Microsimulation reveals changes in human-driven vehicle behavior due to varying automated vehicle influences.
Key Points
Higher market penetration rates of automated vehicles reduced the time headway and acceleration in human-driven vehicles, indicating behavioral adaptation.
The analysis of driving behavior metrics such as lane change frequency showed that aggressive automated vehicles led to increased relative velocity in human-driven vehicles.
A driving simulator experiment with 160 participants provided critical trajectory data for calibrating the microsimulation model using VISSIM software.
These findings emphasize the importance of integrating human-driven vehicle adaptation into traffic assessments to design effective policies.