Advertisement

Enhancing Future Mass ICT with Social Capabilities

  • Andreas RienerEmail author
  • Alois FerschaEmail author
Chapter
Part of the Understanding Complex Systems book series (UCS)

Abstract

Next generation socio-technical systems research is challenged by the complex interactions of technological progress and the social nature of individuals using and adopting technology. As for example, most recent advances in automotive technologies, together with the massive deployment of vehicles worldwide, suggest to no longer understand traffic as a collection of cars, but rather as a web of social connections. In this paper we seek to adopt the capacities of socially aware interactions among individuals to vehicles engaged in mass traffic. We discuss how socially aware cars “ could be making use of their social habitus, i.e. any information which can be inferred from all of its past and present social relations, social interactions and social states when exposing to other vehicles in live traffic. Examples like socially inspired lane changes” and “socially controlled hazard zone avoidance” – evidenced by large scale agent based simulations – show that socially capable vehicles represent a potentially effective way to avoid today undesirable mass traffic phenomena. A prospective is given on how to make social awareness an underpinning design principle for ICT that is deployed at massive scale in general.

Keywords

Traffic Light Controller Area Network Engine Control Unit Antilock Brake System National Highway Traffic Safety Administration 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Handel, S.: Basic principles of social engagement. http://www.theemotionmachine.com/basic-principles-of-social-engagement (2011). Retrieved 2 Nov 2012
  2. 2.
    Pentland, A.: A computational model of social signaling. In: Proceedings of the 18th International Conference on Pattern Recognition (ICPR’06). IEEE Computer Society, pp. 1080–1083. Washington, DC (2006).  10.1109/ICPR.2006.55. URL http://dx.doi.org/10.1109/ICPR.2006.55
  3. 3.
    Gladwell, M.: Blink – The Power of Thinking without Thinking. Little, Brown and Company, New York (2007). ISBN: 9780316010665Google Scholar
  4. 4.
    Ambady, N., Rosenthal, R.: Thin slices of expressive behavior as predictors of interpersonal consequences: a meta-analysis. Psychol. Bull. 111(2), 256–274 (1992)CrossRefGoogle Scholar
  5. 5.
    Bronfenbrenner, U.: Toward an experimental ecology of human development. Am. Psychol. 32(7), 513–531 (1977)CrossRefGoogle Scholar
  6. 6.
    Miorandi, D., Pellegrini, F.D., Mayora, O., Giaffreda, R.: Collective adaptive systems: Scenarios, approaches and challenges. Position paper, CREATE-NET. ftp://ftp.cordis.europa.eu/pub/fp7/ict/docs/fet-proactive/shapefetip-cas10_en.pdf (2010). Retrieved 29 Oct 2012
  7. 7.
    Hinchcliffe, D.: Eight ways to prepare for social engagement at scale. http://www.dachisgroup.com/2012/08/eight-ways-to-prepare-for-social-engagement-at-scale/ (2012). Retrieved 2 Nov 2012
  8. 8.
    Ricci, A., Omicini, A., Viroli, M., Gardelli, L., Oliva, E.: Cognitive Stigmergy: towards a framework based on agents and artifacts. In: Proceedings of the 3rd International Conference on Environments for Multi-Agent Systems III, E4MAS’06, pp. 124–140. Springer-Verlag, Berlin/Heidelberg (2007). URL http://dl.acm.org/citation.cfm?id=1759343.1759352
  9. 9.
    Tonguz, O.: Biologically inspired solutions to fundamental transportation problems. Commun. Mag. IEEE 49(11), 106–115 (2011). doi: 10.1109/MCOM.2011.6069717 CrossRefGoogle Scholar
  10. 10.
    Serbedzja, N.: Privacy in emerging pervasive systems. In: The 3rd International PERADA-ASSYST Summer School on Adaptive Socio-Technical Pervasive Systems, Budapest. Fraunhofer FIRST, Berlin (2010)Google Scholar
  11. 11.
    Bersini, H.: My Vision on “Fundamentals of Collective Adaptive Systems”,. Universite Libre de Bruxelles (IRIDIA), p. 2. (2010)Google Scholar
  12. 12.
