CN111516703A - Fire-fighting vehicle automatic driving method, device, computer equipment and storage medium - Google Patents
Fire-fighting vehicle automatic driving method, device, computer equipment and storage mediumDownload PDFInfo
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Abstract
Description
Translated fromChinese技术领域technical field
本发明涉及车辆自动驾驶领域，具体涉及一种消防车辆自动行驶方法、装置、计算机设备及存储介质。The invention relates to the field of automatic driving of vehicles, in particular to a method, device, computer equipment and storage medium for automatic driving of fire-fighting vehicles.
背景技术Background technique
近些年来火灾时有发生，给人们日常的生活和生产造成了巨大的损失。传统方式下，消防车辆都是由消防人员随车进行操作和控制的，面临的环境非常恶劣危险，对消防人员的人身安全造成了很大的威胁。因此，急需对传统消防车辆系统进行智能化改造，而其中消防车辆自动行驶系统架构是关键环节。In recent years, fires have occurred frequently, causing huge losses to people's daily life and production. Traditionally, fire-fighting vehicles are operated and controlled by firefighters, and the environment they face is very harsh and dangerous, which poses a great threat to the personal safety of firefighters. Therefore, there is an urgent need to carry out intelligent transformation of the traditional fire fighting vehicle system, of which the automatic driving system architecture of fire fighting vehicles is the key link.
发明内容SUMMARY OF THE INVENTION
因此，本发明要解决的技术问题在于克服现有技术中消防车辆需要人工操控行驶的缺陷，从而提供一种消防车辆自动行驶方法、装置、计算机设备及存储介质。Therefore, the technical problem to be solved by the present invention is to overcome the defect in the prior art that fire-fighting vehicles need to be driven manually, thereby providing an automatic driving method, device, computer equipment and storage medium for fire-fighting vehicles.
根据本发明一个方面，提供了一种消防车辆自动行驶方法，包括：According to an aspect of the present invention, there is provided an automatic driving method for a fire fighting vehicle, comprising:
利用多个感知器件采集与消防车辆相关的行驶信息，所述行驶信息包含位置信息、环境信息和运动状态信息；Using multiple sensing devices to collect driving information related to fire fighting vehicles, the driving information includes location information, environmental information and motion state information;
对采集到的所述行驶信息进行数据融合，以确定所述行驶信息中的可信数据；performing data fusion on the collected driving information to determine credible data in the driving information;
将所述可信数据输入消防车辆的自动行驶模型，以输出与所述消防车辆相关的控制参数；inputting the trusted data into an automatic driving model of a fire fighting vehicle to output control parameters related to the fire fighting vehicle;
基于所述控制参数控制所述消防车辆自动行驶。The fire fighting vehicle is controlled to travel automatically based on the control parameter.
优选地，所述利用多个感知器件采集与消防车辆相关的行驶信息的步骤包括：Preferably, the step of using multiple sensing devices to collect driving information related to the fire fighting vehicle includes:
利用GPS定位器和惯性导航定位器采集所述消防车辆的位置信息，利用摄像头和毫米波雷达采集所述消防车辆的环境信息，利用车速传感器采集所述消防车辆的运动状态信息。Use GPS locator and inertial navigation locator to collect the position information of the fire fighting vehicle, use the camera and millimeter wave radar to collect the environmental information of the fire fighting vehicle, and use the vehicle speed sensor to collect the motion state information of the fire fighting vehicle.
优选地，所述对采集到的所述行驶信息进行数据融合，以确定所述行驶信息中的可信数据的步骤包括：Preferably, the step of performing data fusion on the collected driving information to determine credible data in the driving information includes:
获取当前环境光照强度；Get the current ambient light intensity;
在当前环境光照强度大于或等于第一阈值的情况下，将利用摄像头采集的第一环境信息作为可信数据；In the case that the current ambient light intensity is greater than or equal to the first threshold, use the first ambient information collected by the camera as the trusted data;
在当前环境光照强度小于第一阈值的情况下，将利用毫米波雷达采集到的第二环境信息作为可信数据。When the current ambient light intensity is less than the first threshold, the second environment information collected by the millimeter-wave radar is used as credible data.
优选地，所述对采集到的所述行驶信息进行数据融合，以确定所述行驶信息中的可信数据的步骤包括：Preferably, the step of performing data fusion on the collected driving information to determine credible data in the driving information includes:
获取当前无线网络信号的强度；Get the strength of the current wireless network signal;
在当前无线网络信号的强度大于或等于第二阈值的情况下，将利用GPS定位器采集到的第一位置信息作为可信数据；When the strength of the current wireless network signal is greater than or equal to the second threshold, use the first location information collected by the GPS locator as trusted data;
在当前无线网络信号的强度小于第二阈值的情况下，将惯性导航定位器采集到的第二位置信息作为可信数据。When the strength of the current wireless network signal is less than the second threshold, the second position information collected by the inertial navigation locator is used as trusted data.
