SC²S Colloquium - September 14, 2017
|Date:||September 14, 2017|
|Time:||4:00 pm, s.t.|
Imke Helene Drave: Ego-Velocity Estimation Using Environmental Sensors
Currently, a vehicle’s velocity is estimated using measurement from wheel speed sensors. Due to many factors influencing the wheel diameter and the low accuracy of the sensors especially at low speeds, state of the art velocity estimation methods lack accuracy. For highly automated and autonomous driving a more accurate signal is essential. The most obvious alternative is to use GPS signals for velocity estimation. This solution however, is obsolete due to limited availablility of GPS and cost inefficiency of sensors that provide the necesseary safety integrity. This work aims at finding a true alternative velocity estimation strategy that utilizes environmental sensors. As highly automated driving is gaining ground, production vehicles will be equipped with cameras, LiDAR and radar sensors. Current research has already developed theoretical ideas how their measurements can be utilized for 6D-motion estimation. Especially Doppler radar and LiDAR sensors are suited for velocity estimation as is shown within this work.