Design and implementation of smart traffic light controller with emergency vehicle detection on FPGA

Increased traffic volumes resulting from urbanization, industrialization, and population growth have given rise to complex issues, including congestion, accidents, and traffic violations at intersections. In the absence of a functional smart traffic light system, traffic congestion occurs due to imbalanced traffic flow at intersections. Current traffic management lacks provisions for ensuring the unobstructed movement of emergency vehicles, even a small delay for which can have significant consequences. This paper presents a smart traffic light controller developed using Verilog hardware description language (HDL) in Quartus Prime 21.1 and Questa Intel field programmable gate array (FPGA) Starter Edition 2021.2, and implemented on an Altera DE2-115 FPGA. The controller is designed specifically to detect emergency vehicle at four-way intersections for inputs radio frequency identification (RFID) readers and infrared (IR) sensors. The RFID readers and IR sensors are managed through slide switches on the FPGA board. The smart traffic light controller contains three sub-modules: clock division, counter, and finite state machine (FSM) operation, enabling it to manage traffic in scenarios with emergency vehicles, high traffic density, and low traffic density. This proposed system can alleviate intersection congestion by controlling access and allocating time effectively. In conclusion, the project ensures the smooth passage of emergency vehicles by continuously monitoring their presence and giving them priority in traffic flow.

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Publication Details

Journal
International Journal of Reconfigurable and Embedded Systems (IJRES)
Published
2024-12-22
DOI
https://doi.org/10.11591/ijres.v14.i1.pp48-59
Primary Topic
Traffic Prediction and Management Techniques
Type
article
Field-Weighted Citation Impact
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article

Design and implementation of smart traffic light controller with emergency vehicle detection on FPGA

Irni Hamiza Hamzah, Nor Shahanim Mohamad Hadis, Azwati Azmin, Mohammad Nizam Ibrahim et al.
International Journal of Reconfigurable and Embedded Systems (IJRES)
Traffic Prediction and Management Techniques
article

Design and implementation of smart traffic light controller with emergency vehicle detection on FPGA

Irni Hamiza Hamzah, Nor Shahanim Mohamad Hadis, Azwati Azmin, Mohammad Nizam Ibrahim, Samsul Setumin, Samihah Abdullah, Muhammad Ameerul Syafiqie Abdul Sukor
article en

Abstract

Increased traffic volumes resulting from urbanization, industrialization, and population growth have given rise to complex issues, including congestion, accidents, and traffic violations at intersections. In the absence of a functional smart traffic light system, traffic congestion occurs due to imbalanced traffic flow at intersections. Current traffic management lacks provisions for ensuring the unobstructed movement of emergency vehicles, even a small delay for which can have significant consequences. This paper presents a smart traffic light controller developed using Verilog hardware description language (HDL) in Quartus Prime 21.1 and Questa Intel field programmable gate array (FPGA) Starter Edition 2021.2, and implemented on an Altera DE2-115 FPGA. The controller is designed specifically to detect emergency vehicle at four-way intersections for inputs radio frequency identification (RFID) readers and infrared (IR) sensors. The RFID readers and IR sensors are managed through slide switches on the FPGA board. The smart traffic light controller contains three sub-modules: clock division, counter, and finite state machine (FSM) operation, enabling it to manage traffic in scenarios with emergency vehicles, high traffic density, and low traffic density. This proposed system can alleviate intersection congestion by controlling access and allocating time effectively. In conclusion, the project ensures the smooth passage of emergency vehicles by continuously monitoring their presence and giving them priority in traffic flow.

International Journal of Reconfigurable and Embedded Systems (IJRES)Vol. 14(1)
Universiti Teknologi MARA (MY)
Sustainable cities and communities
Openalex Percentile: Top 74%
Traffic Prediction and Management Techniques
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