1. 2nd ASIAN EMME/2 USERS CONFERENCE HONG KONG NOVEMBER 2000

2. Authors: Dave McFarlane VKE Engineers Logan Moodley City of Durban Using Emme/2 to assess the Impact of and influence the restructuring of the apartheid city City of Durban

3. Contents 1.Introduction 2.Background 3.Profile of the City 4.Existing Transport System 5.Public Transport Restructuring 6.Emme/2 Model Structure 7.Results 8.Using Emme/2 Model in a Predictive Mode 9.Concluding Remarks

4. b In 1994 first democratic government elected in South Africa Dramatic impact on planningDramatic impact on planning New legislationNew legislation Purpose of paper b To describe the methodology employed in the latest update of the Emme/2 Model The update and methodology has been influenced by political changesThe update and methodology has been influenced by political changes b To demonstrate how the model will be used in influencing major decisions regarding restructuring and integrating the urban form of the city 1. Introduction

5. Locality

6. Locality Africa

7. Locality

8. Locality - City of Durban

9. DURBAN BAY CBD

10. Prior to 1994 Prior to 1994 Six decades of separate development based on race apartheid Six decades of separate development based on race apartheid Different race groups lived in separately demarcated area Different race groups lived in separately demarcated area Distorted spatial structure Distorted spatial structure Poorest away from CBD Poorest away from CBD 2. Background

11. Prior to 1994 Prior to 1994 Duplication of services, public transport, schools, social facilities Duplication of services, public transport, schools, social facilities Emphasis on private transport road building Emphasis on private transport road building Poorest furthest away from the CBD.. But totally reliant on public transport high PT subsidy costs Poorest furthest away from the CBD.. But totally reliant on public transport high PT subsidy costs 2. Background

12. I n d I a n O c e a n INEQUITIES Durban CBD 40 min 25 min 10 min Effects of Apartheid Planning

13. 2. Background Post 1994 New Government New transport legislation New transport legislation regulateregulate improveimprove promotepromote b Steps to restructure cities densify corridors and nodes - achieve economies of scaledensify corridors and nodes - achieve economies of scale infrastructure investment to support corridorsinfrastructure investment to support corridors improve operational performance - tenderingimprove operational performance - tendering b Better integration b Re-calibration of Emme/2 model

14. b Area = 1366 Km 2 b Population = 2,5 million b No. of households= 609 000 b 60% of employment close to CBD 3. Profile of the City b But 30% of employees living close to CBD long travel distances b Modal split = 57% by PT - varies from 100% to 0%

15. b Contributes to 9% of GDP b Port City - one million containers/annum b Other activities tourismtourism commercecommerce subtropical fruitsubtropical fruit sugar canesugar cane motor manufacturingmotor manufacturing agricultureagriculture constructionconstruction 3. Profile of the City

16. 4. Existing Transport System b 1 500 buses, 6000 mini-bus taxis, 450 000 cars b Over the last twenty years there has been a significant shift to mini-bus taxis b Excellent road system - 3 700 km of freeway, arterial and main routes b Modes of transport

17. 4. Existing Transport System b Rail uses old heavy rolling stock b Generally PT system in a poor state b Huge inefficiencies in system mainly due to the distorted spatial structure b Currently PT subsidies - US $58 million/annum b New legislation has been enacted to restructure the PT industry

18. Modes of Transport Congestion - am peak Rail Infrastructure Typical Bus Mini-bus Taxi

19. 5. Public Transport Restructuring b The public transport restructuring main thrust is to establish a least cost network with optimal modes on the main corridors reduce burden on subsidy b Leads to a more efficient and sustainable system b Supply and demand data surveyed on all public transport modes

20. 5. Public Transport Restructuring b Basis for PT O-D matrix b High priority public transport network output Rail emphasis b O-D information plus high priority public transport network Emme/2 model

21. 6. Emme/2 Model Structure b b NETWORK 3 712 km of roadway3 712 km of roadway 406 km of rail406 km of rail 330 zones (316 internal, 14 external)330 zones (316 internal, 14 external) Annotation files imported from GIS databaseAnnotation files imported from GIS database

22. Emme/2 BaseNetwork I n d I a n O c e a n Durban CBD

23. 6. Emme/2 Model Structure DEMOGRAPHICS b 1996 census data Employment and car ownership - separate sourcesEmployment and car ownership - separate sources Prior to 1996 data collected by race and model structured by race e.g. WHBW, BHBWPrior to 1996 data collected by race and model structured by race e.g. WHBW, BHBW Since 1996 data collected by income group - high, medium, lowSince 1996 data collected by income group - high, medium, low Income grouping used as a proxy for car ownership and hence PT usageIncome grouping used as a proxy for car ownership and hence PT usage This change necessitated a rethink in the structure of the modelThis change necessitated a rethink in the structure of the model

24. 6. Emme/2 Model Structure Detail is lostDetail is lost Required simplification in trip generation and trip distribution models in order to cater for changesRequired simplification in trip generation and trip distribution models in order to cater for changes Typical screenlineTypical screenline DEMOGRAPHICS

