Adaptive Signal Control to Enhance Effective Green Times for Pedestrians: A Case Study

Akyol, Gorkem; Erdağı, İsmet Gökşad; Silgu, Mehmet Ali; Çelikoğlu, Hilmi Berk

doi:10.1016/j.trpro.2020.03.150

Cited by 8 publications

(2 citation statements)

References 14 publications

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“…Another evolution of guiding mechanisms is based on the design of adaptive strategies, which can be a better option when conditions change unexpectedly. [ 10,11,17–23 ] A principal requirement for designing adaptive mechanisms is the availability of real‐time information from the environment over which the control is exercised. Some key technologies needed to obtain this information include sensors to detect hazards, cameras to identify potential hazards or obstacles and obtain pedestrian flow measurements, and wireless networks and mobile devices to communicate with individuals and track their location in real‐time.…”

Section: Introductionmentioning

confidence: 99%

Crowd Evacuation Management with Optimal Time‐Multiplexed Exit‐Choice Recommendations through Simulation Optimization

Lopez‐Carmona,

Paricio‐Garcia

2024

Advcd Theory and Sims

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Exit‐choice behavior significantly influences the performance of egress operations in crowded spaces. Thus, strategically issuing active exit‐choice recommendations that provide clear and concise guidance to pedestrians can help improve evacuation safety and efficiency. This study investigates how to optimally regulate pedestrian density at the exits by generating time‐multiplexed exit‐choice recommendations. The study develops a simulated crowd evacuation scenario with multiple exits, where pedestrians receive periodic sequences of exit‐choice instructions. The optimal period for each instruction is obtained through simulation‐optimization processes with three minimization objectives: evacuation time, cumulative density, and cumulative density variance. First, the effect of collective behaviors on evacuation performance is studied, which justifies the need for active mechanisms to improve exit‐choice decision‐making coordination. Then, several optimal plans for the different objectives are obtained and evaluated regarding evacuation time and cumulative density performance. Finally, the influence of adoption rate and collective commitment to instructions are evaluated. This study suggests that static plans, defined as time‐multiplexed exit‐choice instructions obtained through simulation‐optimization, reasonably represent a first step in the real deployment of intelligent crowd management systems.

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Section: Introductionmentioning

confidence: 99%

Crowd Evacuation Management with Optimal Time‐Multiplexed Exit‐Choice Recommendations through Simulation Optimization

Lopez‐Carmona,

Paricio‐Garcia

2024

Advcd Theory and Sims

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“…Akyol et al [13] utilized the Eclipse SUMO micro-simulator in conjunction with TraCI and proposed an adaptive traffic control system considering the traffic flows of road vehicles and pedestrians with field data. Akyol et al [14] adapted Split, Cycle, and Offset Optimization Technique (SCOOT) in order to manage the pedestrian and vehicular traffic. However, none of the above studies focuses on the origin or destination station selection under station closure.…”

Section: Introductionmentioning

confidence: 99%

A Data-Driven Approach to Detect Passenger Flow Anomaly Under Station Closure

Huang

et al. 2020

IEEE Access

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During daily subway operation, station closure has large impact on subway system organization and has received increasing attention. This article proposes an anomaly detection method based on ensemble algorithms to determine the range of station closure influence on passenger flow. Firstly, Ensemble Algorithm I is developed to identify the stations with passenger flow volume anomaly and origin-destination (OD) pairs with volume anomaly. Secondly, Ensemble Algorithm II is proposed to identify the OD pairs with travel time anomaly. Then, the spatial variation in passenger flow caused by station closure, i.e. shift of passenger flow to neighboring stations and shift of path flow, is analyzed, and the spatial-temporal influence range of station closure is determined. A case study of the Beijing subway system is performed to illustrate the validity of the proposed method.Compared with sub algorithm of ensemble learning and KNN algorithm, Ensemble Algorithm I and II are more robust and have less misjudgment.INDEX TERMS Date driven, passenger flow anomaly, spatial-temporal influence detection, station closure, weighted ensemble algorithm.

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Multi-objective Optimization Framework for Trade-Off Among Pedestrian Delays and Vehicular Emissions at Signal-Controlled Intersections

Akyol,

Göncü,

Silgu

2024

Arab J Sci Eng

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Traffic congestion has several adverse effects on urban traffic networks. Increased travel times of vehicles, with the addition of excessive greenhouse emissions, can be listed as harmful effects. To address these issues, transportation engineers aim to reduce private car usage, reduce travel times through different control strategies, and mitigate harmful effects on urban networks. In this study, we introduce an innovative approach to optimizing traffic signal control settings. This methodology takes into account both pedestrian delays and vehicular emissions. Non-dominated sorting genetic algorithm-II and Multi-objective Artificial Bee Colony algorithms are adopted to solve the multi-objective optimization problem. The vehicular emissions are modeled through the MOVES3 emission model and integrated into the utilized microsimulation environment. Initially, the proposed framework is tested on a hypothetical test network, followed by a real-world case study. Results indicate a significant improvement in pedestrian delays and lower emissions.

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Adaptive Signal Control to Enhance Effective Green Times for Pedestrians: A Case Study

Cited by 8 publications

References 14 publications

Crowd Evacuation Management with Optimal Time‐Multiplexed Exit‐Choice Recommendations through Simulation Optimization

Crowd Evacuation Management with Optimal Time‐Multiplexed Exit‐Choice Recommendations through Simulation Optimization

A Data-Driven Approach to Detect Passenger Flow Anomaly Under Station Closure

Multi-objective Optimization Framework for Trade-Off Among Pedestrian Delays and Vehicular Emissions at Signal-Controlled Intersections

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