國立虎尾科技大學 |

Developing Safety Metrics for Human-system Interaction in Heavy-duty Automated Vehicles.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Developing Safety Metrics for Human-system Interaction in Heavy-duty Automated Vehicles./
Author:	Cosmin-Spanoche, Anna Sofia.
Description:	1 online resource (69 pages)
Notes:	Source: Masters Abstracts International, Volume: 85-12.
Contained By:	Masters Abstracts International85-12.
Subject:	Mechanical engineering. -
Online resource:	click for full text (PQDT)
ISBN:	9798382832401

Developing Safety Metrics for Human-system Interaction in Heavy-duty Automated Vehicles.
Cosmin-Spanoche, Anna Sofia.

Developing Safety Metrics for Human-system Interaction in Heavy-duty Automated Vehicles. - 1 online resource (69 pages)

Source: Masters Abstracts International, Volume: 85-12.

Thesis (M.S.)--University of California, Los Angeles, 2024.

Includes bibliographical references

Incorporating automated driving technologies in commercial heavy-duty operations aims to increase traffic efficiency and safety. However, developers, fleet operators, and regulators must address the unique safety risks that Automated Driving System (ADS) technology introduce. Potential Heavy-Duty Automated Vehicle (HD-AV) fleet operations envision a team of human and machine agents, including the ADS, an onboard safety driver, a fleet operations center, and, in some cases, an onboard safety operator. The complex interactions between these human and machine agents must be addressed when determining the system's safety requirements and design. Safety metrics usually focus on ADS performance, but to adequately inform system design and safety requirements, these metrics must also focus on human-system interactions. This work proposes a system model-based approach to develop human-system interaction metrics focusing on hardware, software, and human impacts on the operational safety of automated driving system fleets.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798382832401Subjects--Topical Terms:

557493
Mechanical engineering.
Subjects--Index Terms:

Automated driving systemsIndex Terms--Genre/Form:

554714
Electronic books.

Developing Safety Metrics for Human-system Interaction in Heavy-duty Automated Vehicles.
LDR:02444ntm a22004097 4500 001 1151655
005 20241113060917.5
006 m o d
007 cr mn ---uuuuu
008 250605s2024 xx obm 000 0 eng d
020 $a 9798382832401
035 $a (MiAaPQ)AAI31331588
035 $a AAI31331588
040 $a MiAaPQ $b eng $c MiAaPQ $d NTU
100 1 $a Cosmin-Spanoche, Anna Sofia. $3 1478464
245 1 0 $a Developing Safety Metrics for Human-system Interaction in Heavy-duty Automated Vehicles.
264 0 $c 2024
300 $a 1 online resource (69 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Masters Abstracts International, Volume: 85-12.
500 $a Advisor: Mosleh, Ali.
502 $a Thesis (M.S.)--University of California, Los Angeles, 2024.
504 $a Includes bibliographical references
520 $a Incorporating automated driving technologies in commercial heavy-duty operations aims to increase traffic efficiency and safety. However, developers, fleet operators, and regulators must address the unique safety risks that Automated Driving System (ADS) technology introduce. Potential Heavy-Duty Automated Vehicle (HD-AV) fleet operations envision a team of human and machine agents, including the ADS, an onboard safety driver, a fleet operations center, and, in some cases, an onboard safety operator. The complex interactions between these human and machine agents must be addressed when determining the system's safety requirements and design. Safety metrics usually focus on ADS performance, but to adequately inform system design and safety requirements, these metrics must also focus on human-system interactions. This work proposes a system model-based approach to develop human-system interaction metrics focusing on hardware, software, and human impacts on the operational safety of automated driving system fleets.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2024
538 $a Mode of access: World Wide Web
650 4 $a Mechanical engineering. $3 557493
650 4 $a Automotive engineering. $3 1104081
650 4 $a Aerospace engineering. $3 686400
650 4 $a Transportation. $3 558117
653 $a Automated driving systems
653 $a Automated vehicles
653 $a Concurrent task analysis
653 $a Human-system interaction
653 $a Safety metrics
655 7 $a Electronic books. $2 local $3 554714
690 $a 0548
690 $a 0540
690 $a 0538
690 $a 0709
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a University of California, Los Angeles. $b Aerospace Engineering 0279. $3 1372820
773 0 $t Masters Abstracts International $g 85-12.
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31331588 $z click for full text (PQDT)