GAP ACCEPTANCE STUDY USING VIDEO IMAGE PROCESSING

Site filming and manual videotape recording are one of the common ways of data collection in gap acceptance studies. Tedious and laborious as it is, this manual method is rather inaccurate in time recording. Using a carefully chosen site for investigation, this thesis proposes that it is possible to employ a more automated process to obtain gap information from videotapes by simple Video Image Processing (VIP) software plus intelligent user algorithms for data reduction. This is achieved by the CAMera Data Acquisition System (CAMDAS)----a traffic detection software based on VIP used for vehicle image recognition. The method allows not only the conventional time gap, but also the projected time gap (an intuitively better measure but hardly measurable using conventional techniques) to be successfully extracted. Despite the fact that both additional and lost detection exist in individual presence detection, CAMDAS is able to record similar gap distributions and variances to that acquired manually. By making use of the automated data collection procedure, a large amount of corresponding conventional and projected time gaps are collected. The suitability of the two measures in representing driver gap acceptance behavior is compared based on two criteria: measure consistency and adaptability to different traffic conditions. It is found that projected time gap is more consistent and adaptable.

Author dc:creator

• WANG ZHONGREN