Journal
IET INTELLIGENT TRANSPORT SYSTEMS
Volume 14, Issue 10, Pages 1183-1189Publisher
WILEY
DOI: 10.1049/iet-its.2019.0826
Keywords
vehicle dynamics; cameras; steering systems; traffic engineering computing; observers; road vehicles; control engineering computing; computer vision; estimation accuracy; intelligent vehicle platform; novel vehicle sideslip angle estimation algorithm; vision information; model accuracy; vehicle dynamic model; intelligent vehicles; visual geometric model; multirate sideslip angle observer; vehicle chassis; vision-aided intelligent vehicle sideslip angle estimation; vehicle dynamic control
Funding
- National Nature Science Foundation of China [51975414]
- National Key Research and Development Program of China [2016YFB0100901]
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The vehicle sideslip angle is an important state for vehicle dynamic control, which needs to be estimated as it could not be obtained directly by the vehicle. To improve the estimation accuracy of the sideslip angle based on the intelligent vehicle platform, this study proposes a novel vehicle sideslip angle estimation algorithm with the fusion of dynamic model and vision information. Firstly, to further improve the model accuracy of the vehicle during lateral acceleration conditions, a vehicle dynamic model is established considering the acceleration error compensation with the assistance of attitude information. In addition, based on the lane line information obtained from the equipped camera in intelligent vehicles, a visual geometric model is established. Owing to the measurement delay and low sampling frequency of the camera, a multi-rate sideslip angle observer with delay compensation is designed to coordinate with the inter-frequency signal of the vehicle chassis. Finally, the effectiveness of the algorithm is verified by the slalom test.
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