TRIP GENERATION.

Presentasi berjudul: "TRIP GENERATION."— Transcript presentasi:

1 TRIP GENERATION

2 The Conventional “Four Step” Modelling Process Hutchinson, 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

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5 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.

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12 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.

13 TRIP-END DEFINITIONS [Tamin, Ofyar Z, 2000]

14 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

15 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

16 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.

17 Alur Pemodelan Regresi:

18 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.

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

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 Regression Models:

30 Regression Models:

31 Regression Models:

32 Regression Models:

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34 Regression Models:

35 Regression Models:

36 Regression Models:

37 Pearson Correlation Matrix:
Y X1 X2 X3 X4 1,00 0,32 0,92 0,95 0,62 0,25 0,19 0,03 0,99 0,29 0,33

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

39 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.

40 TRIP-RATE Analysis [Tamin, Ofyar Z, 2000]

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

42 TRIP-RATE Analysis [Tamin, Ofyar Z, 2000]

43 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.

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

45 Trip Rates obtained from previous Matrix

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

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

48 TRIP GENERATION