Further study on extended back-pressure traffic signal control algorithm

Xiao, Nan; Li, Yitong; Luo, Yiwen; Wang, Yu; Wang, Danwei

doi:10.1109/cdc.2015.7402528

Cited by 10 publications

(7 citation statements)

References 16 publications

(7 reference statements)

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“…They proved that the modified BP can guarantee stability in heavily congested conditions, but not all traffic conditions. Xiao et al [26,27] proposed an extended BP using online estimators with fading memories to estimate queue lengths, turning ratios, and saturation flow rates in real time using measured values from detectors. They then constructed a new pressure formulation using the values from the estimators.…”

Section: Background and Literature Reviewmentioning

confidence: 99%

“…On the other hand, the only BP controller that was tested in the real world [7,8] used travel times instead of queue lengths for pressure calculation due to the difficulty to obtain exact queue length. The only papers that considered the estimation of queue lengths in BP control [26,27] propose an estimator which takes measured queue as inputs without specifying how to measure queues using detectors or probe vehicles (typical real-world instrumentation). There are no study about the robustness of BP to the accuracy of the estimated queue lengths.…”

Section: Background and Literature Reviewmentioning

confidence: 99%

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Backpressure control with estimated queue lengths for urban network traffic

Okoth²,

Jabari

2021

IET Intelligent Trans Sys

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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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Section: Background and Literature Reviewmentioning

confidence: 99%

Section: Background and Literature Reviewmentioning

confidence: 99%

Backpressure control with estimated queue lengths for urban network traffic

Okoth²,

Jabari

2021

IET Intelligent Trans Sys

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show abstract

“…They proved that the modified BP can guarantee stability in heavily con-gested conditions, but not all traffic conditions. Xiao et al [47,48] proposed an extended BP using online estimators with fading memories to estimate queue lengths, turning ratios, and saturation flow rates in real time using measured values from detectors. They then constructed a new pressure formulation using the values from the estimators.…”

Section: It Assumes Infinite Spatial Capacity Of the Road Tomentioning

confidence: 99%

Backpressure Control with Estimated Queue Lengths for Urban Network Traffic

Li,

Okoth,

Jabari

2020

Preprint

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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, we are still far from a fully connected environment in the real world. This paper test the effectiveness of BP control when incomplete or imperfect knowledge about traffic conditions is available. We combine BP control with a speed/density field estimation module suitable for a partially connected environment. We refer to the proposed system as a BP with estimated queue lengths (BP-EQ). We test the robustness of BP-EQ to varying levels of connected vehicle penetration, and we compared BP-EQ 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. Our 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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“…This policy was further extended to allow different priorities for different phases to be activated. However, this extended cyclic phase MP maintains network stability only under mild traffic conditions where the maximum queue length does not exceed half of the maximum storage capacity ( 20 , 21 ).…”

Section: Literature Reviewmentioning

confidence: 99%

“…If η is relatively small, the proportion of each group will tend to be uniform, albeit Le et al ( 4 ) did not elaborate how to determine the value of η . Although this MP scheme provides fixed phase sequence and right of way for each phase in a cycle, tests of its stability property indicate that this control policy cannot achieve the maximum throughput ( 4 , 20 , 21 ).…”

Section: Max Pressure-based Signal Controlmentioning

confidence: 99%

A Simulation Study on Max Pressure Control of Signalized Intersections

Sun

Yin

2018

Transportation Research Record

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In this paper, a decentralized traffic signal control strategy named max pressure control is reviewed and examined. This control strategy aims at optimizing overall network throughputs, but applies a distributed approach that only requires local information to generate timing plans for each intersection. A Vissim simulation study is conducted to compare existing max pressure schemes. The results show that a recently proposed cyclic-based approach performs more poorly than the original non-cyclic approach. Further, to address two issues that hinder existing schemes: frequent changes of phase and queue spillover/blockage, two modifications are suggested. The simulation reveals that network performance can be improved after modifications.

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Further study on extended back-pressure traffic signal control algorithm

Cited by 10 publications

References 16 publications

Backpressure control with estimated queue lengths for urban network traffic

Backpressure control with estimated queue lengths for urban network traffic

Backpressure Control with Estimated Queue Lengths for Urban Network Traffic

A Simulation Study on Max Pressure Control of Signalized Intersections

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