模型驱动开发方法逐渐应用于航空航天等领域的安全关键软件设计与实现中。体系结构分析设计语言(Architecture Analysis and Design Language,AADL)是一种标准化的嵌入式软件体系结构描述语言,通过建模、验证以及代码自动生成为安全关...模型驱动开发方法逐渐应用于航空航天等领域的安全关键软件设计与实现中。体系结构分析设计语言(Architecture Analysis and Design Language,AADL)是一种标准化的嵌入式软件体系结构描述语言,通过建模、验证以及代码自动生成为安全关键软件的设计与实现提供完整支持。然而,工业界实际代码是运行在具有不同特性的目标平台上的,例如不同的软硬件体系结构和编程接口,而现有AADL代码生成研究主要是通过手工将自动生成的代码集成到平台当中,存在工作繁琐且易出错的问题。为此,本文提出一种基于AADL的航天嵌入式软件Ada代码自动生成方法。首先,给出卫星姿轨控系统的AADL建模;其次,给出AADL到平台相关的Ada代码自动转化规则;最后,给出代码生成原型工具,并对卫星姿轨控系统AADL模型所生成的代码进行航天编码规范检查,并运行在相关仿真环境中,验证了本文所提方法的有效性。展开更多
Driving safety field(DSF) model has been proposed to represent comprehensive driving risk formed by interactions of driver-vehicle-road in mixed traffic environment. In this work, we establish an optimization model ba...Driving safety field(DSF) model has been proposed to represent comprehensive driving risk formed by interactions of driver-vehicle-road in mixed traffic environment. In this work, we establish an optimization model based on grey relation degree analysis to calibrate risk coefficients of DSF model. To solve the optimum solution, a genetic algorithm is employed. Finally, the DSF model is verified through a real-world driving experiment. Results show that the DSF model is consistent with driver's hazard perception and more sensitive than TTC. Moreover, the proposed DSF model offers a novel way for criticality assessment and decision-making of advanced driver assistance systems and intelligent connected vehicles.展开更多
The need for efficient and reproducible development processes for sensor and perception systems is growing with their increased use in modern vehicles. Such processes can be achieved by using virtual test environments...The need for efficient and reproducible development processes for sensor and perception systems is growing with their increased use in modern vehicles. Such processes can be achieved by using virtual test environments and virtual sensor models. In the context of this, the present paper documents the development of a sensor model for depth estimation of virtual three-dimensional scenarios. For this purpose, the geometric and algorithmic principles of stereoscopic camera systems are recreated in a virtual form. The model is implemented as a subroutine in the Epic Games Unreal Engine, which is one of the most common Game Engines. Its architecture consists of several independent procedures that enable a local depth estimation, but also a reconstruction of a whole three-dimensional scenery. In addition, a separate programme for calibrating the model is presented. In addition to the basic principles, the architecture and the implementation, this work also documents the evaluation of the model created. It is shown that the model meets specifically defined requirements for real-time capability and the accuracy of the evaluation. Thus, it is suitable for the virtual testing of common algorithms and highly automated driving functions.展开更多
针对2013年8月15—16日先后在辽宁省锦州和抚顺地区发生的特大暴雨,分别以T639和NCEP预报场作为背景场,利用中尺度数值模式WRF(Weather Research and Forecasting Model)和ADAS(ARPS Data Analysis System)同化系统进行了同化多普勒雷...针对2013年8月15—16日先后在辽宁省锦州和抚顺地区发生的特大暴雨,分别以T639和NCEP预报场作为背景场,利用中尺度数值模式WRF(Weather Research and Forecasting Model)和ADAS(ARPS Data Analysis System)同化系统进行了同化多普勒雷达观测资料的试验,检验同化雷达资料和采用不同背景场对暴雨预报的影响。结果表明:(1)同化雷达资料前,使用两种背景场的预报结果对锦州的强降水均出现漏报,同化雷达资料后,均预报出了锦州黑山一带的强降水,而12~24 h预报结果中对位于抚顺地区强降水预报的改善不大,采用T639较NCEP预报作为背景场对抚顺地区强降水的预报更好;(2)ADAS同化雷达资料后对模式初始湿度场的改善较大,700 h Pa和850 h Pa比湿有明显的增量。同时,同化雷达资料后更新了模式初始场中的水物质,水物质增量位置和强降水发生位置有较好的对应关系;(3)通过分析模式预报的风场,回波和水汽通量散度发现,同化试验预报初期在锦州和阜新一带预报出了强度较强且深厚的水汽场,低层西南暖湿气流和高层西北干冷气流的配置在锦州地区水汽区域的左侧激发了强烈的上升辐合运动,而其右侧伴有强烈的辐散是导致锦州黑山强降水爆发的主要原因。展开更多
