Skip to main content
SpringerLink
Log in

Personalised Driver and Traveller Support Systems

  • Chapter
  • First Online:
Towards User-Centric Transport in Europe

Part of the book series: Lecture Notes in Mobility ((LNMOB))

  • 1448 Accesses

Abstract

Personalised services is a field in rapid development. There are plenty of contexts in transport where personalisation could apply, since not all travellers have the same preferences and needs (due to functional limitations, age, or other reasons). Also, not all drivers drive the same way, even if they belong to the same age cluster. In this article, the personalised HMI in four different mobility-related areas and systems is discussed, i.e. multimodal routing, infomobility services, advanced driver assistance systems (ADAS) and driving training on driving simulators. Relevant developments in various research initiatives are presented as examples, whereas their evaluation results by real users are discussed.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
eBook
USD 16.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Aksenov P, Kemperman A, Arentze T (2014) Toward personalised and dynamic cultural routing: a three-level approach. In: 12th international conference on design and decision support systems in architecture and urban planning, DDS, Elsevier, pp 257–269

    Article  Google Scholar 

  • Aoude GS, Desaraju VR, Stephens LH, How JP (2012) Driver behavior classification at intersections and validation on large naturalistic dataset. IEEE Trans Intell Transp Syst 13(2):724–736

    Article  Google Scholar 

  • Bekiaris E, Amditis A, Panou M (2003) DRIVABILITY: a new concept for modelling driving performance. Int J Cognition Technol Work 5(2):152–161. ISSN: 1435-5558. (Springer-Verlag, London Ltd.)

    Google Scholar 

  • Buhalis D, Amaranggana A (2015) Smart tourism destinations enhancing tourism experience through personalisation of services. Inf Commun Technol Tourism

    Google Scholar 

  • Butakov VA, Ioannou P (2015) Personalised driver/vehicle lane change models for ADAS. IEEE transaction on intelligent transportation systems 64(10):4422–4431

    Google Scholar 

  • Butakov VA, Ioannou P (2016) Personalised driver assistance for signalized intersections using V2I communication. IEEE Trans Intell Transp Syst 17(7):1910–1919

    Article  Google Scholar 

  • Carr S (2010) Personalisation: a rough guide. Social Care Institute for Excellence

    Google Scholar 

  • Edwards S et al (2008) ASK-IT Deliverable 4.6.2 ‘Consolidated pilot results’

    Google Scholar 

  • Fu X, Soeffker D (2010) Modeling of individualized human driver model for automated personalised supervision. SAE technical paper, Tech Rep

    Google Scholar 

  • Kasemsuppakorn P, Karimi AH (2009) Personalised routing for wheelchair navigation. Location based services, vol 3, pp 24–54. https://doi.org/10.1080/17489720902837936

    Article  Google Scholar 

  • Kauber M (2004) The emerging market of infomobility services. Elsevier 8:69–87

    Google Scholar 

  • Kauber M, Grammling M, Stab K, Ziora A, Diederichs P, Jeziorowski M (2007) ASK-IT project D2.3.1 Accessible route guidance module

    Google Scholar 

  • Krajzewicz D (2010) Traffic simulation with SUMO—simulation of urban mobility. In: Barcelò J (ed) Fundamentals of traffic simulation. No. 145 in international series in operations research & management science. Springer, New York, pp 269–293

    Chapter  Google Scholar 

  • Lardinois F (2013) The next frontier for google maps is personalisation. TechCrunch

    Google Scholar 

  • Lathia N, Smith C, Froehlich J, Capra L (2013) Individuals among commuters: building personalised transport information services from fare collection systems. Pervasive Mob Comput 9(5):643–664 Elsevier

    Article  Google Scholar 

  • Lefèvre S, Gao Y, Vasquez D, Tseng E, Bajcsy R, Borrelli F (2014a) Lane keeping assistance with learning-based driver model and model predictive control. In: Proceeding of the 12th international symposium on advanced vehicle control, Tokyo, Japan

    Google Scholar 

  • Lefèvre S, Sun C, Bajcsy R, Laugier C (2014b) Comparison of parametric and non-parametric approaches for vehicle speed prediction. In: Proceedings of the American control conference, Portand, Oregon, pp 3494–3499

