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ECSEL 2015 RIA DENSE Autoliv

Reference number
Coordinator Veoneer Sweden AB
Funding from Vinnova SEK 1 552 286
Project duration June 2016 - February 2020
Status Completed

Purpose and goal

DENSE seeks to eliminate one of the most pressing problems of automated driving and advanced driver support system: the inability of current systems to sense their surroundings under all weather conditions. Severe weather such as snow, heavy rain or fog have long been viewed as one of the last remaining technical challenges preventing self-driving cars from being brought to the market. This can only be overcome by developing a fully reliable environment perception technology.

Expected results and effects

DENSE has identified, specified and developed sensors for automated driving under varying visibility conditions, implemented sensor fusion approaches that accommodate the complementing abilities of the involved sensors and finally validated the resulting fused all-weather sensor suite. Evolution of current test methods for tests in fog and rain under controlled environment has been implemented, and new test methods that simulate the spray behind a vehicle driving on a wet road has been developed and thereafter transferred to AstaZero - a Swedish national test facility.

Planned approach and implementation

Veoneer´s has been as a provider of requirements and acted as a system integrator. We learn from other partners about new sensor technology and data fusion methods. The system validation work gives us experience of tests during adverse weather. Developed equipment for testing and characterization of spray behind vehicles running on wet roadway has been transferred after the project to the Swedish national test facility AstaZero, which can thus take on and further develop the test methods and make these test methods available to other players in the Swedish vehicle cluster.

External links

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 17 March 2020

Reference number 2016-01592

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