Highway intelligent route selection method in permafrost region of Qinghai-Tibet Plateau
-
摘要: 为解决传统公路选线方法难以完全考虑青藏高原多年冻土区复杂地理环境的问题, 将地理信息系统(GIS)的空间数据分析技术与智能进化算法引入到多年冻土区的公路选线过程中。利用GIS进行青藏高原多年冻土区的空间数据挖掘, 从冻土病害影响因子的连续度和发育度方面考虑多年冻土区微地貌对公路选线的影响, 建立了冻土病害危险度计算模型。利用面向对象技术开发组件式GIS, 应用于青藏高原多年冻土区, 完成了对多年冻土区复杂地理信息的分析和提取。构建了线位优化遗传算法, 确立了自适应的迭代策略, 借助粒子群算法, 建立了基于遗传算法的路线优化模型。以青藏高原西大滩至昆仑山口路线走廊带某路段为例, 进行了公路智能选线研究, 经算法多次迭代后, 得到了最优的线位方案。研究结果表明: 在实际环境数据试验中, 遗传算法在迭代至第60代左右时得到危险度最低的优选方案, 其综合危险度稳定在3.75左右。可见, 青藏高原多年冻土区公路智能选线方法能够结合各类冻土病害的危险程度, 为公路线位布局指明冻土病害影响较小的区域, 有效兼顾了“主动保护多年冻土, 确保路基稳定, 生态环境友好, 布局经济合理”等要求, 可作为多年冻土区公路路线设计的参考方法。Abstract: To solve the problem that traditional highway route selection method can not fully consider the complex geographical environment in the permafrost region of Qinghai-Tibet Plateau, the spatial data analysis technology of geographic information system(GIS)and intelligent evolutionary algorithm were introduced into the highway route selection process in permafrost region. The spatial data mining in the permafrost region of Qinghai-Tibet Plateau was finished by using GIS, the influence of the microtopography of the permafrost region on highway route selection was considered from the continuity degree and development degree of the influence factors of frozen soil diseases, and the risk degree calculation model of frozen soil disease was established. The component GIS was developed by using object-oriented components technology, and then applied in the permafrost region of Qinghai-Tibet Plateau, so the analysis and extraction of complex geographic information in the permafrost region were completed. The route optimization genetic algorithm and the adaptive iterative method were established, and with the aid of particle swarm algorithm, the route optimization model was set up based on the genetic algorithm. A road section of the route corridor of Qinghai-Tibet Plateau between Xidatan and Kunlun Mountains pass was selected as an example, and the highway intelligent route selection was researched, and the final route position scheme was obtained. Analysis result shows that in the experiment based on real environmental data, the optimal scheme with the least of risk degree is obtained after about 60 th iteration, and the risk degree is stable at about 3. 75. So the intelligent route selection method in the permafrost region of Qinghai-Tibet Plateau can combine the risk of all kinds of frozen soil diseases, and specify the area with less impact of frozen soil disease for highway layout. The optimized scheme effectively takes into account the "initiative protecting permafrost, ensuring the stability of roadbed, friendly ecological environment, economic-reasonable layout"requirements, and can be used as the reference method for highway route design in the permafrost region.
-
图 6 青藏高原多年冻土区危险度识别结果
Figure 6. Risk degree identification result of permafrost region result of Qinghai-Tibet Plateau
表 1 判断矩阵的一般形式
Table 1. General form of judgment matrix
表 2 随机一致性指标取值
Table 2. Values of random coincidence index
表 3 准则层1中各因素的判断矩阵
Table 3. Judgment matrix of factors in criterion layer 1
表 4 准则层1中各因素的相对权重
Table 4. Relative weights of factors in criterion layer 1
表 5 危险度函数中的权重
Table 5. Weights of risk degree function
表 6 准则层2中各因素的判断矩阵
Table 6. Judgment matrix of factors in criterion layer 2
表 7 准则层2中各因素的相对权重
Table 7. Relative weights of factors in criterion layer 2
表 8 连续度函数中的权重
Table 8. Weights of continuity degree function
表 9 准则层3中各因素的判断矩阵
Table 9. Judgment matrix of factors in criterion layer 3
表 10 0准则层3中各因素的相对权重
Table 10. Relative weights of factors in criterion layer 3
表 11 1发育度函数中的权重
Table 11. Weights of development degree function
表 12 2不同的标度分值所对应的冻土病害分级
Table 12. Scale classification of frozen soil disease corresponding to different scales scores
表 13 3地块属性值与总危险度
Table 13. Block attribute values and total risk degrees
表 14 4运行指标
