Behavioral Calibration and Analysis of a Large-Scale Travel Microsimulation

被引:38
|
作者
Floetteroed, Gunnar [1 ]
Chen, Yu [2 ]
Nagel, Kai [2 ]
机构
[1] Ecole Polytech Fed Lausanne, Transport & Mobil Lab TRANSP OR, CH-1015 Lausanne, Switzerland
[2] Berlin Inst Technol, Transport Syst Planning & Transport Telemat Lab, D-10587 Berlin, Germany
来源
NETWORKS & SPATIAL ECONOMICS | 2012年 / 12卷 / 04期
关键词
Multi-agent simulation; Dynamic traffic assignment; Disaggregate demand calibration; Real-world application; MODEL;
D O I
10.1007/s11067-011-9164-9
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
This article reports on the calibration and analysis of a fully disaggregate (agent-based) transport simulation for the metropolitan area of Zurich. The agent-based simulation goes beyond traditional transport models in that it equilibrates not only route choice but all-day travel behavior, including departure time choice and mode choice. Previous work has shown that the application of a novel calibration technique that adjusts all choice dimensions at once from traffic counts yields cross-validation results that are competitive with any state-of-the-art four-step model. While the previous study aims at a methodological illustration of the calibration method, this work focuses on the real-world scenario, and it elaborates on the usefulness of the obtained results for further demand analysis purposes.
引用
收藏
页码:481 / 502
页数:22
相关论文
共 50 条
  • [31] Designing a large-scale public transport network using agent-based microsimulation
    Manser, Patrick
    Becker, Henrik
    Hoerl, Sebastian
    Axhausen, Kay W.
    [J]. TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE, 2020, 137 : 1 - 15
  • [32] Extraction and Analysis of Regionally Specific Behavioral Facilitation Information in the Event of a Large-scale Disaster
    Yamamoto, Futo
    Suzuki, Yu
    Nadamoto, Akiyo
    [J]. 2021 IEEE/WIC/ACM INTERNATIONAL CONFERENCE ON WEB INTELLIGENCE AND INTELLIGENT AGENT TECHNOLOGY (WI-IAT 2021), 2021, : 538 - 543
  • [33] Interaction and Engagement with an Anxiety Management App: Analysis Using Large-Scale Behavioral Data
    Matthews, Paul
    Topham, Phil
    Caleb-Solly, Praminda
    [J]. JMIR MENTAL HEALTH, 2018, 5 (04):
  • [34] Global Calibration of Distributed Hydrological Models for Large-Scale Applications
    Ricard, S.
    Bourdillon, R.
    Roussel, D.
    Turcotte, R.
    [J]. JOURNAL OF HYDROLOGIC ENGINEERING, 2013, 18 (06) : 719 - 721
  • [35] Distributed Signature Learning and Calibration for Large-Scale Sensor Networks
    Ramakrishnan, Naveen
    Ertin, Emre
    Moses, Randolph. L.
    [J]. 2010 CONFERENCE RECORD OF THE FORTY FOURTH ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS AND COMPUTERS (ASILOMAR), 2010, : 1545 - 1549
  • [36] Calibration method for a large-scale structured light measurement system
    Wang, Peng
    Wang, Jianmei
    Xu, Jing
    Guan, Yong
    Zhang, Guanglie
    Chen, Ken
    [J]. APPLIED OPTICS, 2017, 56 (14) : 3995 - 4002
  • [37] An Electrohydraulic Force Control System for Large-Scale Force Calibration
    Cheng, Min
    Jiang, Dayu
    Sun, Bolin
    Chen, Xingxi
    [J]. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2022, 71
  • [38] Challenges in the calibration of large-scale ordinary differential equation models
    Kapfer, Eva-Maria
    Stapor, Paul
    Hasenauer, Jan
    [J]. IFAC PAPERSONLINE, 2019, 52 (26): : 58 - 64
  • [39] Novel system for calibration of large-scale length measuring instruments
    Ma, LQ
    Li, BY
    Jin, SY
    Wang, JH
    Wang, LD
    Wang, XD
    [J]. PROCEEDINGS OF THE THIRD INTERNATIONAL SYMPOSIUM ON INSTRUMENTATION SCIENCE AND TECHNOLOGY, VOL 1, 2004, : 890 - 895
  • [40] Accurate Kinematics Calibration Method for a Large-Scale Machine Tool
    Wan, An
    Wang, Yixuan
    Xue, Guijun
    Chen, Ken
    Xu, Jing
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2021, 68 (10) : 9832 - 9843