Improving Design Understanding of Inclusivity in Autonomous Vehicles: A Driver and Passenger Taskscape Approach

  • M. StrickfadenEmail author
  • P. M. Langdon
Conference paper


Recent developments in autonomous vehicle technology now make SAE Levels 3–5 vehicles (Walker Smith in SAE levels of driving automation., 2016) a realisable goal for transportation over the next 10 years. In particular, SAE Level 3 (conditional automation) automates the main aspects of driving including steering, accelerating and braking on the basis that the driver will frequently respond to a request to intervene. It is likely that in the coming 5 years Level 4 (high automation) will handle all aspects of driving even if a human driver does not intervene. It is also likely that autonomous vehicles will be available in various forms, including conventionally equipped contemporary Original Equipment Manufacturers’ (OEMs) cars and public transport ‘pods’ with no conventional controls. Public perception of such developments has been sampled more frequently in the past 3 years and this reveals increasing awareness of the key technologies and positivity towards introduction. However, while attitudes appear to be changing rapidly, the nature of this awareness throughout the population is partial and opinions vary with methods of sampling. We examine data regarding the public’s understanding of how autonomously capable vehicles could be used to benefit the inclusive population, including those with capability impairments; their carers, and those who require transportation to support dependent family members. We then use a driver and passenger taskscape approach for the analysis of the perceived benefits of use and barriers to use in these populations. This analysis is made in the context of existing transportation conditions and citizen’s needs, and leads towards a tangible conceptual design criterion that may be implemented by design engineers.



This work includes material partly funded by UK EPSRC/JLR TASCC and UK Autodrive.


  1. Albercht G (2003) Disability values, representations and realities. In: Devlieger P, Rusch F, Pfeiffer D (eds) Rethinking disability: the emergence of new definitions, concepts and communities. Garant, AntwerpenGoogle Scholar
  2. Clark B, Parkhurst G, Ricci M (2016) Understanding the socioeconomic adoption scenarios for autonomous vehicles: a literature review. University of the West of England, Bristol, UKGoogle Scholar
  3. Cohen T, Jones P, Cavoli C (2017) Social and behavioural questions associated with automated vehicles: final report scoping study. UCL Transport Institute, Department for Transport, London, UKGoogle Scholar
  4. Devlieger P, Strickfaden M (2012) Reversing the {im}material sense of a non-place: the impact of blindness on the Brussels metro. Space Cult 15(2):224–238CrossRefGoogle Scholar
  5. Ingold T (1993) The temporality of the landscape. World Archaeol 25(2):152–174CrossRefGoogle Scholar
  6. Kirsh D (1996) Adapting the environment instead of oneself. Adapt Behav 4(3/4):415–452CrossRefGoogle Scholar
  7. Kyriakidis M, Happee R, De Winter JCF (2015) Public opinion on automated driving: results of an international questionnaire among 5000 respondents. Transp Res Part F Traffic Psychol Behav 32:127–140CrossRefGoogle Scholar
  8. Macdonald A (2003) Humanizing technology. In: Clarkson J, Coleman R, Keates S, Lebbon C (eds) Inclusive design: design for the whole population. Springer, BerlinGoogle Scholar
  9. Pfleging B, Schmidt AL (2015) (Non-)driving-related activities in the car: defining driver activities for manual and automated driving. In: Workshop on experiencing autonomous vehicles: crossing the boundaries between a drive and a ride. CHI’15, Seoul, Korea, 18–23 Apr 2015Google Scholar
  10. Strickfaden M (2016) In focus: blind photographers challenge visual expectations. In: Devlieger P, Miranda-Galarza B, Brown S, Strickfaden M (eds) Rethinking disability: world perspectives in culture and society. Garant Publishers, AntwerpenGoogle Scholar
  11. Strickfaden M, Vildieu A (2014) On the quest for better communication through tactile images. J Aesthetic Educ (JAE) 48(2):105–122CrossRefGoogle Scholar
  12. Tennant C, Howard S, Franks B, Bauer MW, Stares S (2016) THINKGOOD MOBILITY survey. In: Autonomous vehicles: negotiating a place on the road. A study on how drivers feel about interacting with autonomous vehicles on the road. LSE Consulting, London School of Economics and Political Science, City University of London, UKGoogle Scholar
  13. UK Autodrive (2017) Accessed 15 Nov 2017
  14. Walker Smith B (2016) SAE levels of driving automation. Update 2: 2016 version of SAE J3016. CIS, the Center for Internet and Society. Accessed 15 Nov 2017
  15. Wockatz P, Schartau P (2015) IM traveller needs and UK capability study: supporting the realisation of intelligent mobility in the UK. Transport Systems Catapult, Milton Keynes, UK. Accessed 15 Nov 2017

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Department of Human EcologyUniversity of AlbertaEdmontonCanada
  2. 2.Cambridge Engineering Design CentreThe University of CambridgeCambridgeUK

Personalised recommendations