A Back-Pressure-Based Model With Fixed Phase Sequences for Traffic Signal Optimization Under Oversaturated Networks

Ma, Dongfang; Xiao, Jiawang; Song, Xiang; Ma, Xiaolong; Jin, Sheng

doi:10.1109/tits.2020.2987917

Cited by 40 publications

(23 citation statements)

References 40 publications

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“…The combinational scheduling with traditional buses mainly includes multimode scheduling strategies, such as integrated strategies of all-stop and short-turning strategies, combinatorial scheduling of all-stop and skip-stop tactics [32][33][34][35]. proposed a rule-based method which is short-turning and interlining lines, into the frequency and resource allocation problem to reduce passenger waiting times at stops and operational costs.…”

Section: Related Workmentioning

confidence: 99%

Optimal Electric Bus Scheduling Based on the Combination of All-Stop and Short-Turning Strategies

2021

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The emission of greenhouse gases from public transportation has aroused extensive public attention in recent years. Electric buses have the advantage of zero emission, which could prevent the further deterioration of environmental problems. Since 2018, the number of electric buses has exceeded that of traditional buses. Thus, it is an inevitable trend for the sustainable development of the automobile industry to replace traditional fuel buses, and developing electric buses is an important measure to relieve traffic congestion. Furthermore, the bus scheduling has a significant impact on passenger travel times and operating costs. It is common that passenger demand at different stops is uneven in a public transportation system. Since applying all-stop scheduling only cannot match the passenger demand of some stops with bus resources, this paper proposes an integrated all-stop and short-turning service for electric buses, reducing the influence of uneven ridership on load factor to enhance transit attractiveness. Simultaneously, considering the time-of-use pricing strategy used by the power sector, the combinational charging strategy of daytime and overnight is proposed to reduce electricity costs. Finally, the branch-and-price algorithm is adopted to solve this problem. Compared with all-stop scheduling, the results demonstrate a reduction of 13.5% in total time cost under the combinational scheduling.

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Section: Related Workmentioning

confidence: 99%

Optimal Electric Bus Scheduling Based on the Combination of All-Stop and Short-Turning Strategies

2021

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“…Considering each lane group separately, a multi-commodity model for back-pressure was demonstrated to perform better than the original method [ 25 ]. Back-pressure methods may have an unordered phasing sequence where the phase having the longer queue length is served first, or a fixed and ordered phase sequence like in [ 26 , 27 ] to ensure accommodating all approaches.…”

Section: Related Workmentioning

confidence: 99%

Adaptive Traffic Signal Control: Game-Theoretic Decentralized vs. Centralized Perimeter Control

Elouni

Abdelghaffar

Rakha

2021

Sensors

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This paper compares the operation of a decentralized Nash bargaining traffic signal controller (DNB) to the operation of state-of-the-art adaptive and gating traffic signal control. Perimeter control (gating), based on the network fundamental diagram (NFD), was applied on the borders of a protected urban network (PN) to prevent and/or disperse traffic congestion. The operation of gating control and local adaptive controllers was compared to the operation of the developed DNB traffic signal controller. The controllers were implemented and their performance assessed on a grid network in the INTEGRATION microscopic simulation software. The results show that the DNB controller, although not designed to solve perimeter control problems, successfully prevents congestion from building inside the PN and improves the performance of the entire network. Specifically, the DNB controller outperforms both gating and non-gating controllers, with reductions in the average travel time ranging between 21% and 41%, total delay ranging between 40% and 55%, and emission levels/fuel consumption ranging between 12% and 20%. The results demonstrate statistically significant benefits of using the developed DNB controller over other state-of-the-art centralized and decentralized gating/adaptive traffic signal controllers.

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“…When the driver's face is detected, the feature points of the face are obtained in real time by the above algorithm, as shown in the Figure 4 After extracting 68 feature points with the Dlib toolkit, they can be used to form the face information into a 128dimensional Feature Vector [53][54][55]. In this vector space, the Euclidean distance of the same face is closer than that of different faces.…”

Section: ) Face Feature Location and 128-dimensional Feature Vector mentioning

confidence: 99%

A Fatigue Driving Detection Algorithm Based on Facial Multi-Feature Fusion

Gong

Ren

2020

IEEE Access

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Researches on machine vision-based driver fatigue detection algorithm have improved traffic safety significantly. Generally, many algorithms do not analyze driving state from driver characteristics. It results in some inaccuracy. The paper proposes a fatigue driving detection algorithm based on facial multifeature fusion combining driver characteristics. First, we introduce an improved YOLOv3-tiny convolutional neural network to capture the facial regions under complex driving conditions, eliminating the inaccuracy and affections caused by artificial feature extraction. Second, on the basis of the Dlib toolkit, we introduce the Eye Feature Vector(EFV) and Mouth Feature Vector(MFV), which are the evaluation parameters of the driver's eye state and mouth state, respectively. Then, the driver identity information library is constructed by offline training, including driver eye state classifier library, driver mouth state classifier library, and driver biometric library. Finally, we construct the driver identity verification model and the driver fatigue assessment model by online assessment. After passing the identity verification, calculate the driver's closed eyes time, blink frequency and yawn frequency to evaluate the driver's fatigue state. In simulated driving applications, our algorithm detects the fatigue state at a speed of over 20fps with an accuracy of 95.10%.

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A Back-Pressure-Based Model With Fixed Phase Sequences for Traffic Signal Optimization Under Oversaturated Networks

Cited by 40 publications

References 40 publications

Optimal Electric Bus Scheduling Based on the Combination of All-Stop and Short-Turning Strategies

Optimal Electric Bus Scheduling Based on the Combination of All-Stop and Short-Turning Strategies

Adaptive Traffic Signal Control: Game-Theoretic Decentralized vs. Centralized Perimeter Control

A Fatigue Driving Detection Algorithm Based on Facial Multi-Feature Fusion

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