Resumen
The “classical” SAE LoA for automated driving can present several drawbacks, and
the SAE-L2 and SAE-L3, in particular, can lead to the so-called “irony of automation”, where the
driver is substituted by the artificial system, but is still regarded as a “supervisor” or as a “fallback
mechanism”. To overcome this problem, while taking advantage of the latest technology, we regard
both human and machine as members of a unique team that share the driving task. Depending on
the available resources (in terms of driver’s status, system state, and environment conditions) and
considering that they are very dynamic, an adaptive assignment of authority for each member of the
team is needed. This is achieved by designing a technology enabler, constituted by the intelligent
and adaptive co-pilot. It comprises (1) a lateral shared controller based on NMPC, which applies
the authority, (2) an arbitration module based on FIS, which calculates the authority, and (3) a visual
HMI, as an enabler of trust in automation decisions and actions. The benefits of such a system are
shown in this paper through a comparison of the shared control driving mode, with manual driving
(as a baseline) and lane-keeping and lane-centering (as two commercial ADAS). Tests are performed
in a use case where support for a distracted driver is given. Quantitative and qualitative results
confirm the hypothesis that shared control offers the best balance between performance, safety, and
comfort during the driving task.
Idioma original | Inglés |
---|---|
Número de artículo | 6950 |
Páginas (desde-hasta) | 6950 |
Número de páginas | 1 |
Publicación | Applied Sciences |
Volumen | 11 |
N.º | 15 |
DOI | |
Estado | Publicada - 28 jul 2021 |
Palabras clave
- Human–computer interaction
- Automated driving
- Shared control
- Arbitration
- Model
- Predictive control
- Advance driver assistance systems
- Human-centered vehicle
- Driver–automation cooperation
Project and Funding Information
- Project ID
- info:eu-repo/grantAgreement/EC/H2020/783190/EU/Programmable Systems for Intelligence in Automobiles/PRYSTINE
- Funding Info
- This research was supported by the ECSEL Joint-Undertaking,which funded the PRYSTINE_x000D_ project under the Grant 783190.