[1]闫晟煜,赵转转,赵凌煜,等.基于收费数据的高速公路改扩建路段OD反推方法[J].长安大学学报(自然科学版),2025,45(5):163-171.[doi:10.19721/j.cnki.1671-8879.2025.05.014]
　YAN Sheng-yu,ZHAO Zhuan-zhuan,ZHAO Ling-yu,et al.OD backstepping method for reconstructed and expanded expressway sections based on toll collection data[J].Journal of Chang’an University (Natural Science Edition),2025,45(5):163-171.[doi:10.19721/j.cnki.1671-8879.2025.05.014]
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基于收费数据的高速公路改扩建路段OD反推方法()
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长安大学学报（自然科学版）[ISSN:1006-6977/CN:61-1281/TN]

卷:
第45卷
期数:
2025年5期
页码:
163-171
栏目:
交通工程
出版日期:
2025-09-30

文章信息/Info

Title:
OD backstepping method for reconstructed and expanded expressway sections based on toll collection data
文章编号:
1671-8879(2025)05-0163-09
作者:
闫晟煜1; 赵转转2; 赵凌煜1; 余娜1; 郑鑫1; 刘杨1
(1. 长安大学 汽车学院,陕西 西安 710064; 2. 陕西交通职业技术学院 汽车运用工程学院,陕西 西安 710018)
Author(s):
YAN Sheng-yu1;  ZHAO Zhuan-zhuan2;  ZHAO Ling-yu1;  YU Na1;  ZHENG Xin1;  LIU Yang1
(1. School of Automobile, Chang'an University, Xi'an 710064, Shaanxi, China; 2. School of Automotive Application Engineering, Shaanxi College of Communications Technology, Xi'an 710018, Shaanxi, China)
关键词:
交通工程;  高速公路;  改扩建规划;  出行OD;  最大熵模型;  收费数据
Keywords:
Key words:traffic engineering;  expressway;  reconstructed and expanded planning;  traffic OD;  maximum entropy model;  toll collection data
分类号:
U491.1
DOI:
10.19721/j.cnki.1671-8879.2025.05.014
文献标志码:
A
摘要:
为应对新时期大规模高速公路改扩建规划需求,基于收费数据,提出了一种改扩建路段OD反推方法; 考虑路段节点类型,提出了OD交通小区划分原则; 梳理了改扩建路段OD反推流程,提出了域内型、途经型、到达型和发送型4种OD划分方法; 针对途经型OD的复杂性,提出了途经型初始OD生成方法; 分析了不加约束条件的反推解集,建立了基于最大熵原理的OD反推模型,采用拉格朗日乘数法求解模型,采用容量限制分配法实现了交通分配; 运用TransCAD和Python对途经型OD进行加载与迭代,通过设定收敛误差控制离散统计量和最大上下行偏差率; 以二广高速公路改扩建规划为例,验证了模型的可行性和运行效率,并分析了迭代次数与最大上下行偏差率的关系。研究结果表明:迭代次数增加时最大上下行偏差率减小,分步实施4次交通分配可实现路段交通量有效加载,迭代29次后离散统计量和最大上下行偏差率小于5%,迭代时间为5 min,离散统计量为1.32%,说明提出的路段OD反推模型能够有效且快速地完成实例路段的OD迭代与分配过程; 由路段拓扑结构的8个枢纽可知,有2个枢纽的转向交通量超过了10 000 pcu·d-1的设计标准,需要设置双幅车道。综上所述,研究成果可支撑改扩建路段的规划与设计。
Abstract:
To meet the large-scale need of reconstructed and expanded planning of expressway in the new era, the OD backstepping method for reconstructed and expanded road sections was proposed based on toll collection data. Considering the node types of road section, the division principle of traffic zones for OD was proposed, and the OD backstepping process of the reconstructed and expanded road section was sorted out. A method was proposed for dividing the total OD into domain type, passing type, arrival type, and sending type. In response to the complexity of passing type OD, a method for generating the initial passing type OD was proposed, and the backstepping solution set without any constraints was analyzed. Based on the maximum entropy principle, a OD backstepping model was proposed. The model was solved by Lagrange multiplier model, and the capacity restriction assignment method was adopted to achieve traffic allocation. The passing type OD was loaded and iterated by TransCAD and Python. By setting the convergence error, the discrete statistics and maximum deviation rates of upstream and downstream were controlled. Taking the reconstructed and expanded planning of the Erenhot-Guangzhou Expressway as an example, the feasibility and efficiency of the model were verified, and the relationship between the iteration number and maximum deviation rates of upstream and downstream was analyzed. The research results show that the maximum deviation rate of upstream and downstream decreases as the iteration number increases. By dividing the traffic allocation process into 4 steps, the model can effectively load the traffic volume of road sections. After the 29th iteration, the discrete statistics and maximum deviation rates of upstream and downstream can be limited to 5%, the iteration time is 5 min, and the discrete statistics is 1.32%, indicating that the proposed OD backstepping model for the road section can effectively and quickly complete the OD iteration and allocation process of the example road section. According to the topology structure of the 8 hubs at the road section, there are 2 hubs' turning traffic volumes exceed the design specification 10 000 pcu·d-1, so it is necessary to construct dual lanes. In summary, the analysis results can support the planning and design of reconstructed and expended road section.4 tabs, 4 figs, 31 refs.

