What does this research mean for the field?

A real-time traffic flow forecasting and management system utilizing deep learning models such as LSTM, GRU, and CNN-LSTM can accurately predict traffic conditions to reduce congestion and optimize signal control. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

This project seeks to design a system for accurately forecasting real-time traffic flow using machine and deep learning techniques.

May 10, 2026Open Access

Real Time Traffic Flow Forecasting And Management System

Key Points

This project seeks to design a system for accurately forecasting real-time traffic flow using machine and deep learning techniques.
Developed a forecasting system utilizing machine learning and deep learning models like LSTM, GRU, and CNN–LSTM.
Collected and analyzed real-time and historical traffic data from various sources such as sensors, CCTV cameras, and GPS devices.
Applied data preprocessing techniques to eliminate noise and address missing values.
Implemented models showed significant improvements in traffic flow prediction accuracy based on historical data.
The system enabled effective traffic management decisions, contributing to reduced congestion by optimizing signal control.
Real-time monitoring led to enhanced transportation efficiency and improved road safety.

Abstract

This project focuses on the design and development of a Real-Time Traffic Flow Forecasting and Management System using machine learning and deep learning techniques. The system aims to predict traffic conditions accurately by analyzing real-time and historical traffic data collected from sensors, CCTV cameras, and GPS devices. Data preprocessing techniques are applied to remove noise and handle missing values for improved prediction accuracy. Advanced models such as LSTM, GRU, and CNN–LSTM are implemented to forecast traffic flow and support intelligent traffic management decisions. The proposed system helps reduce traffic congestion, improve road safety, optimize signal control, and enhance transportation efficiency through real-time monitoring and adaptive management strategies.

Real Time Traffic Flow Forecasting And Management System

Key Points

Abstract

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