Skip to main content

BMW Group and Mobileye to use crowd sourced data for automated driving

BMW Group and Mobileye are to collaborate on introducing Mobileye's Road Experience Management (REM) data generation technology in newly-developed BMW Group models entering the market in 2018. They aim to crowd-source real-time data using vehicles equipped with camera-based advanced driver assist system (ADAS) technology to provide next-generation high definition (HD) maps for autonomous vehicle, which will require them to identify and update changes in the environment with near real-time speed enabling
February 24, 2017 Read time: 2 mins
6419 BMW Group and 4279 Mobileye are to collaborate on introducing Mobileye's Road Experience Management (REM) data generation technology in newly-developed BMW Group models entering the market in 2018.

They aim to crowd-source real-time data using vehicles equipped with camera-based advanced driver assist system (ADAS) technology to provide next-generation high definition (HD) maps for autonomous vehicle, which will require them to identify and update changes in the environment with near real-time speed enabling very short ‘time to reflect reality’.

BMW Group sensor data can be merged with data from different automakers, resulting in a larger scale of data used to create Mobileye's Global RoadBook to support and rapidly update HD maps with highly accurate localisation capabilities.

The cameras that enable to collect anonymised, fleet-wide data utilise Mobileye EyeQ processors and software to identify valuable information that is compressed and sent to the cloud. This data can be used to add a dynamic layer to current and future navigation maps, enabling BMW Group customers to access true real-time information on traffic density, potential road hazards, weather conditions, on-street parking and other information.

To support the rapid creation and updating of HD mapping, the BMW Group and Mobileye will transfer anonymised data to Here. Here will use this data and information to conduct real-time updates of Here HD Live Map, its real-time cloud service for partially, highly and fully automated vehicle, and enhance its Open Location Platform, ensuring an accurate depiction of the real world as it changes.

Related Content

  • January 31, 2012
    Travel data critical to traffic management, traveller information
    The ability to bundle together travel data from several discrete sources and fuse it to give a more comprehensive overview of events to stakeholders is the key aim of Viajeo, which is conducting trials in several cities around the world. Here, Ertico's Yanying Li writes about the project in more detail
  • July 27, 2012
    In vehicle systems allow drivers to provide travel information
    The use of a Vehicle Data Translator will allow every vehicle on a given segment of road to contribute to a highly accurate, readily accessible source of localised weather information, thus improving safety in all conditions. Sheldon Drobot and William P. Mahoney III, US National Center for Atmospheric Research, Paul A. Pisano, USDOT/Federal Highway Administration, and Benjamin B. McKeever, USDOT/Research and Innovative Technology Administration, write. On the morning of June 10 2009, under the cover of den
  • November 21, 2013
    Autonomous vehicles, the pros and cons
    Driver interface and human factors could provide the biggest obstacles to autonomous vehicles as Jon Masters discovers.
  • September 6, 2017
    Options abound for road weather sensing
    Meteorological organisations invest millions in super-computers to crunch data for ever-more accurate forecasts but inherent unpredictability means that other methods of alerting drivers and road authorities to fast-changing weather and highway conditions are essential. For years, static weather sensors to measure factors such as surface water, ice or high roadway temperatures have been embedded in highways to provide such data. But that is changing.