技术领域Technical Field
本公开涉及列车安全领域，具体地，涉及一种轨道交通场景的场景危害识别方法、装置、介质及设备。The present disclosure relates to the field of train safety, and in particular, to a method, device, medium and equipment for identifying scene hazards in rail transit scenes.
背景技术Background Art
随着轨道交通的快速发展，针对轨道交通的独立的安全管理方法仍有欠缺。为了保证轨道交通的安全，对于轨道交通的安全管理至关重要，而安全管理通常采用至上而下的工作方式，在安全管理活动的顶层，最重要的一点就是要先能够对轨道交通场景中所面临的场景危害进行识别，从而才能根据识别得到的场景危害来对风险加以控制。With the rapid development of rail transit, there is still a lack of independent safety management methods for rail transit. In order to ensure the safety of rail transit, safety management of rail transit is crucial, and safety management usually adopts a top-down working method. At the top level of safety management activities, the most important point is to first be able to identify the scene hazards faced in rail transit scenes, so that risks can be controlled based on the identified scene hazards.
在现有技术中，常用于识别上述场景危害的标准包括三种通用的国际标准和团体标准，但是在实际的应用中，例如在对轨道交通场景中的场景危害进行识别的过程中，上述通用标准往往不能很好的与实际应用相结合，从而导致对于该轨道交通场景的场景危害识别结果不够全面清楚。In the prior art, the standards commonly used to identify the above-mentioned scene hazards include three general international standards and group standards. However, in actual applications, for example, in the process of identifying scene hazards in rail transit scenes, the above-mentioned general standards are often not well combined with actual applications, resulting in the scene hazard identification results for the rail transit scene being not comprehensive and clear enough.
发明内容Summary of the invention
本公开的目的是提供一种轨道交通场景的场景危害识别方法、装置、介质及设备，能够通过针对该轨道交通场景的危害因素和与危害因素对应的目标状态来对轨道交通场景所对应的场景危害进行识别，从而使得对于该轨道交通场景的场景危害识别结果能够更加全面，清楚，从而使得安全人员能够更加准确地对该轨道交通场景中的场景危害进行控制，降低该轨道交通场景中安全事故发生的可能性。The purpose of the present disclosure is to provide a scene hazard identification method, device, medium and equipment for a rail transit scene, which can identify the scene hazards corresponding to the rail transit scene by targeting the hazard factors of the rail transit scene and the target states corresponding to the hazard factors, so that the scene hazard identification results for the rail transit scene can be more comprehensive and clear, so that safety personnel can more accurately control the scene hazards in the rail transit scene and reduce the possibility of safety accidents in the rail transit scene.
为了实现上述目的，本公开提供一种轨道交通场景的场景危害识别方法，所述方法包括：In order to achieve the above object, the present disclosure provides a method for identifying scene hazards in a rail transit scene, the method comprising:
获取待识别场景的危害因素，所述危害因素至少包括列车因素，地点因素，人员因素；Acquire hazard factors of the scene to be identified, where the hazard factors at least include train factors, location factors, and personnel factors;
确定与所述危害因素对应的目标状态；determining a target state corresponding to the hazard factor;
根据所述待识别场景的所述危害因素以及与所述危害因素对应的目标状态识别与所述待识别场景对应的场景危害。The scene hazard corresponding to the scene to be identified is identified according to the hazard factor of the scene to be identified and the target state corresponding to the hazard factor.
可选地，所述目标状态包括一级目标状态和二级目标状态，所述一级目标状态与所述二级目标状态之间为一对多或一对一的对应关系；Optionally, the target state includes a primary target state and a secondary target state, and there is a one-to-many or one-to-one correspondence between the primary target state and the secondary target state;
所述根据所述待识别场景的所述危害因素以及与所述危害因素对应的目标状态识别与所述待识别场景对应的场景危害包括：The step of identifying the scene hazard corresponding to the scene to be identified according to the hazard factor of the scene to be identified and the target state corresponding to the hazard factor comprises:
根据所述待识别场景的所述危害因素以及与所述危害因素对应的所述一级目标状态和所述二级目标状态识别与所述待识别场景对应的场景危害。The scene hazard corresponding to the scene to be identified is identified according to the hazard factor of the scene to be identified and the primary target state and the secondary target state corresponding to the hazard factor.
可选地，所述根据所述待识别场景的所述危害因素以及与所述危害因素对应的目标状态识别与所述待识别场景对应的场景危害包括：Optionally, the identifying the scene hazard corresponding to the scene to be identified according to the hazard factor of the scene to be identified and the target state corresponding to the hazard factor includes:
根据所述待识别场景的所述危害因素以及与所述危害因素对应的目标状态在预设场景危害数据库中查找识别与所述待识别场景对应的场景危害。According to the hazard factors of the scene to be identified and the target states corresponding to the hazard factors, the scene hazards corresponding to the scene to be identified are searched and identified in a preset scene hazard database.
可选地，在所述获取待识别场景的危害因素之前，所述方法还包括：Optionally, before obtaining the hazard factors of the scene to be identified, the method further includes:
基于所述待识别场景中的所有所述危害因素，和所述危害因素所对应的状态，构建与所述待识别场景对应的所述预设场景危害数据库。Based on all the hazard factors in the scene to be identified and the states corresponding to the hazard factors, the preset scene hazard database corresponding to the scene to be identified is constructed.
可选地，所述方法还包括：Optionally, the method further comprises:
获取所述待识别场景的场景属性，所述场景数据至少包括驾驶模式，运行级别，线路特征中的一者；Acquiring scene attributes of the scene to be identified, wherein the scene data includes at least one of a driving mode, an operating level, and a route feature;
所述根据所述待识别场景的所述危害因素以及与所述危害因素对应的目标状态在预设场景危害数据库中查找识别与所述待识别场景对应的场景危害包括：The searching and identifying the scene hazard corresponding to the scene to be identified in a preset scene hazard database according to the hazard factor of the scene to be identified and the target state corresponding to the hazard factor comprises:
根据所述待识别场景的所述危害因素，与所述危害因素对应的目标状态，以及所述场景属性在所述预设场景危害数据库中查找识别与所述待识别场景对应的场景危害。The scene hazard corresponding to the scene to be identified is searched and identified in the preset scene hazard database according to the hazard factor of the scene to be identified, the target state corresponding to the hazard factor, and the scene attribute.
可选地，所述基于所述待识别场景中的所有所述危害因素，和所述危害因素所对应的状态，构建与所述待识别场景对应的所述预设场景危害数据库包括：Optionally, the constructing the preset scene hazard database corresponding to the scene to be identified based on all the hazard factors in the scene to be identified and the states corresponding to the hazard factors includes:
基于所述待识别场景中的所有所述危害因素，所述危害因素所对应的状态，和所述待识别场景的所有所述场景属性，构建与所述待识别场景对应的所述预设场景危害数据库。Based on all the hazard factors in the scene to be identified, the states corresponding to the hazard factors, and all the scene attributes of the scene to be identified, the preset scene hazard database corresponding to the scene to be identified is constructed.
