KdV–Burgers equation in a new continuum model based on full velocity difference model considering anticipation effect
Rongjun Cheng,
Hongxia Ge and
Jufeng Wang
Physica A: Statistical Mechanics and its Applications, 2017, vol. 481, issue C, 52-59
Abstract:
In this paper, a new continuum model based on full velocity difference car following model is developed with the consideration of driver’s anticipation effect. By applying the linear stability theory, the new model’s linear stability is obtained. Through nonlinear analysis, the KdV–Burgers equation is derived to describe the propagating behavior of traffic density wave near the neutral stability line. Numerical simulation shows that the new model possesses the local cluster, and it is capable of explaining some particular traffic phenomena Numerical results show that when considering the effects of anticipation, the traffic jams can be suppressed efficiently. The key improvement of this new model is that the anticipation effect can improve the stability of traffic flow.
Keywords: Traffic flow; Continuum model; KdV–Burgers equation; Anticipation effect (search for similar items in EconPapers)
Date: 2017
References: View complete reference list from CitEc
Citations: View citations in EconPapers (45)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437117303047
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:481:y:2017:i:c:p:52-59
DOI: 10.1016/j.physa.2017.04.004
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 ().