Validation of an agent-based travel demand model with floating car data

被引:1
|
作者
Llorca, Carlos [1 ]
Amini, Sasan [1 ]
Moreno, Ana Tsui [1 ]
Moeckel, Rolf [1 ]
机构
[1] Tech Univ Munich, Arcisstr 21, D-80333 Munich, Germany
关键词
Travel demand modeling; Floating Car Data (FCD); Agent-based model;
D O I
10.1016/j.trpro.2018.12.189
中图分类号
U [交通运输];
学科分类号
08 ; 0823 ;
摘要
This paper compares the results of the agent-based travel demand model MITO (Microscopic Travel Demand Orchestrator) with Floating Car Data. MITO is developed using household travel survey data, and uses the traffic assignment model MATSim. The model estimates the travel demand for an average working day and is applied to the metropolitan area of Munich. In contrast to traditional approaches where travel demand models are validated using the local traffic counts, average travel speed from Floating Car Data (FCD) are used in this study. The main advantage of using FCD is that they cover extremely large parts of the network, whereas the local traffic counts are sparse and limited to a few major streets. The average link travel time and average speed between the model estimation and the FCD were compared with the goal of validating travel time calculations within an agent based transport model. (C) 2019 The Authors. Published by Elsevier Ltd.
引用
收藏
页码:242 / 249
页数:8
相关论文
共 50 条
  • [21] Travel Time Estimate based on Floating Car
    Yang, Zhaosheng
    Gong, Bowen
    Lin, Ciyun
    ICICTA: 2009 SECOND INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTATION TECHNOLOGY AND AUTOMATION, VOL III, PROCEEDINGS, 2009, : 868 - 871
  • [22] A reactive agent-based neural network car following model
    Panwai, S
    Dia, H
    2005 IEEE INTELLIGENT TRANSPORTATION SYSTEMS CONFERENCE (ITSC), 2005, : 326 - 331
  • [23] Travel Time Prediction in Partitioned Road Networks Based on Floating Car Data
    Rempe, Felix
    Huber, Gerhard
    Bogenberger, Klaus
    2016 IEEE 19TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC), 2016, : 1982 - 1987
  • [24] Estimating congestion zones and travel time indexes based on the floating car data
    Erdelic, Tomislav
    Caric, Tonci
    Erdelic, Martina
    Tisljaric, Leo
    Turkovic, Ana
    Jelusic, Niko
    COMPUTERS ENVIRONMENT AND URBAN SYSTEMS, 2021, 87
  • [25] Mining method of floating car data based on link travel time estimation
    Li, Hui-Bing
    Yang, Xiao-Guang
    Luo, Li-Hua
    Jiaotong Yunshu Gongcheng Xuebao/Journal of Traffic and Transportation Engineering, 2014, 14 (06): : 100 - 109
  • [26] Urban travel behavior analyses and route prediction based on floating car data
    Sun, Daniel
    Zhang, Chun
    Zhang, Lihui
    Chen, Fangxi
    Peng, Zhong-Ren
    TRANSPORTATION LETTERS-THE INTERNATIONAL JOURNAL OF TRANSPORTATION RESEARCH, 2014, 6 (03): : 118 - 125
  • [27] Agent-based model of last-mile parcel deliveries and travel demand incorporating online shopping behavior
    Reiffer, Anna S.
    Kuebler, Jelle
    Kagerbauer, Martin
    Vortisch, Peter
    RESEARCH IN TRANSPORTATION ECONOMICS, 2023, 102
  • [28] Model validation - Methodological problems in agent-based modeling
    Yang, Min
    Xiong, Ze-Jian
    Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice, 2013, 33 (06): : 1458 - 1470
  • [29] Validation and Calibration of an Agent-Based Model: A Surrogate Approach
    Zhang, Yi
    Li, Zhe
    Zhang, Yongchao
    DISCRETE DYNAMICS IN NATURE AND SOCIETY, 2020, 2020
  • [30] Validation in agent-based models: An investigation on the CATS model
    Bianchi, Carlo
    Cirillo, Pasquale
    Gallegati, Mauro
    Vagliasindi, Pietro A.
    JOURNAL OF ECONOMIC BEHAVIOR & ORGANIZATION, 2008, 67 (3-4) : 947 - 964