    Google Scholar 

  • Lefèvre S, Vasquez D, Laugier C (2014c) A survey on motion prediction and risk assessment for intelligent vehicles. Robomech J 1(1):1

    Article  Google Scholar 

  • Lefèvre S, Carvalho A, Gao Y, Tseng HE, Borrelli F (2015a) Driver models for personalised driving assistance. Veh Syst Dyn 53(12):1705–1720

    Article  Google Scholar 

  • Lefèvre S, Carvalho A, Gao Y, Tseng HE, Borrelli F (2015b) Driver models for personalised driving assistance. Veh Syst Dyn 53(12):1705–1720

    Article  Google Scholar 

  • Lefèvre S, Carvalho A, Borrelli F (2016) A learning-based framework for velocity control in autonomous driving. IEEE Trans Autom Sci Eng 13(1):32–42

    Article  Google Scholar 

  • Levine S, Koltun V (2012) Continuous inverse optimal control with locally optimal examples. In: Proceedings of the international conference on machine learning; Edinburgh, Scotland

    Google Scholar 

  • Lin T, Tseng E, Borrelli F (2013) “Modeling driver behavior during complex maneuvers. In: Proceeding of the American control conference, Washington, DC

    Google Scholar 

  • Linden G, Smith B, York J (2003) Amazon.com recommendations: item-to-item collaborative filtering. IEE Internet Computing, 76–80

    Article  Google Scholar 

  • Montini L, Rieser-Schussler N, Axhausen KW (2014) Personalisation in multi-day GPS and accelerometer data processing in: 14th Swiss transport research conference

    Google Scholar 

  • Moraïtis P, Petraki E, Spanoudakis NI (2003) Providing advanced, personalised infomobility services using agent technology

    Google Scholar 

  • Morris B, Doshi A, Trivedi M (2011) Lane change intent prediction for driver assistance: on-road design and evaluation. In: Proceedings of the IEEE intelligent vehicles symposium. Baden-Baden, Germany, pp 895–901

    Google Scholar 

  • Mourtzis D, Doukas M, Psarommatis F, Giannoulis C, Michalos G (2014) A web-based platform for mass customisation and personalisation. CIRP J Manuf Sci Technol 7(2):112–128

    Article  Google Scholar 

  • Musicant O, Bar-Gera H (2011) Individual driver’s undesirable driving events—a temporal analysis. In: Proceeding of the international conference on road safety and simulation, Indianapolis, Indiana

    Google Scholar 

  • Nieto M, Otaegui O, Velez G, Ortega J, Cortes A (2014) On creating vision based ADAS. IET Intell Transp Syst

    Google Scholar 

  • Nishiwaki Y, Miyajima C, Kitaoka N, Itou K, Takeda K (2007) Generation of pedal operation patterns of individual drivers in car-following for personalised cruise control. In: Proceedings of the IEEE intelligent vehicles symposium; Istanbul, Turkey, pp 823–827

    Google Scholar 

  • Panou M (2008) Ph.D. dissertation ‘Advanced personalised travellers’ warning and information system. Aristotle University of Thessaloniki

    Google Scholar 

  • Panou M, Touliou K, Bekiaris E, Gaitanidou E (2010) Pedestrian and multimodal route guidance adaptation for elderly citizens. IST-Africa

    Google Scholar 

  • Panou MC, Bekiaris ED, Touliou A (2010) ADAS module in driving simulation for training young drivers. In: 13th international IEEE conference on intelligent transportation systems, pp 1582–1587, Funchal

    Google Scholar 

  • Panou M, Bekiaris E, Gemou M (2012) OASIS Deliverable 4.5.2 ‘Pilot results consolidation’

    Google Scholar 

  • Peters B (2009) TRAIN-ALL Deliverable 6.2 ‘Demonstration pilot results consolidation’

    Google Scholar 

  • Pomerleau DA (1989) ALVINN: an autonomous land vehicle in a neural network. In: Proceedings of the advances in neural information processing systems, pp 305–313

    Google Scholar 

  • Quercia D, Lathia N, Calabrese F, Di Lorenzo G, Crowcroft J (2010) Recommending social events from mobile phone location data. In: IEEE international conference on data mining

