Time-series AI models for traffic congestion prediction

• Main Author: Low, Carina Su Yun
• Other Authors: Su Rong
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2022
• Subjects: Engineering::Electrical and electronic engineering
• Online Access: https://hdl.handle.net/10356/158059
• Institution: Nanyang Technological University

In recent years, Artificial Intelligence (AI) has gained much popularity in the real world due to its capability to outperform the human mind. With the ever-evolving technologies, AI plays a vital role in society. In fact, it has become a constant necessity in our daily lives and it is projected to continually grow exponentially in the upcoming years. In Intelligent Transporation Systems (ITS), traffic prediction has been a leading topic of interest amongst researchers in specialized fields. In this paper, we will explore the art of deep learning and examine the feasibility of using Time-Series AI models for predicting future traffic flow using historical data in large-scale roadway networks. The goal of this research is to achieve higher traffic precision to minimize traffic congestion.