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Managing Driving Modes in Automated Driving Systems

Current technology is unable to produce massively deployable, fully automated vehicles that do not require human intervention. Given that such limitations are projected to persist for decades, scenarios requiring a driver to assume control of a semiautomated vehicle, and vice versa, will remain a feature of modern roadways for the foreseeable future. Herein, we adopt a comprehensive perspective of this problem by simultaneously considering operational design domain supervision, driver and environment monitoring, trajectory planning, and driver-intervention performance assessment. More specifically, we develop a modeling framework for each of the aforementioned functions by leveraging decision analysis and Bayesian forecasting. Utilizing this framework, a suite of algorithms is subsequently proposed for driving-mode management and early warning emission, according to a management by exception principle. The efficacy of the developed methods is illustrated and examined via a simulated case study.

Ketersediaan

Informasi Detail

Judul Seri

TRANSPORTATION SCIENCE; Vol.56 No.5 September-October 2022

No. Panggil

-

Penerbit

: .,

Deskripsi Fisik

p. 1259-1278

Bahasa

English

ISBN/ISSN

-

Klasifikasi

NONE

Tipe Isi

-

Tipe Media

-

Tipe Pembawa

-

Edisi

-

Subjek

BAYESIAN DECISION ANALYSIS
AUTOMATED DRIVING SYSTEMS
REQUEST TO INTERVENE

Info Detail Spesifik

https://doi.org/10.1287/trsc.2021.1110

Pernyataan Tanggungjawab

David Ríos Insua, William N. Caballero, Roi Naveiro

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