    Google Scholar 

  • Salvucci D, Gray R (2004) A two-point visual control model of steering. Perception. 33(10):1233–1248

    Article  Google Scholar 

  • Schneiderman R (2013) Car makers see opportunities in infotainment, driver-assistance systems. IEEE Signal Process Mag 30(1):11–15

    Article  Google Scholar 

  • Shia V, Gao Y, Vasudevan R, Campbell K, Lin T, Borrelli F, Bajcsy R (2014) Semiautonomous vehicular control using driver modeling. IEEE Trans Intell Transp Syst 15(6):2696–2709

    Article  Google Scholar 

  • Spanoudakis N, Moraitis P, Petraki E, Bekiaris E, Panou M, Kalogirou K, Zochios A (2006) IM@GINE IT Deliverable 3.1 ‘Integrated Multi-Agent System’

    Google Scholar 

  • Spence A, Torres C, Pachinis T, Edwards S, Hübner Y (2011) OASIS project Deliverable 2.3.1 “Elderly-friendly transport information services”

    Google Scholar 

  • Treiber M, Hennecke A, Helbing D (2000) Congested traffic states in empirical observations and microscopic simulations. Phys Rev E 62(2):1805–1824

    Article  Google Scholar 

  • Tsakou G, Tsaprounis T, Agnantis K, Kalogirou K, Tantinger D, Leonidis A, Spence A, Jiménez VM, Telkamp G, Cerda AMN, Kehagias D (2009) OASIS project deliverable 1.5.1 “OASIS AmI framework and agents”

    Google Scholar 

  • Van Der Laan JD, Heino A, De Waard D (1997) A simple procedure for the assessment of acceptance of advanced transport telematics. Transp Res Part C: Emerg Technol 5(1):1–10

    Article  Google Scholar 

  • Vanhulle P (2009) TRAIN ALL project Deliverable 7.4 “Exploitation business plans”

    Google Scholar 

  • Visintainer F, Panou M, Bekiaris E, Kalogirou K, Mourouzis A, Paglé K (2007) ASK IT project Deliverable 2.6.1 “ASK-IT gateway to ADAS/IVICS”

    Google Scholar 

  • Wang W, Xi J, Wang J (2014) Modeling and recognizing driver behavior based on driving data: a survey. Math Prob Eng 2014

    Google Scholar 

  • Wang W, Xi J, Wang J (2015) Human-centered feed-forward control of a vehicle steering system based on a driver’s steering model. In: 2015 American control conference (ACC). IEEE 2015:3361–3366

    Google Scholar 

  • Wang W, Xi J, Liu C, Li X (2017) Human-centered feed-forward control of a vehicle steering system based on a driver’s path-following characteristics. IEEE Trans Intell Transp Syst 18(6):1440–1453. https://doi.org/10.1109/tits.2016.26063

  • Wang W, Zhao D, Xi J, Han W (2017) A learning-based approach for lane departure warning systems with a personalised driver model. IEEE Trans Veh Technol

    Google Scholar 

  • Xiang X, Zhou K, Zhang W-B, Qin W, Mao Q (2015) A closedloop speed advisory model with driver’s behavior adaptability for ecodriving. IEEE Trans Intell Transp Syst 16(6):3313–3324

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Centre for Research and Technology Hellas, Hellenic Institute of Transport, Egialias 52, 15121, Athens, Greece

    Maria Panou, Evangelos Bekiaris & Eleni Chalkia

Authors
  1. Maria Panou
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Evangelos Bekiaris
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Eleni Chalkia
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Maria Panou .

Editor information

Editors and Affiliations

  1. Future Mobility and Europe, VDI/VDE Innovation und Technik GmbH, Berlin, Germany

    Beate Müller

  2. Future Mobility and Europe, VDI/VDE Innovation und Technik GmbH, Berlin, Germany

    Gereon Meyer

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Panou, M., Bekiaris, E., Chalkia, E. (2019). Personalised Driver and Traveller Support Systems. In: Müller, B., Meyer, G. (eds) Towards User-Centric Transport in Europe. Lecture Notes in Mobility. Springer, Cham. https://doi.org/10.1007/978-3-319-99756-8_18

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-99756-8_18

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-99755-1

  • Online ISBN: 978-3-319-99756-8

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation