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TRIP GENERATION

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  1. TRIP GENERATION

  2. The Conventional “Four Step” Modelling ProcessHutchinson, 1973 • Shall I travel somewhere? • The Trip Generation Step • Where shall I go? • The Trip Distribution Step • Which mode of transport shall I use? • The Modal Choice Step • Which route shall I take? • The Traffic Assignment Step

  3. 4 Tipe Pergerakan • Eksternal  Eksternal, zona asal dan tujuan berada diluar daerah kajian; • Internal  Internal, salah satu zona asa atau tujuan berada diluar daerah kajian; • Internal  Internal, zona asal dan tujuan berada didalam daerah kajian; • Intrazona, zona asal dan tujuan berada didalam satu zona tertentu.

  4. Model Bangkitan Pergerakan • Tujuan  menghasilkan model hubungan yang mengaitkan parameter fungsi lahan dengan jumlah pergerakan yang menuju dan meninggalkan suatu zona • Zona asal dan tujuan pergerakan biasanya dikenal dengan istilah TRIP END • Menggunakan data berbasis zona untuk memodelkan besarnya pergerakan yang terjadi.

  5. TRIP-END DEFINITIONS[Tamin, Ofyar Z, 2000]

  6. TRIP-END DEFINITIONS[Papacostas & Prevedouros, 1993] Zone j Zone i Two trip ends; one origin and one destination, or two attractions Two trip ends; one origin and one destination, or two productions

  7. Klasifikasi Pergerakan Berdasarkan: • Tujuan • Kerja, sekolah, belanja, rekreasi • Waktu • Pagi, siang, dan sore hari • Karakteristik Individu • Tingkat pendapatan, pemilikan kendaraan, ukuran dan struktur rumah tangga

  8. Faktor yang Mempengaruhi: • Bangkitan Pergerakan untuk Manusia • Pendapatan, pemilikan kendaraan, ukuran & struktur rumah tangga, nilai lahan, kepadatan penduduk, aksesibilitas. • Tarikan Pergerakan untuk Manusia • Luas lantai kegiatan, jumlah lapangan pekerjaan, aksesibilitas. • Bangkitan dan Tarikan Pergerakan untuk Barang • Jumlah lapangan pekerjaan, jumlah tempat pemasaran, luas lahan industri.

  9. Alur Pemodelan Regresi:

  10. The selected explanatory variables: • Must be linearly related to the dependent variable, • Must be highly correlated with the dependent variable, • Must not be highly correlated between themselves, • Must lend themselves to relatively easy projection.

  11. Regression Models: Simple Y = a + bX Linear Y = a + bX REGRESSION Multiple Y = a + b1X1 + … + bnXn Non-Linear Y = a + bx + cx2 Y = aXb

  12. Regression Models:

  13. Regression Models:

  14. Regression Models:

  15. Regression Models:

  16. Regression Models:

  17. Regression Models:

  18. Regression Models:

  19. Regression Models:

  20. Regression Models:

  21. Regression Models:

  22. Regression Models:

  23. Regression Models:

  24. Regression Models:

  25. Regression Models:

  26. Regression Models:

  27. Regression Models:

  28. Regression Models:

  29. Pearson Correlation Matrix:

  30. Alternative Regression Models: • Y = a0 + a2X2 • Y = b0 + b3X3 • Y = c0 + c4X4 • Y = d0 + d2X2 + d4X4 • Y = e0 + e3X3 + e4X4

  31. TRIP-RATE Analysis [Papacostas & Prevedouros, 1993] Trip-rate analysis refers to several models that are based on the determination of the average trip production or trip attraction rates associated with the important trip generators within the region.

  32. TRIP-RATE Analysis [Tamin, Ofyar Z, 2000]

  33. TRIP-RATE Analysis [Tamin, Ofyar Z, 2000] Perkantoran  42.250m2 , Pertokoan  30.250m2 , Hotel 16.200m2

  34. TRIP-RATE Analysis [Tamin, Ofyar Z, 2000]

  35. Cross-Classification Models [Papacostas & Prevedouros, 1993] Cross-classification (or category analysis) models may be thought of as extensions of the simple trip-rate models. Although they can be calibrated as area- or zone-based models, in trip-generation studies they are almost exclusively used as disaggregate models.

  36. Number of Trips per Household Size by Auto Ownership obtained from Regional Study

  37. Trip Rates obtained from previous Matrix

  38. Forecast Number of Household in Study Zone by Auto Ownership and Household Size

  39. Forecast Number of Trips in Zone determined by multiplying Trip Rates by number of Households in category

  40. TRIP GENERATION