Table 14. Operation indexes
-
[1] SADEK S, KAYSI I, BEDRAN M. Geotechnical and environmental considerations in highway layouts: an integrated GIS assessment approach[J]. International Journal of Applied Earth Observation and Geoinformation, 2000, 2(3/4): 190-198. [2] JONG J C, SCHONFELD P. An evolutionary model for simultaneously optimizing three-dimensional highway alignments[J]. Transportation Research Part B: Methodological, 2003, 37(2): 107-128. doi: 10.1016/S0191-2615(01)00047-9 [3] KANG M W, JHA M K, SCHONFELD P. Applicability of highway alignment optimization models[J]. Transportation Research Part C: Emerging Technologies, 2012, 21(1): 257-286. doi: 10.1016/j.trc.2011.09.006 [4] KAZEMI S F, SHAFAHI Y. An integrated model of parallel processing and PSO algorithm for solving optimum highway alignment problem[C]//IEEE. 27th European Conference on Modelling and Simulation. New York: IEEE, 2013: 551-557. [5] 易思蓉, 张家玲, 邓域才. 生成线路初始平面的自动优化方法[J]. 西南交通大学学报, 2002, 37(1): 1-5. https://www.cnki.com.cn/Article/CJFDTOTAL-XNJT200201000.htmYI Si-rong, ZHANG Jia-ling, DENG Yu-cai. An automatic optimization method for designing the initial horizontal alignment of new railway lines[J]. Journal of Southwest Jiaotong University, 2002, 37(1): 1-5. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-XNJT200201000.htm [6] 许金良, 王海君, 杨少伟. 基于遗传算法的公路纵断面优化[J]. 交通运输工程学报, 2003, 3(2): 48-52. doi: 10.3321/j.issn:1671-1637.2003.02.011XU Jin-liang, WANG Hai-jun, YANG Shao-wei. Optimization of highway profile based on genetic algorithms[J]. Journal of Traffic and Transportation Engineering, 2003, 3(2): 48-52. (in Chinese). doi: 10.3321/j.issn:1671-1637.2003.02.011 [7] 马庆雷. 基于遗传算法的公路平面优化[J]. 中国公路学报, 2006, 19(1): 42-46. doi: 10.3321/j.issn:1001-7372.2006.01.009MA Qing-lei. Optimization of highway plane based on genetic algorithm[J]. China Journal of Highway and Transport, 2006, 19(1): 42-46. (in Chinese). doi: 10.3321/j.issn:1001-7372.2006.01.009 [8] 高华. 基于遗传算法和多目标决策体系的公路选线整体优化[D]. 长沙: 中南大学, 2007.GAO Hua. The overall optimization of highway line selection based on genetic algorithm and multi-objective decision system[D]. Changsha: Central South University, 2007. (in Chinese). [9] 阮沈勇, 黄润秋. 基于GIS的信息量法模型在地质灾害危险性区划中的应用[J]. 成都理工学院学报, 2001, 28(1): 89-92. doi: 10.3969/j.issn.1671-9727.2001.01.018RUAN Shen-yong, HUANG Run-qiu. Application of GISbased information model on assessment of geological hazards risk[J]. Journal of Chengdu University of Technology, 2001, 28(1): 89-92. (in Chinese). doi: 10.3969/j.issn.1671-9727.2001.01.018 [10] 王平, 史培军. 自下而上进行区域自然灾害综合区划的方法研究——以湖南省为案例[J]. 自然灾害学报, 1999, 8(3): 54-60. https://www.cnki.com.cn/Article/CJFDTOTAL-ZRZH199903007.htmWANG Ping, SHI Pei-jun. The research of regional natural disasterregionalization with the"bottom-up"methods—a case study of Hunan Province[J]. Journal of Natural Disasters, 1999, 8(3): 54-60. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-ZRZH199903007.htm [11] 杨宏志, 卢瑜. 公路路线智能优化方法研究[J]. 交通信息与安全, 2009, 27(5): 77-80, 84. doi: 10.3963/j.ISSN1674-4861.2009.05.017YANG Hong-zhi, LU Yu. Intelligent optimization method of highway alignment[J]. Journal of Transport Information and Safety, 2009, 27(5): 77-80, 84. (in Chinese). doi: 10.3963/j.ISSN1674-4861.2009.05.017 [12] 苑福. 多年冻土地区厚层地下冰对铁路的危害与防治[J]. 路基工程, 1992(6): 14-17. https://www.cnki.com.cn/Article/CJFDTOTAL-LJGC199206003.htmYUAN Fu. Damage and control of thick layer underground ice to railway in permafrost regions[J]. Subgrade Engineering, 1992(6): 14-17. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-LJGC199206003.htm [13] 程国栋. 厚层地下冰的形成过程[J]. 中国科学: B辑, 1982(3): 281-288. https://www.cnki.com.cn/Article/CJFDTOTAL-JBXK198203010.htmCHENG Guo-dong. The formation process of thick layer underground ice[J]. Science China: Series B, 1982(3): 281-288. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-JBXK198203010.htm [14] 牛富俊, 程国栋, 赖远明, 等. 青藏高原多年冻土区热融滑塌型斜坡失稳研究[J]. 