Swarm Algorithm for Traffic

This article considers a problem of route simulation of autonomous vehicles in a collision-free traffic. A new swarm algorithm is proposed, based on a microscopic traffic model, which ensures the collision-free motion of agents. The change in the several optimality criteria is considered in the process of the algorithm operation, such as: average speed of agents, throughput, and the number of lane changes. The boundaries of the effective values of the algorithm hyperparameters are estimated. Free flow and an improvement in the optimization criteria are observed for certain density parameters and attraction-repulsion factors in the traffic.

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Publication Details

Journal
Scientific and Technical Information Processing
Published
2024-12-01
DOI
https://doi.org/10.3103/s0147688224700564
Citations
1
Primary Topic
Metaheuristic Optimization Algorithms Research
Type
article
Field-Weighted Citation Impact
0.35
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article

Swarm Algorithm for Traffic

Т. В. Гавриленко, Vsevolod Galkin, O. P. Bobrovskaya
1 citations
Scientific and Technical Information Processing
Metaheuristic Optimization Algorithms Research
0.35
article

Swarm Algorithm for Traffic

Т. В. Гавриленко, Vsevolod Galkin, O. P. Bobrovskaya
article en
1 citations

Abstract

This article considers a problem of route simulation of autonomous vehicles in a collision-free traffic. A new swarm algorithm is proposed, based on a microscopic traffic model, which ensures the collision-free motion of agents. The change in the several optimality criteria is considered in the process of the algorithm operation, such as: average speed of agents, throughput, and the number of lane changes. The boundaries of the effective values of the algorithm hyperparameters are estimated. Free flow and an improvement in the optimization criteria are observed for certain density parameters and attraction-repulsion factors in the traffic.

Scientific and Technical Information ProcessingVol. 51(6)
Surgut State University (RU), Research Institute for System Studies (RU)
Openalex Percentile: Top 29%
Metaheuristic Optimization Algorithms Research
0.35
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