Abstract
Driving a car is a high cognitive-load task requiring full attention behind the wheel. Intelligent navigation, transportation, and in-vehicle interfaces have introduced a safer and less demanding driving experience. However, there is still a gap for the existing interaction systems to satisfy the requirements of actual user experience. Hand gesture as an interaction medium, is natural and less visually demanding while driving. This paper aims to conduct a user-study with 79 participants to validate mid-air gestures for 18 major in-vehicle secondary tasks. We have demonstrated a detailed analysis on 900 mid-air gestures investigating preferences of gestures for in-vehicle tasks, their physical affordance, and driving errors. The outcomes demonstrate that employment of mid-air gestures reduces driving errors by up to 50% compared to traditional air-conditioning control. Results can be used for the development of vision-based in-vehicle gestural interfaces.
Keywords
- Human computer interaction
- Gesture recognition
- In-vehicle interface
- Human-centred design
- User evaluation
This is a preview of subscription content, access via your institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Victor, T., Rothoff, M., Coelingh, E., Ödblom, A., Burgdorf, K.: When autonomous vehicles are introduced on a larger scale in the road transport system: the Drive Me project. In: Watzenig, D., Horn, M. (eds.) Automated Driving, pp. 541–546. Springer, Cham (2017). doi:10.1007/978-3-319-31895-0_24
Drews, F.A., Yazdani, H., Godfrey, C.N., Cooper, J.M., Strayer, D.L.: Text messaging during simulated driving. Hum. Factors: J. Hum. Factors Ergon. Soc. 51, 762–770 (2009)
Gregoriades, A., Sutcliffe, A., Papageorgiou, G., Louvieris, P.: Human-centered safety analysis of prospective road designs. IEEE Trans. Syst. Man Cybern.-Part A: Syst. Hum. 40(2), 236–250 (2010)
Döring, T., Kern, D., Marshall, P., Pfeiffer, M., Schöning, J., Gruhn, V., Schmidt, A.: Gestural interaction on the steering wheel: reducing the visual demand. ACM (2011)
Fariman, H.J., Alyamani, H.J., Kavakli, M., Hamey, L.: Designing a user-defined gesture vocabulary for an in-vehicle climate control system. In: Proceedings of 28th Australian Conference on Computer-Human Interaction, Launceston, Tasmania, Australia. ACM (2016)
Ruikar, M.: National statistics of road traffic accidents in India. J. Orthop. Traumatol. Rehabil. 6(1), 1 (2013)
Bonin-Font, F., Ortiz, A., Oliver, G.: Visual navigation for mobile robots: a survey. J. Intell. Rob. Syst. 53(3), 263 (2008)
Lin, S.-P., Maxemchuk, N.F.: The fail-safe operation of collaborative driving systems. J. Intell. Transp. Syst. 20(1), 88–101 (2016)
Velez, G., Otaegui, O.: Embedding vision-based advanced driver assistance systems: a survey. IET Intell. Transp. Syst. 11(3), 103–112 (2016)
Normark, C.J., Tretten, P., Gärling, A.: Do redundant head-up and head-down display configurations cause distractions. (2009)
Metz, B., Landau, A., Just, M.: Frequency of secondary tasks in driving–results from naturalistic driving data. Saf. Sci. 68, 195–203 (2014)
Chen, S., Epps, J.: Using task-induced pupil diameter and blink rate to infer cognitive load. Hum.-Comput. Interact. 29(4), 390–413 (2014)
Hartson, R.: Cognitive, physical, sensory, and functional affordances in interaction design. Behav. Inf. Technol. 22(5), 315–338 (2003)
Kaptelinin, V., Nardi, B.: Affordances in HCI: toward a mediated action perspective. ACM (2012)
Merrill, D.J.: FlexiGesture: a sensor-rich real-time adaptive gesture and affordance learning platform for electronic music control. Massachusetts Institute of Technology (2004)
Norman, D.A.: Affordance, conventions, and design. Interactions 6(3), 38–43 (1999)
Riedl, R., Davis, F.D., Banker, R., Kenning, P.H.: Neuroscience in Information Systems Research: Applying Knowledge of Brain Functionality Without Neuroscience Tools. Springer, Heidelberg (2017)
