A Reliability-Aware Fusion Concept Toward Robust Ego-Lane Estimation Incorporating Multiple Sources

Tuan Tran Nguyen (Autor)

Buch | Softcover

XXIII, 164 Seiten

2019 | 1st ed. 2020
Springer Fachmedien Wiesbaden GmbH (Verlag)
978-3-658-26948-7 (ISBN)

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To tackle the challenges of the road estimation task, many works employ a fusion of multiple sources. By that, a commonly made assumption is that the sources always are equally reliable. However, this assumption is inappropriate since each source has certain advantages and drawbacks depending on the operational scenarios. Therefore, Tuan Tran Nguyen proposes a novel concept by incorporating reliabilities into the multi-source fusion so that the road estimation task can alternately select only the most reliable sources. Thereby, the author estimates the reliability for each source online using classifiers trained with the sensor measurements, the past performance and the context. Using real data recordings, he shows via experimental results that the presented reliability-aware fusion increases the availability of automated driving up to 7 percentage points compared to the average fusion.

About the Author:

Tuan Tran Nguyen received the Master's degree incomputer science and the Ph.D. degree from Otto-von-Guericke University Magdeburg, Germany, in 2013 and 2019, respectively. His research focuses on methods and architectures for reliability-based sensor fusion in intelligent vehicles.

Tuan Tran Nguyen received the Master's degree in computer science and the Ph.D. degree from Otto-von-Guericke University Magdeburg, Germany, in 2013 and 2019, respectively. His research focuses on methods and architectures for reliability-based sensor fusion in intelligent vehicles.

Reliability-Aware Fusion Framework.- Assessing and Learning Reliability for Ego-Lane Estimation.- Reliability-Based Ego-Lane Estimation Using Multiple Sources.

Erscheinungsdatum	28.06.2019
Reihe/Serie	AutoUni – Schriftenreihe
Zusatzinfo	XXIII, 164 p. 84 illus., 25 illus. in color.
Verlagsort	Wiesbaden
Sprache	englisch
Maße	148 x 210 mm
Gewicht	253 g
Themenwelt	Informatik ► Datenbanken ► Data Warehouse / Data Mining
	Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
	Technik
Schlagworte	classification • Dempster-Shafer Theory • Dempster–Shafer Theory • Ego-Lane and Estimation • Intelligent Vehicles • Learning Reliability • Multi-Source Fusion • Neural networks • random forests • Reliability • Reliability-Aware Fusion • Road Detection • Robust Ego-Lane Estimation
ISBN-10	3-658-26948-0 / 3658269480
ISBN-13	978-3-658-26948-7 / 9783658269487
Zustand	Neuware