Activities per year
Abstract
Estimation of vehicle motion is a pivotal requirement for autonomous vehicles. This paper proposes a robust ego-vehicle motion estimation to achieve precise localization and tracking, especially in the case of highly dynamic driving. An extended H ∞ filter, based on a kinematic motion model assuming constant turn-rate and acceleration is used to fuse LiDAR, IMU, and vehicle dynamic sensors’ measurements. Measurements from a real high-performance autonomous race car, the so-called DevBot 2.0, have been used to validate the fusion approach in a Roborace competition and compared to a standard Kalman-filter approach. The proposed estimation concept adapts the H ∞ robustness bound based on the innovation sequence of the filter. This provides very fast tracking when it comes to highly dynamic movement, but still achieves minimal estimation uncertainty in case of stationary conditions with lower innovation. Furthermore, a pure kinematic model is used, which is robust against vehicle parameters, changes in the tire-road conditions, and changes in driving maneuvers. The resulting estimation concept shows outstanding performance for considered autonomous race scenario and can be used for a wide range of different applications, such as highway driving, urban driving, platooning, etc.
Original language | English |
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Title of host publication | 2020 IEEE 3rd Connected and Automated Vehicles Symposium, CAVS 2020 - Proceedings |
Pages | 1-5 |
Number of pages | 5 |
ISBN (Electronic) | 9781728190013 |
DOIs | |
Publication status | Published - Nov 2020 |
Event | 3rd IEEE Connected and Automated Vehicles Symposium: CAVS 2020 - Virtual, Victoria, Canada Duration: 18 Nov 2020 → 16 Dec 2020 https://ieeexplore.ieee.org/xpl/conhome/9334548/proceeding |
Publication series
Name | 2020 IEEE 3rd Connected and Automated Vehicles Symposium, CAVS 2020 - Proceedings |
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Conference
Conference | 3rd IEEE Connected and Automated Vehicles Symposium |
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Abbreviated title | IEEE CAVS 2020 |
Country/Territory | Canada |
City | Virtual, Victoria |
Period | 18/11/20 → 16/12/20 |
Internet address |
Keywords
- Advanced Motion Models
- Autonomous Racing
- Autonomous Vehicles
- Extended H Filter
- Robust Performance
- Sensor Fusion
- State Estimation
ASJC Scopus subject areas
- Information Systems and Management
- Control and Optimization
- Computer Networks and Communications
- Automotive Engineering
Activities
- 1 Talk at conference or symposium
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Extended H∞ Filter Adaptation Based on Innovation Sequence for Advanced Ego-Vehicle Motion Estimation
Zubača, J. (Speaker), Stolz, M. (Contributor) & Watzenig, D. (Speaker)
18 Nov 2020 → 16 Dec 2020Activity: Talk or presentation › Talk at conference or symposium › Science to science