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Regional longitudinal travel demand surveys - profiting from synergies

Regional longitudinal travel demand surveys - profiting from synergies. Tobias Kuhnimhof Bastian Chlond Institute for Transport Studies University Karlsruhe. Agenda. Need for regional travel demand data Brief overview MOP Regional longitudinal surveys Methodology Challenges

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Regional longitudinal travel demand surveys - profiting from synergies

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  1. Regional longitudinal travel demand surveys - profiting from synergies Tobias Kuhnimhof Bastian Chlond Institute for Transport Studies University Karlsruhe

  2. Agenda • Need for regional travel demand data • Brief overview MOP • Regional longitudinal surveys • Methodology • Challenges • Chances • Possibilities for data pooling • First results from pilot survey

  3. Travel demand in Germany – stagnation and heterogeneity • Economy & Demographie  stagnation of travel demand • economic and demographic diverse development  supposedly regionally heterogeneous development of trvel demand MOP since 1994

  4. Projected regional travel demand surveys Frankfurt Region: Population: 4.1 Mio Municipalities: 300 Completed pilot survey, Panel survey projected Mannheim Region: Population: 2.4 Mio Municipalities: 290 Survey projected for fall 07 Stuttgart Region: Population: 2.7 Mio Municipalities: 180 Survey projected for fall 07

  5. Year 2 Year 3 MOP Survey Design The MOP-survey: 7-day mobility diary in 3 consecutive years since 1994 Year 1

  6. MOP survey design • The cohorts in the MOP survey ~ 200 ~ 250 ~ 350 ~ 800 year n-2 year n-1 year n+1 year n+2 year n

  7. MOP Sample since 1994

  8. Regional longitudinal surveys - methodology • Design of regional panel survey analogues to MOP • Same trip diary and other survey material • Geocoding • Similar recruitment procedure

  9. Regional longitudinal surveys - challenges and chances • Sample Size Problem • Regional surveys require sample sizes similar to national surveys • Regions can not afford these sample sizes • Regions expect immediate use of data • specific problems to solve • But: Panel surveys need time to “mature” • Need to feed survey results in regional demand models • Large data set (MOP) with similar survey design available •  Possibilities to pool data

  10. Regional travel demand panel Continuous MOP survey Possible methods of data pooling • Data availability – cohorts in regional and MOP survey year n-2 year n-1 year n+1 year n+2 year n

  11. data from the specific study region • Data from other regions in Germany that are comparable with the study region e.g.: • commuting distances • economic development • spatial structure Possible methods of data pooling MOP sample Regional survey sample • Data availability year n-3 year n-2 year n-1 year n year n+1 year n+2 year n+3 ~ 1.800 Pper year ~ 900 – 1.500 Pper year

  12. Possible methods of data pooling Total analysis sample MOP sample Regional survey sample • Cross-sectional analysis sample for use data in first survey year year n-3 year n-2 year n-1 year n

  13. Possible methods of data pooling Total analysis sample MOP sample Regional survey sample • Cross-sectional analysis sample for use data in first survey year year n-3 year n-2 year n-1 year n

  14. Possible methods of data pooling Total analysis sample MOP sample Regional survey sample • Annual analysis sample for monitoring development year n-3 year n-2 year n-1 year n year n+1 year n+2 year n+3

  15. Possible methods of data pooling Total analysis sample MOP sample Regional survey sample • Annual analysis sample for monitoring development year n-3 year n-2 year n-1 year n year n+1 year n+2 year n+3

  16. Possible methods of data pooling Total analysis sample MOP sample Regional survey sample • Annual analysis sample - mixing pooling methods year n-3 year n-2 year n-1 year n year n+1 year n+2 year n+3

  17. First results from small pilot survey • Small pilot survey carried out in Frankfurt region • Objective: Test different recruitment methods applicable to regional context • Sampling method: Random selection from phone book / address book

  18. First results from small pilot survey • Sample size: • Regional pilot survey: 176 HH / 7.688 Trips • MOP data from Frankfurt study region (95-05): 426 HH / 16.533 Trips • Mobility figures

  19. Conclusions • The need for regional travel demand data exists • The availability of data with same design enables a number of data pooling methods •  increasing regional sample size •  enabling data analysis from the first year on • Encouraging results from pilot survey • The MOP method can be applied at regional level with minor adaptations in recruitment process • Thank you very much for your attention

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