    Bersini, H., Philemotte, C.: Emergent phenomena only belong to biology. In: Proceedings of the 9th European Conference on Advances in Artificial Life, ECAL’07, pp. 53–62. Springer-Verlag, Berlin/Heidelberg (2007). URL http://dl.acm.org/citation.cfm?id=1771390.1771398
  13. 13.
    Wikipedia: Collective. http://en.wikipedia.org/wiki/Collective (2013). Retrieved 3 Apr 2013
  14. 14.
    Blumer, H.: Collective behavior. In: Principles of Sociology, 18(3), 67–121. Barnes & Noble, New York (1951). URL http://www.jstor.org/stable/799797
  15. 15.
    Wikipedia: Collective behavior. http://en.wikipedia.org/wiki/Collective_behavior (2013). Retrieved 3 Apr 2013
  16. 16.
    Levy, L.: A study of sports crowd behavior: the case of the Great Pumpkin Incident. J. Sport. Soc. Issues. 13(2), 69–91 (1989). DOI  10.1177/019372358901300202. URL http://jss.sagepub.com/content/13/2/69.abstract Google Scholar
  17. 17.
    FET Proactive: Collective adaptive systems – expert consultation workshop. Report, European Commission, Information Society and Media. ftp://ftp.cordis.europa.eu/pub/fp7/ict/docs/fet-proactive/shapefetip-wp2011-12-02_en.pdf (2009). Retrieved 5 Nov 2012
  18. 18.
    Kernbach, S.: Three cases of connectivity and global information transfer in Robot Swarms. ArXiv e-prints. (2011)Google Scholar
  19. 19.
    Kernbach, S., Schmickl, T., Timmis, J.: Collective adaptive systems: challenges beyond evolvability. Workshop fundamentals of collective adaptive systems, European Commission, p. 2, Brussels, 3–4 Nov 2009Google Scholar
  20. 20.
    Aberg, L., Larsen, L., Glad, A., Le: Observed vehicle speed and drivers’ perceived speed of others. Appl. Psychol. 46(3), 287–302 (1997). URL http://dx.doi.org/10.1111/j.1464-0597.1997.tb01231.x
  21. 21.
    Fleiter, J.J., Lennon, A., Watson, B.: How do other people influence your driving speed? Exploring the [“ta]who’ and the [‘ta]how’ of social influences on speeding from a qualitative perspective. Transport. Res. F Traffic Psychol. Behav. 13(1), 49–62 (2010). DOI  10.1016/j.trf.2009.10.002. URL http://www.sciencedirect.com/science/article/B6VN8-4XP8TD0-1/2/dcafb0205722664ca1e745a4893af80d Google Scholar
  22. 22.
    Leinemann, F.: Roadmap to a single European transport area – towards a competitive and resource efficient transport system. White Paper COM (2011) 144 final, European Commission (2011)Google Scholar
  23. 23.
    Houtenbos, M.: Sociale vergevingsgezindheid: Een theoretische verkenning. Techichal Report R-2009–8. Stichting Wetenschappelijk Onderzoek Verkeersveiligheid (SWOV), Leidschendam (2009)Google Scholar
  24. 24.
    Riener, A., Jeon, M., Dey, A.K., Gaggioli, A.: Workshop “the social car – socially inspired car2x interaction”. In: 4th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI’12), p. 3. Adjunct Proceedings, Portsmouth (2012)Google Scholar
  25. 25.
    Consumer Reports Magazine: Vehicle-to-vehicle communication can prevent crashes. http://www.consumerreports.org/cro/magazine/2012/04 (2012)
  26. 26.
    Osborne, B.: The globalization of traffic congestion: IBM 2010 commuter pain survey. Report, IBM (2010)Google Scholar
  27. 27.
    Wegman, F., Aarts, L. (eds.): Advancing Sustainable Safety: National Road Safety Outlook for 2005–2020. SWOV, Leidschendam (2006). ISBN: 978-90-807958-7-7Google Scholar
  28. 28.
    Roamware: Traffic steering intelligence (TSI). http://www.roamware.com/traffic_steering_intelligence.php (2013). Retrieved 3 Apr 2013
  29. 29.
    Lowy, J.: Safety measure lets cars talk to each other to avoid crashes: U.S. will launch real-world test of 3,000 vehicles. Washington Times. http://www.washingtontimes.com/news/2012/jun/10/safety-measure-lets-cars-talk-to-each-other-to-avo (2012)
  30. 30.
