Towards Intelligent Traffic Signaling in Dhaka City Based on Vehicle Detection and Congestion Optimization

Fuente: arXiv
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Main Authors: Azam, Kazi Ababil, Masum, Hasan, Rahaman, Masfiqur, Islam, A. B. M. Alim Al
Format: Preprint
Published: 2025
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author Azam, Kazi Ababil
Masum, Hasan
Rahaman, Masfiqur
Islam, A. B. M. Alim Al
author_facet Azam, Kazi Ababil
Masum, Hasan
Rahaman, Masfiqur
Islam, A. B. M. Alim Al
contents The vehicular density in urbanizing cities of developing countries such as Dhaka, Bangladesh result in a lot of traffic congestion, causing poor on-road experiences. Traffic signaling is a key component in effective traffic management for such situations, but the advancements in intelligent traffic signaling have been exclusive to developed countries with structured traffic. The non-lane-based, heterogeneous traffic of Dhaka City requires a contextual approach. This study focuses on the development of an intelligent traffic signaling system feasible in the context of developing countries such as Bangladesh. We propose a pipeline leveraging Real Time Streaming Protocol (RTSP) feeds, a low resources system Raspberry Pi 4B processing, and a state of the art YOLO-based object detection model trained on the Non-lane-based and Heterogeneous Traffic (NHT-1071) dataset to detect and classify heterogeneous traffic. A multi-objective optimization algorithm, NSGA-II, then generates optimized signal timings, minimizing waiting time while maximizing vehicle throughput. We test our implementation in a five-road intersection at Palashi, Dhaka, demonstrating the potential to significantly improve traffic management in similar situations. The developed testbed paves the way for more contextual and effective Intelligent Traffic Signaling (ITS) solutions for developing areas with complicated traffic dynamics such as Dhaka City.
format Preprint
id arxiv_https___arxiv_org_abs_2510_16622
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Towards Intelligent Traffic Signaling in Dhaka City Based on Vehicle Detection and Congestion Optimization
Azam, Kazi Ababil
Masum, Hasan
Rahaman, Masfiqur
Islam, A. B. M. Alim Al
Hardware Architecture
Systems and Control
The vehicular density in urbanizing cities of developing countries such as Dhaka, Bangladesh result in a lot of traffic congestion, causing poor on-road experiences. Traffic signaling is a key component in effective traffic management for such situations, but the advancements in intelligent traffic signaling have been exclusive to developed countries with structured traffic. The non-lane-based, heterogeneous traffic of Dhaka City requires a contextual approach. This study focuses on the development of an intelligent traffic signaling system feasible in the context of developing countries such as Bangladesh. We propose a pipeline leveraging Real Time Streaming Protocol (RTSP) feeds, a low resources system Raspberry Pi 4B processing, and a state of the art YOLO-based object detection model trained on the Non-lane-based and Heterogeneous Traffic (NHT-1071) dataset to detect and classify heterogeneous traffic. A multi-objective optimization algorithm, NSGA-II, then generates optimized signal timings, minimizing waiting time while maximizing vehicle throughput. We test our implementation in a five-road intersection at Palashi, Dhaka, demonstrating the potential to significantly improve traffic management in similar situations. The developed testbed paves the way for more contextual and effective Intelligent Traffic Signaling (ITS) solutions for developing areas with complicated traffic dynamics such as Dhaka City.
title Towards Intelligent Traffic Signaling in Dhaka City Based on Vehicle Detection and Congestion Optimization
topic Hardware Architecture
Systems and Control
url https://arxiv.org/abs/2510.16622