可选地，所述基于所述待识别场景中的所有所述危害因素，和所述危害因素所对应的状态，构建与所述待识别场景对应的所述预设场景危害数据库包括：Optionally, the constructing the preset scene hazard database corresponding to the scene to be identified based on all the hazard factors in the scene to be identified and the states corresponding to the hazard factors includes:
获取所述待识别场景中的所有所述危害因素；Acquire all the hazard factors in the scene to be identified;
获取每个所述危害因素所对应的所有因素值；Obtain all factor values corresponding to each of the hazard factors;
逐次从每个所述危害因素中选取一个所述因素值作为目标因素值，对所有所述目标因素值进行排列组合；Selecting one factor value from each of the hazard factors one by one as a target factor value, and performing permutations and combinations on all the target factor values;
将每个排列组合与所述危害因素所对应的状态进行组合，以构建所述预设场景危害数据库。Each permutation and combination is combined with the state corresponding to the hazard factor to construct the preset scenario hazard database.
本公开还提供一种轨道交通场景的场景危害识别装置，所述装置包括：The present disclosure also provides a scene hazard identification device for a rail transit scene, the device comprising:
第一获取模块，用于获取待识别场景的危害因素，所述危害因素至少包括列车因素，地点因素，人员因素；A first acquisition module is used to acquire the hazard factors of the scene to be identified, wherein the hazard factors at least include train factors, location factors, and personnel factors;
确定模块，用于确定与所述危害因素对应的目标状态；A determination module, used to determine a target state corresponding to the hazard factor;
识别模块，用于根据所述待识别场景的所述危害因素以及与所述危害因素对应的目标状态识别与所述待识别场景对应的场景危害。An identification module is used to identify the scene hazard corresponding to the scene to be identified based on the hazard factor of the scene to be identified and the target state corresponding to the hazard factor.
本公开还提供一种计算机可读存储介质，其上存储有计算机程序，该程序被处理器执行时实现以上所述轨道交通场景的场景危害识别方法的步骤。The present disclosure also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method for identifying scene hazards in rail transit scenes described above.
本公开还提供一种电子设备，包括：The present disclosure also provides an electronic device, comprising:
存储器，其上存储有计算机程序；a memory having a computer program stored thereon;
处理器，用于执行所述存储器中的所述计算机程序，以实现以上所述轨道交通场景的场景危害识别方法的步骤。A processor is used to execute the computer program in the memory to implement the steps of the scene hazard identification method for the rail transit scene described above.
通过上述技术方案，能够通过针对该轨道交通场景的危害因素和与危害因素对应的目标状态来对轨道交通场景所对应的场景危害进行识别，从而使得对于该轨道交通场景的场景危害识别结果能够更加全面，清楚，从而使得安全人员能够更加准确地对该轨道交通场景中的场景危害进行控制，降低该轨道交通场景中安全事故发生的可能性。Through the above technical scheme, the scene hazards corresponding to the rail transit scene can be identified by targeting the hazard factors of the rail transit scene and the target states corresponding to the hazard factors, so that the scene hazard identification results for the rail transit scene can be more comprehensive and clear, so that safety personnel can more accurately control the scene hazards in the rail transit scene and reduce the possibility of safety accidents in the rail transit scene.
本公开的其他特征和优点将在随后的具体实施方式部分予以详细说明。Other features and advantages of the present disclosure will be described in detail in the following detailed description.
附图说明BRIEF DESCRIPTION OF THE DRAWINGS
附图是用来提供对本公开的进一步理解，并且构成说明书的一部分，与下面的具体实施方式一起用于解释本公开，但并不构成对本公开的限制。在附图中：The accompanying drawings are used to provide a further understanding of the present disclosure and constitute a part of the specification. Together with the following specific embodiments, they are used to explain the present disclosure but do not constitute a limitation of the present disclosure. In the accompanying drawings:
图1是根据本公开一示例性实施例示出的一种轨道交通场景的场景危害识别方法的流程图。FIG1 is a flow chart of a method for identifying scene hazards in a rail transit scene according to an exemplary embodiment of the present disclosure.
图2是根据本公开又一示例性实施例示出的一种轨道交通场景的场景危害识别方法的流程图。FIG2 is a flow chart of a method for identifying scene hazards in a rail transit scene according to yet another exemplary embodiment of the present disclosure.
图3是根据本公开又一示例性实施例示出的一种轨道交通场景的场景危害识别方法的流程图。FIG3 is a flow chart of a method for identifying scene hazards in a rail transit scene according to yet another exemplary embodiment of the present disclosure.
图4是根据本公开又一示例性实施例示出的一种轨道交通场景的场景危害识别方法的流程图。FIG4 is a flow chart of a method for identifying scene hazards in a rail transit scene according to yet another exemplary embodiment of the present disclosure.
图5是根据本公开又一示例性实施例示出的一种轨道交通场景的场景危害识别方法中构建预设场景危害数据库的方法的流程图。FIG5 is a flowchart of a method for constructing a preset scene hazard database in a scene hazard identification method for a rail transit scene according to yet another exemplary embodiment of the present disclosure.
图6是根据本公开一示例性实施例示出的一种轨道交通场景的场景危害识别装置的结构框图。FIG6 is a structural block diagram of a scene hazard identification device for a rail transit scene according to an exemplary embodiment of the present disclosure.
图7是根据本公开又一示例性实施例示出的一种轨道交通场景的场景危害识别装置的结构框图。FIG7 is a structural block diagram of a scene hazard identification device for a rail transit scene according to yet another exemplary embodiment of the present disclosure.
图8是根据本公开又一示例性实施例示出的一种轨道交通场景的场景危害识别装置的结构框图。FIG8 is a structural block diagram of a scene hazard identification device for a rail transit scene according to yet another exemplary embodiment of the present disclosure.
图9是根据一示例性实施例示出的一种电子设备的框图。Fig. 9 is a block diagram of an electronic device according to an exemplary embodiment.
图10是根据又一示例性实施例示出的一种电子设备的框图。Fig. 10 is a block diagram of an electronic device according to yet another exemplary embodiment.
具体实施方式DETAILED DESCRIPTION
以下结合附图对本公开的具体实施方式进行详细说明。应当理解的是，此处所描述的具体实施方式仅用于说明和解释本公开，并不用于限制本公开。The specific implementation of the present disclosure is described in detail below in conjunction with the accompanying drawings. It should be understood that the specific implementation described herein is only used to illustrate and explain the present disclosure, and is not used to limit the present disclosure.
图1是根据本公开一示例性实施例示出的一种轨道交通场景的场景危害识别方法的流程图。如图1所示，所述方法包括步骤101至步骤103。Fig. 1 is a flow chart of a method for identifying scene hazards in a rail transit scene according to an exemplary embodiment of the present disclosure. As shown in Fig. 1 , the method includes steps 101 to 103 .
在步骤101中，获取待识别场景的危害因素，所述危害因素至少包括列车因素，地点因素，人员因素。In step 101, the hazard factors of the scene to be identified are obtained, and the hazard factors at least include train factors, location factors, and personnel factors.
其中，每个危害因素都可以包括多个因素值，例如，列车因素可以包括列车运动、列车静止、列车内部、无列车四个因素值，地点因素可以包括中心（例如主/备控制中心）、场段（包括停车场或车辆段）、区间、车站（含试车线）四个因素值，人员因素可以包括乘客、员工、公众（包括应急救援群体）三个因素值。上述每个危害因素的因素值都是根据轨道交通场景中可能出现的危害因素而确定的。Each hazard factor can include multiple factor values. For example, the train factor can include four factor values: train movement, train stationary, train interior, and no train. The location factor can include four factor values: center (such as main/standby control center), yard (including parking lot or vehicle depot), section, and station (including test line). The personnel factor can include three factor values: passengers, employees, and the public (including emergency rescue groups). The factor value of each of the above hazard factors is determined according to the hazard factors that may appear in the rail transit scenario.
