<p><span>Since the introduction of Automated Vehicles (AVs) on roads, there have been a number of high-profile collisions, which have highlighted significant driver challenges. These include challenges associated with driversβ trust in the automation, their knowledge and awareness of the AVβs capabi
Driving Automation: A Human Factors Perspective
β Scribed by Mark S Young
- Publisher
- CRC Press
- Year
- 2023
- Tongue
- English
- Leaves
- 296
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
"Driving Automation: A Human Factors Perspective addresses a range of issues related to vehicle automation beyond the "how" or "can we" to "what will be the implications". It covers important topics including mental workload and malleable resources theory, effects of adaptive cruise control on mental workload, in-vehicle interface design, driver modeling and monitoring, eco-driving, responses to automation failure, and brake reaction time with automation"--
β¦ Table of Contents
Cover
Half Title
Series Page
Title Page
Copyright Page
Dedication
Contents
Preface
Acknowledgements
Author Biographies
Glossary
STAGE 1: Setting out
1. Context
Overview
Prelude
Timeline
Past
Present
Future
Definitions
Taxonomies
Classical taxonomies
Contemporary taxonomies
Driving automation taxonomies
The human factor
Key points
2. Promises, promisesβ¦
Overview
Introduction
Lessons learned from aviation
Automotive accidents of automation
Collision between a Tesla Model S and a lorry, Williston, Florida, 7 May 2016 (NTSB, 2017)
Collision between Uberβs developmental automated vehicle and a pedestrian, Tempe, Arizona, 18 March 2018
(NTSB, 2019b)
Collision between a Tesla Model X and a crash attenuator, Mountain View, California, 23 March
2018 (NTSB, 2020)
Lessons learned
Problems and ironies
Vigilance
Trust
Complacency
Behavioural adaptation
Situation awareness
Mental workload
Conclusions
Key points
3. Pay attention
Overview
Introduction
Mental workload revisited
Attention
Automaticity
The βproblemβ of underload
Malleable attentional resources theory (MART)
Key Points
STAGE 2: Taking the load off
4. How low is too low?
Overview
Introduction
General methodology
Driving performance Data
Mental workload Data
Attention data
Method β the present study
Design
Procedure
Results
Driving performance data
Mental workload data
Attention ratio data
Discussion
Implications: mental workload and performance
Implications: malleable attentional resources theory
Conclusions
Key Points
5. When is ACC not ACC?
Overview
Introduction
Experiment 1: straight roads
Method
Results
Discussion
Experiment 2: variable-speed lead vehicle
Method
Results
Discussion
General discussion
Summary Of Results
Implications: mental workload and adaptive cruise control
Conclusions
Key Points
6. Whatβs skill got to do with it?
Overview
Introduction
Method
Design
Procedure
Results
Driving performance data
Mental workload data
Attention ratio data
Discussion
Implications: mental workload and performance
Implications: malleable attentional resources theory and skill
Conclusions
Key Points
7. I thought you were driving!
Overview
Introduction
Responses to automation dailure
Reaction times to utomation failure
The experiment
Method
Design
Procedure
Results
Reaction frequencies
Reaction time data
Physiological arousal
Subjective mental workload
Discussion
Implications: malleable attentional resources theory and automaticity
Implications: automation and driver skill
Brake reaction times
Conclusions
Key Points
STAGE 3: Human-centred automation
8. What can automation do for us?
Overview
Introduction
Transient impairment: distraction
In-car distractors
External distractors
Automation-related distractors
Perceptual impairment: eyesight
Cognitive impairment: ageing
Automation lends a hand
Key Points
9. How do we get along?
Overview
Introduction
In-vehicle interface design
Ecological interface design
EID for eco-driving
Development of the Foot-LITE EID
Evaluation
Adaptive interfaces
Adaptive automation
Driver monitoring
Conclusions
Key points
STAGE 4: Letting George do it
10. An autopian future?
Overview
Introduction
What was the problem with automation again?
How to design an automated driving system (from a human factors perspective)
Design philosophies for human-centred automation
Hard or soft, vehicle or driving?
Problem-driven automation
βCliff-edgeβ automation
Human-automation teaming
Driver training
Which way now?
Key points
References
Index
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