可以确定，路边的静止物体距离车辆的横向距离是永远保持不变的，但是由于车辆在行驶过程中，静止物体会从智能摄像头视角的中央位置想视角两侧的边缘位置移动，这样显示在智能摄像头的数据信息上，就是静止物体与车辆的观测横向距离发生变化，因此需要得到观测横向距离和实际横向距离之间的变化关系，获得观测横向距离和实际横向距离之间的补偿系数。本实施例的静止物体是智能摄像头能够识别的路灯、树木等目标。When the vehicle is in a straight state, it can be determined that the lateral distance between the stationary object on the roadside and the vehicle will always remain unchanged, but because the vehicle is moving, the stationary object will be viewed from the center of the smart camera. The edge position moves, which is displayed on the data information of the smart camera, that is, the observed lateral distance between the stationary object and the vehicle changes. Therefore, it is necessary to obtain the changing relationship between the observed lateral distance and the actual lateral distance, and obtain the observed lateral distance and the actual lateral distance. compensation coefficient between. The stationary objects in this embodiment are targets such as street lights and trees that can be identified by the smart camera.
获得观测横向距离和实际横向距离之间的补偿系数后，可以发现补偿系数实际上与车辆与静止物体的观测纵向距离存在一定的关系。摄像头有一个精度区域，摄像头与观测物体的纵向距离处在这个精度区域时，摄像头的实际横向距离与观测横向距离之间的误差最小，即此时的补偿系数最小，当摄像头与观测物体的纵向距离远离这个精度区域的时候，距离这个精度区域越远，补充系数越大，反之补偿系数越小。因此通过大量的实验进行标定，将实际横向距离和观测横向距离之间的比值作为补偿系数，通过获得这种观测纵向距离与补偿系数的对应关系，可以形成该智能摄像头的补偿系数与观测纵向距离之间的查找表。本实施例的观测纵向距离指摄像头观测的车辆距离静止物体的纵向距离，当车辆处于直行状态时观测纵向距离等同于实际纵向距离。After obtaining the compensation coefficient between the observed lateral distance and the actual lateral distance, it can be found that the compensation coefficient actually has a certain relationship with the observed longitudinal distance between the vehicle and the stationary object. The camera has an accuracy area. When the vertical distance between the camera and the observed object is in this accuracy area, the error between the actual horizontal distance of the camera and the observed horizontal distance is the smallest, that is, the compensation coefficient at this time is the smallest. When the distance is far from this precision area, the farther away from this precision area, the larger the supplementary coefficient, and vice versa, the smaller the compensation coefficient. Therefore, through a large number of experiments for calibration, the ratio between the actual lateral distance and the observed lateral distance is used as the compensation coefficient. By obtaining the corresponding relationship between the observed longitudinal distance and the compensation coefficient, the compensation coefficient and the observed longitudinal distance of the smart camera can be formed. lookup table between. The observed longitudinal distance in this embodiment refers to the longitudinal distance between the vehicle and the stationary object observed by the camera, and the observed longitudinal distance is equal to the actual longitudinal distance when the vehicle is in a straight state.
获得该智能摄像头的补偿系数与观测纵向距离之间的查找表后，当车辆再次遇到近处目标时，不管该近处目标是否处于静止状态，也不管车辆此时是否处于直行状态，智能摄像头获取近处目标的观测纵向距离，基于查找表，就可以获得对应的补偿系数，然后通过智能摄像头得到的近处目标与车辆本身的观测横向距离就可以获得近处目标与车辆本身的实际横向距离，从而准确判断近处目标的横向位置。After obtaining the lookup table between the compensation coefficient of the smart camera and the observed longitudinal distance, when the vehicle encounters a near target again, regardless of whether the near target is in a stationary state or whether the vehicle is in a straight state at this time, the smart camera Obtain the observed longitudinal distance of the near target, and based on the look-up table, the corresponding compensation coefficient can be obtained, and then the actual horizontal distance between the near target and the vehicle itself can be obtained through the observed horizontal distance between the near target and the vehicle itself obtained by the smart camera. , so as to accurately determine the lateral position of the near target.