另外，该危害因素中除了该列车因素，地点因素和该人员因素之外，还可以包括其他未在本公开中示例的危害因素。In addition, the hazard factor may include other hazard factors not exemplified in the present disclosure in addition to the train factor, the location factor and the personnel factor.
在获取该待识别场景中的危害因素时，获取到的每个危害因素可以仅包括一个因素值，也可以包括多个因素值。例如，在该待识别场景为列车在运行中的场景时，该待识别场景的危害因素中，列车因素的因素值可以包括列车运动和列车内部，而由于列车在运行中可能会经过多种地点，因此在该待识别场景的危害因素的地点因素可以包括例如中心、区间、场段和车站等四个因素值。同样的，对于该列车在运行中的待识别场景，其危害因素中的人员因素也可以包括乘客、员工、公众三个因素值，因为在该待识别场景中，三种人员都有可能出现。When obtaining the hazard factors in the scene to be identified, each hazard factor obtained may include only one factor value or multiple factor values. For example, when the scene to be identified is a scene in which a train is in motion, the factor values of the train factors in the hazard factors of the scene to be identified may include train movement and the interior of the train. Since the train may pass through a variety of locations during operation, the location factors of the hazard factors in the scene to be identified may include four factor values such as center, section, yard, and station. Similarly, for the scene to be identified in which the train is in motion, the personnel factors in its hazard factors may also include three factor values of passengers, employees, and the public, because all three types of personnel may appear in the scene to be identified.
在步骤102中，确定与所述危害因素对应的目标状态。In step 102, a target state corresponding to the hazard factor is determined.
在获取到该待识别场景中的危害因素之后，可以确定与该危害因素对应的目标状态。该目标状态可以是通过该危害因素的因素值来确定，或者还可以是通过对该待识别场景的监测状况实时判断得到的。该目标状态可以为该待识别场景中可能存在的状态，例如列车与列车相撞，列车与障碍物相撞，或者火灾与爆炸，环境不满足该待识别场景的安全环境要求等。After obtaining the hazard factor in the scene to be identified, the target state corresponding to the hazard factor can be determined. The target state can be determined by the factor value of the hazard factor, or can be obtained by real-time judgment of the monitoring status of the scene to be identified. The target state can be a state that may exist in the scene to be identified, such as a train collision, a train collision with an obstacle, or a fire and explosion, the environment does not meet the safety environment requirements of the scene to be identified, etc.
例如，在该目标状态是根据该危害因素的因素值确定的情况下，在上述待识别场景为列车在运行中的场景中，该列车因素的因素值为列车运动和列车内部，而在该列车因素为列车运动的情况下，该待识别场景中可能出现的状态可能有列车与列车相撞，列车与障碍物相撞，列车与人相撞，列车脱轨，火灾与爆炸，环境不满足该待识别场景的安全环境要求，出现需要应急与救援的情况，或者其他的意外情况，例如未进行封锁时，员工在轨行区进行维护，道岔突然转动等；在该列车因素为列车内部的情况下，该待识别场景中可能出现的状态有例如在列车内部发生危害。For example, in the case where the target state is determined based on the factor value of the hazard factor, in the above-mentioned scene to be identified is a scene in which a train is in operation, the factor value of the train factor is train movement and train interior, and in the case where the train factor is train movement, the states that may occur in the scene to be identified may include train-to-train collision, train-to-obstacle collision, train-to-person collision, train derailment, fire and explosion, the environment does not meet the safety environment requirements of the scene to be identified, situations requiring emergency response and rescue, or other unexpected situations, such as employees performing maintenance in the track area when no blockade is carried out, sudden rotation of switches, etc.; in the case where the train factor is the interior of a train, the states that may occur in the scene to be identified include, for example, hazards occurring inside the train.
由于该待识别场景中的危害因素中不仅包括列车因素，还包括地点因素和人员因素，因此在确定与该危害因素对应的目标状态时，不仅会根据该列车因素的因素值来确定该待识别场景中可能出现的状态，而且还会根据地点因素的因素值和人员因素的因素值来分别确定该待识别场景中可能出现的状态。最后只会将分别与该列车因素、地点因素、人员因素都有对应关系的状态确定为该目标状态。例如，上述列车与列车相撞的状态能够与该列车要素中的列车运动相对应，也能够与该地点要素中的区间或场段或车站相对应，还能够与该人员要素中的乘客或员工或公众相对应，则该列车与列车相撞，就可以为确定为与该危害因素对应的目标状态。Since the hazard factors in the scene to be identified include not only train factors, but also location factors and personnel factors, when determining the target state corresponding to the hazard factor, not only the possible states in the scene to be identified will be determined based on the factor value of the train factor, but also the possible states in the scene to be identified will be determined based on the factor value of the location factor and the factor value of the personnel factor. Finally, only the states that have corresponding relationships with the train factor, location factor, and personnel factor will be determined as the target state. For example, the state of the above-mentioned train-to-train collision can correspond to the train movement in the train element, can also correspond to the section or field or station in the location element, and can also correspond to the passengers or employees or the public in the personnel element. In this case, the train-to-train collision can be determined as the target state corresponding to the hazard factor.
该状态分别与不同危害因素的因素值之间的对应关系可以是预先设置好的，例如，可以是为表1所示的预设对应关系表。The corresponding relationships between the states and the factor values of different hazard factors may be preset, for example, may be a preset corresponding relationship table as shown in Table 1.
表1Table 1
其中，该“环境”状态即可以表征该待识别场景的环境不满足该待识别场景的安全环境要求的状态，该待识别场景的环境可以包括例如自然环境和社会环境，自然环境中可以包括例如温度环境，湿度环境，电磁环境等，社会环境可以包括例如人为恶意破坏情况，基础设置承载不足等等。该“应急与救援”状态即可以表征该待识别场景中出现需要应急与救援的情况的状态，该应急与救援可以包括例如救援、疏散等。该“车站外危害”即可以表征例如列车静止或无列车时，车站固有的一些危害，如：进行乘降作业时，站台门和车门未对应打开，站台门故障、车门与站台门缝隙过大等导致人员从站台跌入轨道等车站特有的状态。该“车内危害”即可以表征列车自身的故障造成的危害，如车门在运行过程中打开，故障列车投入运营，列车蠕动运行等。Among them, the "environment" state can represent the state in which the environment of the scene to be identified does not meet the safety environment requirements of the scene to be identified. The environment of the scene to be identified may include, for example, the natural environment and the social environment. The natural environment may include, for example, the temperature environment, the humidity environment, the electromagnetic environment, etc. The social environment may include, for example, malicious human damage, insufficient infrastructure, etc. The "emergency and rescue" state can represent the state in which the scene to be identified requires emergency and rescue. The emergency and rescue may include, for example, rescue, evacuation, etc. The "hazards outside the station" can represent some inherent hazards of the station when the train is stationary or there is no train, such as: when the platform door and the car door are not opened correspondingly during the boarding and alighting operation, the platform door is faulty, the gap between the car door and the platform door is too large, etc., which causes people to fall from the platform into the track and other station-specific states. The "hazards inside the car" can represent the hazards caused by the failure of the train itself, such as the car door opening during operation, the faulty train being put into operation, the train running in a creeping manner, etc.
