Modeling and control of variable approach lanes on an arterial road: a case study of Dalian

Yao, Ronghan; Zhang, Xiaolin; Wu, Na; Song, Xianmin

doi:10.1139/cjce-2017-0432

Cited by 14 publications

(7 citation statements)

References 14 publications

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“…Regarding equation (18), the number of vehicles in a platoon has an important influence on the optimized value of the offset between paired intersections. When the intersection spacing is certain, such an offset is very sensitive to the number of vehicles in a platoon [32]. If Model CS is used for future design, the number of vehicles in a platoon can be set to 20 pcu, as shown earlier.…”

Section: Discussion and Suggestionsmentioning

confidence: 99%

Comparative Analysis of Optimization Models for Paired Intersections with Left-Turn Bays

Yao

Zhang

Meng

2020

Mathematical Problems in Engineering

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Left-turn bays may be provided at paired intersections when heavy left-turn demands exist on some approaches. Such left-turn bays may have significant effects on intersection operations. Considering the settings of left-turn bays, two single-objective optimization models are developed for paired intersections with uncoordinated and coordinated signals, respectively. Numerical examples are fulfilled to demonstrate and compare the formulated models, and the orthogonal simulation experiments are carried out. Assuming that the relevance of traffic flow exists, the results show that the optimized effective green times and left-turn bay lengths depend on traffic demand, whereas the optimized offset between paired intersections is sensitive to intersection spacing; the optimization model with coordinated signals outstrips that with uncoordinated signals at 99% confidence level when the distance between paired intersections is not too far and traffic demand is not too low, whereas the former may be inferior to the latter when traffic demand is low enough and intersection spacing is far enough.

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Section: Discussion and Suggestionsmentioning

confidence: 99%

Comparative Analysis of Optimization Models for Paired Intersections with Left-Turn Bays

Yao

Zhang

Meng

2020

Mathematical Problems in Engineering

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“…The time interval adopted for short-term traffic flow prediction is usually less than half an hour. Also, the peak 15-minute flow rate is usually adopted for signal timings [6]. Thus, a 15-minute time interval 7 is used to aggregate the selected data.…”

Section: Case Studiesmentioning

confidence: 99%

“…Furthermore, Ma et al [5] indicated that the change rules of traffic flow data during different weekdays are various and those during different weekends are also various. For urban traffic flow, the fluctuations of data during different periods in a day or for different vehicle types are also various [6]. Thus, the period division and vehicle type are considered when predicting traffic flow in this research.…”

Section: Introductionmentioning

confidence: 99%

Period Division-Based Markov Models for Short-Term Traffic Flow Prediction

Yao

Zhang

2020

IEEE Access

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Short-term traffic flow prediction is very important and provides the basic data for traffic management and route guidance. The rules of traffic flow data during different periods in a day are different. Thus, this paper proposes a membership degree-based Markov (MM) model and two period division-based Markov (PM and PW) models. The MM model introduces the membership degree to determine the state of traffic flow. The PM and PW models introduce the Fisher optimal division method to divide one day into several periods based on traffic flow data. Then, the period division-based Markov models integrate the Markov (CM) or weighted Markov (WM) model with the MM model to predict traffic volumes during different periods. The impacts of vehicle type on traffic flow prediction are also discussed. The proposed models are verified using the field data. The results show that: (1) the PM and PW models both perform better than the CM, WM, state membership degree-based Markov and weighted state membership degreebased Markov models; (2) the PW model sometimes performs better than the backward propagation (BP) neural network; (3) when traffic flow data are distinguished by vehicle type, the performance of the PM and PW models can be improved. It is suggested to adopt the proposed period division-based Markov models to predict traffic flow with the concern of vehicle type, so that more accurate traffic flow information can be provided for traffic management and route guidance. INDEX TERMS short-term traffic flow; prediction; Markov models; period division; ordered clustering; traffic flow pattern; vehicle type

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“…For isolated intersections with obvious tidal congestion, it is difficult to solve the congestion problem simply by optimizing traffic signal control. Yao et al [1] pointed out this problem, and solved it considering time-dependent unbalanced directional traffic flow. This problem has been studied by many researchers using the variable lane setting approach effectively.…”

Section: Introductionmentioning

confidence: 99%

A two‐stage robust optimal traffic signal control with reversible lane for isolated intersections

Sun,

Wang,

et al. 2023

IET Intelligent Trans Sys

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The integrated design of traffic signal control (TSC) and reversible lane (RL) is an effective way to solve the problem of tidal congestion with uncertainty at isolated intersections, because of its advantage in making full use of temporal‐spatial transportation facilities. Considering the contradiction between the dynamic TSC scheme and the fixed RL scheme in one period, a two‐stage optimization method based on improved mean‐standard deviation (MSD) model for isolated intersections with historical and real‐time uncertain traffic flow is proposed. In the first stage, applying the same‐period historical data of multiple days, a robust optimal traffic signal control model with reversible lane based on MSD model (MSD‐RTR model) is put forward to obtain the fixed RL scheme and the compatible initial TSC scheme. A double‐layer nested genetic algorithm (DN‐GA) is designed to solve this model. In the second stage, applying real‐time period data and multi‐day same‐period historical data, a robust optimal dynamic traffic signal control model based on MSD model (MSD‐RDT model) is put forward to obtain the dynamic TSC scheme. Three modes which reflect the different weights of historical period and real‐time period in this MSD‐RDT model are presented to improve the model stability, and a multi‐mode genetic algorithm (MM‐GA) is designed. Finally, a case study is presented to demonstrate the efficiency and applicability of the proposed models and algorithms.

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Modeling and control of variable approach lanes on an arterial road: a case study of Dalian

Cited by 14 publications

References 14 publications

Comparative Analysis of Optimization Models for Paired Intersections with Left-Turn Bays

Comparative Analysis of Optimization Models for Paired Intersections with Left-Turn Bays

Period Division-Based Markov Models for Short-Term Traffic Flow Prediction

A two‐stage robust optimal traffic signal control with reversible lane for isolated intersections

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