WO2021218055A1 - 面向轨交全自动无人驾驶场景验证的云仿真装置与方法 - Google Patents

面向轨交全自动无人驾驶场景验证的云仿真装置与方法 Download PDF

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WO2021218055A1
WO2021218055A1 PCT/CN2020/121797 CN2020121797W WO2021218055A1 WO 2021218055 A1 WO2021218055 A1 WO 2021218055A1 CN 2020121797 W CN2020121797 W CN 2020121797W WO 2021218055 A1 WO2021218055 A1 WO 2021218055A1
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layer
management
station
software
vehicle
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PCT/CN2020/121797
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French (fr)
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查伟
孙童海
杜岳升
周建中
邓晗哲
成正波
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卡斯柯信号有限公司
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Priority to US17/596,079 priority Critical patent/US20220319333A1/en
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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B17/00—Systems involving the use of models or simulators of said systems
    • G05B17/02—Systems involving the use of models or simulators of said systems electric
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/20—Monitoring the location of vehicles belonging to a group, e.g. fleet of vehicles, countable or determined number of vehicles
    • G08G1/202—Dispatching vehicles on the basis of a location, e.g. taxi dispatching
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W60/00—Drive control systems specially adapted for autonomous road vehicles
    • B60W60/001—Planning or execution of driving tasks
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B61—RAILWAYS
    • B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
    • B61L27/00—Central railway traffic control systems; Trackside control; Communication systems specially adapted therefor
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/40—Business processes related to the transportation industry
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
    • G08G1/0137—Measuring and analyzing of parameters relative to traffic conditions for specific applications
    • G08G1/0145—Measuring and analyzing of parameters relative to traffic conditions for specific applications for active traffic flow control
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2420/00—Indexing codes relating to the type of sensors based on the principle of their operation
    • B60W2420/40—Photo, light or radio wave sensitive means, e.g. infrared sensors
    • B60W2420/403—Image sensing, e.g. optical camera
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/10—Geometric CAD
    • G06F30/15—Vehicle, aircraft or watercraft design
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation

Definitions

  • the invention relates to the field of fully automatic unmanned driving in rail transit, and in particular to a cloud simulation device and method for the verification of fully automatic unmanned driving in rail transit.
  • the rail transit operation control system is a complex control system with high accuracy requirements and demanding safety requirements. It is also the development direction of the domestic subway operation control system in the future, which can significantly reduce staff and increase efficiency for subway companies.
  • the domestic rail transit industry is actively researching a fully automated unmanned driving system for GOA4 level, which integrates signal, comprehensive monitoring, platform doors, vehicles, communications, automatic fare collection, PIS, PA, CCTV and other majors, Design specifications have been made for all fully automated unmanned driving scenarios, including normal operation scenarios, emergency scenarios, and failure scenarios, to guide the design and implementation of subsequent fully automated unmanned driving projects.
  • the corresponding unmanned driving scenarios are usually researched and extracted from the requirements of fully automated unmanned driving, so as to form an unmanned driving scene file, which is used to refer to the automatic driving of the rails.
  • Development, verification and engineering implementation of human driving system The verification of the rail transit driverless scene spans multiple professional equipment in the rail transit industry, such as signal, integrated monitoring, platform doors, vehicles, communications, automatic fare collection, PIS, PA, CCTV and other subsystems professional equipment . Due to the large number of professional equipment and complex interfaces of each subsystem, it is currently difficult to have a set of system methods and devices that can realize multi-discipline integration and cross-discipline linkage for the verification of rail transit fully automated unmanned driving scenarios.
  • the rail transit fully automatic unmanned driving system has strong specificity and high complexity. It takes a lot of manpower and energy to manage power systems, network systems, and various subsystems when testing and verifying environmental management. The environment such as software and hardware affects the development of the verification work itself.
  • the purpose of the present invention is to provide a cloud simulation device and method for rail transit fully automatic unmanned driving scene verification in order to overcome the above-mentioned defects in the prior art.
  • a cloud simulation device for the verification of rail transit fully automatic unmanned driving scenarios including a cloud access terminal and a cloud server.
  • the cloud server includes a central dispatch module, a station control module, a rail transit module, interface logic management layer, and equipment foundation
  • the cloud access terminal is connected to the central dispatching module, and the central dispatching module is respectively connected to the station control module and the railroad module.
  • the station control module, the railroad module and the interface logic management layer are connected in pairs. Connected, the interface logic management layer is connected to the device base layer.
  • the cloud access terminal is connected to the central dispatch module through a VDI communication protocol;
  • the cloud access terminal is used to implement various controls and operations of cloud access users, and feed back and display the operation results.
  • the central dispatching module includes a driving dispatching server, a vehicle dispatching server, a passenger dispatching server, an equipment dispatching server, a director dispatching server, and a maintenance dispatching server that are connected to each other through a communication network, and each server is implemented by software simulation;
  • the central dispatching module is used for multi-dimensional passenger flow perception and dynamic prediction, to realize accurate map paving, intelligent map adjustment and road network coordination, intelligent identification of faults and emergency scenarios and auxiliary decision-making, and based on big data and intelligent computing engine Multi-professional multi-line integrated command.
  • the station control module includes an ATS workstation, an ISCS workstation, a station ATS server, a station ISCS server, an IBP panel, an LATS server and a station FEP connected to each other through a communication network, and each device is implemented by software simulation;
  • the said station control module revolves around passenger service and provides three functions of intelligent passenger transportation management, equipment management and passenger service, including: 1) Intelligent linkage and modular control of various station systems: efficient linkage in normal mode and failure mode; 2) Intelligent collection and response of passenger flow information; 3) All-round passenger information prompt; 4) Intelligent energy-saving operation of each station system; 5) Intelligent inspection.
  • the track module includes vehicle-mounted equipment and trackside equipment that are all realized by software simulation;
  • the vehicle-mounted equipment includes vehicle-mounted controller, vehicle-mounted PIS, vehicle-mounted TCMS, MVB bus, vehicle-mounted integrated monitoring device, WIFI module, vehicle-ground communication module, and 3D simulation driving module.
