Automated hazard detection for safe airport apron operations using a (weather-)robust LiDAR object recognition system
使用(天气)稳健的 LiDAR 物体识别系统进行自动危险检测,确保机场停机坪安全运行
基本信息
- 批准号:237482626
- 负责人:
- 金额:--
- 依托单位:
- 依托单位国家:德国
- 项目类别:Research Grants
- 财政年份:2013
- 资助国家:德国
- 起止时间:2012-12-31 至 2021-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
In addition to the airport runway being a component that incurs considerable risk to air travel, in particular airfield movement areas are characterized by a substantial and empirical proven accumulation of safety occurrences in the aviation system. Due to a significant low degree of standardization for operators, technology, and procedures on the neighboring airport apron, procedural and technological measures for risk mitigation at the airport have been exclusively focusing on the maneuvering area so far. Preliminary studies conducted at TU Dresden have shown deficiencies in the operators information picture that would significantly contribute to an increased risk on the airport`s movement areas. If such a lack of information occurs, the operator`s capability to recognize the hazard and subsequently avoid damage would be clearly limited. At this point, the augmentation of the information level of quality, enabled by LiDAR sensing, is considered as key element for effective risk mitigation. The respective proof of this hypothesis will be provided along the application of established risk assessment procedures according to EUROCONTROL, a field, in which the applicant has been gathering significant experience for years. Then, after the potential for risk mitigation will have been identified on a methodological basis, the respective potential will be experimentally verified by means of LiDAR sensor technology generating 3D point clouds of all objects on the apron which will be installed at Dresden International Airport. LiDAR is judged of being exceptionally qualified to visualize hazard causes and derived hazard indicators connected to safety critical occurrences. Even more, these fundamental characteristics of LiDAR generated 3D point clouds and thus so gathered experimental results can methodically be transferred to other sensors (e.g. infrared, RADAR).As such, a methodical hazard assessment of the apron controller`s task based on accident and incident data will be conducted, subsequently followed by the identification of visual indicators as corresponding cause. Further, a LiDAR monitoring concept will be developed, including an HMI concept for a 3D point cloud visualization that will be subject to experimental validation. Along this, identified hazards will be modeled with the help of scenarios and will be further analyzed on their estimated contribution to risk mitigation while operating the HMI. In the scope of an envisaged experimental field-test at Dresden Airport, relevant scenarios will be reconstructed and assessed by operational apron controllers (granted by the airport authority). It will be evaluated how far a contribution to a higher detection probability of hazards causes and effective risk mitigation can be achieved by visual means. The respective cooperation agreement from Dresden Airport is attached to this tender.
除了机场跑道是对空中旅行造成相当大风险的一个组成部分之外,特别是机场活动区的特点是航空系统中大量和经验证明的安全事件的积累。由于邻近机场停机坪上的操作人员、技术和程序标准化程度很低,到目前为止,机场风险缓解的程序和技术措施一直只集中在机动区域。在德累斯顿工业大学进行的初步研究表明,运营商的信息图片存在缺陷,这将大大增加机场活动区域的风险。如果出现这种信息缺乏的情况,操作者识别危险并随后避免损害的能力显然会受到限制。在这一点上,通过LiDAR传感实现的信息质量水平的提高被认为是有效降低风险的关键因素。将沿着应用根据EUROCONTROL(申请人在该领域已积累了多年的丰富经验)确定的风险评估程序,提供该假设的相应证据。然后,在方法学基础上确定风险缓解潜力后,将通过激光雷达传感器技术对将安装在德累斯顿国际机场的停机坪上的所有物体进行3D点云实验验证。LiDAR被认为是非常有资格可视化危险原因和与安全关键事件相关的衍生危险指标。更重要的是,激光雷达生成的三维点云的这些基本特征以及因此收集的实验结果可以有条不紊地传输到其他传感器(例如红外线,雷达)。因此,将根据事故和事件数据对停机坪管制员的任务进行有条不紊的危险评估,随后识别视觉指示器作为相应的原因。此外,还将开发LiDAR监测概念,包括用于3D点云可视化的HMI概念,该概念将接受实验验证。沿着,将在场景的帮助下对已识别的危险进行建模,并将进一步分析其对操作HMI时风险缓解的估计贡献。在德累斯顿机场设想的实验性现场测试范围内,将由运行停机坪控制员(由机场当局批准)重建和评估相关场景。将评价通过视觉手段在多大程度上有助于提高危害原因的检测概率和有效的风险缓解。德累斯顿机场的相关合作协议附在本标书中。
项目成果
期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Professor Dr.-Ing. Hartmut Fricke其他文献
Professor Dr.-Ing. Hartmut Fricke的其他文献
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{{ truncateString('Professor Dr.-Ing. Hartmut Fricke', 18)}}的其他基金
Using ADS-B big data pattern analysis to improve the quality of multivariate 4D trajectory optimization strategies
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Improved Continuous Descent Operations considering environmental and mission related uncertainties
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- 批准号:
327114631 - 财政年份:2017
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Enhanced Flight Planning by introducing stochastic trajectory data
通过引入随机轨迹数据增强飞行计划
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347224103 - 财政年份:2017
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Closed-loop stochastic dynamic process optimization under input and state constraints for Ground Process Management at Airports
机场地面流程管理输入和状态约束下的闭环随机动态流程优化
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189795363 - 财政年份:2011
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Integrated micro- and macroscopic Aeronautical Risk Assessment based on technical, procedural and human performance factors with limited parameter sets
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119520566 - 财政年份:2009
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Integrating Safety Metrics into the Arrival Capacity Management of large Aerodromes
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445666898 - 财政年份:
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使用机器学习的集成实时航空控制系统
- 批准号:
517414238 - 财政年份:
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