Wang, Cheng ; Popp, Christoph ; Winner, Hermann (2024)
Acceleration-Based Collision Criticality Metric for Holistic Online Safety Assessment in Automated Driving.
In: IEEE Access, 2022, 10
doi: 10.26083/tuprints-00026574
Artikel, Zweitveröffentlichung, Verlagsversion
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Kurzbeschreibung (Abstract)
Criticality metrics are not only essential for collision avoidance systems but also play a vital role for verification and validation of automated vehicles. With respect to the first application, criticality metrics should be real-time capable and applicable in various traffic situations. For the second application, holistic safety evaluation by criticality metrics is desired. However, existing criticality metrics hardly meet these two requirements. They are either only applicable in post-processing or only assess the safety of maneuvers in longitudinal direction. Therefore, we propose a new acceleration-based criticality metric, which is real-time capable and applicable in both longitudinal and lateral directions. The theory of the proposed criticality metric is introduced and the definition is explained according to different scenarios. A simulation platform is established to validate the criticality metric. The simulation results demonstrate that the proposed criticality metric takes all possible maneuvers into account when meeting a critical situation. Apart from the longitudinal behavior, the lateral behavior of automated vehicles can also be evaluated in real-time. Consequently, it has a wider application scope than other criticality metrics. To demonstrate its contribution to verification and validation of automated vehicles, we apply the criticality metric to a naturalistic driving dataset. The results prove that our criticality metric has a higher precision and recall than Time to Collision. Additionally, it combines the abilities of Time to Collision and Time Head Way to assess the safety of automated vehicles in the longitudinal direction. The proposed criticality metric is real-time capable and is suitable for different situations.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2024 |
| Autor(en): | Wang, Cheng ; Popp, Christoph ; Winner, Hermann |
| Art des Eintrags: | Zweitveröffentlichung |
| Titel: | Acceleration-Based Collision Criticality Metric for Holistic Online Safety Assessment in Automated Driving |
| Sprache: | Englisch |
| Publikationsjahr: | 29 Januar 2024 |
| Ort: | Darmstadt |
| Publikationsdatum der Erstveröffentlichung: | 2022 |
| Ort der Erstveröffentlichung: | New York, NY |
| Verlag: | IEEE |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | IEEE Access |
| Jahrgang/Volume einer Zeitschrift: | 10 |
| Kollation: | 13 Seiten |
| DOI: | 10.26083/tuprints-00026574 |
| URL / URN: | https://tuprints.ulb.tu-darmstadt.de/26574 |
| Zugehörige Links: | |
| Herkunft: | Zweitveröffentlichungsservice |
| Kurzbeschreibung (Abstract): | Criticality metrics are not only essential for collision avoidance systems but also play a vital role for verification and validation of automated vehicles. With respect to the first application, criticality metrics should be real-time capable and applicable in various traffic situations. For the second application, holistic safety evaluation by criticality metrics is desired. However, existing criticality metrics hardly meet these two requirements. They are either only applicable in post-processing or only assess the safety of maneuvers in longitudinal direction. Therefore, we propose a new acceleration-based criticality metric, which is real-time capable and applicable in both longitudinal and lateral directions. The theory of the proposed criticality metric is introduced and the definition is explained according to different scenarios. A simulation platform is established to validate the criticality metric. The simulation results demonstrate that the proposed criticality metric takes all possible maneuvers into account when meeting a critical situation. Apart from the longitudinal behavior, the lateral behavior of automated vehicles can also be evaluated in real-time. Consequently, it has a wider application scope than other criticality metrics. To demonstrate its contribution to verification and validation of automated vehicles, we apply the criticality metric to a naturalistic driving dataset. The results prove that our criticality metric has a higher precision and recall than Time to Collision. Additionally, it combines the abilities of Time to Collision and Time Head Way to assess the safety of automated vehicles in the longitudinal direction. The proposed criticality metric is real-time capable and is suitable for different situations. |
| Status: | Verlagsversion |
| URN: | urn:nbn:de:tuda-tuprints-265748 |
| Zusätzliche Informationen: | This work was supported in part by the Deutsche Forschungsgemeinschaft (DFG—German Research Foundation), and in part by the Open Access Publishing Fund of Technical University of Darmstadt. |
| Sachgruppe der Dewey Dezimalklassifikatin (DDC): | 600 Technik, Medizin, angewandte Wissenschaften > 620 Ingenieurwissenschaften und Maschinenbau 600 Technik, Medizin, angewandte Wissenschaften > 621.3 Elektrotechnik, Elektronik |
| Fachbereich(e)/-gebiet(e): | 16 Fachbereich Maschinenbau 16 Fachbereich Maschinenbau > Fachgebiet Fahrzeugtechnik (FZD) |
| Hinterlegungsdatum: | 29 Jan 2024 10:38 |
| Letzte Änderung: | 30 Jan 2024 06:32 |
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| Suche nach Titel in: | TUfind oder in Google |
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