Older People Driving a High-Tech Automobile: Emergent Driving Routines and New Relationships with Driving

Advanced vehicle technologies (AVTs) (e.g., lane departure warning, blind spot monitoring) are sophisticated computer and electronically mediated communications that provide information to users, and, at times, assume control over parts of the driving task (e.g., automated braking). This article examines how AVTs are refashioning older people’s embodied relationships with driving, including driving routines, skills, sensuous dispositions, and modes of control that are considered integral to driving. Results from interviews with 35 older drivers driving a high-tech car call attention to the opportunities and challenges that entanglements with AVTs can present for aging drivers.Les technologies automobiles de pointe (TAP) (par exemple, les systèmes de suivi de voie et de surveillance d’angle mort) offrent une communication informatique et électronique qui informe les automobilistes et parfois même assume le contrôle d’une partie de la conduite (par exemple, freinage automatique). Cet article examine comment les TAP sont en train de modifier le rapport personnel des aînés envers la conduite, y compris les routines, habiletés, dispositions sensuelles et modes de contrôle qui font partie intégrante de la conduite automobile. Les résultats d’entretiens avec 35 aînés conduisant des automobiles de pointe soulignent les occasions et défis que les TAP peuvent présenter à ces aînés.MOTS CLÉS Phénoménologie; Technologie; Usagers et gratifications; Vieillissement; Personnalisation

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Individual differences in cognitive functioning predict effectiveness of a heads-up lane departure warning for younger and older drivers

Accident Analysis & Prevention ◽

10.1016/j.aap.2016.11.003 ◽

2017 ◽

Vol 99 ◽

pp. 171-183 ◽

Cited By ~ 10

Author(s):

Nazan Aksan ◽

Lauren Sager ◽

Sarah Hacker ◽

Benjamin Lester ◽

Jeffrey Dawson ◽

...

Keyword(s):

Individual Differences ◽

Cognitive Functioning ◽

Older Drivers ◽

Lane Departure Warning ◽

Lane Departure

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Using ADAS to Future-Proof Roads—Comparison of Fog Line Detection from an In-Vehicle Camera and Mobile Retroreflectometer

Sensors ◽

10.3390/s21051737 ◽

2021 ◽

Vol 21 (5) ◽

pp. 1737

Author(s):

Ane Dalsnes Storsæter ◽

Kelly Pitera ◽

Edward McCormack

Keyword(s):

Warning System ◽

Management Systems ◽

Warning Systems ◽

Lane Departure Warning ◽

Automated Driving ◽

Pavement Markings ◽

Lighting Conditions ◽

Lane Marking ◽

Lane Departure ◽

Pavement Marking

Pavement markings are used to convey positioning information to both humans and automated driving systems. As automated driving is increasingly being adopted to support safety, it is important to understand how successfully sensor systems can interpret these markings. In this effort, an in-vehicle lane departure warning system was compared to data collected simultaneously from an externally mounted mobile retroreflectometer. The test, performed over 200 km of driving on three different routes in variable lighting conditions and road classes found that, depending on conditions, the retroreflectometer could predict whether the car’s lane departure systems would detect markings in 92% to 98% of cases. The test demonstrated that automated driving systems can be used to monitor the state of pavement markings and can provide input on how to design and maintain road infrastructure to support automated driving features. Since data about the condition of lane marking from multiple lane departure warning systems (crowd-sourced data) can provide input into the pavement marking management systems operated by many road owners, these findings also indicate that these automated driving sensors have an important role in enhancing the maintenance of pavement markings.

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Lane Departure Warning Estimation Using Yaw Acceleration

Open Engineering ◽

10.1515/eng-2021-0008 ◽

2020 ◽

Vol 11 (1) ◽

pp. 102-111

Author(s):

Em Poh Ping ◽

J. Hossen ◽

Wong Eng Kiong

Keyword(s):

Vehicle Dynamics ◽

Dynamic Responses ◽

Dynamics Simulation ◽

Steering Wheel ◽

Mathematical Representation ◽

Vehicle Speed ◽

Lane Departure Warning ◽

Model Based ◽

Lane Departure ◽

Proposed Model

AbstractLane departure collisions have contributed to the traffic accidents that cause millions of injuries and tens of thousands of casualties per year worldwide. Due to vision-based lane departure warning limitation from environmental conditions that affecting system performance, a model-based vehicle dynamics framework is proposed for estimating the lane departure event by using vehicle dynamics responses. The model-based vehicle dynamics framework mainly consists of a mathematical representation of 9-degree of freedom system, which permitted to pitch, roll, and yaw as well as to move in lateral and longitudinal directions with each tire allowed to rotate on its axle axis. The proposed model-based vehicle dynamics framework is created with a ride model, Calspan tire model, handling model, slip angle, and longitudinal slip subsystems. The vehicle speed and steering wheel angle datasets are used as the input in vehicle dynamics simulation for predicting lane departure event. Among the simulated vehicle dynamic responses, the yaw acceleration response is observed to provide earlier insight in predicting the future lane departure event compared to other vehicle dynamics responses. The proposed model-based vehicle dynamics framework had shown the effectiveness in estimating lane departure using steering wheel angle and vehicle speed inputs.

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Acceptance of Transportation Technologies by Aging Adults

Innovation in Aging ◽

10.1093/geroni/igaa057.1822 ◽

2020 ◽

Vol 4 (Supplement_1) ◽

pp. 555-555

Author(s):

Neil Charness ◽

Dustin Souders ◽

Ryan Best ◽

Nelson Roque ◽

JongSung Yoon ◽

...

Keyword(s):

Older Adults ◽

Older Adult ◽

Detection System ◽

Blind Spot ◽

Driving Performance ◽

Older Drivers ◽

Crash Risk ◽

Warning Systems ◽

Risk Of Death ◽

Spot Detection

Abstract Older adults are at greater risk of death and serious injury in transportation crashes which have been increasing in older adult cohorts relative to younger cohorts. Can technology provide a safer road environment? Even if technology can mitigate crash risk, is it acceptable to older road users? We outline the results from several studies that tested 1) whether advanced driver assistance systems (ADAS) can improve older adult driving performance, 2) older adults’ acceptance of ADAS and Autonomous Vehicle (AV) systems, and 3) perceptions of value for ADAS systems, particularly for blind-spot detection systems. We found that collision avoidance warning systems improved older adult simulator driving performance, but not lane departure warning systems. In a young to middle-aged sample the factor “concern with AV” showed age effects with older drivers less favorable. Older drivers, however, valued an active blind spot detection system more than younger drivers.

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