Online legal driving behavior monitoring for self-driving vehicles

© 2024. The Author(s)..

Defined traffic laws must be respected by all vehicles when driving on the road, including self-driving vehicles without human drivers. Nevertheless, the ambiguity of human-oriented traffic laws, particularly compliance thresholds, poses a significant challenge to the implementation of regulations on self-driving vehicles, especially in detecting illegal driving behaviors. To address these challenges, here we present a trigger-based hierarchical online monitor for self-assessment of driving behavior, which aims to improve the rationality and real-time performance of the monitoring results. Furthermore, the general principle to determine the ambiguous compliance threshold based on real driving behaviors is proposed, and the specific outcomes and sensitivity of the compliance threshold selection are analyzed. In this work, the effectiveness and real-time capability of the online monitor were verified using both Chinese human driving behavior datasets and real vehicle field tests, indicating the potential for implementing regulations in self-driving vehicles for online monitoring.

Medienart:

E-Artikel

Erscheinungsjahr:

2024

Erschienen:

2024

Enthalten in:

Zur Gesamtaufnahme - volume:15

Enthalten in:

Nature communications - 15(2024), 1 vom: 09. Jan., Seite 408

Sprache:

Englisch

Beteiligte Personen:

Yu, Wenhao [VerfasserIn]
Zhao, Chengxiang [VerfasserIn]
Wang, Hong [VerfasserIn]
Liu, Jiaxin [VerfasserIn]
Ma, Xiaohan [VerfasserIn]
Yang, Yingkai [VerfasserIn]
Li, Jun [VerfasserIn]
Wang, Weida [VerfasserIn]
Hu, Xiaosong [VerfasserIn]
Zhao, Ding [VerfasserIn]

Links:

Volltext

Themen:

Journal Article

Anmerkungen:

Date Revised 12.01.2024

published: Electronic

Citation Status PubMed-not-MEDLINE

doi:

10.1038/s41467-024-44694-5

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM366862707