[1]张天龙,何 庆,高岩,等.复杂建设环境下基于HybridA*算法的铁路平面线形绿色优化设计[J].高速铁路技术,2024,(01):47-52.[doi:10.12098/j.issn.1674-8247.2024.01.009]
　ZHANG Tianlong,HE Qing,GAO Yan,et al.Green Optimization Design of Railway Horizontal Alignment under Complex Construction Environment Based on Hybrid A* Algorithm[J].HIGH SPEED RAILWAY TECHNOLOGY,2024,(01):47-52.[doi:10.12098/j.issn.1674-8247.2024.01.009]
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复杂建设环境下基于HybridA*算法的铁路平面线形绿色优化设计()
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《高速铁路技术》[ISSN:1674-8247/CN:51-1730/U]

卷:
期数:
2024年01期
页码:
47-52
栏目:
研究创新
出版日期:
2024-03-20

文章信息/Info

Title:
Green Optimization Design of Railway Horizontal Alignment under Complex Construction Environment Based on Hybrid A* Algorithm
文章编号:
1674-8247（2024）01-0047-06
作者:
张天龙; 何 庆; 高岩; 高天赐; 李子涵
西南交通大学，成都 610031
Author(s):
ZHANG Tianlong; HE Qing; GAO Yan; GAO Tianci; LI Zihan
Southwest Jiaotong University ，Chengdu 610031 ，China
关键词:
铁路线路设计; 水平线路; 绿色生态; Hybrid A*算法
Keywords:
railway line design; horizontal alignment; green ecology; Hybrid A* algorithm
分类号:
U212.32
DOI:
10.12098/j.issn.1674-8247.2024.01.009
文献标志码:
A
摘要:
随着“双碳经济下绿色铁路”理念的兴起，将“绿色生态”融入到铁路平面线路优化已成为近年来的研究热点。本文以铁路建设成本与生态破坏成本的协同优化为目标，引入并改进了一种自动驾驶导航算法（HybridA*算法），以适应复杂的铁路设计问题，同时考虑最小曲线半径、最大曲线半径、最短曲线长度、最短夹直线长度、缓和曲线长度等铁路线形约束。研究结果表明：（1）改进后算法以离散网格方式整合外部环境因素，实现渐进式全局探索，获取接近全局最优的铁路线路设计结果；（2）该方法在复杂外部环境约束下，无需预设水平交点位置和数量，可自动生成符合线路-环境耦合约束的优化平面线路方案。
Abstract:
As the concept of the“green railway”gains momentum within the dual-carbon economy framework，the incorporation of“green ecology”into the enhancement of railway planar alignment has emerged as a significant area of research interest in recent years. This study focused on achieving coordinated optimization between railway construction expenses and ecological impact costs. For this purpose，an autonomous driving navigation algorithm （Hybrid A*algorithm）was introduced and modified to effectively tackle intricate railway design challenges. Paramount to the study is the consideration of critical railway alignment constraints which include the minimum and maximum curve radii，the shortest permissible length of curves and transition curves，and the requisite lengths for transition curves. The findings suggest the following：（1）The modified algorithm incorporates external environmental influences in a discrete grid approach，facilitating advanced global exploration and yielding railway alignment designs that approach the global optimal solution. （2）This technique，when applied in the presence of intricate external environmental constraints，eliminates the need for predefining horizontal intersection points and their quantities. Instead，it can autonomously develop optimized planar alignment plans that satisfy the interdependent restrictions of alignment and environment.

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备注/Memo

备注/Memo:
收稿日期：2023-11-09
作者简介：张天龙（1995-），男，博士研究生。
更新日期/Last Update: 2024-03-20