Publication: Multi-objective optimization framework for trade-off among pedestrian delays and vehicular emissions at signal-controlled intersections
Program
KU-Authors
KU Authors
Co-Authors
Akyol, Görkem
Goncu, Sadullah
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Abstract
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.
Source
Publisher
Springer Heidelberg
Subject
Civil engineering
Citation
Has Part
Source
Arabian Journal for Science and Engineering
Book Series Title
Edition
DOI
10.1007/s13369-024-08898-7