Computing Dynamic User Equilibria on Large-Scale Networks with Software Implementation

被引:35
|
作者
Han, Ke [1 ]
Eve, Gabriel [1 ]
Friesz, Terry L. [2 ]
机构
[1] Imperial Coll London, Dept Civil & Environm Engn, London SW7 2BU, England
[2] Penn State Univ, Dept Ind & Mfg Engn, State Coll, PA 16803 USA
来源
NETWORKS & SPATIAL ECONOMICS | 2019年 / 19卷 / 03期
基金
美国国家科学基金会;
关键词
Dynamic traffic assignment; Dynamic user equilibrium; Dynamic network loading; Traffic flow model; Fixed-point algorithm; Software; VARIATIONAL INEQUALITY FORMULATION; CELL TRANSMISSION MODEL; PARTIAL-DIFFERENTIAL-EQUATION; TRAFFIC ASSIGNMENT MODEL; KINEMATIC WAVES; SIMULTANEOUS ROUTE; EXISTENCE; FLOW; COMPUTATION;
D O I
10.1007/s11067-018-9433-y
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
Dynamic user equilibrium (DUE) is the most widely studied form of dynamic traffic assignment (DTA), in which road travelers engage in a non-cooperative Nash-like game with departure time and route choices. DUE models describe and predict the time-varying traffic flows on a network consistent with traffic flow theory and travel behavior. This paper documents theoretical and numerical advances in synthesizing traffic flow theory and DUE modeling, by presenting a holistic computational theory of DUE, which is numerically implemented in a MATLAB package. In particular, the dynamic network loading (DNL) sub-problem is formulated as a system of differential algebraic equations based on the Lighthill-Whitham-Richards fluid dynamic model, which captures the formation, propagation and dissipation of physical queues as well as vehicle spillback on networks. Then, the fixed-point algorithm is employed to solve the DUE problems with simultaneous route and departure time choices on several large-scale networks. We make openly available the MATLAB package, which can be used to solve DUE problems on user-defined networks, aiming to not only facilitate benchmarking a wide range of DUE algorithms and solutions, but also offer researchers a platform to further develop their own models and applications. The MATLAB package and computational examples are available at https://github.com/DrKeHan/DTA.
引用
收藏
页码:869 / 902
页数:34
相关论文
共 50 条
  • [31] Dynamic Representation Learning for Large-Scale Attributed Networks
    Liu, Zhijun
    Huang, Chao
    Yu, Yanwei
    Song, Peng
    Fan, Baode
    Dong, Junyu
    CIKM '20: PROCEEDINGS OF THE 29TH ACM INTERNATIONAL CONFERENCE ON INFORMATION & KNOWLEDGE MANAGEMENT, 2020, : 1005 - 1014
  • [32] Efficient Online Summarization of Large-Scale Dynamic Networks
    Qu, Qiang
    Liu, Siyuan
    Zhu, Feida
    Jensen, Christian S.
    IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2016, 28 (12) : 3231 - 3245
  • [33] Fast paths in large-scale dynamic road networks
    Giacomo Nannicini
    Philippe Baptiste
    Gilles Barbier
    Daniel Krob
    Leo Liberti
    Computational Optimization and Applications, 2010, 45 : 143 - 158
  • [34] Weak State Routing for Large-Scale Dynamic Networks
    Acer, Utku Guenay
    Kalyanaraman, Shivkumar
    Abouzeid, Alhussein A.
    IEEE-ACM TRANSACTIONS ON NETWORKING, 2010, 18 (05) : 1450 - 1463
  • [35] Implementation and analysis of scalable and flexible node for large-scale networks
    Kodama, T
    Oguchi, N
    Kawasaki, T
    Sudo, T
    Tsuruoka, T
    2005 Asia-Pacific Conference on Communications (APCC), Vols 1& 2, 2005, : 842 - 846
  • [36] A study on analysis engine for large-scale user behavior based on cloud computing
    Dai, Wei
    Jiang, Zilong
    International Journal of Multimedia and Ubiquitous Engineering, 2014, 9 (12): : 37 - 48
  • [37] SOFTWARE AS A LARGE-SCALE SYSTEM
    SAGE, AP
    LARGE SCALE SYSTEMS IN INFORMATION AND DECISION TECHNOLOGIES, 1987, 12 (03): : 185 - 188
  • [38] Proline: an efficient and user-friendly software suite for large-scale proteomics
    Bouyssie, David
    Hesse, Anne-Marie
    Mouton-Barbosa, Emmanuelle
    Rompais, Magali
    Macron, Charlotte
    Carapito, Christine
    de Peredo, Anne Gonzalez
    Coute, Yohann
    Dupierris, Veronique
    Burel, Alexandre
    Menetrey, Jean-Philippe
    Kalaitzakis, Andrea
    Poisat, Julie
    Romdhani, Aymen
    Burlet-Schiltz, Odile
    Cianferani, Sarah
    Garin, Jerome
    Bruley, Christophe
    BIOINFORMATICS, 2020, 36 (10) : 3148 - 3155
  • [39] Large-Scale Dynamic Graph Updating Algorithm in Distributed Computing System
    Rong Xuanyu
    Cui Huanqing
    PROCEEDINGS OF 2019 2ND INTERNATIONAL CONFERENCE ON BIG DATA TECHNOLOGIES (ICBDT 2019), 2019, : 248 - 251
  • [40] Performance optimization of heterogeneous computing for large-scale dynamic graph data
    Wang, Haifeng
    Guo, Wenkang
    Zhang, Ming
    Journal of Supercomputing, 2025, 81 (01):