Creating and sharing knowledge for telecommunications

Project: LandMark

Acronym: LandMark
Main Objective: A key technology for autonomous driving is the real-time high-definition (HD) map of the car's surroundings. The usual approach to fulfil those requirements is to use on-board sensors inside the vehicle, such as LiDAR (Light Detection and Ranging), RADAR (Radio Detection and Ranging) and vision based systems. Due to its accuracy and fast scanning speed LiDAR systems have been adopted by the major car makers. An autonomous vehicle operates in isolation from other vehicles by using its internal sensors. However, better performance can be achieved if connected and cooperative vehicles can exchange sensor information and real-time ultra-high definition (UHD) maps with other vehicles or with the infrastructure, to overcome limitations of their onboard ranging sensors regarding their detection range, angle of view and blockage areas. However, collaborative UHD mapping places high requirements on computing power and data transmission on V2X. Ultra-fast data transmission can be provided by free-space optical wireless communication (OWC). Furthermore, OWC provides small size and light weight transceivers and is highly immune to electromagnetic interference and interception, making itself a secure communication technology. LANDmaRk ambition is to make a giant step forward in autonomous driving, by a revolutionary concept that integrates into high bandwidth OWC systems optical reflectometry concepts. This hybrid technology will increase the available wireless bandwidth by several orders of magnitude, enabling real time cloud based high definition map generation.
Reference: POCI-01-0145-FEDER-031527
Funding: FCT/POCTI
Start Date: 26-07-2018
End Date: 27-07-2021
Team: Maria do Carmo Raposo de Medeiros, Paulo Miguel Nepomuceno Pereira Monteiro, Atílio Manuel da Silva Gameiro, Luis Alberto da Silva Cruz, Henrique José Almeida Silva, Ana Maria Sousa da Rocha
Groups: Optical Networking – Co, Optical Networking – Co, Multimedia Signal Processing – Co
Local Coordinator: Maria do Carmo Raposo de Medeiros
Associated Publications