The Government launched the “Road to Zero” strategy of having zero emissions from cars and vans by 2040, and the AESIN Network is helping the organisations which will develop the enabling technologies achieve this goal. In addition to electrification technology the ways in which ADAS & HAV, Connectivity & Security play a key role in achieving greener, safer and secure transport will also be a focus.
Presentation – ADAS & HAV Track – 13:30 to 15:00
Multipath radar modelling for ADAS and AV simulation
Abstract: The ADAS & AV systems are based on a combination of sensors providing a detailed mapping of the environment. When cameras are susceptible to weather and sunlight, radars operate optimally in almost all external conditions. When radars provide limited resolution and blurry images, lidars provide the most detailed understanding possible of the surroundings of the car, and when lidars are expensive and fragile, cameras are cheap and mature technologies. Therefore all those sensors must be used in a complementary fashion to best model the world around the vehicle.
As part of a complete suite of simulation tools for ADAS and AV development, including a set of customisable physics based sensors and controllers, a simulation manager and a simulation environment, this presentation will focus on the development of a multipath radar sensor.
The radar is based on a Ray Tracing algorithm which is a Computational Model solving Maxwell’s equations using an Asymptotic Method : high frequency approximation. This allows for the use of a simplified version of the Maxwell’s equation for high frequencies.
The algorithm consists of launching millions of rays from a located antenna and work out the interaction of each ray with the environment, until it returns to the receptor. For each interaction with a surface, reflection, both specular and diffuse, and diffraction are modelled and new rays are created. Each of these effects will depend on the nature of the material hit (permittivity, permeability, conductivity); its shape (surface roughness, sharp edges), and the incident wave (polarisation, grazing angle, frequency). The simulator mimics the raw data output of a real radar, with range Doppler map and images of the scene.
We will discuss some of the choices that have been made, such as roughness modelling or scattering pattern. We will also compare the results with real life tests that have been performed as well as literature review, and discuss other future implementations.
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