  • the TCMS is connected to a vehicle-mounted controller, the vehicle-mounted controller is respectively connected with the vehicle-mounted TCMS and the vehicle-ground communication module, and the vehicle-mounted integrated monitoring device is connected with the vehicle-mounted PIS, the vehicle-mounted TCMS, and the WIFI module;
  • the trackside equipment includes screen doors, turnouts, signals and beacons;
  • the track module is used to realize automatic wake-up, vehicle patrol, main line operation, stop and pick up, platform departure, emergency intercom, video clearance and storage sleep.
  • the interface logic management layer includes a scene management platform layer, a logic simulation platform layer, a station interface simulation platform layer, and a vehicle interface simulation platform layer;
  • the interface logic management layer includes interface adaptation with various devices, simulation of rail transit full-automatic logic and scene management of unmanned driving, which is used to receive instructions from the software service layer upwards and pass the software service layer downwards.
  • the message to the basic layer of the device, and provide the corresponding service and management of the platform layer.
  • the logic simulation platform layer includes an IVP server
  • the scenario management platform layer includes verification plan management, scenario use case management, scenario demand management, scenario environment management, verification resource management, scenario configuration management, and scenario report management.
  • the equipment basic layer includes ISCS system, ATC system, ATS system and CI system;
  • the basic layer of the equipment runs real rail transit fully automatic unmanned operation control system software and data, which is used for inter-system interface testing, function and performance testing, information security attack and defense drill testing, and fault injection testing.
  • a cloud simulation method for the verification of rail transit fully automated unmanned driving scenarios including the following steps:
  • Step 1 The cloud access terminal starts the central SaaS layer virtualization equipment software through the Ethernet power management module.
  • the virtualization equipment software includes driving scheduling software, vehicle scheduling software, integrated scheduling software, passenger scheduling software, and maintenance scheduling software.
  • the content covers signal scheduling. , Integrated monitoring and dispatching voice telephone system;
  • Step 2 The central SaaS layer uses remote intelligent station opening instructions to remotely control the station’s SaaS layer virtualization equipment software to realize intelligent remote station opening.
  • the station SaaS layer includes signal ATS workstation software, integrated monitoring ISCS station workstation software, integrated IPB disk software, and stations ATS server software, station ISCS server software, LATS software and station FEP software;
  • the rail SaaS layer is controlled by the center SaaS layer and the station SaaS layer at the same time, and provides real-time feedback to the center and the station.
  • the rail SaaS layer includes vehicle model software, car door platform door model software, and track signal machine turnout model software , Departure indicator software, platform PIS ⁇ PA, SPKS ⁇ ESP model software and congestion display software, integrate various professional station rail area passenger service functions and operational safety equipment models, and conduct comprehensive functional verification of station operation and passenger service scenarios ;
  • Step 4 Send the result instruction calculated by the SaaS layer to the various interface adapter resource pools included in the PaaS layer.
  • the interface adapter resource pool includes the vehicle interface simulation platform resource pool and the station interface simulation platform resource pool for logic in the PaaS layer Simulation platform layer and scene management platform layer service call;
  • the logic simulation platform layer in the PaaS layer includes a set of virtual machine servers for sending and receiving data from the resource pool of the vehicle and station interface simulation platform, and processing various instruction messages of the vehicles and stations at the same time, and is controlled by the PaaS Scene management service platform layer in the layer;
  • the scene management service in the PaaS layer includes a series of basic cloud management services to provide platform-level scene management services that can be invoked by the SaaS layer.
  • the PaaS layer scene management services include verification plan management services and scene use case management services , Scene demand management service, scene environment management service, verification resource management service, scene configuration management service and scene report management service;
  • the IaaS infrastructure service layer includes a series of semi-physical and semi-simulated fully automatic driverless operation and control system facilities. All facilities are physical or virtualized.
  • the IaaS layer facilities provide infrastructure facilities services to the PaaS layer and accept the PaaS layer. Scene management service management;
  • Step 8 The SaaS layer, Pass layer, and IaaS layer interact with each other. All operations originate from the uppermost cloud terminal and provide real-time status data feedback to the cloud terminal.
  • the station SaaS layer has the conditions to achieve communication and linkage with the central SaaS layer and the rail SaaS layer.
  • the station SaaS layer has the conditions to achieve communication and linkage with the central SaaS layer and the rail SaaS layer.
  • the present invention has the following advantages:
  • the real system is linked with the virtual scene to verify the driverless operation scenario: functional modeling of the facilities in the rail transit fully automated driverless system, including fully automated parking lots, vehicles, tracksides, platforms and exhibition hall equipment, etc. , Connect the core professional real equipment, simulate the behavior of passengers and operation and maintenance personnel, import operation and maintenance rules, deduce the system response in various operation scenarios, and verify and evaluate the design of unmanned driving system operation scenarios.
  • Carry out pre-operation research to check the rationality of the operation scenarios and architecture design ensure that the design of functions and rules truly meet the operational needs, and timely discover the easily overlooked problems in the design, and avoid the resulting design regrets and rework costs.
  • the cloud simulation platform can be based on rail transit fully automatic unmanned driving, from the perspectives of smart dispatch, smart station, smart parking, smart operation and maintenance, etc.
  • the operation plan verifies its technical feasibility, and also points the way for the next generation of smart subway research.
  • Figure 1 is a schematic diagram of the structure of the present invention
  • Figure 2 is a schematic diagram of the specific structure of the present invention.
  • a cloud simulation device for rail transit fully automatic driverless scene verification includes a cloud access terminal a and a cloud server.
  • the cloud server includes a central dispatch module b, a station control module c, and rail transit. Module d, interface logic management layer e and equipment basic layer f.
  • the cloud access terminal a is connected to the central dispatching module b, and the central dispatching module b is respectively connected to the station control module c and the track module d.