参考文献/References:

[1] 闫晟煜,赵佳琪,尤文博,等.高速公路货车差异化通行费折扣的双层规划模型[J].清华大学学报(自然科学版),2025,65(7):1347-1358.
YAN Sheng-yu, ZHAO Jia-qi, YOU Wen-bo, et al. Bi-level programming model for differentiated toll discounts for expressway trucks[J]. Journal of Tsinghua University(Science and Technology), 2025, 65(7): 1347-1358.
[2]OHAZULIKE A E, STILL G, KERN W, et al. An origin-destination based road pricing model for static and multi-period traffic assignment problems[J]. Transportation Research Part E: Logistics and Transportation Review, 2013, 58(11): 1-27.
[3]张 蕾.武广高铁客流变化分析与预测[D].长沙:中南大学,2012.
ZHANG Lei. Analysis on the change and forecast passenger flow of Wuhan-Guangzhou High-Speed Railway[D]. Changsha: Central South University, 2012.
[4]HAZELTON M L. Some comments on origin-destination matrix estimation[J]. Transportation Research Part A: Policy and Practice, 2003, 37(10): 811-822.
[5]焦朋朋,陆化普.高速路段动态OD反推模型与算法研究[J].公路交通科技,2005,22(4):95-98.
JIAO Peng-peng, LU Hua-pu. Study on estimation of dynamic origin-destination flows in expressway corridors[J]. Journal of Highway and Transportation Research and Development, 2005, 22(4): 95-98.
[6]易昆南,李志纯.由路段交通量推算OD矩阵的一种有效方法及其应用[J].运筹与管理,2002,11(5):65-70.
YI Kun-nan, LI Zhi-chun. An effective method and application for estimating OD matrix from traffic counts[J]. Operations Research and Management Science, 2002, 11(5): 65-70.
[7]MAHMUDABADI M, ALI BEHZADI G. An algorithm for determining optimum link traffic volume counts for estimation of origin-destination matrix[J]. Civil Engineering Journal-Tehran, 2018, 4(6): 1447-1455.
[8]TSEKERIS T, STATHOPOULOS A. Treating uncertain demand information in origin-destination matrix estimation with traffic counts[J]. Journal of Transportation Engineering, 2008, 134(8): 327-337.
[9]DIXON M P, RILETT L R. Real-time OD estimation using automatic vehicle identification and traffic count data[J]. Computer-Aided Civil and Infrastructure Engineering, 2002, 17(1): 7-21.
[10]宋现敏,刘焕峰,李志慧,等.基于OD分布的环形交叉口车辆行程时间建模[J].吉林大学学报(工学版),2016,46(1):70-75.
SONG Xian-min, LIU Huan-feng, LI Zhi-hui, et al. New model of vehicle travel time at roundabout based on OD distribution[J]. Journal of Jilin University(Engineering and Technology Edition), 2016, 46(1): 70-75.
[11]HE S L, DING F, ZHOU Y, et al. Investigating and modelling the relationship between traffic volume and extracts from cellphone activity data[J]. IET Intelligent Transport Systems, 2019, 13(8): 1299-1308.
[12]CHEN A, CHOOTINAN P, RYU S, et al. An intersection turning movement estimation procedure based on path flow estimator[J]. Journal of Advanced Transportation, 2012, 46(2): 161-176.
[13]KIM H, JAYAKRISHNAN R. The estimation of a time-dependent OD trip table with vehicle trajectory samples[J]. Transportation Planning and Technology, 2010, 33(8): 747-768.
[14]ROSTAMI NASAB M, SHAFAHI Y. Estimation of origin-destination matrices using link counts and partial path data[J]. Transportation, 2020, 47(6): 2923-2950.
[15]TUYDES-YAMAN H, ALTINTASI O, SENDIL N. Better estimation of origin-destination matrix using automated intersection movement count data[J]. Canadian Journal of Civil Engineering, 2015, 42(7): 490-502.
[16]俞礼军.具有路段容量限制的广义系统最优交通分配[J].华南理工大学学报(自然科学版),2021,49(4):140-148.
YU Li-jun. Generalized system-optimal traffic assignment with link capacity constraints[J]. Journal of South China University of Technology(Natural Science Edition), 2021, 49(4): 140-148.
[17]严世祥,李起辉,向宏杨,等.基于高速公路收费数据和交调站数据的省域公路网OD生成技术研究[J].科技通报,2022,38(7):88-95.