该状态也可以包括其他状态，表1中所示的该状态仅仅是根据本公开的一种示例。根据该示例的预设对应关系表，则可以在确定了该待识别场景的危害因素的情况下，确定与该危害因素对应的该目标状态。The state may also include other states, and the state shown in Table 1 is only an example according to the present disclosure. According to the preset correspondence table of this example, when the hazard factor of the scene to be identified is determined, the target state corresponding to the hazard factor can be determined.
在步骤103中，根据所述待识别场景的所述危害因素以及与所述危害因素对应的目标状态识别与所述待识别场景对应的场景危害。In step 103, the scene hazard corresponding to the scene to be identified is identified based on the hazard factor of the scene to be identified and the target state corresponding to the hazard factor.
确定与该待识别场景对应的场景危害的方式可以是通过步骤101中确定的危害因素，以及通过步骤102确定的与该危害因素对应的目标状态，直接通过预设生成模型来自动生成该场景危害。The method of determining the scene hazard corresponding to the scene to be identified can be to automatically generate the scene hazard directly through a preset generation model through the hazard factor determined in step 101 and the target state corresponding to the hazard factor determined in step 102.
例如，在上述待识别场景为列车在运行中的场景时，该列车因素的因素值中可以包括列车运动，该地点因素的因素值中可以包括区间，该人员因素的因素值中可以包括乘客，在该待识别场景中根据该危害因素所对应的目标状态中可以包括列车与列车相撞。在此情况下，则可以直接通过该预设生成模型，根据上述危害因素和与该危害因素对应的目标状态生成如下场景危害：列车运动过程中，在区间列车与列车相撞，乘客受到伤害。For example, when the above-mentioned scene to be identified is a scene in which a train is in motion, the factor value of the train factor may include train movement, the factor value of the location factor may include intervals, the factor value of the personnel factor may include passengers, and the target state corresponding to the hazard factor in the scene to be identified may include a train-to-train collision. In this case, the preset generation model can be directly used to generate the following scene hazard according to the above-mentioned hazard factors and the target state corresponding to the hazard factors: During the movement of the train, the train collides with the train in the interval, and the passengers are injured.
具体的，表2中给出了在上述待识别场景为列车在运行中的场景中，在该目标状态为列车与列车相撞，列车因素的因素值为列车运动的情况下，根据与该目标状态和列车因素对应的地点因素和人员因素，通过该预设生成模型自动生成场景危害的一种示例。Specifically, Table 2 gives an example of automatically generating scene hazards through the preset generation model according to location factors and personnel factors corresponding to the target state and train factors, when the above-mentioned scene to be identified is a scene in which a train is in motion, the target state is a train-train collision, and the factor value of the train factor is train movement.
表2Table 2
如表2中所示，该预设生成模型根据该目标状态和危害因素，便可自动生成用于表征该待识别场景所对应的场景危害的语段，进而就可以对该待识别场景所对应的场景危害进行识别。As shown in Table 2, the preset generation model can automatically generate a paragraph for characterizing the scene hazard corresponding to the scene to be identified based on the target state and hazard factors, and then identify the scene hazard corresponding to the scene to be identified.
在上述待识别场景为列车在运行中的场景中，根据危害因素所确定的目标状态还可以有其他状态，危害因素例如列车因素中所包括的因素值也还可以包括其他因素值，表2仅仅只是对该预设生成模型根据该危害因素和目标装填生成表征该场景危害的语段的示例。In the above-mentioned scenario to be identified where the train is in operation, the target state determined according to the hazard factor may also have other states, and the factor values included in the hazard factor such as the train factor may also include other factor values. Table 2 is only an example of generating a paragraph representing the hazard of the scenario according to the hazard factor and the target loading for the preset generation model.
另外，根据所述待识别场景的所述危害因素以及与所述危害因素对应的目标状态识别与所述待识别场景对应的场景危害还可以通过预设场景危害数据库来实现，具体的将在之后的内容进行详细描述。In addition, identifying the scene hazards corresponding to the scene to be identified based on the hazard factors of the scene to be identified and the target states corresponding to the hazard factors can also be achieved by presetting a scene hazard database, which will be described in detail later.
通过上述技术方案提供的方法，能够通过针对该轨道交通场景的危害因素和与危害因素对应的目标状态来对轨道交通场景所对应的场景危害进行识别，从而使得对于该轨道交通场景的场景危害识别结果能够更加全面，清楚，从而使得安全人员能够更加准确地对该轨道交通场景中的场景危害进行控制，降低该轨道交通场景中安全事故发生的可能性。Through the method provided by the above technical solution, the scene hazards corresponding to the rail transit scene can be identified by targeting the hazard factors of the rail transit scene and the target states corresponding to the hazard factors, so that the scene hazard identification results for the rail transit scene can be more comprehensive and clear, so that safety personnel can more accurately control the scene hazards in the rail transit scene and reduce the possibility of safety accidents in the rail transit scene.
在一种可能的实施方式中，所述目标状态包括一级目标状态和二级目标状态，所述一级目标状态与所述二级目标状态之间为一对多或一对一的对应关系；图1所示的步骤103还可以为：根据所述待识别场景的所述危害因素以及与所述危害因素对应的所述一级目标状态和所述二级目标状态识别与所述待识别场景对应的场景危害。In a possible implementation, the target state includes a primary target state and a secondary target state, and there is a one-to-many or one-to-one correspondence between the primary target state and the secondary target state; step 103 shown in Figure 1 can also be: identifying the scene hazard corresponding to the scene to be identified according to the hazard factor of the scene to be identified and the primary target state and the secondary target state corresponding to the hazard factor.
以该目标状态为列车与列车相撞为例，该目标状态中所包括的该一级目标状态则可以为列车与列车相撞，与该一级目标状态对应的该二级目标状态则可以为例如列车追尾相撞、列车后退相撞、列车侧面相撞、列车迎面相撞、列车解体相撞等。Taking the target state of train-to-train collision as an example, the first-level target state included in the target state can be train-to-train collision, and the second-level target state corresponding to the first-level target state can be, for example, train rear-end collision, train backward collision, train side collision, train head-on collision, train disintegration collision, etc.
该目标状态中所包括的一级目标状态与二级目标状态都是预设好的，该一级目标状态与二级目标状态之间的对应关系也都是预设好的。在通过上述方法确定了在该待识别场景中与该危害因素对应的该目标状态的情况下，就能够确定其中所包括的该以及目标状态、二级目标状态以及其二者之间的对应关系。The primary target state and the secondary target state included in the target state are preset, and the corresponding relationship between the primary target state and the secondary target state is also preset. When the target state corresponding to the hazard factor in the scene to be identified is determined by the above method, the target state, the secondary target state and the corresponding relationship between the two can be determined.
而在该目标状态中包括该一级目标状态和该二级目标状态的情况下，通过上述根据预设生成模型自动生成该场景危害时，则需要根据该一级目标状态与二级目标状态共同生成。In the case where the target state includes the primary target state and the secondary target state, when the scenario hazard is automatically generated according to the preset generation model, it is necessary to generate it together with the primary target state and the secondary target state.
