TY - JOUR
T1 - Resilience Enhancement of Urban Roadway Network During Disruption via Perimeter Control
AU - Zhu, Chunli
AU - Wen, Guanghui
AU - Li, Nan
AU - Bian, Liheng
AU - Wu, Jianping
AU - Kouvelas, Anastasios
N1 - Publisher Copyright:
© 2013 IEEE.
PY - 2024/1/1
Y1 - 2024/1/1
N2 - Frequent happened extreme weather events (EWEs) cause severe disruptions to the operation of large-scale urban road network. Perimeter control is of high application potential in the target scenarios. However, few studies are concerned about the lacking knowledge of the system's response features under EWE. In this work, we proposed a network resilience curve (NRC)-based perimeter control strategy to facilitate the network equilibrium, therefore enhancing the network resilience. The proposed NRC is an extension of the classical macroscopic fundamental diagram (MFD) under disruptions. A real-world trajectory dataset under normal and rainstorm day has been analyzed comparatively by using the present NRC, in which average velocity immediately reduces while average flow reveals the hysteresis effect. We compared the strategies of fixed plan, NRC-based proportional-integral (PI) control without or with connected vehicles, and min-max model predictive control. Case studies show that the proposed NRC-based PI controller improves the average weighted speed by 11.03% over fixed time strategy and recovered 7.14% ahead of the other strategies. Results demonstrate the feasibility and stability of the proposed strategy, which contributes to exploit the reasonable regulatory mechanism of EWE type disruptions.
AB - Frequent happened extreme weather events (EWEs) cause severe disruptions to the operation of large-scale urban road network. Perimeter control is of high application potential in the target scenarios. However, few studies are concerned about the lacking knowledge of the system's response features under EWE. In this work, we proposed a network resilience curve (NRC)-based perimeter control strategy to facilitate the network equilibrium, therefore enhancing the network resilience. The proposed NRC is an extension of the classical macroscopic fundamental diagram (MFD) under disruptions. A real-world trajectory dataset under normal and rainstorm day has been analyzed comparatively by using the present NRC, in which average velocity immediately reduces while average flow reveals the hysteresis effect. We compared the strategies of fixed plan, NRC-based proportional-integral (PI) control without or with connected vehicles, and min-max model predictive control. Case studies show that the proposed NRC-based PI controller improves the average weighted speed by 11.03% over fixed time strategy and recovered 7.14% ahead of the other strategies. Results demonstrate the feasibility and stability of the proposed strategy, which contributes to exploit the reasonable regulatory mechanism of EWE type disruptions.
KW - Network resilience curve
KW - perimeter control
KW - resilience enhancement
KW - urban roadway system
UR - http://www.scopus.com/inward/record.url?scp=85174811429&partnerID=8YFLogxK
U2 - 10.1109/TNSE.2023.3321678
DO - 10.1109/TNSE.2023.3321678
M3 - Article
AN - SCOPUS:85174811429
SN - 2327-4697
VL - 11
SP - 1227
EP - 1237
JO - IEEE Transactions on Network Science and Engineering
JF - IEEE Transactions on Network Science and Engineering
IS - 1
ER -