基于高分辨率点云的大容量和重型运输的增强三维交通分析

IF 2.5 4区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC
Marcus Irmer, Ina Kalder, Marco Tönnemann, René Degen, Lucas Rüggeberg, Karin Thomas, Margot Ruschitzka
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引用次数: 0

摘要

大容量和重型运输对于成功和及时执行大型工业、社会政治和气候相关项目至关重要。随着这些运输的规模和复杂性的增长,规划过程对所有相关利益相关者来说变得越来越具有挑战性。为了克服这些挑战,需要详细的规划过程,特别是运输路线沿线狭窄通道的可通行性。本文介绍了一种先进的方法,用于增强大容量和重型运输的三维通行性分析与碰撞检测。通过采用高分辨率、密集、彩色的3D点云以及详细的运输模型,该方法可以更准确、更全面地评估运输的可行性。该方法被进一步推广,以适应各种各样的运输配置和机动,允许跨不同场景的自动分析。本研究的主要贡献在于能够显著提高碰撞检测精度并提供详细的可视化,从而优化大容量重型运输的数字化规划过程。研究结果表明,与传统的2D方法相比,3D交通分析具有明显的优势,特别是在复杂环境中,可以实现成本效益高、可靠的交通规划。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Enhanced 3D Trafficability Analysis for Large-Volume and Heavy-Duty Transports Based on High-Resolution Point Clouds

Enhanced 3D Trafficability Analysis for Large-Volume and Heavy-Duty Transports Based on High-Resolution Point Clouds

Enhanced 3D Trafficability Analysis for Large-Volume and Heavy-Duty Transports Based on High-Resolution Point Clouds

Enhanced 3D Trafficability Analysis for Large-Volume and Heavy-Duty Transports Based on High-Resolution Point Clouds

Large-volume and heavy-duty transports are essential for the successful and timely execution of large-scale industrial, socio-political and climate-related projects. As these transports grow in size and complexity, the planning process becomes increasingly challenging for all stakeholders involved. To overcome these challenges, detailed planning processes are required, especially for the trafficability of narrow passages along the transportation route. This paper introduces an advanced methodology for an enhanced 3D trafficability analysis with collision detection of large-volume and heavy-duty transports. By employing high-resolution, dense, colored 3D point clouds alongside detailed transport models, this approach offers a more accurate and comprehensive assessment of the feasibility of the transport. The methodology is further generalized to accommodate a wide variety of transport configurations and maneuvers, allowing for automated analysis across different scenarios. The primary contribution of this research lies in its ability to significantly improve collision detection accuracy and provide detailed visualizations, thereby optimizing the digital planning process of large-volume and heavy-duty transports. The findings demonstrate a distinct advantage of the 3D trafficability analysis over traditional 2D methods, especially in complex environments, leading to cost-effective and reliable transportation planning.

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来源期刊
IET Intelligent Transport Systems
IET Intelligent Transport Systems 工程技术-运输科技
CiteScore
6.50
自引率
7.40%
发文量
159
审稿时长
3 months
期刊介绍: IET Intelligent Transport Systems is an interdisciplinary journal devoted to research into the practical applications of ITS and infrastructures. The scope of the journal includes the following: Sustainable traffic solutions Deployments with enabling technologies Pervasive monitoring Applications; demonstrations and evaluation Economic and behavioural analyses of ITS services and scenario Data Integration and analytics Information collection and processing; image processing applications in ITS ITS aspects of electric vehicles Autonomous vehicles; connected vehicle systems; In-vehicle ITS, safety and vulnerable road user aspects Mobility as a service systems Traffic management and control Public transport systems technologies Fleet and public transport logistics Emergency and incident management Demand management and electronic payment systems Traffic related air pollution management Policy and institutional issues Interoperability, standards and architectures Funding scenarios Enforcement Human machine interaction Education, training and outreach Current Special Issue Call for papers: Intelligent Transportation Systems in Smart Cities for Sustainable Environment - https://digital-library.theiet.org/files/IET_ITS_CFP_ITSSCSE.pdf Sustainably Intelligent Mobility (SIM) - https://digital-library.theiet.org/files/IET_ITS_CFP_SIM.pdf Traffic Theory and Modelling in the Era of Artificial Intelligence and Big Data (in collaboration with World Congress for Transport Research, WCTR 2019) - https://digital-library.theiet.org/files/IET_ITS_CFP_WCTR.pdf
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