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This project investigates the use of vehicle light-emitting diode (LED) headlamp devices for improving the accuracy and reliability of traffic (sensing and communication) data measurements required for developing effective intelligent transportation systems (ITS) technologies and solutions. Vehicular communication and sensing technologies are mainly based on conventional radio frequency (RF) or laser technologies. These systems suffer from several issues such as RF interference and poor performance in scenarios where the incidence angle between the speed detector and the vehicle is rapidly varying. Introducing a new sensing technology will add diversity to these systems and enhance the reliability of the real-time data. In this project, we proposed and investigated a novel speed estimation sensing system named “Visible Light Detection and Ranging (ViLDAR)” (patent pending).

ViLDAR utilizes visible light-sensing technology to measure the variation of the vehicle’s headlamp light intensity to estimate the vehicle speed. Similarly, visible light sensing technology is used for data communication purposes, where the vehicle headlamp is utilized for wireless data transmission purposes. This project outlines the ViLDAR system simulations, implementation including hardware and software components, experimental evaluation in both laboratory and outdoor environments. The experimental measurement settings of the ViLDAR experiments are detailed. Encouraging results for both sensing and communication scenarios are obtained. The outcome of this proof-of-concept study both in the laboratory and outdoor validates the merit of the proposed technology in speed estimation (sensing) and data communication. The outcomes of this project will inspire a wide and diverse range of researchers, scientists and practitioners from the ITS community to explore this new and exciting technology. This project built initial steps in exploring this new sensing and communication modality using vehicle headlamps, leaving open a wide field for exploration and novel research.


Tran-SET Project No. 18ITSOSU01