TY - GEN
T1 - Analyzing the Impact of Autonomous Vehicles on Urban Traffic Flow at the Large Scale Network Using Real-World Data
AU - Jang, Hyeokjun
AU - Kim, Inhi
AU - Park, Shin Hyoung
AU - Jang, Kitae
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - This study evaluates the network performance of Daejeon City's traffic based on the market penetration rate of Autonomous Vehicles (AVs). Real-world AV data from the Waymo perception dataset is used to calibrate the parameters of a car-following model. AVs exhibit smoother speed changes, longer time headway, and a larger minimum gap compared to human-driven vehicles. These conservative driving behaviors enhance safety and comfort for passengers in AVs. And they result in a decrease in road capacity by approximately 35% when AVs reach 100% composition of the current road vehicle mix. The study validates previous assumptions and logic in AV research using real-world data, providing insights for policy-making and technological development. Future work should consider incorporating multiple datasets to gain a more comprehensive understanding of the impacts of AVs.
AB - This study evaluates the network performance of Daejeon City's traffic based on the market penetration rate of Autonomous Vehicles (AVs). Real-world AV data from the Waymo perception dataset is used to calibrate the parameters of a car-following model. AVs exhibit smoother speed changes, longer time headway, and a larger minimum gap compared to human-driven vehicles. These conservative driving behaviors enhance safety and comfort for passengers in AVs. And they result in a decrease in road capacity by approximately 35% when AVs reach 100% composition of the current road vehicle mix. The study validates previous assumptions and logic in AV research using real-world data, providing insights for policy-making and technological development. Future work should consider incorporating multiple datasets to gain a more comprehensive understanding of the impacts of AVs.
UR - http://www.scopus.com/inward/record.url?scp=85186502479&partnerID=8YFLogxK
U2 - 10.1109/ITSC57777.2023.10421991
DO - 10.1109/ITSC57777.2023.10421991
M3 - Conference contribution
AN - SCOPUS:85186502479
T3 - IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
SP - 5530
EP - 5535
BT - 2023 IEEE 26th International Conference on Intelligent Transportation Systems, ITSC 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 26th IEEE International Conference on Intelligent Transportation Systems, ITSC 2023
Y2 - 24 September 2023 through 28 September 2023
ER -