    Sousanis, J.: World vehicle population tops 1 billion units. WardsAuto. http://wardsauto.com/ar/world_vehicle_population_110815 (2011). Retrieved 6 July 2012
  31. 31.
    Teufel, D., et al.: Folgen einer globalen Massenmotorisierung. Press release 35, Umwelt- und Prognose-Institut e.V (UPI). http://yigg.de/nachrichten/2008/01/20/folgen-einer-globalen-massenmotorisierung/bar (1995). Retrieved 29 Oct 2012
  32. 32.
    Lang, N.S., Mauerer, S.: Winning the BRIC auto markets – achieving deep localization in Brazil, Russia, India, and China. Technical report, p. 46. Boston Consulting Group (BCG) (2010)Google Scholar
  33. 33.
    Vinciarelli, A., Pantic, M., Bourlard, H., Pentland, A.: Social signal processing: state-of-the-art and future perspectives of an emerging domain. In: Proceedings of the 16th ACM International Conference on Multimedia, MM ’08, pp. 1061–1070. ACM, New York (2008).  10.1145/1459359.1459573. URL http://doi.acm.org/10.1145/1459359.1459573
  34. 34.
    Riener, A., Zia, K., Ferscha, A., Ruiz, C.B., Rubio, J.J.M.: AmI technology helps to sustain speed while merging – a data driven simulation study on Madrid motorway ring M30. In: Proceedings of the 2010 IEEE/ACM 14th International Symposium on Distributed Simulation and Real Time Applications (DS-RT 2010), Fairfax, DS-RT ’10, pp. 111–120. IEEE Computer Society, Washington, DC (2010). ISBN: 978-0-7695-4251-5Google Scholar
  35. 35.
    Zia, K., Riener, A., Ferscha, A.: Reduction of driver stress using AmI technology while driving in motorway merging sections. In: de Ruyter, B., et al. (eds.) First International Joint Conference on Ambient Intelligence (AmI-10), Malaga. Lecture Notes in Computer Science (LNCS), pp. 127–137. Springer, Berlin/Heidelberg (2010). ISBN: 978-3-642-16916-8Google Scholar
  36. 36.
    Mednis, A., Strazdins, G., Zviedris, R., Kanonirs, G., Selavo, L.: Real time pothole detection using android smartphones with accelerometers. In: Distributed Computing in Sensor Systems and Workshops (DCOSS), 2011 International Conference on, pp. 1–6, (2011).  10.1109/DCOSS.2011.5982206
  37. 37.
    Jeon, M., Riener, A., Lee, J.H., Schuett, J., Walker, B.: Cross-cultural differences in the use of in-vehicle technologies and vehicle area network services: Austria, USA, and South Korea. In: 4th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI’12), p. 8. ACM, Portsmouth, 17–19 Oct 2012Google Scholar
  38. 38.
    Jeon, M., Schuett, J., Yim, J.B., Raman, P., Walker, B.: ENGIN (Exploring Next Generation IN-vehicle INterfaces): drawing a new conceptual framework through iterative participatory processes. In: Adjunct Proceedings of the 3rd International Conference on Automotive User Interfaces and Vehicular Applications (AutomotiveUI’11), p.2. Salzburg, Austria (2011)Google Scholar
  39. 39.
    Duckhorn, E.: Right turn process saves money and the environment. http://www.e-myth.com/cs/user/print/post/ups-makes-the-right-turn (2008). Retrieved 6 July 2012
  40. 40.
    UPS Public Relations: Saving fuel: UPS saves fuel and reduces emissions the “right” way by avoiding left turns. http://www.pressroom.ups.com/Fact+Sheets (2008). Retrieved 6 July 2012
  41. 41.
    Spector, D.: Why left-hand turns are burning a hole in your wallet. http://articles.businessinsider.com/2012-03-15/news/31195555_1_fuel-savings-green-arrow-travel-time (2012). Retrieved 6 July 2012
  42. 42.
    Aarts, L.: Background of the five sustainable safety principles. SWOV Fact sheet, p. 5. SWOV, Leidschendam (2010)Google Scholar
  43. 43.
