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Modeling the decisi...
Modeling the decision-making in human driver overtaking
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- Stefansson, Elis (author)
- KTH,Reglerteknik,KTH Royal Inst Technol, Stockholm, Sweden.
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- Jiang, Frank (author)
- KTH,Reglerteknik,KTH Royal Inst Technol, Stockholm, Sweden.
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- Nekouei, Ehsan (author)
- City Univ Hong, Hong Kong, Peoples R China.
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- Nilsson, Håkan, 1976- (author)
- Uppsala universitet,Institutionen för psykologi
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- Johansson, Karl Henrik, 1967- (author)
- KTH,Reglerteknik,KTH Royal Inst Technol, Stockholm, Sweden.
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(creator_code:org_t)
- Elsevier BV, 2020
- 2020
- English.
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In: IFAC PAPERSONLINE. - : Elsevier BV. - 2405-8963. ; , s. 15338-15345
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Abstract
Subject headings
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- We propose models for the decision-making process of human drivers in an overtaking scenario. First, we mathematically formalize the overtaking problem as a decision problem with perceptual uncertainty. Then, we propose and numerically analyze risk-agnostic and risk-aware decision models, which are able to judge whether an overtaking is desirable or not. We show how a driver's decision-making time and confidence level can be primarily characterized through two model parameters, which collectively represent human risk-taking behavior. We detail an experimental testbed for evaluating the decision-making process in the overtaking scenario. Finally, we present some preliminary experimental results from two human drivers.
Subject headings
- TEKNIK OCH TEKNOLOGIER -- Maskinteknik -- Farkostteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Mechanical Engineering -- Vehicle Engineering (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Samhällsbyggnadsteknik -- Transportteknik och logistik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Civil Engineering -- Transport Systems and Logistics (hsv//eng)
- SAMHÄLLSVETENSKAP -- Psykologi -- Psykologi (hsv//swe)
- SOCIAL SCIENCES -- Psychology -- Psychology (hsv//eng)
Keyword
- Human decision-making
- automated vehicles
- overtaking
- risk-aware decision-making
- driving simulator
Publication and Content Type
- ref (subject category)
- kon (subject category)
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