Vision-based nighttime vehicle detection and range estimation for driver assistance

Yen Lin Chen*, Chuan Tsai Lin, Chung Jui Fan, Chih Ming Hsieh, Bing-Fei Wu

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

21 Scopus citations


This paper presents a real-time vision system for assisting driver during nighttime driving. The proposed system provides the following features: 1) Effectively detection and tracking of oncoming and preceding vehicles based on image segmentation and pattern analysis techniques. 2) Robust and adaptive vehicle detection under various illuminated conditions at nighttime urban environments benefited by a novel automatic object segmentation scheme. 3) Providing beneficial information for assisting the driver to perceive surrounding traffic conditions outside the car during nighttime driving. 4) Providing a versatile control strategy for in-vehicle facilities of the autonomous vehicles. 5) Offering real-time traffic event-driven video surveillance machinery for recording evidences of possible traffic accidents. Experimental results demonstrate the feasibility and effectiveness of the proposed system on nighttime driver assistance issues.

Original languageAmerican English
Article number4811753
Pages (from-to)2988-2993
Number of pages6
JournalConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
StatePublished - 1 Dec 2008
Event2008 IEEE International Conference on Systems, Man and Cybernetics, SMC 2008 - Singapore, Singapore
Duration: 12 Oct 200815 Oct 2008


  • Autonomous vehicles
  • Driver assistance
  • Image segmentation
  • Nighttime driving
  • Vehicle detection


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