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Traffic Forecasting Irregularities

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Presentation of traffic forecasting Irregularities found in the Athens metropolitan area in conjuction with the construction of the main motorway of Athens

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Traffic Forecasting Irregularities

  1. 1. 2nd  Interna)onal  Symposium  on  Freeway  and  Tollway  Opera)ons   Honolulu,  Hawaii  –  June  21-­‐24,  2009    Irregulari)es  in  the  output  of  transport   planning  models’  forecasts  for  capital   infrastructure  planning  decisions   C.  Antoniou1,  B.  Psarianos1,  and  W.  Brilon2     1  Na)onal  Technical  University  of  Athens,  Greece   2  Ruhr-­‐University  Bochum,  Germany  
  2. 2. 2nd  Interna)onal  Symposium  on  Freeway  and  Tollway  Opera)ons   Honolulu,  Hawaii  –  June  21-­‐24,  2009       Errors  in     Transporta)on  Planning  Processes  Regarding  Large   Infrastructure  Projects     C.  Antoniou1,  B.  Psarianos1,  and  W.  Brilon2     1  Na)onal  Technical  University  of  Athens,  Greece   2  Ruhr-­‐University  Bochum,  Germany      2 Transporation Planning and Large Infrastructure Projects
  3. 3. Outline   •  Mo)va)on  and  objec)ve   •  Background  and  evidence  from  the  literature   •  Applica)on  in  AUki  Odos  Motorway  (Athens,   Greece)     •  Findings  and  conclusion  3 Transporation Planning and Large Infrastructure Projects
  4. 4. Mo+va+on  Motorway  AUki  Odos  Motorway  Korinthos-­‐Patra  4 Transporation Planning and Large Infrastructure Projects
  5. 5. Mo+va+on   Motorway  AUki  Odos   Motorway  Korinthos-­‐Patra  5 Transporation Planning and Large Infrastructure Projects
  6. 6. Experiences  Source: Halkias, B., Tyrogianni; H.:PPP Projects in Greece: The Case of Attika Tollway, Route-Roads No. 342, 20086 Transporation Planning and Large Infrastructure Projects
  7. 7. Ques+ons   •  Why have the traffic forecasts been so wrong? •  What can we learn from existing experience for future projects?7 Transporation Planning and Large Infrastructure Projects
  8. 8. Ex  ante  -­‐  projec+ons  8 Transporation Planning and Large Infrastructure Projects
  9. 9. Ex  post  -­‐  studies   •  Parthasarathi, Levinson (2009): •  62 % od forecasts were wrong •  Underestimating highway traffic •  Noland (2001): •  Wrong or missing effect of induced traffic •  Flybjerg e.a. (2006): •  Railway projects: 72 % overestimated •  Highway projects: 25 % of cases error > 40 %9 Transporation Planning and Large Infrastructure Projects
  10. 10. %  errors  in  traffic  forecasts  (Flybjerg  et  al.,  2006)     underes)ma)on   overes)ma)on  10 Transporation Planning and Large Infrastructure Projects
  11. 11. Ex  post  -­‐  studies   •  Sammer (2006): •  Inadequate planning methods (practice = state of the art) •  Models are sometimes not understood sufficiently by planners •  Insufficient calibration of parameters and lack of validation •  Point estimation ↔ interval estimation (reliability) •  Wegener & Fuerst (1999): •  Impact of infrastructure on land use11 Transporation Planning and Large Infrastructure Projects
  12. 12. Study  area:  A<ki  Odos  Motorway   65.2 km in length Greece   Opened in full length : 2004 Toll motorway Greater  Athens  Area   1.5km  zone  in  each  side     of  the  motorway  axis  12 Transporation Planning and Large Infrastructure Projects
  13. 13. Study  area:  A<ki  Odos  Motorway   Traffic studies in advance of the project: •  Rather rough analytical data background •  Conventional transport planning methodologies •  Studies were more directed on predicting the toll income than on really expected traffic •  Neglecting of induced traffic13 Transporation Planning and Large Infrastructure Projects
  14. 14. Induced  Traffic   = Traffic which has not been there before the implementation of the new infrastructure 1. kind: traffic generated by the existing land use; the same origins but more distant destinations 2. kind traffic generated by new land use, which is induced by the new infrastructure14 Transporation Planning and Large Infrastructure Projects
  15. 15. Induced  Traffic   = Traffic which has not been there before the implementation of the new infrastructure 1. kind: well treated by adequate transportation traffic modeling 2. kind open question15 Transporation Planning and Large Infrastructure Projects
  16. 16. Case  study:  A<ki  Odos   Determination of modified land use before and after the opening of Attiki Odos Motorway •  Areal photographs •  Interviews Estimation of the number of households within a margin of 1,5 km around the motorway16 Transporation Planning and Large Infrastructure Projects
  17. 17. Case  study:  A<ki  Odos   AUki  Odos  axis   1.5km  zone  limit  17 Transporation Planning and Large Infrastructure Projects
  18. 18. Case   study  results  
  19. 19. Major  Findings   •  Areas  that  were  already  well-­‐built-­‐up  prior  to  the   opera)on  of  AUki  Odos  motorway  show  more   moderate  growth  rates     (s)ll  around  or  even  exceeding  20%  annually     for  a  period  of  8  consecu)ve  years)     •  Areas  that  were  less  developed  and  had  more  room   for  growth  show  annual  growth  rates  exceeding   50%.    19 Transporation Planning and Large Infrastructure Projects
  20. 20. Case  study:  A<ki  Odos   •  For  2000,  the  number  of  households  in  the  influence   zone  in  2000  was  83.802   •  For  2008  the  number  of  households  in  the  influence   zone  (of  1.5km)  grew  up  to       141.038  households.   •  An  annual  increase  in  households  equal  to  8.5%  was   therefore  computed  for  the  en)re  influence  zone.    20 Transporation Planning and Large Infrastructure Projects
  21. 21. Conclusion   •  Considera)on  of  induced  traffic     -­‐1st  and  2nd  kind     is  an  indispensable  element        of  transporta)on  planning          for  large  infrastructure  projects   •  Tradi)onal  aggregated  modeling  frameworks        are  not  longer  a  useful  basis          for  traffic  predic)on            on  large  infrastructure  projects     –  Ac)vity  based  modeling   –  Dealing  with  uncertainty  21 Transporation Planning and Large Infrastructure Projects
  22. 22. Thank  you  for  your  aGen+on  !  22 Transporation Planning and Large Infrastructure Projects
  23. 23. Mo)va)on  •  Traffic  forecasts  are  oaen  underesImaIng     traffic  demand  compared  to  the  actual  traffic  counts      •  An  explana)on  for  the  underes)ma)on  can  be   abributed  to  the  non-­‐incorpora)on  of  induced  traffic   into  the  model  forecas)ng    •  The  gap  between  state-­‐of-­‐the-­‐art  theory  and  pracIce   appears  to  be  widening  •  Problems  include:   –  “black-­‐box”  effect   –  lible  or  no  evidence  for  the  validity  of  the  input  data  used   or  how  the  model  was  calibrated   –  the  results  are  presented  as  point  esImates,  rather  than   interval  es)mates  based  on  a  probability  func)on,  with   confidence  limits  specified  
  24. 24. Objec)ve  •  Provide  insight  into  the  problem  •  Through  analysis  of  one  of  the  aspects   –  Lack  of  adequate  modeling  of  induced  demand  •  By  an  applica)on  in  a  recently  developed   tollway   –  AUki  Odos  Tollway  (Athens,  Greece)  
  25. 25. Stated  causes  of  inaccuracy  (source:  Flybgjerg  et  al.,  2006)    
  26. 26. Case  study:  Overall  methodology  
  27. 27. Main  assump)ons  •  Several  assump)ons  are  required   –  Data  may  be  limited,  unreliable  and/or  difficult  to   obtain  •  Conserva)ve  assump)ons  were  made  that  would   lead  to  an  underes)ma)on  of  the  impacts,  for   example   –  For  a  large  part  of  the  influence  zone  (more  than  half),   in  which  the  changes  were  not  drama)c,  the  number   of  households  was  held  constant     –  For  the  influence  zone,  the  number  of  households  per   building  was  assumed  to  be  constant  (for  the   computa)on  of  the  change  in  the  number  of   households).      

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