TY - JOUR
T1 - Backpressure control with estimated queue lengths for urban network traffic
AU - Li, Li
AU - Okoth, Victor
AU - Jabari, Saif Eddin
N1 - Funding Information:
This work was supported by the NYUAD Center for Interacting Urban Networks (CITIES), funded by Tamkeen under the NYUAD Research Institute Award CG001 and by the Swiss Re Institute under the Quantum CitiesTM initiative. The authors would also like to acknowledge in-kind support received from the Abu Dhabi Department of Transportation, in the form of the high-resolution traffic data that were used in our experiments.
Funding Information:
This work was supported by the NYUAD Center for Interacting Urban Networks (CITIES), funded by Tamkeen under the NYUAD Research Institute Award CG001 and by the Swiss Re Institute under the Quantum Cities initiative. The authors would also like to acknowledge in‐kind support received from the Abu Dhabi Department of Transportation, in the form of the high‐resolution traffic data that were used in our experiments. TM
Publisher Copyright:
© 2021 The Authors. IET Intelligent Transport Systems published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology
PY - 2021/2
Y1 - 2021/2
N2 - Backpressure (BP) control was originally used for packet routing in communications networks. Since its first application to network traffic control, it has undergone different modifications to tailor it to traffic problems with promising results. Most of these BP variants are based on an assumption of perfect knowledge of traffic conditions throughout the network at all times, specifically the queue lengths (more accurately, the traffic volumes). However, it has been well established that accurate queue length information at signalized intersections is never available except in fully connected environments. Although connected vehicle technologies are developing quickly, a fully connected environment in the real world is still far. This paper tests the effectiveness of BP control when incomplete or imperfect knowledge about traffic conditions is available. BP control is combined with a speed/density field estimation module suitable for a partially connected environment. The proposed system is referred to as a BP with estimated queue lengths (BP-EQ). The robustness of BP-EQ is tested to varying levels of connected vehicle penetration, and BP-EQ is compared with the original BP (i.e. assuming accurate knowledge of traffic conditions), a real-world adaptive signal controller, and optimized fixed timing control using microscopic traffic simulation with field calibrated data. These results show that with a connected vehicle penetration rate as little as 10%, BP-EQ can outperform the adaptive controller and the fixed timing controller in terms of average delay, throughput, and maximum stopped queue lengths under high demand scenarios.
AB - Backpressure (BP) control was originally used for packet routing in communications networks. Since its first application to network traffic control, it has undergone different modifications to tailor it to traffic problems with promising results. Most of these BP variants are based on an assumption of perfect knowledge of traffic conditions throughout the network at all times, specifically the queue lengths (more accurately, the traffic volumes). However, it has been well established that accurate queue length information at signalized intersections is never available except in fully connected environments. Although connected vehicle technologies are developing quickly, a fully connected environment in the real world is still far. This paper tests the effectiveness of BP control when incomplete or imperfect knowledge about traffic conditions is available. BP control is combined with a speed/density field estimation module suitable for a partially connected environment. The proposed system is referred to as a BP with estimated queue lengths (BP-EQ). The robustness of BP-EQ is tested to varying levels of connected vehicle penetration, and BP-EQ is compared with the original BP (i.e. assuming accurate knowledge of traffic conditions), a real-world adaptive signal controller, and optimized fixed timing control using microscopic traffic simulation with field calibrated data. These results show that with a connected vehicle penetration rate as little as 10%, BP-EQ can outperform the adaptive controller and the fixed timing controller in terms of average delay, throughput, and maximum stopped queue lengths under high demand scenarios.
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U2 - 10.1049/itr2.12027
DO - 10.1049/itr2.12027
M3 - Article
AN - SCOPUS:85102033464
VL - 15
SP - 320
EP - 330
JO - IET Intelligent Transport Systems
JF - IET Intelligent Transport Systems
SN - 1751-956X
IS - 2
ER -