Abstract
Highly automated driving is on the advance and is linked to various benefits such as increased overall comfort for the driver as well as rising fuel and transport efficiency. Especially within the domain of truck driving in terms of long distance haulage, it seems as if highly automated driving systems could positively enhance the conditions for drivers and transport companies. Literature suggests that the acceptance of new technologies is a major determinant of whether a developing technology is used. This paper describes an approach aimed at assessing truck drivers’ attitudes towards highly automated driving. Furthermore, fleet managers’ opinions regarding the potential and limitations of highly automated driving systems were queried to investigate whether transport companies would invest in this new technology. Data was collected by an online and paper-based questionnaire. The results reflect the major areas of acceptance and doubts towards highly automated driving from the drivers’ as well as the fleet managers’ perspectives. Both groups are found to be the most concerned about legal liability issues and the general safety and reliability of such technology. Comfort and safety seem to have the biggest influence on the acceptance of highly automated driving. Truck drivers were concerned about reduced driving pleasure as well as being redundant. Results show that the majority of truck drivers do not have a clear idea of highly automated systems. In contrast, fleet managers claim to have an idea of the system.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Ribeiro, S.K., Kobayashi, S., Beuthe, M., Gasca, J., Greene, D., Lee, D. S., Wit, R.: Transportation and its infrastructure. Institute of Transportation Studies (2007)
Gasser, T.M., Arzt, C., Ayoubi, M., Bartels, A., Bürkle, L., Eier, J., Lotz, C.: Rechtsfolgen zunehmender Fahrzeugautomatisierung, p. 83. Unterreihe Fahrzeugtechnik, Berichte der Bundesanstalt Für Strassenwesen (2012)
Anderson, J.M., Nidhi, K., Stanley, K.D., Sorensen, P., Samaras, C., Oluwatola, O.A.: Autonomous vehicle technology: a guide for policymakers. Rand Corporation (2014)
Howard, D., Dai, D.: Public perceptions of self-driving cars: the case of Berkeley, California. In: Paper presented at the 93rd Annual Meeting TRB, Washington, DC (2014) http://www.danielledai.com/academic/howard-dai-selfdrivingcars.pdf
Kauer-Franz, M., Franz, B., Abendroth, B.: Akzeptanz teilautomatisierter Fahrzeugführung. Erkenntnisse aus sieben Jahren Forschung. Institut für Arbeitswissenschaft, Technische Universität Darmstadt, Rollen, Aufgaben, Emotionen (2015)
Merat, N., Jamson, A.H., Lai, F.C., Carsten, O.: Highly automated driving, secondary task performance, and driver state. Hum. Factors: J. Hum. Factors Ergon. Soc. 54(5), 762–771 (2012)
De Winter, J.C., Happee, R., Martens, M.H., Stanton, N.A.: Effects of adaptive cruise control and highly automated driving on workload and situation awareness: a review of the empirical evidence. TransP. Res. Part F: Traffic Psychol. Behav. 27, 196–217 (2014)
Davis Jr, F.D.: A technology acceptance model for empirically testing new end-user information systems: theory and results, Doctoral Dissertation, Massachusetts Institute of Technology (1986)
Karrer, K., Glaser, C., Clemens, C., Bruder, C.: Technikaffinität erfassen – der Fragebogen TA-EG. Der Mensch im Mittelpunkt technischer Systeme 8, 196–201 (2009)
Hoogendoorn, R., van Arem, B., Happee, R., Espinoza, M.M., Kotiadis, D.: Towards safe and efficient driving through vehicle automation: the Dutch automated vehicle initiative (2013)
Kyriakidis, M., Happee, R., De Winter, J.C.F.: Public opinion on automated driving: results of an international questionnaire among 5000 respondents. Transp. Res. Part F: Traffic Psychol. Behav. 32, 127–140 (2015)
Schmitz, C.: LimeSurvey: an open source survey tool. LimeSurvey Project Hamburg, Germany (2012) http://www.limesurvey.org
IBM Corp. Released.: IBM SPSS statistics for windows, Version 22.0. Armonk, NY: IBM Corp (2013)
Casley, S.V., Jardim, A.S., Quartulli, A.M.: A study of public acceptance of autonomous cars (Bachelor of Science), Worcester Polytechnic Institute, Worcester, MA, USA (2013) http://www.wpi.edu/Pubs/E-project/Available/E-project-043013-155601/unrestricted/A_Study_of_Public_Acceptance_of_Autonomous_Cars.pdf
Schoettle, B., Sivak, M.: A survey of public opinion about autonomous and self-driving vehicles in the US, the UK, and Australia (2014)
Garton, L., Haythornthwaite, C., Wellman, B.: Studying online social networks. In: Jones, S. (ed.) Doing Internet Research: Critical Issues and Methods for Examining the Net, pp. 75–105. Sage, Thousand Oaks, CA (1999)
Hudson, J.M., Bruckman, A.: “Go away”: participant objections to being studied and the ethics of chatroom research. Inf. Soc. 20(2), 127–139 (2004)
Andrews, D., Nonnecke, B., Preece, J.: Electronic survey methodology: a case study in reaching hard-to-involve internet users. Int. J. Hum Comput. Inter. 16(2), 185–210 (2003)
Stanton, J.M.: An empirical assessment of data collection using the Internet. Pers. Psychol. 51(3), 709–725 (1998)
Ackroyd, S.: Data collection in context. Longman Group United Kingdom (1992)
Acknowledgments
Natalie Richardson was the initiator of the idea of this article and contributed to development of the questionnaire. Fabian Doubek, Kevin Kuhn and Annika Stumpf contributed to the development and to data collection. Markus Lienkamp revised the manuscript critically for important intellectual content. He gave final approval of the version to be published and agrees with all aspects of the work. The research was conducted with basic research funds of the Institute of Automotive Technology.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing Switzerland
About this paper
Cite this paper
Richardson, N., Doubek, F., Kuhn, K., Stumpf, A. (2017). Assessing Truck Drivers’ and Fleet Managers’ Opinions Towards Highly Automated Driving. In: Stanton, N., Landry, S., Di Bucchianico, G., Vallicelli, A. (eds) Advances in Human Aspects of Transportation. Advances in Intelligent Systems and Computing, vol 484. Springer, Cham. https://doi.org/10.1007/978-3-319-41682-3_40
Download citation
DOI: https://doi.org/10.1007/978-3-319-41682-3_40
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-41681-6
Online ISBN: 978-3-319-41682-3
eBook Packages: EngineeringEngineering (R0)