Jahani Fariman, H., Ahmad, S.A., Hamiruce Marhaban, M., Ali Jan Ghasab, M., Chappell, P.H.: Simple and computationally efficient movement classification approach for EMG-controlled prosthetic hand: ANFIS vs. artificial neural network. Intell. Autom. Soft Comput. 21, 1–15 (2015). Taylor and Francis
Kucukyildiz, G., Ocak, H., Karakaya, S., Sayli, O.: Design and implementation of a multi sensor based brain computer interface for a robotic wheelchair. J. Intell. Rob. Syst. 1–17 (2017)
Boyali, A., Hashimoto, N.: Spectral collaborative representation based classification for hand gestures recognition on electromyography signals. Biomed. Signal Process. Control 24, 11–18 (2016)
Rodger, J.A.: Reinforcing inspiration for technology acceptance: improving memory and software training results through neuro-physiological performance. Comput. Hum. Behav. 38, 174–184 (2014)
Lin, Y., Breugelmans, J., Iversen, M., Schmidt, D.: An adaptive interface design (AID) for enhanced computer accessibility and rehabilitation. Int. J. Hum Comput Stud. 98, 14–23 (2017)
Riener, A.: Gestural interaction in vehicular applications. Computer 4, 42–47 (2012)
Jæger, M.G., Skov, M.B. Thomassen, N.G. You can touch, but you can’t look: interacting with in-vehicle systems. ACM (2008)
Jamson, A.H., Westerman, S.J., Hockey, G.R.J., Carsten, O.M.: Speech-based e-mail and driver behavior: effects of an in-vehicle message system interface. Hum. Factors: J. Hum. Factors Ergon. Soc. 46(4), 625–639 (2004)
Akl, A., Valaee, S.: Accelerometer-based gesture recognition via dynamic-time warping, affinity propagation, & compressive sensing. IEEE (2010)
Riener, A., Ferscha, A., Bachmair, F., Hagmüller, P., Lemme, A., Muttenthaler, D., Pühringer, D., Rogner, H., Tappe, A., Weger, F.: Standardization of the in-car gesture interaction space. ACM (2013)
Wobbrock, J.O., Morris, M.R., Wilson, A.D.: User-defined gestures for surface computing. ACM (2009)
Ruiz, J., Li, Y., Lank, E.: User-defined motion gestures for mobile interaction. ACM (2011)
Obaid, M., Häring, M., Kistler, F., Bühling, R., André, E.: User-defined body gestures for navigational control of a humanoid robot. In: Ge, S.S., Khatib, O., Cabibihan, J.-J., Simmons, R., Williams, M.-A. (eds.) ICSR 2012. LNCS, vol. 7621, pp. 367–377. Springer, Heidelberg (2012). doi:10.1007/978-3-642-34103-8_37
Silpasuwanchai, C., Ren, X.: Designing concurrent full-body gestures for intense gameplay. Int. J. Hum. Comput. Stud. 80, 1–13 (2015)
Ha, T., Billinghurst, M., Woo, W.: An interactive 3D movement path manipulation method in an augmented reality environment. Interact. Comput. 24(1), 10–24 (2012)
Nielsen, M., Störring, M., Moeslund, T.B., Granum, E.: A procedure for developing intuitive and ergonomic gesture interfaces for HCI. In: Camurri, A., Volpe, G. (eds.) GW 2003. LNCS, vol. 2915, pp. 409–420. Springer, Heidelberg (2004). doi:10.1007/978-3-540-24598-8_38
Kühnel, C., Westermann, T., Hemmert, F., Kratz, S., Müller, A., Möller, S.: I’m home: defining and evaluating a gesture set for smart-home control. Int. J. Hum. Comput. Stud. 69(11), 693–704 (2011)
Seyed, T., Burns, C., Costa Sousa, M., Maurer, F., Tang, A.: Eliciting usable gestures for multi-display environments. ACM (2012)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Jahani, H., Alyamani, H.J., Kavakli, M., Dey, A., Billinghurst, M. (2017). User Evaluation of Hand Gestures for Designing an Intelligent In-Vehicle Interface. In: Maedche, A., vom Brocke, J., Hevner, A. (eds) Designing the Digital Transformation. DESRIST 2017. Lecture Notes in Computer Science(), vol 10243. Springer, Cham. https://doi.org/10.1007/978-3-319-59144-5_7
Download citation
DOI: https://doi.org/10.1007/978-3-319-59144-5_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-59143-8
Online ISBN: 978-3-319-59144-5
eBook Packages: Computer ScienceComputer Science (R0)