Skip to main content

Analysing Behavioural Data from On-Road Driving Studies: Handling the Challenges of Data Processing

  • Chapter
  • First Online:
UR:BAN Human Factors in Traffic

Part of the book series: ATZ/MTZ-Fachbuch ((ATZMTZ))

  • 1713 Accesses

Abstract

The analysis of real world driving data entails numerous challenges. In this chapter, several strategies are proposed to meet challenges that surface in data storage, data extraction, data correction and data enrichment. The strategies are illustrated with examples from a study that had been conducted as part of the UR:BAN research project ”Behaviour Prediction and Intention Detection” (VIE), which aimed at investigating driving behaviour when approaching intersections under real environmental conditions in order to predict turning manoeuvres at urban intersections. It was demonstrated that with the proposed data infrastructure, correction procedures and extracted filters for potentially confounding variables, it is possible to establish a “clean” data basis to implement and adjust a prediction algorithm for turning manoeuvres according to individual driver characteristics.

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

Access this chapter

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 119.99
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

  1. Lietz, H., Petzoldt, T., Henning, M., Haupt, J., Wanielik, G., Krems, J., Noyer, U.: Methodische und technische Aspekte einer Naturalistic Driving Study. BASt FE 82.0351/2008. FAT Schriftenreihe, vol. 229. VDA, Berlin (2011)

    Google Scholar 

  2. Statistisches Bundesamt (Destatis): Verkehrsunfälle – Fachserie 8 Reihe 7 – 2014. Wiesbaden (2015)

    Google Scholar 

  3. Fastenmeier, W., Gstalter, H.: Driving task analysis as a tool in traffic safety research and practice. Saf Sci 45(9), 952–979 (2007). doi:10.1016/j.ssci.2006.08.023

    Article  Google Scholar 

  4. Federal Highway Administration (FHWA): Task analysis of intersection driving scenarios: Information processing bottlenecks (No. FHWA-HRT-06-033) (2006)

    Google Scholar 

  5. Gstalter, H., Fastenmeier, W.: Reliability of drivers in urban intersections. Accid Analysis Prev 42(1), 225–234 (2010). doi:10.1016/j.aap.2009.07.021

    Article  Google Scholar 

  6. Donges, E.: Aspekte der aktiven Sicherheit bei der Führung von Personenkraftwagen. Automobil-Industrie 2, 183–190 (1982)

    Google Scholar 

  7. Werneke, J., Vollrath, M.: What does the driver look at? The influence of intersection characteristics on attention allocation and driving behavior. Accid Analysis Prev 45, 610–619 (2012). doi:10.1016/j.aap.2011.09.048

    Article  Google Scholar 

  8. Köhler, L., Mergl, C., Blaese, D., Bengler, K.: Fahrerbeanspruchung im urbanen Raum: Erhebung der subjektiven Beanspruchung des Fahrers bei einer Kreuzungsüberquerung. Der Fahrer im 21. Jahrhundert. Fahrer, Fahrerunterstützung und Bedienbarkeit, 7. VDI-Tagung, Braunschweig, 5. und 6. November 2013. VDI-Berichte, vol. 2205. VDI, Düsseldorf, pp 237–250 (2013)

    Google Scholar 

  9. Endsley, M.R.: Toward a Theory of Situation Awareness in Dynamic Systems. Hum Factors 37(1), 32–64 (1995). doi:10.1518/001872095779049543

    Article  Google Scholar 

  10. Liebner, M., Klanner, F.: Driver intent inference and risk assessment. In: Winner, H., Hakuli, S., Lotz, F., Singer, C. (eds.) Handbook of driver assistance systems. Basic Information, Components and Systems for Active Safety and Comfort. Springer International Publishing, Cham (2016)

    Google Scholar 

  11. Köhler, L., Bengler, K., Mergl, C., Maier, K., Wimmer, M.: Validation of a telephone manager for stressful driving situations. In: de Waard, D., Sauer, J., Röttger, S., Kluge, A., Manzey, D., Weikert, C., Hoonhout, J. (eds.) Proceedings of the Human Factors and Ergonomics Society Europe Chapter 2014 Annual Conference. Human Factors in high reliability industries (2015)

