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SUMMARY:Estimating travel times from abundant data
DTSTART:20110414T121500
DTSTAMP:20260510T202328Z
UID:97886d05d228cd187b1a1f4b16f6e0556c0c3c9f4b2487d49c67a7f8
CATEGORIES:Conferences - Seminars
DESCRIPTION:Prof. Dr. Benjamin Heydecker\nContemporary Intelligent Transpo
 rt Systems (ITS) provide abundant data that can be used to monitor\, manag
 e and control transport systems. However\, the quality of the data is in g
 eneral not known and the volume is too great for record-by-record investig
 ation to be a practical proposition. In this seminar\, we will see how sta
 tistical analysis can be applied to filter a dataset by treating it as a w
 hole by fitting a discrete mixture of statistical distributions We then ex
 plore how this reflects on the individual observations. To illustrate use 
 of this approach\, it is applied to a certain dataset of travel times that
  is generated by matching time-stamped records of vehicle registration pla
 tes from automatic number-plate recognition (ANPR) system. Analysis of the
  mixed distribution leads to estimates of the error rate of the data colle
 ction methods\, and by eliminating the corresponding component the travel 
 time distribution can be estimated. This has dual importance: it shows how
  distributions of travel times can be extracted from ITS of this kind to p
 rovide estimates for direct use\, and beyond that it shows how statistical
  analysis can be applied to manage the abundant data streams that we now r
 eceive from ITS.\n\n\n\nAbout the speaker\n\nBenjamin Heydecker is the Hea
 d of Centre for Transport Studies and Professor of Transport Studies at Un
 iversity College\, London. His research lies in developing and applying ma
 thematical and statistical analyses in transport studies. He has pursued t
 his along three broad themes within the field: Traffic management and cont
 rol\, including real-time information and control systems\; Transport safe
 ty\, including the analysis and interpretation of road accident data\; and
  Transport planning methods\, including dynamic transport modelling. The i
 nterrelationships between these themes\, and between each of them and meth
 odologies for estimation\, design and management are of special interest t
 o him. He is a fellow of the Institution of Mathematics and its Applicatio
 ns and of the Royal Statistical Society. Heydecker is involved in the EU F
 P7 Network of Excellence for Advanced Road Cooperative Traffic Management 
 in the Information Society (NEARCTIS)\, where he is investigating the rese
 arch agenda for developments in ITS to promote a wide range of potential b
 enefits.
LOCATION:GC C3 30
STATUS:CONFIRMED
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