YAN Shi-xiang, LI Qi-hui, XIANG Hong-yang, et al. OD estimation of provincial highway network based on freeway toll data and traffic count station data[J]. Bulletin of Science and Technology, 2022, 38(7): 88-95.
[18]MICHAU G, PUSTELNIK N, BORGNAT P, et al. A primal-dual algorithm for link dependent origin destination matrix estimation[J]. IEEE Transactions on Signal and Information on Processing over Networks, 2017, 3(1): 104-113.
[19]TOLEDO T, KOLECHKINA T. Estimation of dynamic origin-destination matrices using linear assignment matrix approximations[J]. IEEE Transactions on Intelligent Transportation Systems, 2013, 14(2): 618-626.
[20]闫晟煜,王钊龙,武 瑾,等.省域高速公路网车辆碳排放量测算方法[J].中国环境科学,2024,44(12):7095-7104.
YAN Sheng-yu, WANG Zhao-long, WU Jin, et al. Estimation model of vehicle carbon emission for provincial expressway networks[J]. China Environmental Science, 2024, 44(12): 7095-7104.
[21]王 炜,孙 俊.大型交通网络OD矩阵推算方法研究[J].东南大学学报,1996,26(6):47-54.
WANG Wei, SUN Jun. Research on method of estimating O-D matrices for large-sized transportation network[J]. Journal of Southeast University, 1996, 26(6): 47-54.
[22]汪成亮,张 晨,黄文龙.面向车联网的高速路OD矩阵估计模型[J].西南交通大学学报,2013,48(6):1078-1083.
WANG Cheng-liang, ZHANG Chen, HUANG Wen-long. Origin-destination matrix estimation model for freeway oriented internet of vehicles[J]. Journal of Southwest Jiaotong University, 2013, 48(6): 1078-1083.
[23]KUUSINEN J M, SORSA J, SIIKONEN M L. The elevator trip origin-destination matrix estimation problem[J]. Transportation Science, 2015, 49(3): 559-576.
[24]VIGOS G, PAPAGEORGIOU M, WANG Y B. Real-time estimation of vehicle-count within signalized links[J]. Transportation Research Part C: Emerging Technologies, 2008, 16(1): 18-35.
[25]TANG J J, WANG Y P, HU C, et al. A spectral clustering enabled SPSA algorithm for dynamic origin-destination demand matrix estimation[J]. Transportmetrica B-Transport Dynamics, 2025, 13(1): 2459928.
[26]HE S X. A graphical approach to identify sensor locations for link flow inference[J]. Transportation Research Part B: Methodological, 2013, 51(3): 65-76.
[27]GONZÁLEZ P H, CLÍMACO G, MAURI G R, et al. New approaches for the traffic counting location problem[J].Expert Systems with Applications, 2019, 132(10): 189-198.
[28]HU S R, WANG C M. Vehicle detector deployment strategies for the estimation of network origin-destination demands using partial link traffic counts[J]. IEEE Transactions on Intelligent Transportation Systems, 2008, 9(2): 288-300.
[29]刘 晟,王卫星,曹 霆,等.基于差分计盒维数及最大熵阈值的裂缝提取[J].长安大学学报(自然科学版),2015,35(5):13-21.
LIU Sheng, WANG Wei-xing, CAO Ting, et al. Road crack extraction based on differential box dimension and maximum entropy threshold[J]. Journal of Chang'an University(Natural Science Edition), 2015, 35(5): 13-21.
[30]郭仁拥,黄海军.考虑OD需求变异的网络交通流演化模型[J].系统工程理论与实践,2009,29(1):118-123.
GUO Ren-yong, HUANG Hai-jun. Network traffic flow evolution model considering OD demand mutation[J]. Systems Engineering-Theory and Practice, 2009, 29(1): 118-123.
[31]程国柱,李金禹,陈永胜,等.高速公路异构交通流HDV建模及其特征[J].长安大学学报(自然科学版),2024,44(4):97-107.
CHENG Guo-zhu, LI Jin-yu, CHEN Yong-sheng, et al. Modeling of human-driven vehicles and characteristics of heterogeneous traffic flow for freeway[J]. Journal of Chang'an University(Natural Science Edition), 2024, 44(4): 97-107.

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备注/Memo

备注/Memo:
收稿日期:2025-02-25
基金项目:国家重点研发计划项目(2023YFB3209803); 陕西省重点研发计划项目(2025CY-YBXM-064); 中央高校基本科研业务费专项资金项目(300102224206); 陕西省教育厅科学研究计划项目(23JK0335)
作者简介:闫晟煜(1987-),男,黑龙江绥化人,副教授,工学博士,E-mail:Leo9574@163.com。
更新日期/Last Update: 2025-09-30