Railway alignment optimization in regions with densely-distributed obstacles based on semantic topological maps

IF 5.8 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Xinjie Wan, Hao Pu, Paul Schonfeld, Taoran Song, Wei Li, Lihui Peng
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引用次数: 0

Abstract

Railway alignment development in a study area with densely-distributed obstacles, in which regions favorable for alignments are isolated (termed an isolated island effect, i.e., IIE), is a computation-intensive and time-consuming task. To enhance search efficiency and solution quality, an environmental suitability analysis is conducted to identify alignment-favorable regions (AFRs), focusing the subsequent alignment search on these areas. Firstly, a density-based clustering algorithm (DBSCAN) and a specific criterion are customized to distinguish AFR distribution patterns: continuously-distributed AFRs, obstructed effects, and IIEs. Secondly, a study area characterized by IIEs is represented with a semantic topological map (STM), integrating between-island and within-island paths. Specifically, between-island paths are derived through a multi-directional scanning strategy, while within-island paths are optimized using a Floyd-Warshall algorithm. To this end, the intricate alignment optimization problem is simplified into a shortest path problem, tackled with conventional shortest path algorithms (of which Dijkstra’s algorithm is adopted in this work). Lastly, the proposed method is applied to a real case in a mountainous region with karst landforms. Numerical results indicate its superior performance in both construction costs and environmental suitability compared to human designers and a prior alignment optimization method.

基于语义拓扑图的障碍物密集区域铁路线路优化
摘要在障碍物密集分布的研究区域内进行铁路选线开发是一项计算密集且耗时的任务,因为在该区域内有利于选线的区域是孤立的(称为孤岛效应,即 IIE)。为了提高搜索效率和解决方案质量,我们进行了环境适宜性分析,以确定有利于配准的区域(AFRs),并将后续配准搜索集中在这些区域。首先,定制了基于密度的聚类算法(DBSCAN)和特定标准,以区分 AFR 分布模式:连续分布的 AFR、阻碍效应和 IIE。其次,用语义拓扑图(STM)表示以IIEs为特征的研究区域,整合岛间路径和岛内路径。具体来说,岛间路径是通过多向扫描策略得出的,而岛内路径则是通过 Floyd-Warshall 算法优化的。为此,错综复杂的对齐优化问题被简化为最短路径问题,并采用传统的最短路径算法(本研究采用的是 Dijkstra 算法)加以解决。最后,将所提出的方法应用于喀斯特地貌山区的一个实际案例。数值结果表明,与人工设计人员和之前的排列优化方法相比,该方法在施工成本和环境适宜性方面都表现出色。
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来源期刊
Integrated Computer-Aided Engineering
Integrated Computer-Aided Engineering 工程技术-工程:综合
CiteScore
9.90
自引率
21.50%
发文量
21
审稿时长
>12 weeks
期刊介绍: Integrated Computer-Aided Engineering (ICAE) was founded in 1993. "Based on the premise that interdisciplinary thinking and synergistic collaboration of disciplines can solve complex problems, open new frontiers, and lead to true innovations and breakthroughs, the cornerstone of industrial competitiveness and advancement of the society" as noted in the inaugural issue of the journal. The focus of ICAE is the integration of leading edge and emerging computer and information technologies for innovative solution of engineering problems. The journal fosters interdisciplinary research and presents a unique forum for innovative computer-aided engineering. It also publishes novel industrial applications of CAE, thus helping to bring new computational paradigms from research labs and classrooms to reality. Areas covered by the journal include (but are not limited to) artificial intelligence, advanced signal processing, biologically inspired computing, cognitive modeling, concurrent engineering, database management, distributed computing, evolutionary computing, fuzzy logic, genetic algorithms, geometric modeling, intelligent and adaptive systems, internet-based technologies, knowledge discovery and engineering, machine learning, mechatronics, mobile computing, multimedia technologies, networking, neural network computing, object-oriented systems, optimization and search, parallel processing, robotics virtual reality, and visualization techniques.
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