    Google Scholar 

  12. Zademach, M.: Analyse des Fahrerverhaltens an innerstädtischen Kreuzungen: Ermittlung von Anforderungen an ein System zur Vermeidung von Kollisionen. Verlag Dr. Hut, München (2016)

    Google Scholar 

  13. Zademach, M., Mergl, C., Färber, B.: Analyse des Fahrerverhaltens im Kreuzungsbereich: Ableitung einer Verhaltensprognose anhand von Fahrzeugdaten. Der Fahrer im 21. Jahrhundert. Fahrer, Fahrerunterstützung und Bedienbarkeit, 7. VDI-Tagung, Braunschweig, 5. und 6. November 2013. VDI-Berichte, vol. 2205. VDI, Düsseldorf (2013)

    Google Scholar 

  14. ACE Auto Club Europa: Dem Blinkmuffel keine Chance. Argumentationspapier (2008). https://www.ace-online.de/fileadmin/user_uploads/Der_Club/Dokumente/ACE_Aktionen/Argumentationspapier_4c.pdf. Accessed 17. Apr. 2017

    Google Scholar 

  15. Ponziani, R.: Turn signal usage rate results: A comprehensive field study of 12,000 observed turning vehicles. Sae Tech Pap (2012). 2012-01-0261 doi:10.4271/2012-01-0261

  16. Hennessy, D.: Social, personality, and affective constructs in driving. In: Porter, B.E. (ed.) Handbook of Traffic Psychology, 1st edn., pp. 149–163. Elsevier/Academic Press, Amsterdam (2011)

    Chapter  Google Scholar 

  17. Skippon, S.M., Reed, N., Luke, T., Robbins, R., Chattington, M., Harrison, A.H.: Relationships between driving style, self-reported driving behaviour and personality. In: Dorn, L. (ed.) Human Factors in Road and Rail Transport. Driver behaviour and training, vol. IV, Ashgate, Farnham, Surrey, England, Burlington, VT (2010)

    Google Scholar 

  18. Deml, B., Freyer, J., Färber, B.: Ein Beitrag zur Prädiktion des Fahrstils. VDI-Berichte, vol. 2015. VDI, Düsseldorf (2007). Fahrer im 21. Jahrhundert. Human Machine Interface, 4. VDI-Fachtagung, 14. und 15. November 2007, Braunschweig

    Google Scholar 

  19. Sagberg, F., Selpi, Piccinini, G.F.B., Engstrom, J.: A review on driving styles and road safety. Hum Factors 57(7), 1248–1275 (2015). doi:10.1177/0018720815591313

    Article  Google Scholar 

  20. Quimby, A., Maycock, G., Palmer, C., Buttress, S.: The factors that influence a driver’s choice of speed – a questionnaire study. TRL REPORT, vol. 325. (1999)

    Google Scholar 

  21. Ahie, L.M., Charlton, S.G., Starkey, N.J.: The role of preference in speed choice. Transportation Res Part F: Traffic Psychol Behav 30, 66–73 (2015). doi:10.1016/j.trf.2015.02.007

    Article  Google Scholar 

  22. Beggiato, M.: Changes in motivational and higher level cognitive processes when interacting with in-vehicle automation (Doctoral dissertation). Technische Universität Chemnitz, Chemnitz (2015). http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-167333. Accessed 17. Apr. 2017

    Google Scholar 

  23. Pereira, M., Lietz, H., Beggiato, M.: Development of a database for storage and analysis of behavioural data. In: Stevens, A., Krems, J., Brusque, C. (eds.) Driver adaptation to information and assistance systems, pp. 301–317. The Institution of Engineering and Technology, London (2014)

    Google Scholar 

  24. Blum, R.: PostgreSQL 8 for Windows. Database professional’s library. McGraw-Hill, New York (2007)

    Google Scholar 

  25. Obe, R.O., Hsu, L.S.: PostGIS in action. Safari Tech Books Online. Manning, Greenwich, Connecticut (2011)

    Google Scholar 

  26. Charlton, S.G.: Restricting intersection visibility to reduce approach speeds. Accid Analysis Prev 35(5), 817–823 (2003). doi:10.1016/S0001-4575(02)00052-0

