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Joint Development of Land Use and Light Rail Stations

Regional Science Association International - The Israeli Section. Joint Development of Land Use and Light Rail Stations. Daniel Shefer, Shlomo Bekhor, Avigail Ferdman Centre for Urban and Regional Studies Transportation Research Institute Technion – Israel Institute of Technology.

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Joint Development of Land Use and Light Rail Stations

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  1. Regional Science Association International -The Israeli Section Joint Development of Land Use and Light Rail Stations Daniel Shefer, Shlomo Bekhor, Avigail Ferdman Centre for Urban and Regional Studies Transportation Research Institute Technion – Israel Institute of Technology The Case of Tel Aviv Beer Sheva University 6/6/04 “New Direction in Urban and Regional Development”

  2. Structure of the presentation • Introduction • Literature Review • Purpose of the Study • Hypotheses • Methodology • Findings • Conclusions

  3. Introduction • The land-use transportation interaction • Empirical evidence of the built environment’s impact on travel demand • Land-use intensification and mixed land uses – their impact on transit use • The role and function of Light Rail Transit - LRT

  4. What can light rail transit do? LRT is perceived as a powerful mode for transferring ridership from private to public transportation at the micro level • Enhancing accessibility • “Getting people out of their cars” at the macro level • Relieving traffic congestion • Reducing emissions • Rejuvenating urban centres • Stimulating economic growth Literature Review

  5. Tel Aviv as a case study Purpose of the study exploring various scenarios of the built environment around planned LRT stations • 1st light rail line in Tel Aviv, due to open in 2010. • Connects 4 major cities • The stations location was based on travel demand Purpose of the Study

  6. The built environment and travel demand Impacts on daily travel demand: • Intensified areas attract trips • Mixed land uses around LRT stations induce transit use and walking/cycling • Trip generation is not affected by land use Hypotheses

  7. Land uses and travel demand Methodology Parameters of land use scenarios: • population densities, • commercial densities, • degree of land use mix • workforce-population ratio

  8. Land Use Scenarios workforce-population ratio Methodology

  9. Alternative scenarios produce differential trip generation demand Trip Generation Findings – trip generation No difference between NTA models & retrofitted models, save for scenario 4

  10. Mixed and intensified land uses attract more trips Trip attraction Findings

  11. Job–population ratios affect home-base-work trips Home-base-work trip attraction Job-population ratio Higher job–population rates – attract more motorized home-base-work trips Scenarios 1-2-3 have a greater concentration of jobs Findings – trip attraction

  12. Intensified commercial areas attract less motorized home-base commuting trips More trip attraction at the outer stations Less trip attraction Findings – trip attraction

  13. Findings Mixed land uses attract more trip chaining Non-home-base trip attraction per workplace

  14. Main findings • Intensified land uses tend to generate more motorized trips per household than mixed land uses or the base scenario • Intensified and mixed land uses attract more trips per worker Findings

  15. Conclusions Alternative land use scenarios generate and attract differential trip rates Mixed land uses are different from intensified land uses, in terms of travel demand High density & mixed land uses can serve as strategic decision variables in locating transit stations Conclusions

  16. Joint Development of Land Use and Light Rail Stations Thank you

  17. Further research • Metropolitan level forecasts • Exploring the most conducive land use mix for lrt ridership - • Before and after lrt introduction • Comparison to other lrt systems • Trip mode share • Exploring station location by trip demand and land use characteristics

  18. Trip generation with same workforce ratio for all the scenarios

  19. Planned LRT red line in Metropolitan Tel Aviv

  20. Differences in population densities

  21. Differences in job densities

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