  • the station control module c, the track module d and the interface logic management layer e are connected in pairs, and the interface logic management layer e is connected to the equipment basic layer f.
  • the cloud is the core of cloud computing simulation testing, and controls all cloud testing resources through network and interface adaptation. When users have test requirements, they only need to send a service request to the cloud test platform through the network.
  • the cloud computing simulation test platform will automatically calculate the optimal test resource configuration and run it automatically in the background, and finally feedback the test results to the local terminal.
  • the cloud access terminal a is connected to the central scheduling module b through the VDI communication protocol;
  • the cloud access terminal also known as the cloud terminal
  • the cloud access terminal is a terminal device of cloud desktop technology, which connects to the cloud system through the VDI communication protocol (virtual desktop infrastructure)
  • the desktop is displayed to the front end, and the output and input data of the cloud terminal is redirected to the cloud server.
  • This module includes front-end operation and display programs, and the back-end implements external network communication for an extensible VDI architecture.
  • various controls and operations of cloud access users can be mainly realized, and the operation results are fed back and displayed.
  • the central dispatch module b includes a driving dispatch server b1, a vehicle dispatch server b2, a passenger dispatch server b3, an equipment dispatch server b4, a director dispatch server b5, and a maintenance dispatch server connected to each other through a communication network.
  • each server is realized through software simulation;
  • the central dispatching module b is used for multi-dimensional passenger flow perception and dynamic prediction, realizing accurate map paving, intelligent map adjustment and road network coordination, intelligent identification of faults and emergency scenarios and auxiliary decision-making, and based on big data and intelligent computing engine Multi-professional multi-line integrated command.
  • the station control module c includes ATS workstation c1, ISCS workstation c2, station ATS server c3, station ISCS server c4, IBP disk c5, LATS server c6, and station FEP c7, which are connected to each other through a communication network. Simulation to achieve;
  • the said station control module c focuses on passenger services and provides three functions of intelligent passenger transportation management, equipment management and passenger services, including: 1) Intelligent linkage and modular control of various station systems: efficient linkage in normal mode and failure mode 2) Intelligent collection and response of passenger flow information; 3) All-round passenger information prompt; 4) Intelligent energy-saving operation of each station system; 5) Intelligent inspection.
  • the track module d includes vehicle-mounted equipment and trackside equipment that are all realized by software simulation; the vehicle-mounted equipment includes vehicle-mounted controller d1, vehicle-mounted PIS d2, vehicle-mounted TCMS d3, MVB bus d4, vehicle-mounted integrated monitoring device d5, WIFI module d6, vehicle-ground communication module d7, and 3D simulation driving module d8.
  • the MVB bus is connected to the vehicle integrated monitoring device, the vehicle TCMS and the vehicle controller respectively, and the vehicle controller communicates with the vehicle TCMS and the vehicle ground respectively.
  • Module connection the vehicle integrated monitoring device is respectively connected to the vehicle PIS, the vehicle TCMS and the WIFI module;
  • the trackside equipment includes the screen door d9, the switch d10, the signal d11 and the beacon d12;
  • the track module d is used to realize automatic wake-up, vehicle patrol, main line operation, stop and pick-up, platform departure, emergency intercom, video clearance and storage dormancy.
  • the interface logic management layer e includes a scene management platform layer e1, a logic simulation platform layer e2, a station interface simulation platform layer e3, and a vehicle interface simulation platform layer e4;
  • the said interface logic management layer e includes interface adaptation with various devices, simulation of rail transit automatic logic and scene management of unmanned driving, which is used to receive instructions issued by the software service layer upwards and deliver software services downwards.
  • the message of the layer reaches the basic layer of the device, and provides corresponding services and management at the platform layer.
  • the logic simulation platform layer includes an IVP server
  • the scenario management platform layer includes verification plan management, scenario use case management, scenario demand management, scenario environment management, verification resource management, scenario configuration management, and scenario report management.
  • the equipment basic layer f includes ISCS system f1, ATC system f2, ATS system f3 and CI system f4;
  • the equipment basic layer f runs real rail transit fully automatic unmanned operation control system software and data, which is used for inter-system interface testing, function and performance testing, information security attack and defense drill testing, and fault injection testing.
  • the present invention divides the entire rail transit fully automated driverless system according to the cloud architecture according to the top-down architecture of fully automated unmanned driving, and is divided into: SaaS software as a service layer, PaaS platform as a service Layer and IaaS infrastructure as a service layer.
  • SaaS software as a service layer
  • PaaS platform as a service Layer
  • IaaS infrastructure as a service layer.
  • Each level is composed of the corresponding software and hardware of the cloud server, most of which use software virtualization technology, and a small number of observable devices are composed of hardware.
  • a cloud simulation method and device for the verification of rail transit fully automated unmanned driving scenarios, the method includes the following steps:
  • Step 1 Cloud customers start the central SaaS layer virtualization equipment software through the Ethernet power management module.
  • the virtualization software includes traffic scheduling software, vehicle scheduling software, integrated scheduling software, passenger scheduling software, and maintenance scheduling software.
  • the content covers signal scheduling and integration Monitor and dispatch the voice phone system. It adopts a centralized structure as a whole, which can dynamically switch and log in each dispatching work type, has an online linkage mode, and has the conditions for linkage with vehicles, platform doors and signal systems;
  • Step 2 The central SaaS layer uses remote intelligent station opening instructions to remotely control the station's SaaS layer virtualization equipment software to realize intelligent remote station opening.
  • the station SaaS level covers signal ATS workstation software, integrated monitoring ISCS station workstation software, integrated IPB disk software, station ATS server software, station ISCS server software, LATS software and station FEP software. It has the conditions to realize communication and linkage with the central SaaS layer and the rail SaaS layer. Through the integration of multiple subsystem functions involved in the station SaaS layer, it verifies highly linked station operation scenarios and emergency scenarios;
  • Step 3 The rail SaaS layer is controlled by the central SaaS layer and the station SaaS layer at the same time, and real-time information feedback is given to the center and the station.
