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| Reihe | Springer Theses |
|---|---|
| ISBN | 9783030459048 |
| Sprache | Englisch |
| Erscheinungsdatum | 26.04.2020 |
| Genre | Technik/Elektronik, Elektrotechnik, Nachrichtentechnik |
| Verlag | Springer International Publishing |
| Lieferzeit | Lieferbar in 11 Werktagen |
| Herstellerangaben | Anzeigen Springer Nature Customer Service Center GmbH ProductSafety@springernature.com |
This book describes an effective decision-making and planning architecture for enhancing the navigation capabilities of automated vehicles in the presence of non-detailed, open-source maps. The system involves dynamically obtaining road corridors from map information and utilizing a camera-based lane detection system to update and enhance the navigable space in order to address the issues of intrinsic uncertainty and low-fidelity. An efficient and human-like local planner then determines, within a probabilistic framework, a safe motion trajectory, ensuring the continuity of the path curvature and limiting longitudinal and lateral accelerations. LiDAR-based perception is then used to identify the driving scenario, and subsequently re-plan the trajectory, leading in some cases to adjustment of the high-level route to reach the given destination. The method has been validated through extensive theoretical and experimental analyses, which are reported here in detail.
| Reihe | Springer Theses |
|---|---|
| ISBN | 9783030459048 |
| Sprache | Englisch |
| Erscheinungsdatum | 26.04.2020 |
| Genre | Technik/Elektronik, Elektrotechnik, Nachrichtentechnik |
| Verlag | Springer International Publishing |
| Lieferzeit | Lieferbar in 11 Werktagen |
| Herstellerangaben | Anzeigen Springer Nature Customer Service Center GmbH ProductSafety@springernature.com |
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