以某型号的车辆为例，该车辆配置某型号的智能摄像头，该智能摄像头具有车道识别功能。当该车辆初次行驶时，对智能摄像头进行标定。如图1所示，车辆行驶在直行车道中，且车辆处于直行状态，智能摄像头观测到前方路边的路灯，此时车辆距离该路灯的实际横向距离为L＝2.46m，智能摄像头获取的车辆距离该路灯的观测横向距离为L1＝2.41m、车辆距离该路灯A的观测纵向距离为20m，此时智能摄像头对车辆的实际横向距离与观测纵向距离的补偿系数为1.02。车辆继续行驶，智能摄像头获取车辆距离该路灯A的观测纵向距离变化为8m，智能摄像头获取的车辆距离该路灯A的观测横向距离为L2＝1.91m，由于车辆处于直行状态，车辆距离该路灯A的实际横向距离还是为L＝2.46m，此时智能摄像头对车辆的实际横向距离与观测纵向距离的补偿系数为1.29。依次记录补偿系数与观测纵向距离，形成查找表，如下表所示：Taking a certain type of vehicle as an example, the vehicle is equipped with a certain type of smart camera, and the smart camera has the function of lane recognition. When the vehicle is driving for the first time, the smart camera is calibrated. As shown in Figure 1, the vehicle is driving in the straight lane, and the vehicle is in a straight state. The smart camera observes the street light on the road ahead. At this time, the actual lateral distance between the vehicle and the street light is L=2.46m. The vehicle acquired by the smart camera The observed lateral distance from the street lamp is L 1 =2.41m, and the observed longitudinal distance from the vehicle to the street lamp A is 20m. At this time, the compensation coefficient between the actual lateral distance of the vehicle and the observed longitudinal distance by the smart camera is 1.02. The vehicle continues to drive, the observed longitudinal distance between the vehicle and the street lamp A obtained by the smart camera changes to 8m, and the observed lateral distance between the vehicle and the street lamp A obtained by the intelligent camera is L 2 =1.91m. Since the vehicle is in a straight state, the vehicle is far from the street lamp. The actual lateral distance of A is still L=2.46m. At this time, the compensation coefficient between the actual lateral distance of the vehicle and the observed longitudinal distance by the smart camera is 1.29. Record the compensation coefficient and the observed longitudinal distance in turn to form a look-up table, as shown in the following table:
表1：某车辆智能摄像头的补偿系数与观测纵向距离的对应表Table 1: Correspondence table between the compensation coefficient of a vehicle's smart camera and the observed longitudinal distance
获得查找表后，车辆行驶过程中，车辆前方路边出现闯红灯者，此时智能摄像头观测到闯红灯者距离车辆的观测纵向距离为1.1m、观测纵向向距离为12m，通过查阅查找表，找出对应的补偿系数为1.20，计算得到此时闯红灯者距离车辆的实际横向距离为1.32m，将该信息反馈到高级辅助驾驶系统(ADAS)，由高级辅助驾驶系统(ADAS)判断是否采取紧急制动措施。After obtaining the look-up table, when the vehicle is running, there is a red light runner on the road in front of the vehicle. At this time, the smart camera observes that the red light runner is 1.1m away from the vehicle in the observed longitudinal distance, and the observed longitudinal distance is 12m. By consulting the look-up table, find out The corresponding compensation coefficient is 1.20, and it is calculated that the actual lateral distance between the red light runner and the vehicle is 1.32m. This information is fed back to the Advanced Assisted Driving System (ADAS), and the Advanced Assisted Driving System (ADAS) will determine whether to take emergency braking. measure.
本实施例的纵向指汽车沿汽车行驶方向，即图1中的上下方向，横向指垂直汽车行驶的方向，即图1中的左右方向。In this embodiment, the longitudinal direction refers to the direction in which the vehicle travels along the vehicle, that is, the up and down direction in FIG.
以上显示和描述了本发明的基本原理、主要特征和本发明的优点。本行业的技术人员应该了解，本发明不受上述实施例的限制，上述实施例和说明书中描述的只是说明本发明的原理，在不脱离本发明精神和范围的前提下本发明还会有各种变化和改进，这些变化和改进都落入要求保护的本发明范围内。本发明要求保护范围由所附的权利要求书及其等同物界定。The foregoing has shown and described the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above-mentioned embodiments. The above-mentioned embodiments and descriptions only illustrate the principle of the present invention. Such changes and improvements fall within the scope of the claimed invention. The claimed scope of the present invention is defined by the appended claims and their equivalents.
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