Analyzing Traffic Signal Delay Models in Tehran Network: A Comprehensive Examination under Varied Traffic Conditions via the Complementary Algorithm

authors:
1. Amir Zare Kazemabadi
Department of Road and Transportation Engineering, Technical College, Faculty of Civil Engineering, University of Tehran, PhD student in Civil Engineering majoring in Transportation
2. Mohammad Norouzi Shavir
Department of Road and Transportation Engineering, Technical College, Faculty of Civil Engineering, University of Tehran, Master's student in Civil Engineering majoring in Road and Transportation
Type of document: Conference Article
language: English
title of the conference: 9th International Conference on Civil, Structural and Seismic Engineering
website: http://cs.bcnf.ir
Issue: civil engineering
Publication date: 2024
DSI: DSI141251788672
DOI:
paper link: http://scieropub.com/pv/DSI141251788672
keyword: Traffic network, Travel time, Traffic signal delay, complementary algorithm, Tehran network.
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The travel time experienced by users stands as a fundamental determinant of road network service quality at its core. Beyond the inherent delays within road segments, travel time on routes across the network encompasses additional impediments arising from intersections regulated by traffic signals. However, signal delay often remains inadequately addressed within Traffic Assignment models, primarily due to incomplete network information and associated complexities. This article aims to rectify this oversight by leveraging the complementary Traffic Assignment algorithm to incorporate crucial signal delay functions within the Tehran network context. By doing so, we endeavor to shed light on the nuanced impact of signal delays on travel time dynamics, particularly under both undersaturated and oversaturated traffic conditions. The application of the complementary Traffic Assignment algorithm allows for a more comprehensive evaluation of travel time, elucidating the intricate interplay between signal delays and overall network performance. Through comparative analysis across varied traffic scenarios, this study seeks to discern the differential effects of signal delays on route efficiency and user experience, thereby offering valuable insights for traffic management and infrastructure optimization efforts.

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