Objectives
- To develop a new approach for measuring congestion relief impacts of public transport
- To explore the congestion relief impacts of public transport in world cities
- To examine the relationship between public transport congestion relief and various urban and transport characteristics of cities.
Method
- Use of existing dataset covering 60 world cities to estimate key travel characteristics with and without public transport
- Regression analysis of elements of urban and transport characteristics that influence public transport congestion relief.
Key results
Hong Kong, Moscow and Cracow have the highest levels of public transport congestion relief.
Table 1 Ranking of cities in terms of congestion relief impacts of public transport
| 1. Hong Kong |
| 2. Moscow |
| 3. Cracow |
| 4. Tokyo |
| 5. Osaka |
| 6. Prague |
| 7. Budapest |
| 8. Singapore |
| 9. Barcelona |
| 10. Rome |
| 11. Berlin |
| 12. London |
| 13. Munich |
| 14. Vienna |
| 15. Sapporo |
| 16. Berne |
| 17. Milan |
| 18. Helsinki |
| 19. Paris |
| 20. Zurich |
| 21. Brussels |
| 22. Graz |
| 23. Stockholm |
| 24. Madrid |
| 25. Athens |
| 26. Hamburg |
| 27. Amsterdam |
| 28. Newcastle |
| 29. Frankfurt |
| 30. Stuttgart |
| 31. Copenhagen |
| 32. Dusseldorf |
| 33. Marseille |
| 34. Oslo |
| 35. Sydney |
| 36. Nantes |
| 37. Manchester |
| 38. Ruhr |
| 39. Geneva |
| 40. Bologna |
| 41. Montreal |
| 42. Glasgow |
| 43. New York |
| 44. Lyon |
| 45. Toronto |
| 46. Ottawa |
| 47. Melbourne |
| 48. Vancouver |
| 49. Calgary |
| 50. Brisbane |
| 51. Perth |
| 52. Washington |
| 53. Chicago |
| 54. San Francisco |
| 55. Los Angeles |
| 56. Denver |
| 57. Atlanta |
| 58. San Diego |
| 59. Phoenix |
| 60. Houston |
Source: Aftabuzzaman et al. (2010)
- Hong Kong, Moscow and Cracow have the highest levels of public transport congestion relief, while San Diego, Phoenix and Houston have the lowest levels of congestion relief
- Three key dimensions were found to positively influence public transport congestion relief: (1) transit-orientation factors, (2) car-deterrence factors, and (3) urban form factors
- The new approach provides insight to the congestion relief impacts of public transport systems without the need for comprehensive modelling.
Research Papers
Aftabuzzaman, M., Currie, G. & Sarvi, M. (2010) Exploring the underlying dimensions of elements affecting traffic congestion relief impact of transit. Cities, Vol. 28, pp. 36-44.
Aftabuzzaman, M., Currie, G. & Sarvi, M. (2010) Evaluating the congestion relief impacts of public transport in monetary terms, Europe and the US. Journal of Public Transportation, Vol. 13, No. 1, pp. 1-24.
Nguyen-Phuoc, D.Q., Currie, G. & Young, W. (2015) Public Transport Congestion Relief Measurement – A New Framework and Its Impacts. Presented at the 37th Australasian Transport Research Forum (ATRF), Sydney, Australia.