Evaluating Traffic Control Strategies for Autonomous Shuttle in Different AV Penetration, Using SUMO Traffic Simulation

Evaluating Traffic Control Strategies for Autonomous Shuttle in Different AV Penetration, Using SUMO Traffic Simulation

연구 분야: Strategies

학회: International Conference on Intelligent Transport Systems

The rapid growth of autonomous vehicles (AVs) and traffic strategies promises to transform urban mobility, necessitating a comprehensive investigation of their impacts on traffic. This study assessed the effects of different traffic control strategies on a network with an autonomous vehicles shuttle and varying levels of AV penetration. The simulation of Urban Mobility (SUMO) software was utilized as an open-source and flexible traffic microsimulation, creating a realistic simulation environment. Three traffic control strategies for shuttle movements were examined in a section of Turin, Italy: mixed traffic, dynamic lane, and separated lane strategies within the network. Each strategy was evaluated across five AV penetration levels. The simulation results demonstrated that increasing the AV integration leads to reduced travel times and greater road efficiency. Both the separated lane and dynamic lane strategies improve travel times for the shuttle but have negative effects on other vehicles. However, the dynamic lane offers improvement for the shuttle while causing a lower negative impact on other vehicles compared to the separated lane strategy. Dynamic lanes offer a flexible and effective solution for modern traffic management, helping cities improve their mobility and reduce congestion. The findings highlight the importance of developing various control strategies and AV-compatible infrastructure to achieve traffic efficiency, reduced congestion, and an updated urban mobility framework.