优选地，所述环境信息包括左侧车道线信息和右侧车道线信息，所述对采集到的所述行驶信息进行数据融合，以确定所述行驶信息中的可信数据的步骤还包括：Preferably, the environmental information includes left lane line information and right lane line information, and the step of performing data fusion on the collected driving information to determine credible data in the driving information further includes:
获取所述左侧车道线信息的第一强度和右侧车道线信息的第二强度；acquiring the first intensity of the left lane line information and the second intensity of the right lane line information;
当所述第一强度和所述第二强度均大于或等于第三阈值时，基于所述左侧车道线信息和所述右侧车道线信息确定当前时刻的车道线曲率、车辆航向角和车辆横向偏移；When both the first intensity and the second intensity are greater than or equal to a third threshold, determine the lane line curvature, the vehicle heading angle and the vehicle at the current moment based on the left lane line information and the right lane line information lateral offset;
当所述第一强度大于或等于所述第三阈值、所述第二强度小于所述第三阈值时，基于所述左侧车道线信息确定当前时刻的车道线曲率、车辆航向角和车辆横向偏移；When the first intensity is greater than or equal to the third threshold, and the second intensity is less than the third threshold, determine the lane curvature, vehicle heading angle and vehicle lateral direction at the current moment based on the left lane line information offset;
当所述第二强度大于或等于所述第三阈值、所述第一强度小于所述第三阈值时，基于所述右侧车道线信息确定当前时刻的车道线曲率、车辆航向角和车辆横向偏移；When the second intensity is greater than or equal to the third threshold, and the first intensity is less than the third threshold, determine the lane curvature, the vehicle heading angle and the vehicle lateral direction at the current moment based on the right lane line information offset;
当所述第一强度和所述第二强度均小于第三阈值时，确定当前时刻的车道线曲率、车辆航向角和车辆横向偏移与前一时刻的车道线曲率、车辆航向角和车辆横向偏移相同。When both the first intensity and the second intensity are less than the third threshold, determine the lane line curvature, the vehicle heading angle and the vehicle lateral offset at the current moment and the lane line curvature, vehicle heading angle and vehicle lateral offset at the previous moment The offset is the same.
优选地，所述将所述可信数据输入消防车辆的自动行驶模型，以输出与所述消防车辆相关的控制参数的步骤包括：Preferably, the step of inputting the trusted data into an automatic driving model of a fire fighting vehicle to output control parameters related to the fire fighting vehicle includes:
将前一时刻获取到的可信数据输入所述自动行驶模型，以输出当前时刻与所述消防车辆相关的控制参数；Input the trusted data obtained at the previous moment into the automatic driving model to output the control parameters related to the fire fighting vehicle at the current moment;
将当前时刻获取到的可信数据输入所述自动行驶模型，以输出后一时刻与所述消防车辆相关的控制参数；Input the credible data obtained at the current moment into the automatic driving model to output the control parameters related to the fire fighting vehicle at the next moment;
其中，所述控制参数包括油门踏板开度和方向盘转向角度。Wherein, the control parameters include the accelerator pedal opening and the steering angle of the steering wheel.
优选地，所述基于所述控制参数控制所述消防车辆自动行驶的步骤包括：Preferably, the step of controlling the automatic driving of the fire fighting vehicle based on the control parameter includes:
基于所述油门踏板开度和方向盘转向角度控制所述消防车辆的油门和方向盘以实现自动行驶。The accelerator and steering wheel of the fire fighting vehicle are controlled based on the accelerator pedal opening and steering angle of the steering wheel to realize automatic driving.
根据本发明第二方面，提供了一种消防车辆自动行驶装置，包括：According to a second aspect of the present invention, an automatic driving device for fire fighting vehicles is provided, comprising:
信息采集单元，用于利用多个感知器件采集与消防车辆相关的行驶信息，所述行驶信息包含位置信息、环境信息和运动状态信息；an information collection unit, configured to use a plurality of sensing devices to collect driving information related to the fire fighting vehicle, where the driving information includes location information, environmental information and motion state information;
数据融合单元，用于对采集到的所述行驶信息进行数据融合，以确定所述行驶信息中的可信数据；a data fusion unit, configured to perform data fusion on the collected driving information to determine credible data in the driving information;
控制参数输出单元，用于将所述可信数据输入消防车辆的自动行驶模型，以输出与所述消防车辆相关的控制参数；a control parameter output unit for inputting the credible data into an automatic driving model of a fire fighting vehicle to output control parameters related to the fire fighting vehicle;
自动行驶单元，用于基于所述控制参数控制所述消防车辆自动行驶。An automatic travel unit, configured to control the fire fighting vehicle to travel automatically based on the control parameters.