  • the track SaaS layer includes vehicle model software, car door platform door model software, track signal switch model software, departure indicator software, platform PIS ⁇ PA, SPKS ⁇ ESP model software and congestion display software. Integrate various professional passenger service functions and operational safety equipment models in station rail areas, and conduct comprehensive functional verification of station operation and passenger service scenarios;
  • Step 4 Send the result instructions calculated by the SaaS layer to the resource pools of various interface adapters included in the PaaS layer.
  • the interface adapter resource pool is also called the verification interface basic resource pool, which is mainly composed of the vehicle interface simulation platform resource pool and the station interface simulation platform resource pool, which is used for the logic simulation platform layer and the scene management platform layer service call in the PaaS layer;
  • the logic simulation platform layer in the PaaS layer is mainly composed of a set of virtual machine servers. On the one hand, it sends and receives data from the resource pool of the vehicle and station interface simulation platform, and at the same time processes various instruction messages of the vehicles and stations, and controls them.
  • the scene management service platform layer in the PaaS layer is mainly composed of a set of virtual machine servers. On the one hand, it sends and receives data from the resource pool of the vehicle and station interface simulation platform, and at the same time processes various instruction messages of the vehicles and stations, and controls them.
  • the scene management service in the PaaS layer is composed of a series of cloud management basic services, providing platform-level scene management services, which can be invoked by the SaaS layer.
  • PaaS layer scenario management services include but are not limited to: verification plan management services, scenario use case management services, scenario demand management services, scenario environment management services, verification resource management services, scenario configuration management services, and scenario report management services;
  • the IaaS infrastructure service layer is mainly composed of a series of semi-physical and semi-simulated fully automatic driverless operation and control system facilities, and all facilities can be materialized or virtualized.
  • the IaaS layer facilities provide infrastructure facilities services to the PaaS layer, and accept the management of the PaaS layer scene management services, which are the foundation of the entire cloud simulation system.
  • Step 8 The SaaS layer, Pass layer, and IaaS layer interact with each other. All operations originate from the uppermost cloud terminal and provide real-time status data feedback to the cloud terminal.
