2020/01/27 by Yi Sun, Sun, Yi, Changhui Tan +1
Engineering · Mathematics · Physics and Astronomy · Social Sciences · #Traffic Prediction and Management Techniques #Traffic control and management #Transportation Planning and Optimization #math.PR #msc:35L65 #msc:35Q82 #msc:60K30 #msc:90B20 #nlin.CG #physics.soc-ph
paper · pdf · doi:10.48550/arxiv.2001.10017
24 pages, 6 figures
arxiv created 2020/01/27 · arxiv updated 2020/01/29
This paper presents a new class of one-dimensional (1D) traffic models with look-ahead rules that take into account of two effects: nonlocal slow-down effect and right-skewed non-concave asymmetry in the fundamental diagram. The proposed 1D cellular automata (CA) models with the Arrhenius type look-ahead interactions implement stochastic rules for cars' movement following the configuration of the traffic ahead of each car. In particular, we take two different look-ahead rules: one is based on the distance from the car under consideration to the car in front of it; the other one depends on the car density ahead. Both rules feature a novel idea of multiple moves, which plays a key role in recovering the non-concave flux in the macroscopic dynamics. Through a semi-discrete mesoscopic stochastic process, we derive the coarse-grained macroscopic dynamics of the CA model. We also design a numerical scheme to simulate the proposed CA models with an efficient list-based kinetic Monte Carlo (KMC) algorithm. Our results show that the fluxes of the KMC simulations agree with the coarse-grained macroscopic averaged fluxes for the different look-ahead rules under various parameter settings.