表3给出了在与表2相同的情况下，该目标状态中包括的一级目标状态为列车与列车相撞，且与该一级目标状态向对应的该二级目标状态为列车追尾相撞、列车后退相撞、列车侧面相撞、列车解体相撞时，通过该预设生成模型识别场景危害的示例。Table 3 gives an example of identifying scenario hazards through the preset generation model under the same circumstances as Table 2, when the first-level target state included in the target state is a train-train collision, and the second-level target state corresponding to the first-level target state is a train rear-end collision, a train backward collision, a train side collision, and a train disintegration collision.
表3Table 3
通过上述技术方案，能够通过对该目标状态中一级目标状态和二级目标状态的设置，将该目标状态所表征的该待识别场景可能对应的场景危害进行更加细粒度的划分，从而能够使得在对该待识别场景中对其对应的场景危害进行识别时，识别得到更加具体的场景危害，进而使得安全人员能够更加准确地对该轨道交通场景中的场景危害进行控制，进一步降低该轨道交通场景中安全事故发生的可能性。Through the above technical scheme, by setting the first-level target state and the second-level target state in the target state, the scene hazards that may correspond to the scene to be identified represented by the target state can be divided more finely, so that when identifying the corresponding scene hazards in the scene to be identified, more specific scene hazards can be identified, thereby enabling safety personnel to more accurately control the scene hazards in the rail transit scene, and further reduce the possibility of safety accidents in the rail transit scene.
图2是根据本公开又一示例性实施例示出的一种轨道交通场景的场景危害识别方法的流程图。如图2所示，所述方法包括步骤101和步骤102，还包括步骤201。Fig. 2 is a flow chart of a method for identifying scene hazards in a rail transit scene according to another exemplary embodiment of the present disclosure. As shown in Fig. 2 , the method includes steps 101 and 102 , and further includes step 201 .
在步骤201中，根据所述待识别场景的所述危害因素以及与所述危害因素对应的目标状态在预设场景危害数据库中查找识别与所述待识别场景对应的场景危害。In step 201, the scene hazards corresponding to the scene to be identified are searched and identified in a preset scene hazard database according to the hazard factors of the scene to be identified and the target states corresponding to the hazard factors.
该预设场景危害数据库可以是预先将所有状态与危害因素都列举之后预先生成的包括所有场景危害的数据库，其中包括所有已知场景危害，以及每个场景危害与每个危害因素的因素值以及该状态之间的对应关系。在需要对该待识别场景进行场景危害的识别的情况下，只需要获取该待识别场景的危害因素，并确定与该危害因素对应的目标状态，就可以在该预设场景危害数据库中查找到于该危害因素和目标状态对应的场景危害。The preset scene hazard database may be a database of all scene hazards that is pre-generated after all states and hazard factors are listed in advance, including all known scene hazards, and the corresponding relationship between each scene hazard and the factor value of each hazard factor and the state. In the case where the scene hazard needs to be identified for the scene to be identified, it is only necessary to obtain the hazard factor of the scene to be identified and determine the target state corresponding to the hazard factor, and then the scene hazard corresponding to the hazard factor and the target state can be found in the preset scene hazard database.
通过上述技术方案，能够进一步简化对该轨道交通场景的场景危害进行识别的过程，不仅能够识别得到更加全面的场景危害，而且提高了对该场景危害的识别速度。Through the above technical solution, the process of identifying the scene hazards of the rail transit scene can be further simplified, which can not only identify more comprehensive scene hazards but also improve the speed of identifying the scene hazards.
图3是根据本公开又一示例性实施例示出的一种轨道交通场景的场景危害识别方法的流程图。如图3所示，所述方法包括步骤101、步骤102和步骤201，还包括步骤301。Fig. 3 is a flow chart of a method for identifying scene hazards in a rail transit scene according to another exemplary embodiment of the present disclosure. As shown in Fig. 3 , the method includes steps 101 , 102 , and 201 , and further includes step 301 .
在步骤301中，基于所述待识别场景中的所有所述危害因素，和所述危害因素所对应的状态，构建与所述待识别场景对应的所述预设场景危害数据库。In step 301, based on all the hazard factors in the scene to be identified and the states corresponding to the hazard factors, the preset scene hazard database corresponding to the scene to be identified is constructed.
由于不同的待识别场景所适用的目标状态和危害因素有可能不同，因此，在根据该预设场景危害数据库来识别该待识别场景对应的场景危害时，可以预先根据不同的待识别场景来确定所有可能包括的危害因素，以及与该危害因素对应的可能的状态，从而来针对该待识别场景进行该预设场景危害数据库的构建。Since the target states and hazard factors applicable to different scenes to be identified may be different, when identifying the scene hazards corresponding to the scene to be identified based on the preset scene hazard database, all possible hazard factors and possible states corresponding to the hazard factors can be determined in advance based on different scenes to be identified, so as to construct the preset scene hazard database for the scene to be identified.
图4是根据本公开又一示例性实施例示出的一种轨道交通场景的场景危害识别方法的流程图。如图4所示，所述方法包括步骤101、步骤102和步骤301，还包括步骤402和步骤403。Fig. 4 is a flow chart of a method for identifying scene hazards in a rail transit scene according to another exemplary embodiment of the present disclosure. As shown in Fig. 4 , the method includes steps 101 , 102 and 301 , and also includes steps 402 and 403 .
在步骤402中，获取所述待识别场景的场景属性，所述场景数据至少包括驾驶模式，运行级别，线路特征中的一者。In step 402, the scene attributes of the scene to be identified are obtained, and the scene data includes at least one of a driving mode, an operating level, and a route feature.
该驾驶模式可以为例如全自动无人驾驶模式(FAM)或列车自动驾驶模式(AM)等，运行级别可以为例如无驾驶员运行 (Driverless Train Operation, DTO)或无人看守运行 (Unattended Train Operation, UTO)等，线路特征可以为例如地上线路或地下线路等。另外该场景属性还可以包括例如场景中所包括的列车的产品制式，例如地铁或者磁悬浮等。上述场景属性在确定该待识别场景的情况下就可以相应确定。The driving mode may be, for example, a fully automatic unmanned driving mode (FAM) or an automatic train driving mode (AM), the operation level may be, for example, a driverless train operation (DTO) or an unattended train operation (UTO), and the line feature may be, for example, an above-ground line or an underground line. In addition, the scene attribute may also include, for example, a product format of a train included in the scene, such as a subway or a maglev. The above scene attributes may be determined accordingly when the scene to be identified is determined.
在步骤403中，根据所述待识别场景的所述危害因素，与所述危害因素对应的目标状态，以及所述场景属性在所述预设场景危害数据库中查找识别与所述待识别场景对应的场景危害。In step 403, the scene hazard corresponding to the scene to be identified is searched and identified in the preset scene hazard database according to the hazard factor of the scene to be identified, the target state corresponding to the hazard factor, and the scene attribute.
