SearcharxivSearch

arXiv · 2008.02405

Research on PM emission and energy consumption of mixed traffic flow based on cellular automata FI model

Abstract

Traffic congestion leads to a sharp increase in fuel consumption and exhaust emissions, which easily leads to air pollution and fuel waste. Based on Fukui-Ishibashi (FI) model, this paper studies particulate matter(PM) emission and energy dissipation of traffic flow by considering the maximum speed, mixing ratio and random slowing probability. Simulation results show that the energy dissipation of the traffic flow consisting of the same length and different maximum velocity is associated with the maximum velocity. The greater the maximum velocity, the more the energy consumes. When the maximum velocity is different, the PM emission is similar to the change of energy consumption. Moreover, for the same maximum velocity and different mixing ratio, the energy dissipation and the PM emission related to the mixing ratio. There are the maximum fuel consumption and emission value in the maximum flow. For the same maximum velocity and length of vehicles, their energy consumption and emission are determined by random slowing probability.

Explore related subjects

Keep this discovery

BibTeXRIS

Dong Chen, Yanping Huang, Xue Wang, Mi Tan, Bingling Cen. 2020-08-06. Research on PM emission and energy consumption of mixed traffic flow based on cellular automata FI model. https://arxiv.org/abs/2008.02405

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Optical free space extreme learning machine for the implementation of emergent complex systems

Cellular automata conform a set of computational models which evolve with a reduced set of simple rules, yet still are able to show extremely complex emergent phenomena such as fractals and universal computation. Despite their apparent simplicity, they have shown great potential in simulating natural systems and solving challenging computational tasks such as classification and image generation. Instead of implementing cellular automata purely at the software level, it is desirable to design novel analog computing platforms that physically evolve following the automata's underlying rules, thereby reducing power requirements and latency. Here, we introduce an optical extreme learning machine for the simulation of a wide range of cellular automata. Our system operates in free space, and uses a spatial light modulator to encode the evolution rules of the system, while coherent wave propagation performs the corresponding computations. Our results demonstrate a simple, fully-programmable, cost and power efficient, and easy to build and align platform for the implementation of a wide range of complex computational systems such as elementary cellular automata, Conway's Game of Life, and two-dimensional Turing machines.

nlin.CG

The istr-graph: Interactive Visualisation of any Classic-Graph in DDLab

Any type of attractor basin (classic-graph) created in DDLab can now be visualised, manipulated, and deconstructed as a drag/drop ``interactive state transition graph'' (istr-graph). The new istr-graph applies to subtrees, single basins, the basin of attraction field, compression, and all other classic-graph parameters. This is an important update on the pre-existing ``interactive basin of attraction field graph'' (ibaf-graph) specific to just the complete uncompressed field, but the ibaf-graph is nevertheless retained for some of its unique attributes. These issues are discussed with a focus on the scope and implementation of the new istr-graph.

nlin.CG

Game of Life on Archimedean Lattices: Glider Guns and Phase Dynamics

I explore Conway's Game of Life (GoL) on six composite Archimedean lattices. On the Kagome lattice, on which small gliders and puffers appear particularly frequently across inputs, I use the output of a symmetry-constrained evolutionary search algorithm to construct a novel glider gun. The glider gun comprises four interacting bouncers and stably emits a small glider every 276th generation. Serving as an extension of classical GoL, I also propose cells with a phase degree of freedom and an associated local phase rule, which on the Kagome lattice is demonstrated to host phase-periodic gliders. This enables the possibility of phase-sensitive and interference-based computations.

nlin.CG