A two-stage approach to modeling vacant taxi movements

被引:31
|
作者
Wong, R. C. P. [1 ]
Szeto, W. Y. [1 ]
Wong, S. C. [1 ]
机构
[1] Univ Hong Kong, Dept Civil Engn, Hong Kong, Hong Kong, Peoples R China
基金
中国国家自然科学基金;
关键词
Two-stage approach; Taxi customer-search behavior; Enhanced sequential logit model; Logit-opportunity model; Global positioning system data; SEARCHING BEHAVIOR; NETWORK MODEL; ROAD NETWORKS; SERVICES; INFORMATION; COMPETITION; DEMAND; LEVEL;
D O I
10.1016/j.trc.2015.04.029
中图分类号
U [交通运输];
学科分类号
08 ; 0823 ;
摘要
In this paper, a two-stage modeling approach is proposed to predict vacant taxi movements in searching for customers. The taxi movement problem is formulated into a two-stage model that consists of two sub-models, namely the first and second stage sub-models. The first stage sub-model estimates the zone choice of vacant taxi drivers for customer-search and the second stage sub-model determines the circulation time and distance of vacant taxi drivers in each zone by capturing their local customer-search decisions in a cell-based network within the zone chosen in the first stage sub-model. These two sub-models are designed to influence each other, and hence an iterative solution procedure is introduced to solve for a convergent solution. The modeling concept, advantages, and applications are illustrated by the global positioning system data of 460 Hong Kong urban taxis. The results demonstrate that the proposed model formulation offers a great improvement in terms of root mean square error as compared with the existing taxi customer-search models, and show the model capabilities of predicting the changes in vacant taxi trip distributions with respect to the variations in the fleet size and fare. Potential taxi policies are investigated and discussed according to the findings to provide insights in managing the Hong Kong taxi market. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:147 / 163
页数:17
相关论文
共 50 条
  • [1] A Two-Stage Approach to Modeling Vacant Taxi Movements
    Wong, R. C. P.
    Szeto, W. Y.
    Wong, S. C.
    21ST INTERNATIONAL SYMPOSIUM ON TRANSPORTATION AND TRAFFIC THEORY, 2015, 7 : 254 - 275
  • [2] A TWO-STAGE DEEP MODELING APPROACH TO ARTICULATORY INVERSION
    Shahrebabaki, Abdolreza Sabzi
    Olfati, Negar
    Imran, Ali Shariq
    Johnsen, Magne Hallstein
    Siniscalchi, Sabato Marco
    Svendsen, Torbjorn
    2021 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP 2021), 2021, : 6453 - 6457
  • [3] A two-stage modeling approach for breast cancer survivability prediction
    Sedighi-Maman, Zahra
    Mondello, Alexa
    INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS, 2021, 149
  • [4] A Two-Stage Response Surface Approach to Modeling Drug Interaction
    Zhao, Wei
    Zhang, Lanju
    Zeng, Lingmin
    Yang, Harry
    STATISTICS IN BIOPHARMACEUTICAL RESEARCH, 2012, 4 (04): : 375 - 383
  • [5] A batch reinforcement learning approach to vacant taxi routing
    Yu, Xinlian
    Gao, Song
    TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2022, 139
  • [6] A novel facility location problem for taxi hailing platforms A two-stage neighborhood search heuristic approach
    Ma, Hong
    Shen, Ni
    Zhu, Jing
    Deng, Mingrong
    INDUSTRIAL MANAGEMENT & DATA SYSTEMS, 2020, 120 (03) : 526 - 546
  • [7] A two-stage taxi scheduling strategy at airports with multiple independent runways
    Zou, X.
    Cheng, P.
    Liu, W. D.
    Cheng, N.
    Zhang, J. P.
    TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2018, 95 : 165 - 184
  • [8] Lung cancer survival prognosis using a two-stage modeling approach
    Aggarwal, Preeti
    Marwah, Namrata
    Kaur, Ravreet
    Mittal, Ajay
    MULTIMEDIA TOOLS AND APPLICATIONS, 2024, 83 (22) : 61407 - 61434
  • [9] A Two-Stage Diffusion Modeling Approach to the Compelled-Response Task
    Diederich, Adele
    Colonius, Hans
    PSYCHOLOGICAL REVIEW, 2021, 128 (04) : 787 - 802
  • [10] Meta-analytic structural equation modeling: A two-stage approach
    Cheung, MWL
    Chan, W
    PSYCHOLOGICAL METHODS, 2005, 10 (01) : 40 - 64