    Article  Google Scholar 

  27. Harwood, D.W., Bauer, K.M., Potts, I.B., Torbic, D.J., Richard, K.R., Rabbani, E.R.K., Elefteriadou, L.: Safety effectiveness of intersection left- and right-turn lanes (No. FHWA-RD-02-089) (2002)

    Google Scholar 

  28. Louveton, N., Bootsma, R.J., Guerin, P., Berthelon, C., Montagne, G.: Intersection crossing considered as intercepting a moving traffic gap: Effects of task and environmental constraints. Acta Psychol (Amst) 141(3), 287–294 (2012). doi:10.1016/j.actpsy.2012.08.003

    Article  Google Scholar 

  29. Harwood, L.C., Doerzaph, Z.: LiDAR: Another potential data source. Fourth international symposium on naturalistic driving research, Blacksburg, August 25–28, 2014. (2014). http://vtechworks.lib.vt.edu/handle/10919/53969. Accessed 17. Apr. 2017

    Google Scholar 

  30. Khattak, Aemal, J., Hallmark, Shauna, L., Souleyrette, Reginald, R.: An application of lidar technology to highway safety. In: Transportation Research Board (TRB) (ed.) 82nd Annual Meeting compendium of papers. CD-ROM Washington, January 12–16, 2003. (2003)

    Google Scholar 

  31. Pech, T., Lindner, P., Wanielik, G.: Head tracking based glance area estimation for driver behaviour modelling during lane change execution. 2014 IEEE 17th International Conference on Intelligent Transportation Systems (ITSC 2014), Qingdao, 8–11 Oct. 2014. IEEE, Piscataway (2014)

    Book  Google Scholar 

  32. Wittenburg, P., Brugman, H., Russel, A., Klassmann, A., Sloetjes, H.: ELAN: A professional framework for multimodality research. Proceedings of the 5th international conference on language resources and evaluation (LREC 2006), pp 1556–1559 (2006)

    Google Scholar 

  33. Beggiato, M., Krems, J.F.: Sequence analysis of glance patterns to predict lane changes on urban arterial roads. 6. Tagung Fahrerassistenz, 28.–29. November 2013. München (2013). Der Weg zum automatischen Fahren. Konferenz an der TUM. http://mediatum.ub.tum.de/doc/1187197/1187197.pdf

    Google Scholar 

  34. Graichen, M., Nitsch, V.: Effects of driver characteristics and driver state on predicting turning maneuvers in urban areas: Is there a need for individualized parametrization? 2016 AHFE International, 7th International Conference on Applied Human Factors and Ergonomics, Walt Disyney World Swan and Dolphin Hotel, Florida, 27–31 July 2016. (2016)

    Google Scholar 

  35. Liebner, M., Klanner, F., Baumann, M., Ruhhammer, C., Stiller, C.: Velocity-Based Driver Intent Inference at Urban Intersections in the Presence of Preceding Vehicles. IEEE Intell Transportation Syst Mag 5(2), 10–21 (2013). doi:10.1109/MITS.2013.2246291

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Fachmedien Wiesbaden GmbH

About this chapter

Cite this chapter

Graichen, M., Nitsch, V., Färber, B. (2018). Analysing Behavioural Data from On-Road Driving Studies: Handling the Challenges of Data Processing. In: Bengler, K., Drüke, J., Hoffmann, S., Manstetten, D., Neukum, A. (eds) UR:BAN Human Factors in Traffic. ATZ/MTZ-Fachbuch. Springer Vieweg, Wiesbaden. https://doi.org/10.1007/978-3-658-15418-9_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-658-15418-9_9

  • Published:

  • Publisher Name: Springer Vieweg, Wiesbaden

  • Print ISBN: 978-3-658-15417-2

  • Online ISBN: 978-3-658-15418-9

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics