Publication:
Multi-objective optimization framework for trade-off among pedestrian delays and vehicular emissions at signal-controlled intersections

Thumbnail Image

Departments

School / College / Institute

Program

KU Authors

Co-Authors

Akyol, Görkem
Goncu, Sadullah

Publication Date

Language

Embargo Status

Journal Title

Journal ISSN

Volume Title

Alternative Title

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

item.page.datauri

Link

Rights

Copyrights Note

Endorsement

Review

Supplemented By

Referenced By

3

Views

5

Downloads

View PlumX Details