Me Mental Mo Mode dels an and ADA DAS: A Summa mmary of CS - PowerPoint PPT Presentation

 PUBLIC 公開 Me Mental Mo Mode dels an and ADA DAS: A Summa mmary of CS CSRC RC Hu Huma man-Center ered ed Resea Re earch ch an and d De Developme ment Activities John K. Lenneman, Ph.D. Collaborative Safety Research Center Human-Technology Integration Febr bruar ary 2 27, 7, 2 201 019

 PUBLIC 公開 A A BEH BEHAVIORAL EVAL EVALUATION O OF MEN ENTAL MODEL EL D DEVEL ELOPMEN PMENT The Rockville Institute September 2017 – September 2019

 PUBLIC 公開 Our ur E End nd Goal oal Saf afety i is #1 #1 goal goal – an an appr appropriat ate m ment ental al model odel fac acilitat ates s saf afe behav behavior or/respo pons nse/int nteraction on Not understanding how these products work can have disastrous consequences

 PUBLIC 公開 Our ur E End nd Goal oal “Unde nderstand nding” ng” is not not the he end end goal goal O Outcome bas based ed appr approa oach

 PUBLIC 公開 Overal all P Proj oject ct G Goal oals  With regard to ADAS/ADS technologies:  What are the nature of, and variants of drivers’ mental models?  How are drivers’ mental models formed?  How do drivers’ mental models change over time?  What are the sources of change?  Specific events that occur while driving  Exposure to other sources of information (vehicle manual, service people, friends, Internet, ads, etc.)

 PUBLIC 公開 Ant ntici cipat pated O ed Out utcom comes es  Taxonomy of drivers’ mental models  Indicates the most important dimensions or aspects of users’ MM that can be used to characterize and classify them.  The taxonomy may help to explain differences between drivers’ behavior and changes in their behavior over time.  Description of the information and experiences that influence formation of drivers’ mental models.  Description of the information and experiences that influence changes in drivers’ mental models over time.  Links between drivers’ mental models and specific behaviors

 PUBLIC 公開 Thr hree ee Phas hases Subjective/qualitative research Objective/behavioral research 12 12

 PUBLIC 公開 On On-road D oad Driver ver Behav ehavior or S Study udy Methods  12 vehicle owners:  8 purchased in the last month; 4 with no restriction.  Target vehicles that have Toyota Safety Sense or Lexus Safety System+  8 recruited. Target completion August 2019 Corolla RAV4 Camry LS

 PUBLIC 公開 On On-road D oad Driver ver Behav ehavior or S Study: udy: Met Methods hods

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 PUBLIC 公開 Appl pplicat cation on Scouting  System design  Consumer education Ideally, we design technology so consumer education is not needed.  Research findings Proof-of-concepts/demonstrations

 PUBLIC 公開 Bey eyond H ond Human F uman Fac actor ors Promote the use of advanced statistical techniques and leverage methods in machine learning. + ANNOYANCE MODEL

 PUBLIC 公開 Bey eyond H ond Human F uman Fac actor ors

 PUBLIC 公開 Be Behav haviou oura ral Ad Adap aptat ation on Mod odel el to Lane ane Depar partur ure Wa Warn rning ngs Rudin-Brown & Noy, 2002

 PUBLIC 公開 Human uman-Technol chnolog ogy I y Int ntegr egrat ation G on Grou oup T p Topi opics Infrastructure Driver State Mixed Automation Human-in-the- Detection Levels Loop Licensing/Education Driving Road User Interaction Personalization & Behavior/Culture Experience

 PUBLIC 公開 Human uman-Technol chnolog ogy I y Int ntegr egrat ation G on Grou oup T p Topi opics ACCEPTANCE TRUST & Infrastructure Driver State Mixed Automation Human-in-the- Detection Levels Loop Licensing/Education Driving Road User Interaction Personalization & Behavior/Culture Experience