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There is an emerging and strong demand for new techniques to enable the robust design and verification & validation (V&V) of ADAS features in a safe, repeatable, controlled and scientifically rigorous environment. This is driven by a number of challenges: reduced engagement of, and reliance on, the driver in the driving task; the very high number and complexity of use cases & test scenarios; reduced access to prototype vehicles; and limited test time, human resources and cost constraints.

The SAVVY project will, therefore, deliver a novel, efficient and accelerated simulation and simulator-based V&V process for ADAS technologies. This project will create the building blocks for the V&V of future technologies based on Field Programmable Gate Array (FPGA) using deep learning and Convolutional Neural Network (CNN) algorithms. These methodologies will be evaluated throughout a product development lifecycle of a real-time ADAS control system.

This project will facilitate collaboration between AVL (consortium lead), WMG, University of Warwick, Vertizan, Myrtle Software, and Horiba MIRA, and will bring together the learning and innovations from 3 past Innovate UK funded feasibility studies.


WMG's Role:

Within the SAVVY project, WMG is responsible for identification and definition of test scenarios and execution of the test scenarios in the WMG 3xD Simulator for Intelligent Vehicles. In order to derive suitable scenario variants from high-level scenario definitions, a methodology to identify suitable scenario parameters will be developed. WMG is also responsible for integrating the AVL vehicle under test in the 3xD simulator which involves emulation of the radar sensor and simulation of the camera input to the camera sensor.

WMG Project team