    Houtenbos, M.: Social forgivingness and vulnerable road users. In: 11th International Walk21 Conference, The Hague, p. 9 (2010)Google Scholar
  44. 44.
    Aarts, L.: Sustainable safety: principles, misconceptions, and relations with other visions. SWOV Fact sheet, p. 5. SWOV, Leidschendam (2010)Google Scholar
  45. 45.
    Wierwille, W.: Automotive ergonomics. In: Visual and Manual Demands of In-Car Controls and Displays, pp. 229–320. Taylor & Francis, London (1993)Google Scholar
  46. 46.
    Edelstein, S.: Nhtsa rules for black box event data recorders take effect September 1. http://www.digitaltrends.com/cars/nhtsa-rules-for-black-box-event-recorders-to-be-released-september-1 (2012). Retrieved 2012
  47. 47.
    Riener, A., Zia, K., Ferscha, A., Ruiz Beltran, C., Minguez Rubio, J.J.: Traffic flow harmonization in expressway merging. Personal Ubiquitous Comput. 17(3), 519–532 (2013)CrossRefGoogle Scholar
  48. 48.
    Leen, G., Heffernan, D.: Expanding automotive electronic systems. Computer 35, 88–93 (2002). http://doi.ieeecomputersociety.org/10.1109/2.976923 CrossRefGoogle Scholar
  49. 49.
    Ferreira, G.: Networked mobility – Audi at CeBIT. http://3d-car-shows.com/2012/networked-mobility-audi-at-cebit-2/ (2012)
  50. 50.
    Leen, G., Heffernan, D., Dunne, A.: Digital networks in the automotive vehicle. Comput. Control Eng. J. 10(6), 257–266 (1999). doi: 10.1049/ccej:19990604 CrossRefGoogle Scholar
  51. 51.
    Robert Bosch GbmH: Controller area network (can). http://www.semiconductors.bosch.de/en/ipmodules/can/can.asp (2012). Retrieved 31 May 2012
  52. 52.
    Albert, A.: Comparison of event-triggered and time-triggered concepts with regard to distributed control systems. In: Embedded World 2004, Nürnberg, 17–19 September 2004. pp. 235–252. Robert Bosch GmbH, Corporate Research and Development (2004)Google Scholar
  53. 53.
    Faezipour, M., Nourani, M., Saeed, A., Addepalli, S.: Progress and challenges in intelligent vehicle area networks. Commun. ACM. 55(2), 90–100 (2012). doi: 10.1145/2076450.2076470. URL http://doi.acm.org/10.1145/2076450.2076470 CrossRefGoogle Scholar
  54. 54.
    Bhm, P.: The FlexRay protocol. http://www-wjp.cs.uni-saarland.de/lehre/seminar/ss05/reports/boehm-slides-fl.pdf (2005). Retrieved 6 Nov 2012
  55. 55.
    MOST Cooperation. The MOST cooperation. http://www.mostcooperation.com (2013). Retrieved 3 Apr 2013
  56. 56.
    Riener, A., Aly, M., Ferscha, A.: Heart on the road: Hrv analysis for monitoring a driver’s affective state. In: First International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI 2009), p. 8. ACM Digital Library, Essen, 21–22 Sept 2009. URL http://portal.acm.org/toc.cfm?id=1620509&type = proceeding
  57. 57.
    Riener, A., Ferscha, A., Frech, P., Hackl, M., Kaltenberger, M.: Subliminal vibro-tactile based notification of CO2 economy while driving. In: Proceedings of the 2nd International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI 2010), Pittsburgh, pp. 92–101. ACM, Pittsburgh (2010). http://doi.acm.org/10.1145/1620509.1620511. ISBN: 978-1-4503-0437-5
  58. 58.
    Riener, A.: Reaction time differences in real and simulated driving. In: First International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI 2009), p. 1. Essen, 21–22 Sept 2009. Poster Abstract, Adjunct Proceedings 2009Google Scholar
  59. 59.
    Riener, A.: Simulating on-the-road behavior using driving simulators. In: Proceedings of the 3rd International Conference on Advances in Computer-Human Interactions (ACHI 2010), p. 6. St. Maarten, 10–16 Feb 2010Google Scholar
  60. 60.