根据本发明第三方面，提供了一种计算机设备，包括存储器、处理器以及存储在存储器上并可在处理器上运行的计算机程序，所述处理器执行所述计算机程序时实现上述方法的步骤。According to a third aspect of the present invention, a computer device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor implementing the steps of the above method when executing the computer program .
根据本发明第四方面，提供了一种计算机可读存储介质，其上存储有计算机程序，所述计算机程序被处理器执行时实现上述方法的步骤。According to a fourth aspect of the present invention, there is provided a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the steps of the above method are implemented.
本发明技术方案，具有如下优点：The technical scheme of the present invention has the following advantages:
本发明对通过多种感知器件采集到的信息进行数据融合，可以保证自动行驶过程中的输入信息更加准确，从而提高消防汽车自动行驶的精确度。一方面，本发明对于多个感知器件同时采集同一个物理量的情况，根据实际场景从多个传感器采集的信息中选择最为可信的数据，从而提高采集数据的可靠性。另一方面，由于车道线同时包含左右两侧的信息，本发明根据两侧车道线的强度确定利用哪一侧或者两侧的车道线信息进行车道线预估，从而可以保证预估的车道线信息更加准确。The invention performs data fusion on the information collected by various sensing devices, which can ensure that the input information in the automatic driving process is more accurate, thereby improving the accuracy of the automatic driving of the fire-fighting vehicle. On the one hand, the present invention selects the most credible data from the information collected by the multiple sensors according to the actual scene when multiple sensing devices collect the same physical quantity at the same time, thereby improving the reliability of the collected data. On the other hand, since the lane line contains the information of the left and right sides at the same time, the present invention determines which side or the lane line information on both sides is used to estimate the lane line according to the strength of the lane lines on both sides, so that the estimated lane line can be guaranteed. Information is more accurate.
附图说明Description of drawings
为了更清楚地说明本发明具体实施方式或现有技术中的技术方案，下面将对具体实施方式或现有技术描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图是本发明的一些实施方式，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。In order to illustrate the specific embodiments of the present invention or the technical solutions in the prior art more clearly, the following briefly introduces the accompanying drawings that need to be used in the description of the specific embodiments or the prior art. Obviously, the accompanying drawings in the following description The drawings are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can also be obtained based on these drawings without creative efforts.
图1为本发明实施例1中消防车辆自动行驶方法的一个具体示例的流程图；FIG. 1 is a flowchart of a specific example of a method for automatic driving of a fire-fighting vehicle in Embodiment 1 of the present invention;
图2为本发明实施例2中消防车辆自动行驶装置的一个具体示例的原理框图；2 is a schematic block diagram of a specific example of an automatic driving device for fire fighting vehicles in Embodiment 2 of the present invention;
图3为本发明实施例2中消防车辆自动行驶装置的一个具体示例的硬件结构示意图。FIG. 3 is a schematic diagram of a hardware structure of a specific example of an automatic driving device for a fire fighting vehicle in Embodiment 2 of the present invention.
具体实施方式Detailed ways
下面将结合附图对本发明的技术方案进行清楚、完整地描述，显然，所描述的实施例是本发明一部分实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的范围。The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are a part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.
在本发明的描述中，需要说明的是，术语“中心”、“上”、“下”、“左”、“右”、“竖直”、“水平”、“内”、“外”等指示的方位或位置关系为基于附图所示的方位或位置关系，仅是为了便于描述本发明和简化描述，而不是指示或暗示所指的装置或元件必须具有特定的方位、以特定的方位构造和操作，因此不能理解为对本发明的限制。此外，术语“第一”、“第二”、“第三”仅用于描述目的，而不能理解为指示或暗示相对重要性。In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. The indicated orientation or positional relationship is based on the orientation or positional relationship shown in the accompanying drawings, which is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the indicated device or element must have a specific orientation or a specific orientation. construction and operation, and therefore should not be construed as limiting the invention. Furthermore, the terms "first", "second", and "third" are used for descriptive purposes only and should not be construed to indicate or imply relative importance.
此外，下面所描述的本发明不同实施方式中所涉及的技术特征只要彼此之间未构成冲突就可以相互结合。In addition, the technical features involved in the different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.
实施例1Example 1
本实施例提供一种消防车辆自动行驶方法，如图1所示，包括如下步骤：This embodiment provides an automatic driving method for a fire fighting vehicle, as shown in FIG. 1 , including the following steps:
S100:利用多个感知器件采集与消防车辆相关的行驶信息，所述行驶信息包含位置信息、环境信息和运动状态信息。S100: Use multiple sensing devices to collect driving information related to the fire fighting vehicle, where the driving information includes location information, environmental information and motion state information.
