A Strategic Approach to Intelligent Functions in Vehicles


Intelligent vehicles can make road traffic safer, more efficient, and cleaner. We provide an overview of current and emerging intelligent functions in vehicles. We focus on intelligent functions that actively interfere with the task of driving a vehicle. We give a classification based on the driving task, the type of road, and the level of support. We give a review of route guidance systems, advanced driver assistance systems, as well as automated vehicles. We discuss the non-technological issues that need to be addressed for the successful deployment of intelligent vehicles, such as cooperation between industry and public authorities, increasing awareness amongst stakeholders, research and development, and legal framework. Finally, we introduce the subjects that will be addressed in the remainder of this section.


Traffic Safety Automate Driving Adaptive Cruise Control Driver Assistance System Intelligent Vehicle 
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. Ehmanns D, Spannheimer H (2003) Roadmap, Deliverable D2D of the European project ADASE- II (IST-2000-28010)Google Scholar
  2. Kulmala R (2010) Ex-ante assessment of the safety effects of intelligent transport systems. Accid Anal Prev 42:1359–1369. doi:10.1016/j.aap. 2010.03.001CrossRefGoogle Scholar
  3. Lee J, Park B (2008) Evaluation of vehicle infrastructure integration (VII) based route guidance strategies under incident conditions. In: Proceedings of the 87th TRB 2008 annual meeting, Washington, DCGoogle Scholar
  4. Michon JA (1985) A critical view of driver behavior models: What do we know, what should we do? In: Evans L, Schwing RC (eds) Human behavior and traffic safety. Plenum, New YorkGoogle Scholar
  5. RESPONSE 3 (2006) D11.2 Code of practice for the design and evaluation of ADAS, Deliverable RESPONSE3 subproject V3.0, 31.10.2006. www.prevent-ip.org, Accessed 27 Dec 2010
  6. van Driel CJG, Hoedemaeker M, van Arem B (2007) Impacts of a congestion assistant on driving behaviour and acceptance using a driving simulator. Transp Res F 10(2):139–152CrossRefGoogle Scholar
  7. van Driel CJG, van Arem B (2005) Investigation of user needs for driver assistance: results of an Internet questionnaire. Eur J Transp Infrastruct Res 5(4):297–316Google Scholar
  8. van Driel CJG, van Arem B (2010) The impact of a congestion assistant on traffic flow efficiency and safety in congested traffic caused by a lane drop. J Intell Transp Syst: Technol Plann Operat 14(4):197–208Google Scholar

Copyright information

© Springer-Verlag London Ltd. 2012

Authors and Affiliations

  1. 1.Civil Engineering and Geoscience Transport & PlanningDelft University of TechnologyDelftThe Netherlands

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