2020
DOI: 10.1080/15472450.2020.1822174
|View full text |Cite
|
Sign up to set email alerts
|

Impact of lane keeping assist system camera misalignment on driver behavior

Abstract: This research investigated the impact of sensor camera misalignment on the quality of the lane keeping assistance, end user experience and driving performance. Testing was performed with 16 participants, both males and females, with an age range from 25 to 35. The Lane Keeping Assist System (LKAS) errors in lateral offset ranged from À0.66 m to 0.66 m and testing was performed on two roads. The results indicated that introducing an error in the LKAS system of 0.66 m caused the mean lane position of the vehicle… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

0
2
0

Year Published

2021
2021
2024
2024

Publication Types

Select...
5
1

Relationship

0
6

Authors

Journals

citations
Cited by 7 publications
(2 citation statements)
references
References 23 publications
0
2
0
Order By: Relevance
“…Human ability disparities can be seen in how quickly people react to danger, perceive it, and how well they can get beyond it. The person's psychophysical capacities, the vehicle's technical qualities, the road's characteristics, and the local environment must all be in harmony for safe traffic operation [34], [35].…”
Section: Methodsmentioning
confidence: 99%
“…Human ability disparities can be seen in how quickly people react to danger, perceive it, and how well they can get beyond it. The person's psychophysical capacities, the vehicle's technical qualities, the road's characteristics, and the local environment must all be in harmony for safe traffic operation [34], [35].…”
Section: Methodsmentioning
confidence: 99%
“…The computation of TLC could be arrived at in certain ways depending on the shape/contour of the road and the conditions surrounding the making of the vehicle model. A major disadvantage of TLC-based LKASs is the false alarms they raise owing to previously set required thresholds [4]. Alternatively, lane departures can be predicted by maneuver recognition algorithms.…”
Section: Introductionmentioning
confidence: 99%