本实施例中的感知器件可以包括各类传感器、定位器、视频采集装置等可以采集周围信息的装置，例如光学传感器、温度传感器、惯性传感器、车速传感器、UWB感知系统、GPS定位器、雷达装置、摄像头等。The sensing device in this embodiment may include various types of sensors, locators, video collection devices, and other devices that can collect surrounding information, such as optical sensors, temperature sensors, inertial sensors, vehicle speed sensors, UWB sensing systems, GPS locators, and radar devices. , camera, etc.
本实施例所述的行驶信息，包括消防车辆在行驶过程中可以反映周边环境及自身状态的信息，例如位置信息、环境信息和运动状态信息。其中位置信息可以是消防车辆所处的地理位置，例如经纬度信息，还可以包含车辆本身的姿态信息，例如车头朝向正北方向、西南方向等。环境信息可以包括消防车辆的周边环境，例如通过摄像头采集到的行人、自行车、机动车、道路轨迹线、路牌、信号灯等车辆前向和左右侧环境信息，车辆左前方和右前方的空间的探测信息，以及地面的车道线信息等。运动状态信息可以包括消防车辆当前处于静止状态还是运动状态，具体可以通过车速传感器采集到的车辆行驶速度来确定。The driving information described in this embodiment includes information that can reflect the surrounding environment and its own state during the driving process of the fire fighting vehicle, such as location information, environmental information and motion state information. The location information may be the geographic location where the fire fighting vehicle is located, such as longitude and latitude information, and may also include attitude information of the vehicle itself, such as the head of the vehicle facing due north, southwest, and the like. The environmental information can include the surrounding environment of the fire fighting vehicle, such as pedestrians, bicycles, motor vehicles, road trajectories, road signs, signal lights and other vehicle front and left side environmental information collected by the camera, and the detection of the space in front of the left and right of the vehicle information, as well as the lane line information on the ground, etc. The motion state information may include whether the fire fighting vehicle is currently in a stationary state or a motion state, which may be specifically determined by the vehicle speed collected by the vehicle speed sensor.
S200:对采集到的所述行驶信息进行数据融合，以确定所述行驶信息中的可信数据。S200: Perform data fusion on the collected driving information to determine credible data in the driving information.
本实施例所称的数据融合，是指将多个感知器件采集到的各类信息进行比较整理，从中筛选出可信度较高的数据，去除可信度较低的数据。可以理解，对于同一个物理量，不同感知器件采集到的参数信息可能会存在差异。例如利用摄像头和雷达均可以检测出前方的障碍物，而根据摄像头获取到的图像信息和雷达获取到的反射波信息所确定的障碍物的形状、位置等可能并不完全相同。因此，如何对这些存在差异的参数信息进行处理以得出关于上述物理量的最准确的参数信息，即为本步骤进行数据融合的目的。The data fusion referred to in this embodiment refers to comparing and sorting out various types of information collected by multiple sensing devices, screening out data with higher reliability, and removing data with lower reliability. It can be understood that for the same physical quantity, there may be differences in the parameter information collected by different sensing devices. For example, both the camera and the radar can detect the obstacle ahead, but the shape and position of the obstacle determined according to the image information obtained by the camera and the reflected wave information obtained by the radar may not be exactly the same. Therefore, how to process these different parameter information to obtain the most accurate parameter information about the above-mentioned physical quantities is the purpose of data fusion in this step.
本实施例经过数据融合后得到的数据包括两类，一类是直接监测到的数据，例如温度数据、车速数据等；另一类是需要进行计算之后间接获取到的数据，例如前方障碍物距离数据、前方障碍物速度数据、车道线预估数据等。The data obtained after data fusion in this embodiment includes two types, one is directly monitored data, such as temperature data, vehicle speed data, etc.; the other is indirectly obtained data after calculation, such as the distance to obstacles ahead Data, speed data of obstacles ahead, estimated lane line data, etc.
S300:将所述可信数据输入消防车辆的自动行驶模型，以输出与所述消防车辆相关的控制参数。S300: Input the credible data into an automatic driving model of the fire fighting vehicle to output control parameters related to the fire fighting vehicle.
自动行驶模型是基于消防车辆的运动规律建立的数字化模型，用于模拟消防车辆在不同时刻下的运动状态，基于不同的输入参数输出对应的控制参数。本实施例中的自动行驶模型可以包括以后轴为原点的车辆运动模型、以质心为中心的车辆运动学模型、阿克曼转向几何模型等，通过求解满足目标函数以及各种约束的优化问题，最终输出一系列控制参数序列。本实施例并不对具体的自动行驶模型、目标函数及约束条件进行限制，本领域技术人员可以根据实际情况采用现有技术中的任意车辆运动模型，通过任意合适的目标函数及约束条件获得控制参数。The automatic driving model is a digital model established based on the motion law of fire-fighting vehicles, which is used to simulate the motion state of fire-fighting vehicles at different times, and output corresponding control parameters based on different input parameters. The automatic driving model in this embodiment may include a vehicle kinematic model with the rear axis as the origin, a vehicle kinematic model with the center of mass as the center, and an Ackerman steering geometric model. By solving the optimization problem that satisfies the objective function and various constraints, Finally, a series of control parameter sequences are output. This embodiment does not limit the specific automatic driving model, objective function and constraint conditions. Those skilled in the art can adopt any vehicle motion model in the prior art according to the actual situation, and obtain control parameters through any suitable objective function and constraint conditions. .
