4.6 Article

Long memory is important: A test study on deep-learning based car-following model

Journal

Publisher

ELSEVIER
DOI: 10.1016/j.physa.2018.09.136

Keywords

Car-following; Long memory; Hysteresis; Deep learning

Funding

  1. National Natural Science Foundation of China [61790565]
  2. Beijing Municipal Science and Technology Commission Program, China [D171100000317002]
  3. Beijing Municipal Commission of Transport, China [ZC179074Z]
  4. Natural Science Foundation of Beijing Municipality, China [9172013]

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Whether long memory effect plays an important role in car-following models remains unsolved. In this paper, we study the possible relationship between long memory effect and hysteresis phenomena observed in practice. Especially, we have compared the performance of different deep learning based car-following models that take various time-scale historical information as inputs. Test show that hysteresis phenomena can be correctly simulated only by car-following models with long memory. So, we argue that car-following models should embed long memory effect appropriately. (C) 2018 Elsevier B.V. All rights reserved.

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