Semi-autonomous advanced parking assistants: do they really have to be learned if steering is automated?

Totzke, Ingo; Jessberger, S; Mühlbacher, Dominik; Krüger, Hans‐Peter

doi:10.1049/iet-its.2010.0112

Cited by 12 publications

(6 citation statements)

References 3 publications

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“…Studies testing these types of systems in real-world settings with middle-age and older drivers have found that use of the system: reduced mental workload when parking (Tachibana 2011; Totzke et al 2010); reduced stress as measured by a reduction in heart rate (Reimer et al 2010); improved parking behavior as measured by a number of factors (Reimer et al 2010; Totzke et al 2011); rated more positively and might transfer learning so that parking will be improved even when the system is not being used (Reimer et al 2010; Totzke et al 2011; Kawabata et al 2008). …”

Section: Resultsmentioning

confidence: 99%

Use, perceptions, and benefits of automotive technologies among aging drivers

et al. 2016

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Advanced in-vehicle technologies have been proposed as a potential way to keep older adults driving for as long as they can safely do so, by taking into account the common declines in functional abilities experienced by older adults. The purpose of this report was to synthesize the knowledge about older drivers and advanced in-vehicle technologies, focusing on three areas: use (how older drivers use these technologies), perception (what they think about the technologies), and outcomes (the safety and/or comfort benefits of the technologies). Twelve technologies were selected for review and grouped into three categories: crash avoidance systems (lane departure warning, curve speed warning, forward collision warning, blind spot warning, parking assistance); in-vehicle information systems (navigation assistance, intelligent speed adaptation); and other systems (adaptive cruise control, automatic crash notification, night vision enhancement, adaptive headlight, voice activated control). A comprehensive and systematic search was conducted for each technology to collect related publications. 271 articles were included into the final review. Research findings for each of the 12 technologies are synthesized in relation to how older adults use and think about the technologies as well as potential benefits. These results are presented separately for each technology. Can advanced in-vehicle technologies help extend the period over which an older adult can drive safely? This report answers this question with an optimistic “yes.” Some of the technologies reviewed in this report have been shown to help older drivers avoid crashes, improve the ease and comfort of driving, and travel to places and at times that they might normally avoid.

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Section: Resultsmentioning

confidence: 99%

Use, perceptions, and benefits of automotive technologies among aging drivers

et al. 2016

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“…If the driver does not comprehend the system's behavior as it actually is, "automation surprise" occurs when the system behaves unexpectedly. Therefore, interaction concepts for these systems have to take into account phenomena such as "over trust" and "over reliance" on the system to avoid serious problems [129]. Currently, numerous ADASs are available as mature products to support longitudinal and lateral vehicle control.…”

Section: International Journal Of Vehicular Technologymentioning

confidence: 99%

Automotive Technology and Human Factors Research: Past, Present, and Future

Akamatsu

Green

Bengler

2013

International Journal of Vehicular Technology

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This paper reviews the history of automotive technology development and human factors research, largely by decade, since the inception of the automobile. The human factors aspects were classified into primary driving task aspects (controls, displays, and visibility), driver workspace (seating and packaging, vibration, comfort, and climate), driver’s condition (fatigue and impairment), crash injury, advanced driver-assistance systems, external communication access, and driving behavior. For each era, the paper describes the SAE and ISO standards developed, the major organizations and conferences established, the major news stories affecting vehicle safety, and the general social context. The paper ends with a discussion of what can be learned from this historical review and the major issues to be addressed. A major contribution of this paper is more than 180 references that represent the foundation of automotive human factors, which should be considered core knowledge and should be familiar to those in the profession.

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“…So, the combination of those sensors cannot detect close objects. For example, the parking assistance system (PAS) prioritizes the detection of short-range objects within 1 m and sometimes uses ultrasonic sensors for detection [3]. A current ultrasonic module for vehicles calculates the distance to an object by measuring the round trip time of a transmitted pulse.…”

Section: Introductionmentioning

confidence: 99%

An Ultrasonic Object Detection Applying the ID Based on Spread Spectrum Technique for a Vehicle

Jin

Kim

et al. 2020

Sensors

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When an ultrasonic sensor generates an ultrasonic wave and detects an obstacle from a reflected wave, a signal transmitted by other ultrasonic sensors would be interference. In this paper, to overcome the interference, a transducer transmits a signal with a unique ID modulated. The interference is ignored by verifying that the reflected signal includes its ID. The ID verification process uses a correlation between the received signal and the ID. Therefore, the ID is selected from orthogonal codes with good cross-correlation. Long code has the advantage of being more robust to interference. However, the reflected wave from nearby obstacles might return before the transmission ends. Therefore, the 7-bit Barker code is applied for near obstacle detection and a 31-bit Gold code is used for distant obstacle detection. The modulation technique is DQPSK, which is available in a narrow bandwidth and has a simple receiver structure. In ID recognition based on correlation, a near–far problem occurs due to a large amplitude difference between the received wave and interference. The addition of a zero-crossing detector solves this problem. The hardware is implemented based on the algorithm proposed in this paper. The simulation showed a detection rate of at least 90% and the the result of the real measurement represented a detection rate of 97.3% at 0.5 m and 94.5% at 2 m.

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Semi-autonomous advanced parking assistants: do they really have to be learned if steering is automated?

Cited by 12 publications

References 3 publications

Use, perceptions, and benefits of automotive technologies among aging drivers

Use, perceptions, and benefits of automotive technologies among aging drivers

Automotive Technology and Human Factors Research: Past, Present, and Future

An Ultrasonic Object Detection Applying the ID Based on Spread Spectrum Technique for a Vehicle

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