語系:
繁體中文
English
說明(常見問題)
回圖書館首頁
手機版館藏查詢
登入
回首頁
到查詢結果
[ null ]
切換:
標籤
|
MARC模式
|
ISBD
Human Operator-Autonomous Vehicle In...
~
Fu, Ernestine,
FindBook
Google Book
Amazon
博客來
Human Operator-Autonomous Vehicle Interactions with System Bias and Transitions of Control /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Human Operator-Autonomous Vehicle Interactions with System Bias and Transitions of Control // Ernestine Fu.
作者:
Fu, Ernestine,
面頁冊數:
1 electronic resource (147 pages)
附註:
Source: Dissertations Abstracts International, Volume: 84-05, Section: B.
Contained By:
Dissertations Abstracts International84-05B.
標題:
Failure. -
電子資源:
https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29755741
ISBN:
9798357504685
Human Operator-Autonomous Vehicle Interactions with System Bias and Transitions of Control /
Fu, Ernestine,
Human Operator-Autonomous Vehicle Interactions with System Bias and Transitions of Control /
Ernestine Fu. - 1 electronic resource (147 pages)
Source: Dissertations Abstracts International, Volume: 84-05, Section: B.
Autonomous vehicles are considered the future of transportation. They offer several potential long-term benefits, including reduction in driving and navigation chores, enhanced mobility for individuals with disabilities, improved safety and decreases in traffic collisions, and reduced infrastructure costs. Currently, however, autonomous vehicle systems in development are still limited by their abilities to detect their surroundings, interpret sensory information, and fully navigate without human input. The human operator needs to both supervise the imperfect system and collaborate with it to navigate the driving environment. The research presented in this dissertation was aimed at better understanding human operator and autonomous vehicle interactions and how they affect system design and implementation.An immersive driving simulator was modified to develop experimental studies that analyzed interactions between the human operator and the autonomous vehicle system. The first part of this research focused on the inherent algorithmic biases present in designing autonomous vehicle systems, and the effects of changes in the system's sensitivity level and autonomy level were analyzed. The results show that a system biased towards lower sensitivity can improve operator vigilance and performance. The results further demonstrate that higher levels of autonomy in vehicles can result in reduced operator performance during potentially fatal events.Subsequent research focused on transitions of control from automation, in which the system hands control of the vehicle over to the human operator because there is a failure in the autonomous driving system. The effect of varying alert frequencies and levels of failure severity on the human operator's ability to successfully navigate a transition was analyzed. Significant differences in operator performance between the presence or lack of an alarm were observed, as well as the fact that an initial system failure's severity level did not seem to affect operator performance in a later failure event.Overall, the results of this work show that engineers and designers of autonomous vehicle systems need to consider a number of scenarios when specifying system actions and responses. This research provides a starting point for further exploration of the implications of system bias, particularly with varying levels of automation. It also provides insights that can help inform the design of transitions of control. A better understanding of human operator and autonomous vehicle interactions remains critical as vehicles with higher levels of automation become more prevalent on the road.
English
ISBN: 9798357504685Subjects--Topical Terms:
3561225
Failure.
Human Operator-Autonomous Vehicle Interactions with System Bias and Transitions of Control /
LDR
:04092nmm a22003973i 4500
001
2431077
005
20250603110647.5
006
m o d
007
cr|nu||||||||
008
261011s2019 miu||||||m |||||||eng d
020
$a
9798357504685
035
$a
(MiAaPQD)AAI29755741
035
$a
(MiAaPQD)STANFORDbj672yt5213
035
$a
AAI29755741
040
$a
MiAaPQD
$b
eng
$c
MiAaPQD
$e
rda
100
1
$a
Fu, Ernestine,
$e
author.
$3
3819719
245
1 0
$a
Human Operator-Autonomous Vehicle Interactions with System Bias and Transitions of Control /
$c
Ernestine Fu.
