64th AAAM Annual Scientific Conference - AAAM 2020, Portland (United States of America). 12-16 October 2020
Summary:
Research question/Objective To understand the anthropometric and driving factors that determine user preferences in the selection of vehicle seating configurations and positions across different travelling scenarios involving a fully automated vehicle (FAV). Methods Participants completed an online survey in which they were asked to imagine traveling in a FAV across seven hypothetical travelling scenarios. In addition to demographic questions, participants were asked about their anthropometric characteristics, and also about their previous driving experience. Specifically, participants were asked to select between five different seating configurations and four positions within the FAV for each travelling scenario (see Figure 1). The study describes the sample, as well as the multinomial regression analyses that were conducted to understand the significance of potential influential variables in the preferences. All analyses were performed controlling for participants age and gender. This study was approved by the relevant Ethics committees from participating institutions. Data Sources Online survey. Participants were recruited through social media platforms up to October 2019. Results 730 participants (387 women, 339 men) completed the online survey. Participants resided in Australia (34.5%), Spain (12.6%), Sweden (13.8%), Lebanon (30.1%), Colombia (3.0%) and several other countries (5.9%). The height and weight distributions of the participants are shown in Figure 2. Three independent height and weight groups were created (low, medium, high) for the multinomial analyses. Results below correspond only to the scenario of riding alone in the car, but all scenarios will be included in the full publication. Configuration 3 was the preferred seating configuration for almost 74% of the participants, followed by Configuration 2 (13%). When weight was included in the models, participants height was not significant (p-value equal to 0.05) in their preferences for seating configuration. The medium weight group (60 kg- 89 kg) was less inclined to choose Configuration 1 over Configuration 3 (p-value less than 0.05), as was the tallest group (p less than 0.10). Within Configuration 5, the medium weight group preferred position C over position A (p-value less than 0.05), but preferred position A over positions B and D (p-value less than 0.05). Despite more than 50% of the participants reporting experiencing motion sickness at some point when travelling in a vehicle, this experience did not significantly influence their preferred seating configuration (Configuration 3), nor the chosen seating position within their preferred configuration (i.e., tended (p-value less than 0.10) to choose position C over position A in Configuration 3). Significance of results This study follows up previous work which describes data that has shown differences in participants preferences for seating configurations and positions depending on age, sex and country. In addition, while increasing the sample size, the current study analyses other factors, such as anthropometry, motion sickness susceptibility or exposure to traffic that might be associated to choosing one seating configuration and position over others. As these factors are directly related to the likelihood of sustaining injuries in the event of a motor vehicle crash, the information included here provides important insights regarding the potential risk factors for occupants in FAV.
Keywords: Seating configurations, seating positions, fully automated vehicles, autonomous vehicle
DOI: 
https://doi.org/10.1080/15389588.2020.1810245
Published in Traffic Injury Prevention, pp: S19-S24, ISSN: 1538-9588
Publication date: 2020-10-12.
Citation:
F.J. López-Valdés, K. Bohman, J.R. Jiménez-Octavio, D. Logan, W. Raphael, L. Quintana Jiménez, S. Koppel, Understanding factors related to users' preferences in the selection of vehicle seating configurations and positions in fully automated vehicles, 64th AAAM Annual Scientific Conference - AAAM 2020, Portland (United States of America). 12-16 October 2020. In: Traffic Injury Prevention, vol. 21, nº. Supl 1, ISSN: 1538-9588
