Comparison of gap-based and flow-based control strategies using a new controlled stochastic cellular automaton model for traffic flow

Fuente: arXiv
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Hauptverfasser: Kinjo, Kayo, Tomoeda, Akiyasu
Format: Preprint
Veröffentlicht: 2023
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author Kinjo, Kayo
Tomoeda, Akiyasu
author_facet Kinjo, Kayo
Tomoeda, Akiyasu
contents Autonomous vehicles are essential to future transportation systems, potentially reducing traffic congestion. This study examines the impact of different vehicle control strategies on traffic flow through simulations. We propose a novel stochastic cellular automaton model, the controlled stochastic optimal velocity (CSOV) model, which incorporates vehicle control effects. Within the CSOV model, two control strategies are implemented: gap-based control (GC), which adjusts vehicle velocity to balance the gaps between adjacent vehicles, and flow-based control (FC), which aims to maintain a consistent local flow between the front and rear vehicles. Results show that both control strategies improve traffic flow. However, under weaker control, the GC sometimes resulted in lower flow compared to no control. In contrast, the FC consistently enhanced flow across control strengths, yielding more robust outcomes. Furthermore, when both strategies achieved comparable flow rates, the FC provided a more stable velocity distribution under varying traffic densities than the GC.
format Preprint
id arxiv_https___arxiv_org_abs_2308_14291
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Comparison of gap-based and flow-based control strategies using a new controlled stochastic cellular automaton model for traffic flow
Kinjo, Kayo
Tomoeda, Akiyasu
Cellular Automata and Lattice Gases
Statistical Mechanics
Physics and Society
Autonomous vehicles are essential to future transportation systems, potentially reducing traffic congestion. This study examines the impact of different vehicle control strategies on traffic flow through simulations. We propose a novel stochastic cellular automaton model, the controlled stochastic optimal velocity (CSOV) model, which incorporates vehicle control effects. Within the CSOV model, two control strategies are implemented: gap-based control (GC), which adjusts vehicle velocity to balance the gaps between adjacent vehicles, and flow-based control (FC), which aims to maintain a consistent local flow between the front and rear vehicles. Results show that both control strategies improve traffic flow. However, under weaker control, the GC sometimes resulted in lower flow compared to no control. In contrast, the FC consistently enhanced flow across control strengths, yielding more robust outcomes. Furthermore, when both strategies achieved comparable flow rates, the FC provided a more stable velocity distribution under varying traffic densities than the GC.
title Comparison of gap-based and flow-based control strategies using a new controlled stochastic cellular automaton model for traffic flow
topic Cellular Automata and Lattice Gases
Statistical Mechanics
Physics and Society
url https://arxiv.org/abs/2308.14291