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The IUP Journal of Electrical and Electronics Engineering

Efficiency Improvement at Signalized Intersections: Investigating Smart Green Time Allocation with Two LiDAR Sensors and AIMSUN Microsimulation

Article Details

Pub. Date	: Oct, 2023
Product Name	: The IUP Journal of Electrical and Electronics Engineering
Product Type	: Article
Product Code	: IJEEE011023
Author Name	: Alireza Ansariyar
Availability	: YES
Subject/Domain	: Engineering
Download Format	: PDF Format
No. of Pages	: 26

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Abstract

This paper addresses the critical issue of intersection efficiency through the implementation of Smart Green Time Allocation (SGTA) strategies at a signalized intersection equipped with two LiDAR sensors. It investigates optimal GTA provided by two LiDAR sensors and analyzes the LiDAR results by microsimulation in AIMSUN. Through meticulous modeling and simulation, the research explores the optimal green allocation at morning, mid-day and afternoon peak hour scenarios to comprehensively assess the impact of LiDAR-enabled dynamic signal control. The findings demonstrate that smart GTA, informed by real-time LiDAR data and implemented through AIMSUN microsimulation, significantly enhances intersection efficiency. By adapting signal timings to real-time traffic demands, congestion, travel time and emission are reduced. The paper highlights that optimal GTA in morning, mid-day and afternoon peak hour intervals can improve the delay time by 55.3%, 59.7% and 55.6%, respectively. In conclusion, the paper sheds light on the potential of LiDAR technology to transform intersection management.

Introduction

The challenge of managing urban mobility becomes more difficult as cities grow. Signalized intersections play a crucial role in ensuring the smooth operation of cities (Ansariyar, 2023a; 2023b; 2023c; and 2023d). These intersections serve as critical nodes in transportation network, orchestrating the flow of vehicles, pedestrians and cyclists. The efficacy of traffic control at these junctions is essential for mitigating congestion, reducing emissions and ensuring the safety of all road users (Ansariyar, 2023a; 2023d; Zhang and Wang, 2010; and Ansariya and Taherpour, 2023a). In pursuit of enhanced intersection efficiency, recent years have witnessed the emergence of smart and data-driven traffic management systems. Among these innovations, light detection and ranging (LiDAR) technology has shown great promise in revolutionizing the precision and adaptability of