A Vehicle-to-Vehicle Based Collision Warning and Avoidance System using Visible Light Communication

Home A Vehicle-to-Vehicle Based Collision Warning and Avoidance System using Visible Light Communication

A Vehicle-to-Vehicle Based Collision Warning and Avoidance System using Visible Light Communication, PI: Ahmad Araf, Funder: KFAS, Award amount: 11300 KWD, Start: June 2024, End: December 2026

Funded by KFAS

June 2024

Award Amount:
11300 KWD

PI: Dr. Ahmad Arafa

Start date: June 2024
End date: Dec 2026
Status: Ongoing

Research Theme:
Internet of Things (IoT), Sensors, and Networking

Impact (SDG):
Good health and well-being (SDG3), Sustainable Cities and Communities (SDG11)

Collaborators:
Julian Webber, Abdullah Al-Abdulellah, Mohamed Fairouz, Abolfzl Mehbodniya, Amr Alwakeel

Figure 3 Graphical abstract- A Vehicle-to-Vehicle Based Collision Warning and Avoidance System using Visible Light Communication

Description:
According to the World Health Organization traffic accidents claim millions of people's lives worldwide. In the hope of make driving safer, this project proposes a Vehicle-to Vehicle (V2V) collision warning and avoidance system using Visible light communication. Visible light is ideal since it already exists in vehicles, and therefore adding little to no additional cost, plus the fact that vehicles are fitted with Light-emitting-Diodes (LED) which can be modulated at Tera-Hz speeds which is essential for the safety critical application. Vehicles will be fitted with photodiodes (Light sensitive elements), that can measure the angle at which the light from the lead vehicle is coming from and calculate the distance to that vehicle, and therefore, alerting the driver of a possible collision. Compared to Radio frequency-based collision avoidance systems, Visible light is more secure, does not suffer from multipath nor from doppler effect and requires a less complex receiver circuitry.
All these advantages make them ideal for distance estimation between vehicles. The proposed system can assist GPS in attaining lane-level positioning accuracy which is essential for fully autonomous vehicles.

Outcome publications:

Al-Abdulellah, A. Arafa, J. Webber, M. Fairouz, A. Mehbodniya, "An IOT-based Character Recognition System using Visible Light", submitted to the symposium on smart, sustainable, and secure Internet of Things, 6-7 May, 2025, Kuwait.