    Riener A., Wintersberger P.: Natural, intuitive finger based input as substitution for traditional vehicle control. In: Proceedings of the 3rd International Conference on Automotive User Interfaces and Interactive Vehicular Applications, Automotive UI ’11, Salzburg, pp. 159–166Google Scholar
  61. 61.
    Riener, A.: Hand and finger gestures in vehicular applications. Computer 45(4), 42–47 (2012). doi: 10.1109/MC.2012.108. URL http://www.computer.org/csdl/mags/co/2012/04/mco2012040042-abs.html MathSciNetCrossRefGoogle Scholar
  62. 62.
    Traffic flow harmonization in expressway merging. Springer (2012). DOI  10.1007/s00779-012-0505-6. URL http://www.springerlink.com/content/t185667716627055/
  63. 63.
    Riener, A., Ferscha, A.: Effect of proactive braking on traffic flow and road throughput. In: 13th IEEE/ACM International Symposium on Distributed Simulation and Real Time Applications (DS-RT 2009), p. 8, IEEE Computer Society Press, Singapore, 25–28 Oct 2009Google Scholar
  64. 64.
    Lugg, M., et al.: Prevention and a better cure – potholes review. Technical report, Department for Transport, Highway Maintenance Efficiency Programme (HMEP) (2012). ISBN: 978 1 84864 134 1Google Scholar
  65. 65.
    Law Offices of Michael Pines: Top 25 causes of car accidents – potholes. http://seriousaccidents.com/legal-advice/top-causes-of-car-accidents/potholes/ (2012). Retrieved 2012
  66. 66.
    Eriksson, J., Girod, L., Hull, B., Newton, R., Madden, S., Balakrishnan, H.: The pothole patrol: Using a mobile sensor network for road surface monitoring. In: The Sixth Annual International Conference on Mobile Systems, Applications and Services (MobiSys 2008), p. 11. ACM, Breckenridge (2008). ISBN: 978-1-60558-139-2Google Scholar
  67. 67.
    Ngowi, R.: Boston testing automatic pothole detector app. CBS Boston. http://boston.cbslocal.com/2012/07/20/boston-testing-automatic-pothole-detector-app/ (2012). Retrieved 29 Oct 2012
  68. 68.
    Padgett, T.: Car culture – you want a revolution. Time Mag. 172(11), 53 (2008)Google Scholar
  69. 69.
    Breuss-Schneeweis, P.: Wikitude drive: Never take your eyes off the road again. http://www.wikitude.com/author/philipp (2010). Accessed 3 Apr 2013
  70. 70.
    U.S. Department of Energy: Driving more efficiently. http://www.fueleconomy.gov/feg/driveHabits.shtml (2013). Retrieved 3 Apr 2013
  71. 71.
    Namatame, A.: Adaptation and Evolution in Collective Systems (Advances in Natural Computation). World Scientific Publishing, River Edge (2006)Google Scholar
  72. 72.
    Jeon, M., Riener, A., Lee, J.H., Schuett, J., Walker, B.: Vehicle area network (VAN)-survey: evaluation and implications. www.pervasive.jku.at/VAN-Survey/ (2012)
  73. 73.
    Ferscha, A., Riener, A.: Pervasive adaptation in car crowds. In: First International Workshop on User-Centric Pervasive Adaptation (UCPA) at MOBILWARE 2009, p. 6. Springer, Berlin/Heidelberg (2009)Google Scholar
  74. 74.
    Kosch, T.: Technical concept and prerequisites of car-to-car communication. In: In Proceedings of 5th European Congress and Exhibition on Intelligent Transport Systems and Services, p. 12. BMW Group Research and Technology (2005)Google Scholar
  75. 75.
    Beckers, R., Holl, O.E., Deneubourg, J.L.: From local actions to global tasks: Stigmergy and collective robotics. In: Artificial Life IV, pp. 181–189. MIT Press, Cambridge (1994)Google Scholar
  76. 76.
    Navlakha, S., Bar-Joseph, Z.: Algorithms in nature: the convergence of systems biology and computational thinking. Mol. Syst. Biol. 7, 1–11 (2011). URL http://dx.doi.org/10.1038/msb.2011.78

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Institute for Pervasive ComputingJohannes Kepler UniversityLinzAustria

Personalised recommendations