Fully Automated Vehicle (AV) Simulation Study in Budapest Improved Road Network Capacity by Increasing Maximum Traffic Flow by 23.81 Percent Going from Zero AV Penetration to a Full AV Scenario.

Simulation Study Conducted Using Budapest Road Network Explored Potential Capacity Impacts of AV Deployment Under Different Conditions.

Date Posted
04/30/2025
Identifier
2025-B01952

The impact of autonomous vehicles on urban traffic network capacity: an experimental analysis by microscopic traffic simulation

Summary Information

Recent advances in vehicle automation have raised interest in their potential to improve urban traffic systems. Fully Automated Vehicles (AVs), in particular, may help ease traffic congestion by reducing the need for parking and maintaining smoother, more consistent traffic flow. To better understand these benefits, this study explored the potential capacity impacts of AV deployment through microscopic traffic simulation. Specifically, the investigation focuses on AVs operating without connected technology by modeling them with distinct behavioral parameters compared to conventional vehicles in a microsimulation simulator. The simulation experiments were conducted on both a synthetic grid network and a real-world road system in Budapest, aiming to assess how AVs might influence urban traffic network capacity under different conditions.

METHODOLOGY

To determine the impacts of variations in market penetration of conventional vehicles and AVs, different simulation scenarios were characterized to represent various combinations of both types of vehicles. The adoption of AVs varied from zero to 100 percent, with 20 percent increments. The simulation results were analyzed with a generalized additive model to find the relationship between average speed and vehicle density, so the flow–density relationship with respect to AVs penetration rate could be identified.

FINDINGS

  • Results for the virtual grid network showed a capacity gain of 16.01 percent going from zero AV to full AV scenario.
  • Budapest network simulation results showed a capacity increment value of 23.81 percent with vehicle traffic going from zero AV penetration to a full AV scenario.
Goal Areas
Results Type
Deployment Locations