文摘模型驱动开发方法逐渐应用于航空航天等领域的安全关键软件设计与实现中。体系结构分析设计语言(Architecture Analysis and Design Language,AADL)是一种标准化的嵌入式软件体系结构描述语言,通过建模、验证以及代码自动生成为安全关键软件的设计与实现提供完整支持。然而,工业界实际代码是运行在具有不同特性的目标平台上的,例如不同的软硬件体系结构和编程接口,而现有AADL代码生成研究主要是通过手工将自动生成的代码集成到平台当中,存在工作繁琐且易出错的问题。为此,本文提出一种基于AADL的航天嵌入式软件Ada代码自动生成方法。首先,给出卫星姿轨控系统的AADL建模;其次,给出AADL到平台相关的Ada代码自动转化规则;最后,给出代码生成原型工具,并对卫星姿轨控系统AADL模型所生成的代码进行航天编码规范检查,并运行在相关仿真环境中,验证了本文所提方法的有效性。
基金Projects(51475254,51625503)supported by the National Natural Science Foundation of ChinaProject(MCM20150302)supported by the Joint Project of Tsinghua and China Mobile,ChinaProject supported by the joint Project of Tsinghua and Daimler Greater China Ltd.,Beijing,China
文摘Driving safety field(DSF) model has been proposed to represent comprehensive driving risk formed by interactions of driver-vehicle-road in mixed traffic environment. In this work, we establish an optimization model based on grey relation degree analysis to calibrate risk coefficients of DSF model. To solve the optimum solution, a genetic algorithm is employed. Finally, the DSF model is verified through a real-world driving experiment. Results show that the DSF model is consistent with driver's hazard perception and more sensitive than TTC. Moreover, the proposed DSF model offers a novel way for criticality assessment and decision-making of advanced driver assistance systems and intelligent connected vehicles.
文摘The need for efficient and reproducible development processes for sensor and perception systems is growing with their increased use in modern vehicles. Such processes can be achieved by using virtual test environments and virtual sensor models. In the context of this, the present paper documents the development of a sensor model for depth estimation of virtual three-dimensional scenarios. For this purpose, the geometric and algorithmic principles of stereoscopic camera systems are recreated in a virtual form. The model is implemented as a subroutine in the Epic Games Unreal Engine, which is one of the most common Game Engines. Its architecture consists of several independent procedures that enable a local depth estimation, but also a reconstruction of a whole three-dimensional scenery. In addition, a separate programme for calibrating the model is presented. In addition to the basic principles, the architecture and the implementation, this work also documents the evaluation of the model created. It is shown that the model meets specifically defined requirements for real-time capability and the accuracy of the evaluation. Thus, it is suitable for the virtual testing of common algorithms and highly automated driving functions.
文摘针对2013年8月15—16日先后在辽宁省锦州和抚顺地区发生的特大暴雨,分别以T639和NCEP预报场作为背景场,利用中尺度数值模式WRF(Weather Research and Forecasting Model)和ADAS(ARPS Data Analysis System)同化系统进行了同化多普勒雷达观测资料的试验,检验同化雷达资料和采用不同背景场对暴雨预报的影响。结果表明:(1)同化雷达资料前,使用两种背景场的预报结果对锦州的强降水均出现漏报,同化雷达资料后,均预报出了锦州黑山一带的强降水,而12~24 h预报结果中对位于抚顺地区强降水预报的改善不大,采用T639较NCEP预报作为背景场对抚顺地区强降水的预报更好;(2)ADAS同化雷达资料后对模式初始湿度场的改善较大,700 h Pa和850 h Pa比湿有明显的增量。同时,同化雷达资料后更新了模式初始场中的水物质,水物质增量位置和强降水发生位置有较好的对应关系;(3)通过分析模式预报的风场,回波和水汽通量散度发现,同化试验预报初期在锦州和阜新一带预报出了强度较强且深厚的水汽场,低层西南暖湿气流和高层西北干冷气流的配置在锦州地区水汽区域的左侧激发了强烈的上升辐合运动,而其右侧伴有强烈的辐散是导致锦州黑山强降水爆发的主要原因。