本实施例中的控制参数是指对消防车辆的自动行驶起关键控制作用的参数。例如油门踏板开度和方向盘转向角度。The control parameters in this embodiment refer to parameters that play a key role in controlling the automatic driving of the fire fighting vehicle. Such as accelerator pedal opening and steering wheel steering angle.
S400:基于所述控制参数控制所述消防车辆自动行驶。S400: Control the fire fighting vehicle to drive automatically based on the control parameter.
本步骤用于控制消防车辆实现自动驾驶。具体的，例如基于所述油门踏板开度和方向盘转向角度控制所述消防车辆的油门和方向盘以实现自动行驶。This step is used to control the fire fighting vehicle to realize automatic driving. Specifically, for example, the accelerator and the steering wheel of the fire fighting vehicle are controlled based on the accelerator pedal opening and the steering angle of the steering wheel to realize automatic driving.
通过以上步骤，可以精准控制消防车辆实现自动驾驶，有利于扑救难度大、危险性强、消防人员无法接近的恶性石油、化工、有毒有害液体气体、化学危险品等特殊火灾，保障消防人员的生命安全。Through the above steps, the firefighting vehicles can be precisely controlled to achieve automatic driving, which is beneficial to fighting the difficult, dangerous, and inaccessible special fires such as vicious petroleum, chemical, toxic and harmful liquid gases, and hazardous chemicals, and protects the lives of firefighters. Safety.
优选地，步骤S200包括：Preferably, step S200 includes:
获取当前环境光照强度，例如可以通过光敏传感器直接获取光照强度，或者根据天气状况是晴天还是阴天间接获取光照强度。The current ambient light intensity is obtained, for example, the light intensity can be obtained directly through a photosensitive sensor, or the light intensity can be obtained indirectly according to whether the weather condition is sunny or cloudy.
在当前环境光照强度大于或等于第一阈值的情况下，将利用摄像头采集的第一环境信息作为可信数据；在当前环境光照强度小于第一阈值的情况下，将利用毫米波雷达采集到的第二环境信息作为可信数据。When the current ambient light intensity is greater than or equal to the first threshold, the first environment information collected by the camera is used as trusted data; when the current ambient light intensity is less than the first threshold, the The second environment information is used as trusted data.
本示例用于在摄像头采集的图像信息和毫米波雷达采集的反射波信息之间进行选择，将更加符合真实情况的信息作为可信数据。可以理解，摄像头采集的图像信息的质量与环境光照有密切关系。当环境光照较充足时，摄像头采集到的图像信息较为清晰，参考价值较高；而毫米波雷达采集到的反射波信号容易在建筑物较多时受到干扰而存在误差。因此在环境光照较充足的情况下，将利用摄像头采集的第一环境信息作为可信数据。反之当环境光照较暗时，摄像头采集到的图像信息容易模糊不清，而毫米波雷达采集到的反射波信号并不会收到环境光照的影响，此时毫米波雷达采集到的反射波信号的参考价值更高。因此在环境光照不充足的情况下，将利用毫米波雷达采集到的第二环境信息作为可信数据。This example is used to choose between the image information collected by the camera and the reflected wave information collected by the millimeter-wave radar, and use the information that is more in line with the real situation as the trusted data. It can be understood that the quality of the image information collected by the camera is closely related to the ambient lighting. When the ambient light is sufficient, the image information collected by the camera is clearer and has a higher reference value; while the reflected wave signal collected by the millimeter-wave radar is prone to be interfered with when there are many buildings, resulting in errors. Therefore, in the case of sufficient ambient light, the first environmental information collected by the camera is used as trusted data. On the other hand, when the ambient light is dark, the image information collected by the camera is easily blurred, and the reflected wave signal collected by the millimeter-wave radar will not be affected by the ambient light. At this time, the reflected wave signal collected by the millimeter-wave radar The reference value is higher. Therefore, in the case of insufficient ambient light, the second environmental information collected by the millimeter-wave radar is used as credible data.
