Correlation between safety assessments in the driver–car interaction design process

Broström, Robert; Bengtsson, Peter; Axelsson, Jakob

doi:10.1016/j.apergo.2010.06.019

Cited by 15 publications

(5 citation statements)

References 19 publications

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“…However, different conditions, will lead to differences in timemotion, as in a stressful situation or a state of emergency, and IVIS (In Vehicle Information System) as one of the important elements in both the commercial vehicle and military vehicles, whose function can be a distraction or interruption in the operation of the vehicle (Brostrom et al 2011) so the instruments that support the mental models or perceptions of the user is required (Alfredson 2011) to facilitate user cognitive and to reduce user error. However, not only that, the product design process requires a synergy between the knowledge management, supervision and good design practices, so that the development of a design can produce good output (Chandrasegaran et al 2012).…”

Section: Literature Reviewmentioning

confidence: 99%

Engineering Psychology and Cognitive Ergonomics

Harris

2015

Lecture Notes in Computer Science

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Section: Literature Reviewmentioning

confidence: 99%

Engineering Psychology and Cognitive Ergonomics

Harris

2015

Lecture Notes in Computer Science

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“…Significant attention was devoted in the past to judging the impact of in-car activities [1]. The Lane change Test (LCT) [3] and subjective tests using questionnaires such as NASA TLX and DALI [6] are examples of popular methods used to assess the impact of various in-car tasks that are secondary to the primary task of driving.…”

Section: Related Workmentioning

confidence: 99%

“…C. 4 Request for confirmation without expected reply (1). It happens that the dictating person asks without real waiting for confirmation (example: "OK?"…”

Section: C3 Request For Confirmation (32)mentioning

confidence: 99%

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Speech-Based Text Correction Patterns in Noisy Environment

Kunc

Macek

Labský

et al. 2013

Human-Computer Interaction. Interaction Modalities and Techniques

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We present a study focused on observation of methods of dictation and error correction between humans in a noisy environment. The purpose of this study is to gain insight to natural communication patterns which can then be applied to human -machine interaction. We asked 10 subjects to conduct the standard Lane Change Test (LCT) while dictating messages to a human counterpart who had to note down the message texts. Both parties were located in separate rooms and communicated over Skype. Both were exposed to varying types and levels of noise, which made their communication difficult and forced the subjects to deal with misunderstandings. Dictation of both short and longer messages was tested. We observed how the subjects behaved and we analyzed their communication patterns. We identified and described more then 20 elementary observations related to communication techniques such as synchronization and grounding of parties, error checking and error correction. We also report frequencies of use for each communication pattern and provide basic characteristics of driving distraction during the test.

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“…Over 25% of heavy-truck accidents are related to lane-change events. Additionally, driver inattention is the cause of 78% of crashes across all segments [2]. Several emerging technologies hold great promise to improve situational awareness for the heavy vehicle driver.…”

Section: Introductionmentioning

confidence: 99%

Clarity of View: An AHP Multi-Factor Evaluation Framework for Driver Awareness Systems in Heavy Vehicles

Kivett

Smith

2015

SAE Technical Paper Series

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One of the most difficult aspects of any new human-machine interface development is that of evaluating the user's subjective reaction to the system. In some cases, fears about the usability of a new technology may actually prevent its approval for use due to the perception of potential risk. This is especially true in the automotive industry where driver interface design directly affects safety. In this case study, a new evaluation framework is presented: Clarity of View. It incorporates both the results of the industrypublished methods for evaluating a rearview vision system and combine with it additional new factors that contain both subjective perception and quantitative elements.This AHP based evaluation framework is more closely aligned with the actual decision making process of fleet owners in the trucking industry who are often bombarded with information about potential new safety technology for their fleets, but may otherwise have had a difficult time sorting through the many dissimilar elements of information.This case study serves as a potential model not only for other driver interface systems within the automotive industry, but for any industry that needs to consider both quantitative measures alongside subjective user perception in order to make a fully informed technology selection decisions.

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Correlation between safety assessments in the driver–car interaction design process

Cited by 15 publications

References 19 publications

Engineering Psychology and Cognitive Ergonomics

Engineering Psychology and Cognitive Ergonomics

Speech-Based Text Correction Patterns in Noisy Environment

Clarity of View: An AHP Multi-Factor Evaluation Framework for Driver Awareness Systems in Heavy Vehicles

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