ASLAN
To accelerate the progression of driverless technology, Project ASLAN launched an open-source and rapidly deployable self-driving software platform. The free and open software stack has been launched expressly to foster engineering collaboration.
The platform provides mature and stable code combined with plug and play ease of use, offering real-world self-driving capability validated by public highway trials as well as complete simulation capability for users without access to driverless vehicle hardware.
The collaboration’s founder members and advisory board represent a wide spectrum of skills unified by a common purpose and world-class expertise, including HAN University of Applied Sciences, Holland, RoboSense, an advanced LiDAR technology company, StreetDrone, the end-to-end urban mobility company, cybersecurity experts, Enkrypta, Jim O’Reilly, Strategic Product and Innovation Manager at Ordnance Survey, Prof Siraj Ahmed Shaikh, Professor of Systems Security at the Institute of Future Transport and Cities (IFTC) at Coventry University, Garry Staunton of RACE (Remote Applications in Challenging Environments) as part of Testbed UK and Hai L. Vu, Professor, Intelligent Transport Systems at Monash University, Melbourne, Australia.
Project ASLAN has identified the high investment demands required to pursue end-to-end driverless technologies presents a clear barrier to progress. The project has set itself the ambition to remove these barriers to entry and prioritise the benefits of driverless vehicles for metropolitan and low speed use cases where the benefits are the greatest and a collaborative approach is already determined by the involvement of multiple public agencies and private companies.
By focusing on a more defined operational domain based on slow speeds in cities as well as embracing an open-source approach, Project ASLAN opens up a smaller problem to a far larger group of collaborative engineering capability from across the world.
From today at www.project-aslan.org, engineers can freely download an open-source resource enriched by software contributed by the founders and augmented with data from 22 autonomous vehicles currently deployed in a variety of trial use-cases in locations ranging from Hong Kong to the UK.
Organisations utilisatrices ou intéressées pour utiliser la ressource : Movin'On Lab, Université de Rennes2, VEDECOM, INSA Toulouse
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Tags : Autonomous, platform, navette autonome
Catégories : Logiciel, Communauté
Thème : Voiture Connectée, Navettes autonomes, Logiciel Libre
Référent :
Défi auquel répond la ressource : Abaisser les barrières pour innover sur le véhicule, Rendre accessible une mobilité individuelle à bas coût pour tous sans externalités négatives
Personnes clés à solliciter :
Autre commun proche : Apollo, DriveSeg Dataset for Dynamic Driving Scene Segmentation, Lyft Dataset from Lidar camera, Open DBC Comma, Open Pilot Community Comma, Véhicule Libre, Waymo open dataset
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Communauté d'intérêt : Communauté autour des navettes autonomes, Communauté du Logiciel Libre, Communauté du véhicule Open Source
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Liste des acteurs qui utilisent ou souhaitent utiliser ce commun : aucun pour le moment
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