# Dissipation of traffic congestion using agent-based car-following model with modified optimal velocity

## TL;DR

This paper models traffic flow using a stochastic agent-based car-following approach with a modified optimal velocity, demonstrating how autonomous agents and adaptive speed limits can reduce congestion and improve overall traffic efficiency.

## Contribution

It introduces a modified optimal velocity model incorporating autonomous agents and safety rules, showing their effects on traffic dynamics and congestion mitigation.

## Key findings

- Agents increase average velocity and traffic current.
- Presence of agents delays traffic congestion onset.
- Adaptive speed limits can help exit congested phases.

## Abstract

We investigate dynamical properties of traffic flow using the stochastic car-following model with modified optimal velocity on circular road. The safety distance following the two-second rule and autonomous vehicles, acting as agents, obeying simple requirements are incorporated into the model. The dynamic safety distance increases in a light traffic condition where the average driving velocity is high, while decreases in a dense traffic condition in anticipation of slower traffic motion. The results show that the presence of the agents can enhance overall velocity and traffic current of the system, and postpone the traffic congestion. In a particular phase region, imposing a speed limit enables the system to leave the congested flow phase. The density-dependent speed limit in agent-free condition is obtained to achieve the optimal traffic flow.