在上述待识别场景为列车在运行中的场景的示例中，根据该待识别场景下所获取的危害因素以及与该危害因素对应的目标状态所识别得到的场景危害，可能会多于实际会出现的场景危害，例如，如表1中所示出的列车与障碍物相撞的状态被确定为目标状态，其中可以包括列车与障碍物相撞为一级目标状态，该一级目标状态可以对应但不仅对应如下两种二级目标状态：列车与防淹门相撞；列车与人防门相撞。上述两种二级目标状态仅存在与列车行驶于地下线路中的场景中，若该待识别场景中的列车都是行驶于地上线路，或者该待识别场景中的列车的产品制式为例如悬挂式等，则该待识别场景中一般不会出现上述列车与防淹门相撞和列车与人防门相撞的场景危害。In the above example where the scene to be identified is a scene where a train is running, the scene hazards identified based on the hazard factors obtained in the scene to be identified and the target state corresponding to the hazard factors may be more than the scene hazards that will actually occur. For example, the state of a train colliding with an obstacle as shown in Table 1 is determined as a target state, which may include a train colliding with an obstacle as a first-level target state. The first-level target state may correspond to but not only to the following two second-level target states: a train colliding with a flood-proof door; a train colliding with a civil air defense door. The above two second-level target states only exist in scenes where the train is running on underground lines. If the trains in the scene to be identified are all running on ground lines, or the product format of the trains in the scene to be identified is, for example, a suspended type, then the scene hazards of the train colliding with a flood-proof door and the train colliding with a civil air defense door generally will not appear in the scene to be identified.
因此，在识别该场景危害之前，对该待识别场景的场景属性进行获取，并在识别该场景危害时还根据该场景属性进行识别，则就能够进一步提高对该场景危害的识别准确性，进而使得安全人员够更加准确地对该轨道交通场景中的场景危害进行控制，进一步降低该轨道交通场景中安全事故发生的可能性。Therefore, before identifying the scene hazard, the scene attributes of the scene to be identified are obtained, and when identifying the scene hazard, it is also identified based on the scene attributes. This can further improve the accuracy of identifying the scene hazard, thereby enabling safety personnel to more accurately control the scene hazards in the rail transit scene, and further reduce the possibility of safety accidents in the rail transit scene.
在一种可能的实施方式中，如图4所示，所述方法还可以包括步骤401。在步骤401中，基于所述待识别场景中的所有所述危害因素，所述危害因素所对应的状态，和所述待识别场景的所有所述场景属性，构建与所述待识别场景对应的所述预设场景危害数据库。也即，在根据该场景属性在该预设场景危害数据库之前，先将基于该待识别场景中的所有场景属性对该预设场景危害数据库进行构建。从而就能够进一步提高对该场景危害的识别效率。In a possible implementation, as shown in FIG4 , the method may further include step 401. In step 401, based on all the hazard factors in the scene to be identified, the states corresponding to the hazard factors, and all the scene attributes of the scene to be identified, the preset scene hazard database corresponding to the scene to be identified is constructed. That is, before the preset scene hazard database is constructed based on the scene attributes, the preset scene hazard database is first constructed based on all the scene attributes of the scene to be identified. Thereby, the efficiency of identifying the hazard of the scene can be further improved.
图5是根据本公开又一示例性实施例示出的一种轨道交通场景的场景危害识别方法中构建预设场景危害数据库的方法的流程图。如图5所示，所述方法包括步骤501至步骤504。Fig. 5 is a flowchart of a method for constructing a preset scene hazard database in a scene hazard identification method for a rail transit scene according to another exemplary embodiment of the present disclosure. As shown in Fig. 5 , the method includes steps 501 to 504 .
在步骤501中，获取所述待识别场景中的所有所述危害因素。In step 501, all the hazard factors in the scene to be identified are obtained.
例如，该待识别场景中的所有危害因素可以如表1中所示，包括列车因素，地点因素，人员因素。For example, all the hazard factors in the scene to be identified may be as shown in Table 1, including train factors, location factors, and personnel factors.
在步骤502中，获取每个所述危害因素所对应的所有因素值。In step 502, all factor values corresponding to each of the hazard factors are obtained.
每个危害因素所对应的所有因素值也可以如表1中所示，该列车可以对应的所有因素值可以包括列车运动、列车静止、列车内部、无列车四个因素值，地点因素对应的所有因素值可以包括例如中心、场段、区间、车站四个因素值，人员因素对应的所有因素值可以包括例如乘客、员工、公众三个因素值。All factor values corresponding to each hazard factor can also be shown in Table 1. All factor values corresponding to the train can include four factor values: train movement, train stationary, train interior, and no train. All factor values corresponding to location factors can include, for example, four factor values: center, section, section, and station. All factor values corresponding to personnel factors can include, for example, three factor values: passengers, employees, and the public.
在步骤503中，逐次从每个所述危害因素中选取一个所述因素值作为目标因素值，对所有所述目标因素值进行排列组合。In step 503, one factor value is selected from each of the hazard factors as a target factor value, and all the target factor values are arranged and combined.
也即，可以在该列车因素中选择列车运动作为目标因素值，在该地点因素中选择区间作为目标因素值，在该人员因素中选择乘客作为目标因素值，这样就组成了一个组合，这样每次在一个危害因素中选择一个目标因素，就能得到多个排列组合，且每个排列组合中都包括每个危害因素中的一个因素值。That is, you can select train movement as the target factor value in the train factor, select the interval as the target factor value in the location factor, and select the passenger as the target factor value in the personnel factor, thus forming a combination. In this way, each time a target factor is selected in a hazard factor, you can get multiple permutations and combinations, and each permutation and combination includes a factor value from each hazard factor.
在步骤504中，将每个排列组合与所述危害因素所对应的状态进行组合，以构建所述预设场景危害数据库。In step 504, each permutation combination is combined with the state corresponding to the hazard factor to construct the preset scenario hazard database.
最后将步骤503中确定的排列组合分别与该待识别场景中可能出现的状态进行组合，就能得到最终的预设场景危害数据库。Finally, the permutations and combinations determined in step 503 are combined with the possible states in the scene to be identified, and the final preset scene hazard database can be obtained.
在一种可能的实施方式中，为了是该预设场景危害数据库更加合理，同时减少该预设场景危害数据库对存储空间的占用，安全人员可以在构建该预设场景危害数据库时，根据实际情况将不合理的组合删除，同时也可删除与该不合理的组合相对应的不合理的场景危害。In one possible implementation, in order to make the preset scenario hazard database more reasonable and reduce the storage space occupied by the preset scenario hazard database, security personnel can delete unreasonable combinations according to actual conditions when constructing the preset scenario hazard database, and can also delete unreasonable scenario hazards corresponding to the unreasonable combinations.
图6是根据本公开一示例性实施例示出的一种轨道交通场景的场景危害识别装置100的结构框图。如图6所示，所述装置100包括：第一获取模块10，用于获取待识别场景的危害因素，所述危害因素至少包括列车因素，地点因素，人员因素；确定模块20，用于确定与所述危害因素对应的目标状态；识别模块30，用于根据所述待识别场景的所述危害因素以及与所述危害因素对应的目标状态识别与所述待识别场景对应的场景危害。Fig. 6 is a structural block diagram of a scene hazard identification device 100 for a rail transit scene according to an exemplary embodiment of the present disclosure. As shown in Fig. 6, the device 100 includes: a first acquisition module 10, used to obtain the hazard factors of the scene to be identified, the hazard factors at least including train factors, location factors, and personnel factors; a determination module 20, used to determine the target state corresponding to the hazard factors; an identification module 30, used to identify the scene hazard corresponding to the scene to be identified according to the hazard factors of the scene to be identified and the target state corresponding to the hazard factors.
通过上述技术方案提供的装置，能够通过针对该轨道交通场景的危害因素和与危害因素对应的目标状态来对轨道交通场景所对应的场景危害进行识别，从而使得对于该轨道交通场景的场景危害识别结果能够更加全面，清楚，从而使得安全人员能够更加准确地对该轨道交通场景中的场景危害进行控制，降低该轨道交通场景中安全事故发生的可能性。The device provided by the above technical solution can identify the scene hazards corresponding to the rail transit scene by targeting the hazard factors of the rail transit scene and the target states corresponding to the hazard factors, thereby making the scene hazard identification results for the rail transit scene more comprehensive and clear, so that safety personnel can more accurately control the scene hazards in the rail transit scene and reduce the possibility of safety accidents in the rail transit scene.
