Neural network architecture for the estimation of drivers' route choice

被引:0
|
作者
Kyung Whan Kim
Dae Hyon Kim
Hyun Yeal Seo
机构
[1] College of Engineering,Urban Engineering Major, Division of Construction Engineering
[2] Gyeongsang National University,Environment & Regional Development Institute
[3] Yosu National University,Transportation Engineering Major, Division of Transportation & Logistics System Engineering
[4] Gyeongsang National,Department of Urvan Engineering, Graduate School
关键词
artificial neural network; customized neural network; logit model; route choice;
D O I
10.1007/BF02829155
中图分类号
学科分类号
摘要
The artificial neural network has recently been applied in many areas including transport engineering and planning. However, since the general neural network considers all the listed variables in a batch, the network seemed to be unsophisticated. A more sophisticated neural network model therefore had to be developed. In this study, a sophisticated neural network model was developed for drivers' route choice model. Its performance was then compared with the performance of the Logit model. For the development of the neural network model, two different neural network models-the general neural network model and the customized neural network model whose architecture is similar to the Logit models-were considered. The results showed that the customized neural network could perform better than other models in terms of prediction accuracy and goodness-of-fit.
引用
收藏
页码:329 / 336
页数:7
相关论文
共 50 条
  • [31] An application of cumulative prospect theory to freeway drivers' route choice behaviours
    Jou, Rong-Chang
    Chen, Ke-Hong
    TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE, 2013, 49 : 123 - 131
  • [32] Drivers' route choice and learning mechanism under bounded information environment
    Do, Myungsik
    Ryu, Sikyun
    Lee, Seungjae
    Journal of Advanced Transportation, 1600, 40 (02): : 164 - 182
  • [33] ROUTE CHOICE WITH HETEROGENEOUS DRIVERS AND GROUP-SPECIFIC CONGESTION COSTS
    ARNOTT, R
    DEPALMA, A
    LINDSEY, R
    REGIONAL SCIENCE AND URBAN ECONOMICS, 1992, 22 (01) : 71 - 102
  • [34] Exploring the role of social networks in modeling drivers' route choice behavior
    Liang, Hongfeng
    Qian, Yiheng
    Zhu, Mengxiao
    Chen, Ying
    TRANSPORTATION RESEARCH PART F-TRAFFIC PSYCHOLOGY AND BEHAVIOUR, 2024, 104 : 154 - 169
  • [35] Empirical Evaluation of Drivers' Route Choice Behavioral Responses to Social Navigation
    Djavadian, Shadi
    Hoogendoorn, Raymond G.
    van Arem, Bart
    Chow, Joseph Y. J.
    TRANSPORTATION RESEARCH RECORD, 2014, (2423) : 52 - 60
  • [36] Influence of smartphone traffic application information on drivers' route choice behaviours
    Qi, Xinyi
    Ji, Yanjie
    Yu, Jiajie
    Bu, Qing
    Samal, Dmitry Ivanovich
    IET INTELLIGENT TRANSPORT SYSTEMS, 2022, 16 (10) : 1413 - 1426
  • [37] Modelling drivers' compliance and route choice behaviour in response to travel information
    Dia, Hussein
    Panwai, Sakda
    NONLINEAR DYNAMICS, 2007, 49 (04) : 493 - 509
  • [38] Drivers' route choice and learning mechanism under bounded information environment
    Do, Myungsik
    Ryu, Sikyun
    Lee, Seungjae
    JOURNAL OF ADVANCED TRANSPORTATION, 2006, 40 (02) : 165 - 183
  • [39] Influence of Expressway Construction Area Information on Drivers' Route Choice Behaviours
    Li, Yuexiang
    Guo, Bao
    Zhao, Wei
    Lv, Mengqi
    Lu, Peng
    Wang, Chengcheng
    Ji, Zhonggang
    Xu, Qiuchen
    JOURNAL OF ADVANCED TRANSPORTATION, 2024, 2024
  • [40] The combined effect of information and experience on drivers’ route-choice behavior
    Eran Ben-Elia
    Ido Erev
    Yoram Shiftan
    Transportation, 2008, 35 : 165 - 177