Abstract
While Advanced Driver Assistance Systems (ADAS) are becoming the longer the more common, most interest has been devoted either to highway traffic or to special situations like parking. Against this background, this paper focuses on overtaking maneuvers on country roads, and a stochastic model predictive control (MPC) algorithm is implemented to manage this task. The behavior of the surrounding vehicles is predicted stochastically by using Bayesian networks. The overtaking algorithm is tested for various country road traffic scenarios in a stochastic traffic environment. To compare the performance of the controller to that of a real human driver a dedicated study in this stochastic traffic environment is carried out. The results of this study show that the control algorithm provides the safest trip in acceptable travel time.
| Originalsprache | Englisch |
|---|---|
| Titel | 2020 American Control Conference (ACC) |
| Seiten | 1217-1222 |
| Seitenumfang | 6 |
| ISBN (elektronisch) | 9781538682661 |
| DOIs | |
| Publikationsstatus | Veröffentlicht - Juli 2020 |
Publikationsreihe
| Name | Proceedings of the American Control Conference |
|---|---|
| Band | 2020-July |
| ISSN (Print) | 0743-1619 |
UN SDGs
Dieser Output leistet einen Beitrag zu folgendem(n) Ziel(en) für nachhaltige Entwicklung
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SDG 11 – Nachhaltige Städte und Gemeinschaften
Wissenschaftszweige
- 206002 Elektromedizinische Technik
- 207109 Schadstoffemission
- 202 Elektrotechnik, Elektronik, Informationstechnik
- 202027 Mechatronik
- 202034 Regelungstechnik
- 203027 Verbrennungskraftmaschinen
- 206001 Biomedizinische Technik
JKU-Schwerpunkte
- Digital Transformation
- Sustainable Development: Responsible Technologies and Management
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