在一种可能的实施方式中，所述目标状态包括一级目标状态和二级目标状态，所述一级目标状态与所述二级目标状态之间为一对多或一对一的对应关系；该识别模块30还用于：根据所述待识别场景的所述危害因素以及与所述危害因素对应的所述一级目标状态和所述二级目标状态识别与所述待识别场景对应的场景危害。In a possible implementation, the target state includes a primary target state and a secondary target state, and there is a one-to-many or one-to-one correspondence between the primary target state and the secondary target state; the identification module 30 is also used to: identify the scene hazards corresponding to the scene to be identified based on the hazard factors of the scene to be identified and the primary target state and the secondary target state corresponding to the hazard factors.
在一种可能的实施方式中，该识别模块30还用于：根据所述待识别场景的所述危害因素以及与所述危害因素对应的目标状态在预设场景危害数据库中查找识别与所述待识别场景对应的场景危害。In a possible implementation, the identification module 30 is further used to search and identify scene hazards corresponding to the scene to be identified in a preset scene hazard database according to the hazard factors of the scene to be identified and the target states corresponding to the hazard factors.
图7是根据本公开又一示例性实施例示出的一种轨道交通场景的场景危害识别装置100的结构框图。如图7所示，所述装置100还包括：构建模块40，用于在所述获取待识别场景的危害因素之前，基于所述待识别场景中的所有所述危害因素，和所述危害因素所对应的状态，构建与所述待识别场景对应的所述预设场景危害数据库。Fig. 7 is a structural block diagram of a scene hazard identification device 100 for a rail transit scene according to another exemplary embodiment of the present disclosure. As shown in Fig. 7, the device 100 further includes: a construction module 40, which is used to construct the preset scene hazard database corresponding to the scene to be identified based on all the hazard factors in the scene to be identified and the states corresponding to the hazard factors before obtaining the hazard factors of the scene to be identified.
在一种可能的实施方式中，如图7所示，所述装置100还包括第二获取模块50，用于获取所述待识别场景的场景属性，所述场景数据至少包括驾驶模式，运行级别，线路特征中的一者；该识别模块30还用于：根据所述待识别场景的所述危害因素，与所述危害因素对应的目标状态，以及所述场景属性在所述预设场景危害数据库中查找识别与所述待识别场景对应的场景危害。In a possible implementation, as shown in FIG. 7 , the device 100 further includes a second acquisition module 50 for acquiring scene attributes of the scene to be identified, wherein the scene data includes at least one of a driving mode, an operating level, and a line feature; the identification module 30 is further used to search and identify scene hazards corresponding to the scene to be identified in the preset scene hazard database according to the hazard factors of the scene to be identified, the target state corresponding to the hazard factors, and the scene attributes.
在一种可能的实施方式中，该构建模块40还用于：基于所述待识别场景中的所有所述危害因素，所述危害因素所对应的状态，和所述待识别场景的所有所述场景属性，构建与所述待识别场景对应的所述预设场景危害数据库。In a possible implementation, the construction module 40 is also used to: construct the preset scene hazard database corresponding to the scene to be identified based on all the hazard factors in the scene to be identified, the states corresponding to the hazard factors, and all the scene attributes of the scene to be identified.
图8是根据本公开又一示例性实施例示出的一种轨道交通场景的场景危害识别装置100的结构框图。如图8所示，该构建模块40包括：第一获取子模块401，用于获取所述待识别场景中的所有所述危害因素；第二获取子模块402，用于获取每个所述危害因素所对应的所有因素值；第一处理子模块403，用于逐次从每个所述危害因素中选取一个所述因素值作为目标因素值，对所有所述目标因素值进行排列组合；第二处理子模块404，用于将每个排列组合与所述危害因素所对应的状态进行组合，以构建所述预设场景危害数据库。Fig. 8 is a structural block diagram of a scene hazard identification device 100 for a rail transit scene according to another exemplary embodiment of the present disclosure. As shown in Fig. 8, the construction module 40 includes: a first acquisition submodule 401, used to acquire all the hazard factors in the scene to be identified; a second acquisition submodule 402, used to acquire all factor values corresponding to each hazard factor; a first processing submodule 403, used to successively select one factor value from each hazard factor as a target factor value, and perform permutations and combinations on all the target factor values; a second processing submodule 404, used to combine each permutation and combination with the state corresponding to the hazard factor to construct the preset scene hazard database.
关于上述实施例中的装置，其中各个模块执行操作的具体方式已经在有关该方法的实施例中进行了详细描述，此处将不做详细阐述说明。Regarding the device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.
图9是根据一示例性实施例示出的一种电子设备900的框图。如图9所示，该电子设备900可以包括：处理器901，存储器902。该电子设备900还可以包括多媒体组件903，输入/输出（I/O）接口904，以及通信组件905中的一者或多者。Fig. 9 is a block diagram of an electronic device 900 according to an exemplary embodiment. As shown in Fig. 9, the electronic device 900 may include: a processor 901, a memory 902. The electronic device 900 may also include one or more of a multimedia component 903, an input/output (I/O) interface 904, and a communication component 905.
其中，处理器901用于控制该电子设备900的整体操作，以完成上述的轨道交通场景的场景危害识别方法中的全部或部分步骤。存储器902用于存储各种类型的数据以支持在该电子设备900的操作，这些数据例如可以包括用于在该电子设备900上操作的任何应用程序或方法的指令，以及应用程序相关的数据，例如联系人数据、收发的消息、图片、音频、视频等等。该存储器902可以由任何类型的易失性或非易失性存储设备或者它们的组合实现，例如静态随机存取存储器（Static Random Access Memory，简称SRAM），电可擦除可编程只读存储器（Electrically Erasable Programmable Read-Only Memory，简称EEPROM），可擦除可编程只读存储器（Erasable Programmable Read-Only Memory，简称EPROM），可编程只读存储器（Programmable Read-Only Memory，简称PROM），只读存储器（Read-OnlyMemory，简称ROM），磁存储器，快闪存储器，磁盘或光盘。多媒体组件903可以包括屏幕和音频组件。其中屏幕例如可以是触摸屏，音频组件用于输出和/或输入音频信号。例如，音频组件可以包括一个麦克风，麦克风用于接收外部音频信号。所接收的音频信号可以被进一步存储在存储器902或通过通信组件905发送。音频组件还包括至少一个扬声器，用于输出音频信号。I/O接口904为处理器901和其他接口模块之间提供接口，上述其他接口模块可以是键盘，鼠标，按钮等。这些按钮可以是虚拟按钮或者实体按钮。通信组件905用于该电子设备900与其他设备之间进行有线或无线通信。无线通信，例如Wi-Fi，蓝牙，近场通信（NearField Communication，简称NFC），2G、3G、4G、NB-IOT、eMTC、或其他5G等等，或它们中的一种或几种的组合，在此不做限定。因此相应的该通信组件905可以包括：Wi-Fi模块，蓝牙模块，NFC模块等等。The processor 901 is used to control the overall operation of the electronic device 900 to complete all or part of the steps in the above-mentioned method for identifying the scene hazards of the rail transit scene. The memory 902 is used to store various types of data to support the operation of the electronic device 900. For example, these data may include instructions for any application or method used to operate on the electronic device 900, and application-related data, such as contact data, sent and received messages, pictures, audio, video, etc. The memory 902 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (Static Random Access Memory, referred to as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), erasable programmable read-only memory (Erasable Programmable Read-Only Memory, referred to as EPROM), programmable read-only memory (Programmable Read-Only Memory, referred to as PROM), read-only memory (Read-Only Memory, referred to as ROM), magnetic memory, flash memory, disk or optical disk. The multimedia component 903 may include a screen and an audio component. The screen may be, for example, a touch screen, and the audio component is used to output and/or input audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signal may be further stored in the memory 902 or sent through the communication component 905. The audio component also includes at least one speaker for outputting audio signals. The I/O interface 904 provides an interface between the processor 901 and other interface modules, and the other interface modules may be keyboards, mice, buttons, etc. These buttons may be virtual buttons or physical buttons. The communication component 905 is used for wired or wireless communication between the electronic device 900 and other devices. Wireless communication, such as Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G, 4G, NB-IOT, eMTC, or other 5G, etc., or a combination of one or more of them, is not limited here. Therefore, the corresponding communication component 905 may include: Wi-Fi module, Bluetooth module, NFC module, etc.