本实施例中的摄像头和雷达用户获取消防车辆行驶过程中的环境信息，根据不同情况选择摄像头采集的环境信息或雷达采集的环境信息作为可信数据，可以使环境信息更加准确可靠，提高自动行驶的准确性。In this embodiment, the user of the camera and the radar obtains the environmental information during the driving of the fire fighting vehicle, and selects the environmental information collected by the camera or the environmental information collected by the radar as credible data according to different situations, which can make the environmental information more accurate and reliable, and improve automatic driving. accuracy.
优选地，步骤S200还包括：Preferably, step S200 further includes:
获取当前无线网络信号的强度；Get the strength of the current wireless network signal;
在当前无线网络信号的强度大于或等于第一阈值的情况下，将利用GPS定位器采集到的第一位置信息作为可信数据；在当前无线网络信号的强度小于第一阈值的情况下，将惯性导航定位器采集到的第二位置信息作为可信数据。When the strength of the current wireless network signal is greater than or equal to the first threshold, the first position information collected by the GPS locator is used as the trusted data; when the strength of the current wireless network signal is less than the first threshold, the The second position information collected by the inertial navigation locator is used as trusted data.
本领域技术人员可以理解，GPS定位器成本比较低廉，计算复杂度适中，而惯性导航定位器成本昂贵，精度较高，运算量大，长时间启用时还会出现延时的可能。因此在通常能顺利获取到无线网络信号的情况下采用GPS定位器确定位置信息是合理的。然而当车辆行驶在隧道、山区等区域中，无线网络信号强度不够的情况下，则无法通过GPS定位器获取到准确的位置信息。此时可以通过惯性导航定位器来获取位置信息，从而保证无论在任何环境都能准确获取到消防车辆的位置信息，为准确实现自动驾驶提供必要保证。Those skilled in the art can understand that a GPS locator has relatively low cost and moderate computational complexity, while an inertial navigation locator is expensive, has high precision, and requires a large amount of computation, and may cause delays when it is activated for a long time. Therefore, it is reasonable to use the GPS locator to determine the location information under the condition that the wireless network signal can usually be obtained smoothly. However, when the vehicle is driving in areas such as tunnels and mountainous areas, and the signal strength of the wireless network is insufficient, it is impossible to obtain accurate location information through the GPS locator. At this time, the position information can be obtained through the inertial navigation locator, so as to ensure that the position information of the fire fighting vehicle can be accurately obtained in any environment, and provide the necessary guarantee for the accurate realization of automatic driving.
优选地，所述环境信息包括左侧车道线信息和右侧车道线信息，步骤S200还包括：Preferably, the environmental information includes left lane line information and right lane line information, and step S200 further includes:
获取所述左侧车道线信息的第一强度和右侧车道线信息的第二强度。以通过摄像头采集的环境信息作为可信数据为例，左侧车道线信息的第一强度和右侧车道线信息的第二强度用来表征摄像头采集的图像中，左侧车道线和侧车道线是否可见以及可见的车道线的清晰程度。某侧车道线信息的强度越高，表明该侧车道线信息的可信度越高。本实施例获取左侧车道线信息和右侧车道线信息的强度，是为了基于左侧车道线信息和右侧车道线信息的不同权重来进行车道线预估。本实施例所述的车道线预估，就是根据每个时刻获取到的左侧车道线信息和右侧车道线信息，估计整体的车道线曲率、车辆航向角和车辆横向偏移。Obtain the first intensity of the left lane line information and the second intensity of the right lane line information. Taking the environmental information collected by the camera as the trusted data as an example, the first intensity of the left lane line information and the second intensity of the right lane line information are used to represent the left lane line and the side lane line in the image collected by the camera. Whether and how clearly the visible lane lines are visible. The higher the intensity of the lane line information on a certain side, the higher the reliability of the lane line information on the side. In this embodiment, the intensities of the left lane line information and the right lane line information are obtained in order to perform lane line estimation based on different weights of the left lane line information and the right lane line information. The lane line estimation described in this embodiment is to estimate the overall lane line curvature, the vehicle heading angle and the vehicle lateral offset according to the left lane line information and the right lane line information obtained at each moment.
本实施例中的第三阈值可以为零。根据第一强度和第二强度的不同取值，分别从以下四种情况进行车道线预估：The third threshold in this embodiment may be zero. According to the different values of the first intensity and the second intensity, the lane lines are estimated from the following four situations:
(1)当第一强度和第二强度均大于或等于零时，基于左侧车道线信息和右侧车道线信息确定当前时刻的车道线曲率、航向角和横向偏移。(1) When both the first intensity and the second intensity are greater than or equal to zero, determine the lane line curvature, heading angle and lateral offset at the current moment based on the left lane line information and the right lane line information.