岩土工程学报, 2004, 26(3): 402-406. doi: 10.3321/j.issn:1000-4548.2004.03.021NIU Fu-jun, CHENG Guo-dong, LAI Yuan-ming, et al. Instability study on thaw slumping in permafrost regions of Qinghai-Tibet Plateau[J]. Chinese Jounal of Geotechnical Engineering, 2004, 26(3): 402-406. (in Chinese). doi: 10.3321/j.issn:1000-4548.2004.03.021 [15] RAUTIAINEN K, PARKKINEN T, LEMMETYINEN J, et al. SMOS prototype algorithm for detecting autumn soil freezing[J]. Remote Sensing of Environment, 2016, 180: 346-360. doi: 10.1016/j.rse.2016.01.012 [16] 王平. 青藏铁路多年冻土区冻胀丘发展特征及其对路基稳定性的影响[J]. 铁道标准设计, 2013(5): 1-4. https://www.cnki.com.cn/Article/CJFDTOTAL-TDBS201305002.htmWANG Ping. Development features of frost mound in permafrost region and their influence on subgrade stability along Qinghai-Tibet Railway[J]. Railway Standard Design, 2013(5): 1-4. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-TDBS201305002.htm [17] ZHOU Wan-fang, BECK B F, ADAMS A L. Application of matrix analysis in delineating sinkhole risk areas along highway(I-70near Frederic, Maryland)[J]. Environmental Geology, 2003, 44(7): 834-842. doi: 10.1007/s00254-003-0828-8 [18] KAO Y C, CHEN M H, HUANG Y T. A hybrid algorithm based on ACO and PSO for capacitated vehicle routing problems[J]. Mathematical Problems in Engineering, 2012, 2012(1024-123X): 1-17. [19] 谢翠明. 基于GIS的公路地质灾害区域危险性评价与预测[D]. 长沙: 中南大学, 2008.XIE Cui-ming. Evaluation and prediction of regional risk of highway geological hazards based on GIS[D]. Changsha: Central South University, 2008. (in Chinese). [20] 黄杏元, 徐寿成. GIS动态缓冲带分析模型及其应用[J]. 中国图象图形学报, 1998, 3(10): 871-873. doi: 10.3969/j.issn.1006-8961.1998.10.014HUANG Xing-yuan, XU Shou-cheng. GIS-based dynamic buffer analysis model and its applications[J]. Journal of Image and Graphics, 1998, 3(10): 871-873. (in Chinese). doi: 10.3969/j.issn.1006-8961.1998.10.014 [21] 郑镝. 青藏高原腹地多年冻土区典型地质灾害研究[D]. 北京: 中国地质大学, 2009.ZHENG Di. The study on the typical geological hazards at permafrost areas in the center of Qinghai-Tibet Plateau[D]. Beijing: China University of Geosciences, 2009. (in Chinese). [22] CHANG P C, HUANG W H, TING C J. A hybrid geneticimmune algorithm with improved lifespan and elite antigen for flow-shop scheduling problems[J]. International Journal of Production Research, 2011, 49(17): 5207-5230. doi: 10.1080/00207543.2010.510808 [23] 涂圣文, 苏州. 基于GIS和遗传-粒子群的公路智能选线方法[J]. 长安大学学报: 自然科学版, 2010, 30(4): 39-45. doi: 10.3969/j.issn.1671-8879.2010.04.008TU Sheng-wen, SU Zhou. Intelligent route selection of highway alignments based on GIS and hybrid genetic algorithm and particle swarm optimization[J]. Journal of Chang'an University: Natural Science Edition, 2010, 30(4): 39-45. (in Chinese). doi: 10.3969/j.issn.1671-8879.2010.04.008 [24] 杨宏志, 韩跃杰, 李芬, 等. 基于GIS和遗传算法的公路智能选线[J]. 长安大学学报: 自然科学版, 2009, 29(3): 48-53. doi: 10.3321/j.issn:1671-8879.2009.03.011YANG Hong-zhi, HAN Yue-jie, LI Fen, et al. Highway intelligent alignment selection based on GIS and genetic algorithms[J]. Journal of Chang'an University: Natural Science Edition, 2009, 29(3): 48-53. (in Chinese). doi: 10.3321/j.issn:1671-8879.2009.03.011 [25] 秦广军. 遗传算法的改进研究与应用[D]. 郑州: 郑州大学, 2006.QIN Guang-jun. Improved research and application of genetic algorithm[D]. Zhengzhou: Zhengzhou University, 2006. (in Chinese). [26] LUKES Z, RAIDA Z. Multi-objective optimization of wire antennas: genetic algorithms versus particle swarm optimization[J]. Radioengineering, 2005, 14(4): 91-97. [27] ALTUN A A. A combination of genetic algorithm, particle swarm optimization and neural network for palmprint recognition[J]. Neural Computing and Applications, 2013, 22(1): 27-33. [28] 蔡菂迪. 改进遗传算法在车辆路径问题中的研究应用[D]. 哈尔滨: 哈尔滨工程大学, 2013.CAI Di-di. Improved genetic algorithm to solve the vehicle routing problem[D]. Harbin: Harbin Engineering University, 2013. (in Chinese). -
下载:
点击查看大图
计量
- 文章访问数: 725
- HTML全文浏览量: 164
- PDF下载量: 753
- 被引次数: 0
