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

Xiao Wang, Rui Jiang, Li Li, Yi-Lun Lin and Fei-Yue Wang

Physica A: Statistical Mechanics and its Applications, 2019, vol. 514, issue C, 786-795

Abstract: 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.

Keywords: Car-following; Long memory; Hysteresis; Deep learning (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437118312639
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:514:y:2019:i:c:p:786-795

DOI: 10.1016/j.physa.2018.09.136

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().