假设ρ1为左侧车道线曲率，ρ2为右侧车道线曲率，Yaw1为左侧航向角，Yaw2为右侧航向角，α1为左侧横向偏移，α2为右侧横向偏移。其中ρ1，ρ2，Yaw1，Yaw2，α1和α2均可以通过左侧车道线信息和右侧车道线信息计算得出。那么预估整体的车道线曲率ρ、航向角Yaw和横向偏移α分别为：Suppose ρ1 is the left lane line curvature, ρ2 is the right lane line curvature, Yaw1 is the left heading angle, Yaw2 is the right heading angle, α1 is the left lateral offset, and α2 is the right lateral offset. Among them, ρ1 , ρ2 , Yaw1 , Yaw2 , α1 and α2 can be calculated from the left lane line information and the right lane line information. Then the estimated overall lane curvature ρ, heading angle Yaw and lateral offset α are:
即，基于同样权重的左侧车道线信息和右侧车道线信息进行车道线预估。That is, the lane line estimation is performed based on the left lane line information and the right lane line information with the same weight.
(2)当第一强度大于或等于零、第二强度小于零时，基于左侧车道线信息确定当前时刻的车道线曲率、车辆航向角和车辆横向偏移。预估整体的车道线曲率ρ、航向角Yaw和横向偏移α分别为：(2) When the first intensity is greater than or equal to zero and the second intensity is less than zero, determine the lane line curvature, vehicle heading angle and vehicle lateral offset at the current moment based on the left lane line information. The estimated overall lane curvature ρ, heading angle Yaw and lateral offset α are:
(3)当第二强度大于或等于零、第一强度小于零时，基于右侧车道线信息确定当前时刻的车道线曲率、车辆航向角和车辆横向偏移。预估整体的车道线曲率ρ、航向角Yaw和横向偏移α分别为：(3) When the second intensity is greater than or equal to zero and the first intensity is less than zero, determine the lane line curvature, the vehicle heading angle and the vehicle lateral offset at the current moment based on the right lane line information. The estimated overall lane curvature ρ, heading angle Yaw and lateral offset α are:
(4)当第一强度和第二强度均小于零时，确定当前时刻的车道线曲率、车辆航向角和车辆横向偏移与前一时刻的车道线曲率、车辆航向角和车辆横向偏移相同。本实施例中的每个时刻可以是摄像头的每个采样时刻，可以用前一时刻、当前时刻、后一时刻来表示相邻的三个采样时刻。(4) When both the first intensity and the second intensity are less than zero, determine that the lane line curvature, vehicle heading angle and vehicle lateral offset at the current moment are the same as the lane curve curvature, vehicle heading angle and vehicle lateral offset at the previous moment . Each moment in this embodiment may be each sampling moment of the camera, and the previous moment, the current moment, and the next moment may be used to represent three adjacent sampling moments.
第一强度和第二强度均小于零，相当于当前时刻采集的左侧车道线信息和右侧车道线信息可信度均不高，此时不再重新进行车道线预估，而是保持与前一时刻的车道线曲率、车辆航向角和车辆横向偏移相同。Both the first intensity and the second intensity are less than zero, which means that the information about the left lane line and the right lane line information collected at the current moment are not very reliable. The lane line curvature, vehicle heading angle, and vehicle lateral offset are the same at the previous moment.
根据两侧车道线信息的不同强度进行车道线预估，可以提高车道线预估的准确率，降低错误估计的概率。Predicting lane lines according to the different intensities of lane line information on both sides can improve the accuracy of lane line prediction and reduce the probability of erroneous estimation.
优选地，本实施例的步骤S300中输出控制参数的频率与摄像头的采样频率相对应，并且输出的控制参数对应于输入参数的下一时刻。即，前一时刻的输入参数对应输出当前时刻的输出控制参数，当前时刻的输入参数对应输出后一时刻的输出控制参数。如此循环，构成完整的模型预测控制过程。Preferably, the frequency of the output control parameter in step S300 of this embodiment corresponds to the sampling frequency of the camera, and the output control parameter corresponds to the next moment of the input parameter. That is, the input parameters at the previous time correspond to the output control parameters at the current time, and the input parameters at the current time correspond to the output control parameters at the next time after the output. This cycle constitutes a complete model predictive control process.
实施例2Example 2
本施例提供一种消防车辆自动行驶装置20，如图2所示，包括：This embodiment provides an
信息采集单元21，用于利用多个感知器件采集与消防车辆相关的行驶信息，所述行驶信息包含位置信息、环境信息和运动状态信息；The information collection unit 21 is used for collecting driving information related to the fire fighting vehicle by using a plurality of sensing devices, and the driving information includes position information, environmental information and motion state information;
数据融合单元22，用于对采集到的所述行驶信息进行数据融合，以确定所述行驶信息中的可信数据；A data fusion unit 22, configured to perform data fusion on the collected driving information to determine credible data in the driving information;
控制参数输出单元23，用于将所述可信数据输入消防车辆的自动行驶模型，以输出与所述消防车辆相关的控制参数；a control parameter output unit 23, configured to input the credible data into the automatic driving model of the fire fighting vehicle to output control parameters related to the fire fighting vehicle;
自动行驶单元24，用于基于所述控制参数控制所述消防车辆自动行驶。The automatic driving unit 24 is configured to control the automatic driving of the fire fighting vehicle based on the control parameters.
