Traffic Signal Information in a Real Residential Area

  • Benno Schweiger
  • Regina Glas
  • Christian Raubitschek
  • Johann Schlichter
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 200)


In this study we share an evaluation of measurements performed in a traffic light communication test bed in real life traffic. We describe our hardware and software architecture and present our measurement methods. As a basis for the evaluation, we selected two use cases: Micropause Infotainment and Fuel Efficient Traffic Light Approach. We develop, train and evaluate a model for estimating micropauses at traffic lights and determine the value of predictive traffic light information in terms of fuel efficiency.


Traffic Light Information Micropause Test Bed Uninformed Drivers Signal Phase And Timing (SPAT) 
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.


  1. 1.
    Asadi B, Vahidi A (2010) Predictive cruise control: utilizing upcoming traffic signal information for improving fuel economy and reducing trip time. IEEE Trans Control Syst Technol 19(3):707–714CrossRefGoogle Scholar
  2. 2.
    Schweiger B, Raubitschek C, Bäker B, Schlichter J (2011) ElisaTM—car to infrastructure communication in the field. Comput Netw 55(14):3169–3178Google Scholar
  3. 3.
    Society of Automotive Engineers I (2009) Draft SAE J2735 Dedicated short range communications (DSRC) message set dictionary. ElementsGoogle Scholar
  4. 4.
    DRIVE C2X Consortium (2012) DRIVE C2X—accelerate cooperative mobility. From Accessed July 10, 2012
  5. 5.
    Aktiv Forschungsinitative (2012) aktiv Website. From Accessed July 10, 2012
  6. 6.
    simTD Consortium (2012) simTD Website. From Accessed July 10, 2012
  7. 7.
    Mandava S, Boriboonsomsin K, Barth M (2009) Arterial velocity planning based on traffic signal information under light traffic conditions. In: 12th international IEEE conference on intelligent transportation systems, St. Louis, Mo, pp 160–165Google Scholar
  8. 8.
    Raubitschek C, Schütze N, Kozlov E, Bäker B (2011) Predictive driving strategies under urban conditions for reducing fuel consumption based on vehicle environment information. In: IEEE forum on integrated and sustainable transportation systems 2011. Vienna, AustriaGoogle Scholar
  9. 9.
    Gärtner T (2012) Entwicklung von Strategien zur optimalen Nutzung der Mikropausenassistenz. Diploma Thesis, TU BraunschweigGoogle Scholar
  10. 10.
    BMW Forschung und Technik (2008) KAS—AKTIV communication unit. White Paper. Accessed from
  11. 11.
    Triggs TJ, Harris WG (1982) Reaction time of drivers to road stimuli. Human Factors Report, HFR-12(June)Google Scholar
  12. 12.
    Hoffmann G, Nielsen S-M (1994) Beschreibung von Verkehrsabläufen an signalisierten Knotenpunkten. Typo-Druck & Verlagsgesellschaft, BonnGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Benno Schweiger
    • 1
  • Regina Glas
    • 2
  • Christian Raubitschek
    • 2
  • Johann Schlichter
    • 3
  1. 1.BMW Research and TechnologyMunichGermany
  2. 2.BMW GroupMunichGermany
  3. 3.Technische Universität MünchenMunichGermany

Personalised recommendations