  • the present invention has been fully applied to the verification of rail transit fully automatic unmanned driving scenes, including the integration test verification of signal system and unmanned driving system function verification, and supports the comprehensive function verification, training and demonstration of unmanned driving system.
  • Cloud simulation interface for debugging, testing and verification of signal interconnection with external manufacturers.
  • it can also provide real-time scene deduction, design verification, interface testing, system integration and other pre-operation services for unmanned engineering projects to improve the quality of engineering design in an all-round way, save construction period and cost, and ensure that the project runs at the highest level The automation level is put into use at one time.

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Abstract

一种面向轨交全自动无人驾驶场景验证的云仿真装置与方法，面向轨交全自动无人驾驶场景验证的云仿真装置包括云访问终端（a）以及云服务端，云服务端包括中心调度模块（b）、车站控制模块（c）、轨行模块（d）、接口逻辑管理层（e）和设备基础层（f），云访问终端（a）与中心调度模块（b）连接，中心调度模块（b）分别与车站控制模块（c）、轨行模块（d）连接，车站控制模块（c）、轨行模块（d）和接口逻辑管理层（e）之间两两连接，接口逻辑管理层（e）与设备基础层（f）连接。面向轨交全自动无人驾驶场景验证的云仿真装置与方法，具有灵活进行故障注入测试，能更加全面地进行降级和紧急运行场景下的功能测试，避免现场大规模的验证工作的优点。

Description

面向轨交全自动无人驾驶场景验证的云仿真装置与方法 技术领域
本发明涉及轨道交通全自动无人驾驶领域，尤其是涉及一种面向轨交全自动无人驾驶场景验证的云仿真装置与方法。
背景技术
轨道交通运行控制系统是一种精确度要求高、安全性要求苛刻的复杂控制系统，也是未来国内地铁运行控制系统的发展方向，可以明显地为地铁公司实现减员增效。目前国内轨交行业正在积极研究面向GOA4级的全自动运行无人驾驶系统，集成了信号、综合监控、站台门、车辆、通信、自动售检票、PIS、PA、CCTV等专业，并对轨交中所有的全自动无人驾驶场景，包括正常运营场景、应急场景和故障场景做出了设计规范，用于指导后续全自动无人驾驶的项目设计与实施。
目前在轨道交通全自动无人驾驶研究领域，通常从全自动无人驾驶需求中，研究并提取总结出相应的无人驾驶场景，从而形成无人驾驶场景文件，用以指导轨交全自动无人驾驶系统的开发、验证及工程实施。而对于轨交无人驾驶场景的验证，横跨了轨道交通行业中多个专业设备，如信号、综合监控、站台门、车辆、通信、自动售检票、PIS、PA、CCTV等子系统专业设备。由于各个子系统专业设备数量繁多，接口复杂，目前轨交行业内很难有一套能实现多专业集成、跨专业联动的面向轨交全自动无人驾驶场景验证的系统方法与装置。
轨交全自动无人驾驶场景验证系统如果采用全部真实的硬件设备，需要花费大量的硬件设备采购成本，对于空间和布线的要求也非常高，具体问题有：
1、成本问题：轨道交通相关硬件设备价格昂贵，相应的验证平台由于过多使用了实物硬件，导致开发建设成本过高，空间占用率高。
2、空间问题：过多采用实物硬件，导致机柜设备数量增多，造成空间的浪费。
3、验证平台兼容扩展性问题：如果验证平台大部分设备都由硬件实体设备组成，每种设备都有着本身特定的软硬件接口，导致仿真接口在兼容扩展性上有所限制，很难实现多专业的联动集成验证。
4、应用管理灵活性问题：轨交全自动无人驾驶系统专用性强，复杂度高，在做 测试验证环境管理时需要花费大量的人力和精力去管理诸如电源系统、网络系统、各子系统软硬件等环境，影响验证工作本身的开展。
发明内容
本发明的目的就是为了克服上述现有技术存在的缺陷而提供一种面向轨交全自动无人驾驶场景验证的云仿真装置与方法。
本发明的目的可以通过以下技术方案来实现：
一种面向轨交全自动无人驾驶场景验证的云仿真装置，包括云访问终端以及云服务端，其中云服务端包括中心调度模块、车站控制模块、轨行模块、接口逻辑管理层和设备基础层，所述的云访问终端与中心调度模块连接，所述的中心调度模块分别与车站控制模块、轨行模块连接，所述的车站控制模块、轨行模块和接口逻辑管理层之间两两连接，所述的接口逻辑管理层与设备基础层连接。
优选地，所述的云访问终端通过VDI通信协议与中心调度模块连接；
所述的云访问终端用于实现云访问用户的各种控制和操作，反馈并显示操作结果。
优选地，所述的中心调度模块包括相互之间通过通信网络连接的行车调度服务器、车辆调度服务器、乘客调度服务器、设备调度服务器、主任调度服务器和维修调度服务器，各服务器通过软件模拟来实现；
所述的中心调度模块，用于多维度客流量感知和动态预测，实现精准铺图、智能调图及路网协同，故障及应急场景智能识别和辅助决策，以及基于大数据和智能计算引擎的多专业多线路融合指挥。
优选地，所述的车站控制模块包括相互之间通过通信网络连接的ATS工作站、ISCS工作站、车站ATS服务器、车站ISCS服务器、IBP盘、LATS服务器和车站FEP，各设备通过软件模拟来实现；
所述的车站控制模块围绕乘客服务，提供智能的客运管理、设备管理和乘客服务三大功能，包括：1)车站各系统的智能联动、模式化控制：正常模式、故障模式下的高效联动；2)客流信息智能收集与应对；3)全方位的乘客信息提示；4)车站各系统智能节能运行；5)智能巡检。
优选地，所述的轨行模块包括均通过软件模拟实现的车载设备和轨旁设备；
所述的车载设备包括车载控制器、车载PIS、车载TCMS、MVB总线、车载综合监控装置、WIFI模块、车地通信模块和3D模拟驾驶模块，所述的MVB总线分别与车载综合监控装置、车载TCMS和车载控制器连接，所述的车载控制器分别与车载TCMS和车地通信模块连接，所述的车载综合监控装置分别与车载PIS、车载TCMS和WIFI模块连接；
所述的轨旁设备包括屏蔽门、道岔、信号机和信标；
所述的轨行模块用于实现自动唤醒、车辆巡道、正线运营、停站上客、站台发车、紧急对讲、视频清客和入库休眠。
优选地，所述的接口逻辑管理层包括场景管理平台层、逻辑仿真平台层、车站接口仿真平台层和车辆接口仿真平台层；
所述的接口逻辑管理层包含与各类设备的接口适配，轨交全自动逻辑的仿真与无人驾驶的场景管理，用于向上接收软件服务层下发的指令，向下传递软件服务层的消息至设备基础层，并提供平台层相应的服务和管理。
优选地，所述的逻辑仿真平台层包括IVP服务器，所述的场景管理平台层包括验证计划管理、场景用例管理、场景需求管理、场景环境管理、验证资源管理、场景配置管理和场景报告管理。
优选地，所述的设备基础层包括ISCS系统、ATC系统、ATS系统和CI系统；
所述的设备基础层运行真实的轨交全自动无人驾驶运控系统软件和数据，用于进行系统间接口测试、功能和性能测试、信息安全攻防演练测试、故障注入测试。
一种面向轨交全自动无人驾驶场景验证的云仿真方法，包括以下步骤：
步骤1，云访问终端通过以太网电源管理模块启动中心SaaS层虚拟化设备软件，虚拟化设备软件包括行车调度软件、车辆调度软件、综合调度软件、乘客调度软件和维修调度软件，内容覆盖信号调度、综合监控和调度语音电话系统；
步骤2，中心SaaS层通过远程智能开站指令，遥控车站SaaS层虚拟化设备软件实现智能远程开站，其中车站SaaS层级涵盖信号ATS工作站软件、综合监控ISCS车站工作站软件、综合IPB盘软件、车站ATS服务器软件、车站ISCS服务器软件、LATS软件和车站FEP软件；
步骤3，轨行SaaS层同时受控于中心SaaS层和车站SaaS层，并实时给予中心和车站信息反馈，其中轨行SaaS层包括车辆模型软件、车门站台门模型软件、轨道 信号机道岔模型软件、发车指示器软件、站台PIS\PA、SPKS\ESP模型软件和拥挤度显示软件，集成各专业的车站轨行区乘客服务功能及运行安全设备模型，对车站运营和乘客服务场景进行全面功能验证；
步骤4，通过SaaS层计算的结果指令，发送到PaaS层级所包含的各类接口适配器资源池，接口适配器资源池包括车辆接口仿真平台资源池和车站接口仿真平台资源池，供PaaS层中的逻辑仿真平台层和场景管理平台层服务调用；
步骤5，PaaS层中的逻辑仿真平台层包括一套虚拟机服务器，用于收发车辆、车站接口仿真平台资源池发过来的数据，同时处理车辆、车站的各类指令消息，并受控于PaaS层中的场景管理服务平台层；
步骤6，PaaS层中的场景管理服务包括一系列云管理基础服务用于，提供平台级的场景管理服务，可被SaaS层调用，其中PaaS层场景管理服务包括验证计划管理服务、场景用例管理服务、场景需求管理服务、场景环境管理服务、验证资源管理服务、场景配置管理服务和场景报告管理服务；
步骤7，IaaS基础架构服务层包括一系列半实物半仿真的全自动无人驾驶运控系统设施，所有设施为实物化或虚拟化，IaaS层设施向PaaS层提供基础架构设施服务，接受PaaS层场景管理服务的管理；
步骤8，SaaS层、Pass层和IaaS层相互做数据交互，所有操作来源于最上层级的云终端，并向云终端提供实时的状态数据反馈。
优选地，所述的车站SaaS层具备可与中心SaaS层、轨行SaaS层实现通信和联动的条件，通过集成车站SaaS层涉及的多个子系统功能，验证高度联动的车站运营场景和应急场景。
与现有技术相比，本发明具有以下优点：
1、轨交无人驾驶全专业的集成与跨专业的联动：集成信号、车辆、通信、BAS、FAS、站台门、AFC、PIS/PA、CCTV等专业，可验证在不同场景下各系统的功能设计及接口设计是否满足需求。在不依赖于外场测试线的情况下，进行无人驾驶系统各专业间的接口测试、系统的功能和性能测试，以提前完成系统集成确认，减少现场调试工作，优化项目工期，保证发布质量。与现场测试相比，具有灵活进行故障注入测试的优点，能更加全面地进行降级和紧急运行场景下的功能测试，避免现场大规模的验证工作。
2、真实系统与虚拟场景联动，进行无人驾驶运营场景验证：对轨交全自动无人驾驶系统中的设施进行功能建模，包括全自动停车场、车辆、轨旁、站台和展厅设备等，连接核心专业的真实设备，模拟乘客及运维人员行为，导入运维规则，推演各类运营场景下系统反应，对无人驾驶系统运营场景的设计进行验证和评估。进行运营前置研究，检验运营场景和架构设计的合理性，保证功能和规则的设计真正满足运营需求，及时发现设计中容易忽视的问题，避免由此导致的设计遗憾和返工成本。
3、面向未来新一代智慧地铁全自动运行方案的研究验证：该云仿真平台，可基于轨交全自动无人驾驶，从智能调度、智能车站、智能车场、智能运维等维度研究智慧地铁的运营方案，验证其技术可行性，也为下一代智慧地铁研究道路指明方向。
附图说明
图1为本发明的结构示意图；
图2为本发明的具体结构示意图。
具体实施方式
下面将结合本发明实施例中的附图，对本发明实施例中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的一部分实施例，而不是全部实施例。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的前提下所获得的所有其他实施例，都应属于本发明保护的范围。
如图1所示，一种面向轨交全自动无人驾驶场景验证的云仿真装置，包括云访问终端a以及云服务端，其中云服务端包括中心调度模块b、车站控制模块c、轨行模块d、接口逻辑管理层e和设备基础层f，所述的云访问终端a与中心调度模块b连接，所述的中心调度模块b分别与车站控制模块c、轨行模块d连接，所述的车站控制模块c、轨行模块d和接口逻辑管理层e之间两两连接，所述的接口逻辑管理层e与设备基础层f连接。云端是云计算仿真测试的核心，并通过网络和接口适配的方式控制所有云测试资源。当用户有测试需求时，只需要通过网络向云测试平台发送服务请求，云计算仿真测试平台将自动计算最优的测试资源配置并在后台自动化运行，最终向本地终端反馈测试结果。
所述的云访问终端a通过VDI通信协议与中心调度模块b连接；云访问终端(又 称云终端)为云桌面技术的终端设备，通过VDI通信协议(虚拟桌面基础架构)来连接云端的系统桌面并显示到前端来，并将云终端的输出输入数据重定向到云服务器上。该模块包括前端的操作和显示程序，后台为可扩展的VDI架构实现对外部的网络通信。在云访问终端a上，主要可实现云访问用户的各种控制和操作，反馈并显示操作结果。
如图2所示，所述的中心调度模块b包括相互之间通过通信网络连接的行车调度服务器b1、车辆调度服务器b2、乘客调度服务器b3、设备调度服务器b4、主任调度服务器b5和维修调度服务器b6，各服务器通过软件模拟来实现；
所述的中心调度模块b，用于多维度客流量感知和动态预测，实现精准铺图、智能调图及路网协同，故障及应急场景智能识别和辅助决策，以及基于大数据和智能计算引擎的多专业多线路融合指挥。
所述的车站控制模块c包括相互之间通过通信网络连接的ATS工作站c1、ISCS工作站c2、车站ATS服务器c3、车站ISCS服务器c4、IBP盘c5、LATS服务器c6和车站FEP c7，各设备通过软件模拟来实现；
所述的车站控制模块c围绕乘客服务，提供智能的客运管理、设备管理和乘客服务三大功能，包括：1)车站各系统的智能联动、模式化控制：正常模式、故障模式下的高效联动；2)客流信息智能收集与应对；3)全方位的乘客信息提示；4)车站各系统智能节能运行；5)智能巡检。所述的轨行模块d包括均通过软件模拟实现的车载设备和轨旁设备；所述的车载设备包括车载控制器d1、车载PIS d2、车载TCMS d3、MVB总线d4、车载综合监控装置d5、WIFI模块d6、车地通信模块d7和3D模拟驾驶模块d8，所述的MVB总线分别与车载综合监控装置、车载TCMS和车载控制器连接，所述的车载控制器分别与车载TCMS和车地通信模块连接，所述的车载综合监控装置分别与车载PIS、车载TCMS和WIFI模块连接；所述的轨旁设备包括屏蔽门d9、道岔d10、信号机d11和信标d12；
所述的轨行模块d用于实现自动唤醒、车辆巡道、正线运营、停站上客、站台发车、紧急对讲、视频清客和入库休眠。
所述的接口逻辑管理层e包括场景管理平台层e1、逻辑仿真平台层e2、车站接口仿真平台层e3和车辆接口仿真平台层e4；
所述的接口逻辑管理层e包含与各类设备的接口适配，轨交全自动逻辑的仿真与 无人驾驶的场景管理，用于向上接收软件服务层下发的指令，向下传递软件服务层的消息至设备基础层，并提供平台层相应的服务和管理。
所述的逻辑仿真平台层包括IVP服务器，所述的场景管理平台层包括验证计划管理、场景用例管理、场景需求管理、场景环境管理、验证资源管理、场景配置管理和场景报告管理。
所述的设备基础层f包括ISCS系统f1、ATC系统f2、ATS系统f3和CI系统f4；
所述的设备基础层f运行真实的轨交全自动无人驾驶运控系统软件和数据，用于进行系统间接口测试、功能和性能测试、信息安全攻防演练测试、故障注入测试。
如图1所示，本发明按照全自动无人驾驶自顶向下的架构，把整个轨交全自动无人驾驶系统按照云架构划分，分别划分为：SaaS软件即服务层，PaaS平台即服务层和IaaS基础架构即服务层。每个层级由云服务端相应的软件和硬件组成，大多数采用了软件虚拟化技术，少量的可观测设备由硬件组成。面向轨交全自动无人驾驶场景验证的云仿真方法与装置，该方法包括以下步骤：
步骤1，云客户通过以太网电源管理模块启动中心SaaS层虚拟化设备软件，虚拟化软件含行车调度软件、车辆调度软件、综合调度软件、乘客调度软件和维修调度软件，内容覆盖信号调度、综合监控和调度语音电话系统。整体上采用集中架构，可在各个调度工种动态切换登录，具备在线联动模式，具备与车辆、站台门以及信号系统联动条件；
步骤2，中心SaaS层通过远程智能开站指令，遥控车站SaaS层虚拟化设备软件实现智能远程开站。车站SaaS层级涵盖信号ATS工作站软件、综合监控ISCS车站工作站软件、综合IPB盘软件、车站ATS服务器软件、车站ISCS服务器软件、LATS软件和车站FEP软件。具备可与中心SaaS层、轨行SaaS层实现通信和联动的条件。通过集成车站SaaS层涉及的多个子系统功能，验证高度联动的车站运营场景和应急场景；
步骤3，轨行SaaS层同时受控于中心SaaS层和车站SaaS层，并实时给予中心和车站信息反馈。轨行SaaS层含车辆模型软件、车门站台门模型软件、轨道信号机道岔模型软件、发车指示器软件、站台PIS\PA、SPKS\ESP模型软件和拥挤度显示软件。集成各专业的车站轨行区乘客服务功能及运行安全设备模型，对车站运营和乘客服务场景进行全面功能验证；
步骤4，通过SaaS层计算的结果指令，发送到PaaS层级所包含的各类接口适配器资源池。接口适配器资源池又称为验证接口基础资源池，主要有车辆接口仿真平台资源池和车站接口仿真平台资源池组成，供PaaS层中的逻辑仿真平台层和场景管理平台层服务调用；
步骤5，PaaS层中的逻辑仿真平台层主要由一套虚拟机服务器构成，一方面收发车辆、车站接口仿真平台资源池发过来的数据，同时处理车辆、车站的各类指令消息，并受控于PaaS层中的场景管理服务平台层；
步骤6，PaaS层中的场景管理服务由一系列云管理基础服务组成，提供平台级的场景管理服务，可被SaaS层调用。PaaS层场景管理服务包括但不仅限于：验证计划管理服务，场景用例管理服务，场景需求管理服务，场景环境管理服务，验证资源管理服务，场景配置管理服务和场景报告管理服务；
步骤7，IaaS基础架构服务层主要由一系列半实物半仿真的全自动无人驾驶运控系统设施组成，所有设施可实物化也可虚拟化。IaaS层设施向PaaS层提供基础架构设施服务，接受PaaS层场景管理服务的管理，为整个云仿真系统的基础。
步骤8，SaaS层、Pass层和IaaS层相互做数据交互，所有操作来源于最上层级的云终端，并向云终端提供实时的状态数据反馈。
本发明已经被全面应用于轨交全自动无人驾驶场景的验证，包括信号系统的集成测试验证和无人驾驶系统功能验证，并支持无人驾驶系统综合性功能验证、培训及演示，同时具备与外厂家信号互联互通的调试、测试与验证的云仿真接口。除此以外，还可以为无人驾驶工程项目的实时提供场景推演、设计验证、接口测试、系统集成和其他运营前置服务，全方位提升工程设计质量，节省工期和成本，保证项目按最高运行自动化等级一次性投用。通过云计算仿真的方法与装置，为轨交全自动运营场景中其他设施建立功能模型，加载高性能仿真引擎，采用虚实结合、集成联动的方式，进行无人驾驶功能的测试与场景验证，达到与现场实际运行相同的效果。
以上所述，仅为本发明的具体实施方式，但本发明的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本发明揭露的技术范围内，可轻易想到各种等效的修改或替换，这些修改或替换都应涵盖在本发明的保护范围之内。因此，本发明的保护范围应以权利要求的保护范围为准。

Claims (10)

  1. 一种面向轨交全自动无人驾驶场景验证的云仿真装置，其特征在于，包括云访问终端(a)以及云服务端，其中云服务端包括中心调度模块(b)、车站控制模块(c)、轨行模块(d)、接口逻辑管理层(e)和设备基础层(f)，所述的云访问终端(a)与中心调度模块(b)连接，所述的中心调度模块(b)分别与车站控制模块(c)、轨行模块(d)连接，所述的车站控制模块(c)、轨行模块(d)和接口逻辑管理层(e)之间两两连接，所述的接口逻辑管理层(e)与设备基础层(f)连接。
  2. 根据权利要求1所述的一种面向轨交全自动无人驾驶场景验证的云仿真装置，其特征在于，所述的云访问终端(a)通过VDI通信协议与中心调度模块(b)连接；
    所述的云访问终端(a)用于实现云访问用户的各种控制和操作，反馈并显示操作结果。
  3. 根据权利要求1所述的一种面向轨交全自动无人驾驶场景验证的云仿真装置，其特征在于，所述的中心调度模块(b)包括相互之间通过通信网络连接的行车调度服务器、车辆调度服务器、乘客调度服务器、设备调度服务器、主任调度服务器和维修调度服务器，各服务器通过软件模拟来实现；
    所述的中心调度模块(b)，用于多维度客流量感知和动态预测，实现精准铺图、智能调图及路网协同，故障及应急场景智能识别和辅助决策，以及基于大数据和智能计算引擎的多专业多线路融合指挥。
  4. 根据权利要求1所述的一种面向轨交全自动无人驾驶场景验证的云仿真装置，其特征在于，所述的车站控制模块(c)包括相互之间通过通信网络连接的ATS工作站、ISCS工作站、车站ATS服务器、车站ISCS服务器、IBP盘、LATS服务器和车站FEP，各设备通过软件模拟来实现；
    所述的车站控制模块(c)围绕乘客服务，提供智能的客运管理、设备管理和乘客服务三大功能，包括：1)车站各系统的智能联动、模式化控制：正常模式、故障模式下的高效联动；2)客流信息智能收集与应对；3)全方位的乘客信息提示；4)车站各系统智能节能运行；5)智能巡检。
  5. 根据权利要求1所述的一种面向轨交全自动无人驾驶场景验证的云仿真装置，其特征在于，所述的轨行模块(d)包括均通过软件模拟实现的车载设备和轨旁设备；
    所述的车载设备包括车载控制器、车载PIS、车载TCMS、MVB总线、车载综 合监控装置、WIFI模块、车地通信模块和3D模拟驾驶模块，所述的MVB总线分别与车载综合监控装置、车载TCMS和车载控制器连接，所述的车载控制器分别与车载TCMS和车地通信模块连接，所述的车载综合监控装置分别与车载PIS、车载TCMS和WIFI模块连接；
    所述的轨旁设备包括屏蔽门、道岔、信号机和信标；
    所述的轨行模块(d)用于实现自动唤醒、车辆巡道、正线运营、停站上客、站台发车、紧急对讲、视频清客和入库休眠。
  6. 根据权利要求1所述的一种面向轨交全自动无人驾驶场景验证的云仿真装置，其特征在于，所述的接口逻辑管理层(e)包括场景管理平台层、逻辑仿真平台层、车站接口仿真平台层和车辆接口仿真平台层；
    所述的接口逻辑管理层(e)包含与各类设备的接口适配，轨交全自动逻辑的仿真与无人驾驶的场景管理，用于向上接收软件服务层下发的指令，向下传递软件服务层的消息至设备基础层，并提供平台层相应的服务和管理。
  7. 根据权利要求6所述的一种面向轨交全自动无人驾驶场景验证的云仿真装置，其特征在于，所述的逻辑仿真平台层包括IVP服务器，所述的场景管理平台层包括验证计划管理、场景用例管理、场景需求管理、场景环境管理、验证资源管理、场景配置管理和场景报告管理。
  8. 根据权利要求1所述的一种面向轨交全自动无人驾驶场景验证的云仿真装置，其特征在于，所述的设备基础层(f)包括ISCS系统、ATC系统、ATS系统和CI系统；
    所述的设备基础层(f)运行真实的轨交全自动无人驾驶运控系统软件和数据，用于进行系统间接口测试、功能和性能测试、信息安全攻防演练测试、故障注入测试。
  9. 一种面向轨交全自动无人驾驶场景验证的云仿真方法，其特征在于，包括以下步骤：
    步骤1，云访问终端(a)通过以太网电源管理模块启动中心SaaS层虚拟化设备软件，虚拟化设备软件包括行车调度软件、车辆调度软件、综合调度软件、乘客调度软件和维修调度软件，内容覆盖信号调度、综合监控和调度语音电话系统；
    步骤2，中心SaaS层通过远程智能开站指令，遥控车站SaaS层虚拟化设备软件实现智能远程开站，其中车站SaaS层级涵盖信号ATS工作站软件、综合监控ISCS 车站工作站软件、综合IPB盘软件、车站ATS服务器软件、车站ISCS服务器软件、LATS软件和车站FEP软件；
    步骤3，轨行SaaS层同时受控于中心SaaS层和车站SaaS层，并实时给予中心和车站信息反馈，其中轨行SaaS层包括车辆模型软件、车门站台门模型软件、轨道信号机道岔模型软件、发车指示器软件、站台PIS\PA、SPKS\ESP模型软件和拥挤度显示软件，集成各专业的车站轨行区乘客服务功能及运行安全设备模型，对车站运营和乘客服务场景进行全面功能验证；
    步骤4，通过SaaS层计算的结果指令，发送到PaaS层级所包含的各类接口适配器资源池，接口适配器资源池包括车辆接口仿真平台资源池和车站接口仿真平台资源池，供PaaS层中的逻辑仿真平台层和场景管理平台层服务调用；
    步骤5，PaaS层中的逻辑仿真平台层包括一套虚拟机服务器，用于收发车辆、车站接口仿真平台资源池发过来的数据，同时处理车辆、车站的各类指令消息，并受控于PaaS层中的场景管理服务平台层；
    步骤6，PaaS层中的场景管理服务包括一系列云管理基础服务用于，提供平台级的场景管理服务，可被SaaS层调用，其中PaaS层场景管理服务包括验证计划管理服务、场景用例管理服务、场景需求管理服务、场景环境管理服务、验证资源管理服务、场景配置管理服务和场景报告管理服务；
    步骤7，IaaS基础架构服务层包括一系列半实物半仿真的全自动无人驾驶运控系统设施，所有设施为实物化或虚拟化，IaaS层设施向PaaS层提供基础架构设施服务，接受PaaS层场景管理服务的管理；
    步骤8，SaaS层、Pass层和IaaS层相互做数据交互，所有操作来源于最上层级的云终端，并向云终端提供实时的状态数据反馈。
  10. 根据权利要求9所述的方法，其特征在于，所述的车站SaaS层具备可与中心SaaS层、轨行SaaS层实现通信和联动的条件，通过集成车站SaaS层涉及的多个子系统功能，验证高度联动的车站运营场景和应急场景。
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