Effects of environmental,vehicle and human factors on comfort in partially automated driving: A scenario-based study |
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| Affiliation: | 1. Cognition, Languages, Language and Ergonomics (CLLE) Laboratory, University of Toulouse - Jean Jaurès, Toulouse, France;2. Toulouse Computer Science Research Institute (IRIT), Paul Sabatier University, Toulouse, France;1. Faculty of Transport and Traffic Sciences, University of Zagreb, Zagreb, Croatia;2. Faculty of Croatian Studies, Department of Psychology, University of Zagreb, Zagreb, Croatia;1. School of Business, Jianghan University, Wuhan 430056, China;2. Institute of Intelligent Decision-Making, Jianghan University, Wuhan 430056, China;3. Manufacturing Industry Development Research Centre on Wuhan City Circle, Wuhan 430056, China;4. School of Accounting, Information Systems and Supply Chain, RMIT University, Melbourne, VIC 3000, Australia;1. Hamburg University of Technology (TUHH), Hamburg, Germany;2. Centre for Entrepreneurship, College of Business & Economics, Qatar University, P.O. Box 2713, Doha, Qatar;1. School of Marxism, Dalian Ocean University, Dalian, Liaoning, PR China;2. School of Psychology, Liaoning Normal University, Dalian, Liaoning, PR China;1. Chair of Work, Engineering & Organizational Psychology, Department of Psychology and Ergonomics, Technische Universität Berlin, Marchstraße 12, 10587 Berlin, Germany;2. Chair of Engineering Psychology and Applied Cognitive Research, Technische Universität Dresden, Dresden, Germany;1. State Key Laboratory of Advanced Design And Manufacturing for the Vehicle Body, Hunan University, No. 2 Lushan South Rd, Yuelu District, Changsha, Hunan 410082, China;2. State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China |
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| Abstract: | Although it is key to improving acceptability, there is sparse scientific literature on the experience of humans as passengers in partially automated cars. The present study therefore investigated the influence of road type, weather conditions, traffic congestion level, vehicle speed, and human factors (e.g., trust in automated cars) on passenger comfort in an automated car classified as Level 3 according to the Society of Automotive Engineers (SAE). Participants were exposed to scenarios in which a character is driven by an SAE Level 3 automated car in different combinations of conditions (e.g., highway × heavy rain × very congested traffic × vehicle following prescribed speed). They were asked to rate their perceived comfort as if they were the protagonist. Results showed that comfort was negatively affected by driving in downtown (vs. highway), heavy rain, and congested traffic. Interaction analyses showed that reducing the speed of the vehicle improved comfort in these two last conditions, considered either individually or in combination. Cluster analysis revealed four profiles: trusting in automation, averse to speed reduction, risk averse, and mistrusting automation. These profiles were all influenced differently by the driving conditions, and corresponded to varying levels of trust in automated cars. This study suggests that optimizing comfort in automated cars should take account of both driving conditions and human profiles. |
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| Keywords: | Driving automation Discomfort Drivenger Passenger Scenario |
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