实施例3Example 3
本实施例还提供一种计算机设备，如可以执行程序的智能手机、平板电脑、笔记本电脑、台式计算机、机架式服务器、刀片式服务器、塔式服务器或机柜式服务器(包括独立的服务器，或者多个服务器所组成的服务器集群)等。本实施例的计算机设备30至少包括但不限于：可通过系统总线相互通信连接的存储器31、处理器32，如图3所示。需要指出的是，图3仅示出了具有组件31-32的计算机设备30，但是应理解的是，并不要求实施所有示出的组件，可以替代的实施更多或者更少的组件。This embodiment also provides a computer device, such as a smart phone, a tablet computer, a notebook computer, a desktop computer, a rack server, a blade server, a tower server, or a cabinet server (including independent servers, or A server cluster composed of multiple servers), etc. The
本实施例中，存储器31(即可读存储介质)包括闪存、硬盘、多媒体卡、卡型存储器(例如，SD或DX存储器等)、随机访问存储器(RAM)、静态随机访问存储器(SRAM)、只读存储器(ROM)、电可擦除可编程只读存储器(EEPROM)、可编程只读存储器(PROM)、磁性存储器、磁盘、光盘等。在一些实施例中，存储器31可以是计算机设备30的内部存储单元，例如该计算机设备30的硬盘或内存。在另一些实施例中，存储器31也可以是计算机设备30的外部存储设备，例如该计算机设备30上配备的插接式硬盘，智能存储卡(Smart Media Card,SMC)，安全数字(Secure Digital,SD)卡，闪存卡(Flash Card)等。当然，存储器31还可以既包括计算机设备30的内部存储单元也包括其外部存储设备。本实施例中，存储器31通常用于存储安装于计算机设备30的操作系统和各类应用软件，例如实施例二的自动行驶装置20的程序代码等。此外，存储器31还可以用于暂时地存储已经输出或者将要输出的各类数据。In this embodiment, the memory 31 (ie, a readable storage medium) includes a flash memory, a hard disk, a multimedia card, a card-type memory (eg, SD or DX memory, etc.), random access memory (RAM), static random access memory (SRAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), Programmable Read Only Memory (PROM), Magnetic Memory, Magnetic Disk, Optical Disk, etc. In some embodiments, the
处理器32在一些实施例中可以是中央处理器(Central Processing Unit，CPU)、控制器、微控制器、微处理器、或其他数据处理芯片。该处理器32通常用于控制计算机设备30的总体操作。本实施例中，处理器32用于运行存储器31中存储的程序代码或者处理数据，例如运行消防汽车自动行驶装置500，以实现实施例一的消防汽车自动行驶方法。In some embodiments, the
实施例4Example 4
本实施例还提供一种计算机可读存储介质，如闪存、硬盘、多媒体卡、卡型存储器(例如，SD或DX存储器等)、随机访问存储器(RAM)、静态随机访问存储器(SRAM)、只读存储器(ROM)、电可擦除可编程只读存储器(EEPROM)、可编程只读存储器(PROM)、磁性存储器、磁盘、光盘、服务器、App应用商城等等，其上存储有计算机程序，程序被处理器执行时实现相应功能。本实施例的计算机可读存储介质用于存储消防汽车自动行驶装置20，被处理器执行时实现实施例一的消防汽车自动行驶方法。This embodiment also provides a computer-readable storage medium, such as a flash memory, a hard disk, a multimedia card, a card-type memory (for example, SD or DX memory, etc.), random access memory (RAM), static random access memory (SRAM), only Read-only memory (ROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Programmable Read-Only Memory (PROM), magnetic memory, magnetic disk, optical disk, server, App application mall, etc., on which computer programs are stored, When the program is executed by the processor, the corresponding function is realized. The computer-readable storage medium of this embodiment is used to store the fire-fighting vehicle
显然，上述实施例仅仅是为清楚地说明所作的举例，而并非对实施方式的限定。对于所属领域的普通技术人员来说，在上述说明的基础上还可以做出其它不同形式的变化或变动。这里无需也无法对所有的实施方式予以穷举。而由此所引伸出的显而易见的变化或变动仍处于本发明创造的保护范围之中。Obviously, the above-mentioned embodiments are only examples for clear description, and are not intended to limit the implementation manner. For those of ordinary skill in the art, changes or modifications in other different forms can also be made on the basis of the above description. There is no need and cannot be exhaustive of all implementations here. And the obvious changes or changes derived from this are still within the protection scope of the present invention.
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