在一示例性实施例中，电子设备900可以被一个或多个应用专用集成电路（Application Specific Integrated Circuit，简称ASIC）、数字信号处理器（DigitalSignal Processor，简称DSP）、数字信号处理设备（Digital Signal Processing Device，简称DSPD）、可编程逻辑器件（Programmable Logic Device，简称PLD）、现场可编程门阵列（Field Programmable Gate Array，简称FPGA）、控制器、微控制器、微处理器或其他电子元件实现，用于执行上述的轨道交通场景的场景危害识别方法。In an exemplary embodiment, the electronic device 900 can be implemented by one or more application specific integrated circuits (ASIC), digital signal processors (DSP), digital signal processing devices (DSPD), programmable logic devices (PLD), field programmable gate arrays (FPGA), controllers, microcontrollers, microprocessors or other electronic components to execute the above-mentioned scene hazard identification method for rail transit scenes.
在另一示例性实施例中，还提供了一种包括程序指令的计算机可读存储介质，该程序指令被处理器执行时实现上述的轨道交通场景的场景危害识别方法的步骤。例如，该计算机可读存储介质可以为上述包括程序指令的存储器902，上述程序指令可由电子设备900的处理器901执行以完成上述的轨道交通场景的场景危害识别方法。In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided, and when the program instructions are executed by a processor, the steps of the scene hazard identification method for the rail transit scene are implemented. For example, the computer-readable storage medium can be the above-mentioned memory 902 including program instructions, and the above-mentioned program instructions can be executed by the processor 901 of the electronic device 900 to complete the above-mentioned scene hazard identification method for the rail transit scene.
图10是根据一示例性实施例示出的一种电子设备1000的框图。例如，电子设备1000可以被提供为一服务器。参照图10，电子设备1000包括处理器1022，其数量可以为一个或多个，以及存储器1032，用于存储可由处理器1022执行的计算机程序。存储器1032中存储的计算机程序可以包括一个或一个以上的每一个对应于一组指令的模块。此外，处理器1022可以被配置为执行该计算机程序，以执行上述的轨道交通场景的场景危害识别方法。FIG10 is a block diagram of an electronic device 1000 according to an exemplary embodiment. For example, the electronic device 1000 may be provided as a server. Referring to FIG10 , the electronic device 1000 includes a processor 1022, which may be one or more, and a memory 1032 for storing a computer program executable by the processor 1022. The computer program stored in the memory 1032 may include one or more modules, each corresponding to a set of instructions. In addition, the processor 1022 may be configured to execute the computer program to execute the above-mentioned scene hazard identification method for the rail transit scene.
另外，电子设备1000还可以包括电源组件1026和通信组件1050，该电源组件1026可以被配置为执行电子设备1000的电源管理，该通信组件1050可以被配置为实现电子设备1000的通信，例如，有线或无线通信。此外，该电子设备1000还可以包括输入/输出（I/O）接口1058。电子设备1000可以操作基于存储在存储器1032的操作系统，例如WindowsServerTM，Mac OS XTM，UnixTM，LinuxTM等等。In addition, the electronic device 1000 may further include a power supply component 1026 and a communication component 1050, wherein the power supply component 1026 may be configured to perform power management of the electronic device 1000, and the communication component 1050 may be configured to implement communication of the electronic device 1000, for example, wired or wireless communication. In addition, the electronic device 1000 may further include an input/output (I/O) interface 1058. The electronic device 1000 may operate based on an operating system stored in the memory 1032, such as Windows ServerTM , Mac OS XTM , UnixTM , LinuxTM , etc.
在另一示例性实施例中，还提供了一种包括程序指令的计算机可读存储介质，该程序指令被处理器执行时实现上述的轨道交通场景的场景危害识别方法的步骤。例如，该计算机可读存储介质可以为上述包括程序指令的存储器1032，上述程序指令可由电子设备1000的处理器1022执行以完成上述的轨道交通场景的场景危害识别方法。In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided, and when the program instructions are executed by a processor, the steps of the scene hazard identification method for the rail transit scene are implemented. For example, the computer-readable storage medium can be the memory 1032 including the program instructions, and the program instructions can be executed by the processor 1022 of the electronic device 1000 to complete the scene hazard identification method for the rail transit scene.
在另一示例性实施例中，还提供一种计算机程序产品，该计算机程序产品包含能够由可编程的装置执行的计算机程序，该计算机程序具有当由该可编程的装置执行时用于执行上述的轨道交通场景的场景危害识别方法的代码部分。In another exemplary embodiment, a computer program product is also provided, which includes a computer program that can be executed by a programmable device, and the computer program has a code portion for executing the above-mentioned scene hazard identification method for rail transit scenes when executed by the programmable device.
以上结合附图详细描述了本公开的优选实施方式，但是，本公开并不限于上述实施方式中的具体细节，在本公开的技术构思范围内，可以对本公开的技术方案进行多种简单变型，这些简单变型均属于本公开的保护范围。The preferred embodiments of the present disclosure are described in detail above in conjunction with the accompanying drawings; however, the present disclosure is not limited to the specific details in the above embodiments. Within the technical concept of the present disclosure, a variety of simple modifications can be made to the technical solution of the present disclosure, and these simple modifications all fall within the protection scope of the present disclosure.
另外需要说明的是，在上述具体实施方式中所描述的各个具体技术特征，在不矛盾的情况下，可以通过任何合适的方式进行组合。为了避免不必要的重复，本公开对各种可能的组合方式不再另行说明。It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, the present disclosure will not further describe various possible combinations.
此外，本公开的各种不同的实施方式之间也可以进行任意组合，只要其不违背本公开的思想，其同样应当视为本公开所公开的内容。In addition, various embodiments of the present disclosure may be arbitrarily combined, and as long as they do not violate the concept of the present disclosure, they should also be regarded as the contents disclosed by the present disclosure.
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| CN110457826A (en)* | 2019-08-14 | 2019-11-15 | 中车株洲电力机车研究所有限公司 | A method and device for judging the safety integrity level of an intelligent rail express tram |
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