Reference
N. Wu, D. Li, Y. Xi, and B. De Schutter, "Distributed event-triggered model
predictive control for urban traffic lights,"
IEEE
Transactions on Intelligent Transportation Systems, vol. 22, no. 8, pp.
4975-4985, Aug. 2021.
Abstract
Effective traffic signal control strategies are critical for traffic management
in urban traffic networks. Most existing optimization-based urban traffic
control approaches update the traffic signal at regular time instants, where
the length of the fixed update time interval is determined based on a trade-off
between the computational efficiency and the control performance. Since
event-triggered control (ETC) allows for more flexible and more efficient
control than conventional time-triggered control by triggering the control
action by events, and since it can refrain from redundant optimization while
retaining a satisfactory behavior, we use an ETC scheme for traffic light
control. In addition, based on the geographically distributed feature of
traffic networks, a distributed paradigm is adopted to reduce the computational
complexity for the optimization. We propose a distributed threshold-based
event-triggered control strategy, where the independent triggering of agents
leads to an asynchronous update of traffic signals in the system. The triggered
agent then solves a mixed-integer linear programming problem and updates its
traffic signals. The proposed approach is evaluated under various traffic
demands by simulation, and is shown to yield the best trade-off between control
performance and computational complexity compared to other control strategies.
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BibTeX
@article{WuLi:20-014,
author = {Wu, Na and Li, Dewei and Xi, Yugeng and De Schutter, Bart},
title = {Distributed Event-Triggered Model Predictive Control for Urban
Traffic Lights},
journal = {IEEE Transactions on Intelligent Transportation Systems},
volume = {22},
number = {8},
pages = {4975--4985},
month = aug,
year = {2021}
}