264
1
$a
Ann Arbor :
$b
ProQuest Dissertations & Theses,
$c
2019
300
$a
1 electronic resource (147 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: Dissertations Abstracts International, Volume: 84-05, Section: B.
500
$a
Advisors: Fischer, Martin; Leifer, Larry J. Committee members: Cutkosky, Mark R. ; Sirkin, David Andrew; Weyant, John P. ; Gumport, Patricia J. .
502
$b
Ph.D.
$c
Stanford University
$d
2019.
520
$a
Autonomous vehicles are considered the future of transportation. They offer several potential long-term benefits, including reduction in driving and navigation chores, enhanced mobility for individuals with disabilities, improved safety and decreases in traffic collisions, and reduced infrastructure costs. Currently, however, autonomous vehicle systems in development are still limited by their abilities to detect their surroundings, interpret sensory information, and fully navigate without human input. The human operator needs to both supervise the imperfect system and collaborate with it to navigate the driving environment. The research presented in this dissertation was aimed at better understanding human operator and autonomous vehicle interactions and how they affect system design and implementation.An immersive driving simulator was modified to develop experimental studies that analyzed interactions between the human operator and the autonomous vehicle system. The first part of this research focused on the inherent algorithmic biases present in designing autonomous vehicle systems, and the effects of changes in the system's sensitivity level and autonomy level were analyzed. The results show that a system biased towards lower sensitivity can improve operator vigilance and performance. The results further demonstrate that higher levels of autonomy in vehicles can result in reduced operator performance during potentially fatal events.Subsequent research focused on transitions of control from automation, in which the system hands control of the vehicle over to the human operator because there is a failure in the autonomous driving system. The effect of varying alert frequencies and levels of failure severity on the human operator's ability to successfully navigate a transition was analyzed. Significant differences in operator performance between the presence or lack of an alarm were observed, as well as the fact that an initial system failure's severity level did not seem to affect operator performance in a later failure event.Overall, the results of this work show that engineers and designers of autonomous vehicle systems need to consider a number of scenarios when specifying system actions and responses. This research provides a starting point for further exploration of the implications of system bias, particularly with varying levels of automation. It also provides insights that can help inform the design of transitions of control. A better understanding of human operator and autonomous vehicle interactions remains critical as vehicles with higher levels of automation become more prevalent on the road.
546
$a
English
590
$a
School code: 0212
650
4
$a
Failure.
$3
3561225
650
4
$a
Braking systems.
$3
3689804
650
4
$a
Success.
$3
518195
650
4
$a
Self report.
$3
3699703
650
4
$a
Autonomous vehicles.
$3
2179092
650
4
$a
Roads & highways.
$3
3555163
650
4
$a
Design.
$3
518875
650
4
$a
False alarms.
$3
3767057
650
4
$a
Camcorders.
$3
1471094
650
4
$a
Automotive engineering.
$3
2181195
650
4
$a
Transportation.
$3
555912
690
$a
0389
690
$a
0540
690
$a
0709
710
2
$a
Stanford University.
$e
degree granting institution.
$3
3765820
720
1
$a
Fischer, Martin
$e
degree supervisor.
720
1
$a
Leifer, Larry J.
$e
degree supervisor.
773
0
$t
Dissertations Abstracts International
$g
84-05B.
790
$a
0212
791
$a
Ph.D.
792
$a
2019
856
4 0
$u
https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29755741
筆 0 讀者評論
館藏地:
全部
電子資源
出版年:
卷號:
館藏
1 筆 • 頁數 1 •
1
條碼號
典藏地名稱
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
W9526772
電子資源
11.線上閱覽_V
電子書
EB
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
評論
新增評論
分享你的心得
Export
取書館
處理中
...
變更密碼
登入
(1)帳號:一般為「身分證號」;外籍生或交換生則為「學號」。 (2)密碼:預設為帳號末四碼。
帳號
.
密碼
.
請在此電腦上記得個人資料
取消
忘記密碼? (請注意!您必須已在系統登記E-mail信箱方能使用。)