25. 6. Emme/2 Model Structure b Racial classification Income classification b Existing parameters as far as possible b Simplify model b Census data : High income R72 000/annumHigh income R72 000/annum Medium Income R 30 000 - R72 000/annumMedium Income R 30 000 - R72 000/annum Low income R0 - R30 000/annumLow income R0 - R30 000/annum b Why income classification ? Trip generation incomeTrip generation income Car usage incomeCar usage income Improved distribution of HBW tripsImproved distribution of HBW trips TRIP GENERATION - OVERALL APPROACH

26. TRIP GENERATION EQUATIONS HOME BASED WORK (HBW) TRIPS - 2 HOUR AM PEAK Productions= 0.60 * Employed residents Attractions= 0.60 * Employment NON-WORK (NW) TRIPS - 2 HOUR AM PEAK Productions= 0.05 * (L.Pop+M.Pop + (1.50*H.Pop)) + 0.05*(L.Emp + (2.0*M.Emp) + (4.0*H.Emp)) + 0.05*(L.Emp + (2.0*M.Emp) + (4.0*H.Emp)) Attractions = (0.008 * L.Pop) + (0.024*M.Pop) + (0.039*H.Pop) (Activity zones) +( 0.591*M.Emp) + (1.182*H.Emp) Attractions= (0.008 * L.Pop) + (0.024*M.Pop) + (0.039*H.Pop) (Other zones) +( 0.117*M.Emp) + (0.234*H.Emp) TRUCK TRIPS Productions= (0.04*H.Emp) + (0.1*M.Emp) Attractions= (0.05*H.Emp) + (0.07*M.Emp) + (0.007*L. Emp) 6. Emme/2 Model Structure

27. b High correlation income and car ownership b Modal split at origins based on graphs MODAL SPLIT 6. Emme/2 Model Structure b Four modes - auto, rail, bus, mini-bus taxi Auxillary transit mode - walk Auxillary transit mode - walk

28. Modal Split Curve (HBW Trips) b

29. Modal Split Curve (NW Trips)

30. TRIP DISTRIBUTION b Develop cost matrices –Car > Travel time matrix –PT > Cost of travel b Both generated in previous assignment b Intra-zonal costs added to each matrix b The PT trip cost was refined further : –Determine transposed matrix –Determine minimum of original and transposed matrices –This compensated for off peak direction costs 6. Emme/2 Model Structure

31. TRIP DISTRIBUTION b Simple gravity model deterrence function applied to these times/costs : F(c) = exp(-c* ) b Separate beta value, impedance matrices used for PT and cars b Distribution undertaken for four trip types –HBW - low income –HBW - medium income –HBW - high income –NW trips 6. Emme/2 Model Structure

32. TRIP DISTRIBUTION b Distribution Method –Two dimensional matrix with two input origin matrices (car and PT) and a single destination matrix –Model distributes trips based on the deterrence matrices and relative attractiveness of car/PT for each destination –Use of INRO macro - BALMPROD.MAC –Output eight matrices (4 car, 4 PT), combined into two matrices (car, PT), for assignment 6. Emme/2 Model Structure

33. CALIBRATION PROCESS b Iterative process TG, MS, TD, Ass b Emphasis in TD phase b Three tools used in the calibration process : 1. value is inverse of the average (weighted ) cost value 2. Three dimensional balancing with Emme/2 origin totals origin totals destination totals destination totals trips crossing screenlines - 11 in total trips crossing screenlines - 11 in total 6. Emme/2 Model Structure

34. CALIBRATION PROCESS this whole process was automated for the 11 screenlines for car and PT this whole process was automated for the 11 screenlines for car and PT results of the 1st 3-D balance using the first screenline was passed onto the second and so forth results of the 1st 3-D balance using the first screenline was passed onto the second and so forth origins kept same, destinations modified origins kept same, destinations modified 3. DEMANDJ.MAC - adjustment of demand matrix based on counts (for comparison/calibration purposes only) final matrices used in assignment not adjusted in this way final matrices used in assignment not adjusted in this way 6. Emme/2 Model Structure

35. Calibration Process

36. ASSIGNMENT b Car assignment first with PT lines pre-loaded as Pcu value b PT assignment run second, speed of road based PT a function of car assignment speeds 6. Emme/2 Model Structure

37. 7. Results b Reasonably good results Cars 174 link counts R 2 = 0.921 Cars 174 link counts R 2 = 0.921 Public Transport 22 screenlines R 2 = 0.984 Public Transport 22 screenlines R 2 = 0.984 Public Transport (buses) 22 screenlines Public Transport (buses) 22 screenlines R 2 = 0.890 Public Transport (mini-bus taxi) 22 screenlines R 2 = 0.826 Public Transport (mini-bus taxi) 22 screenlines R 2 = 0.826 Public Transport (rail) 22 screenlines R 2 = 0.950 Public Transport (rail) 22 screenlines R 2 = 0.950

38. Public Transport at Screenlines

39. Link Scattergram

40. 8. Using Emme/2 in a Predictive Mode b Simulate future scenarios b Simple trend projections to various intervention policies b Emphasis on public transport enhancement b Main areas of influence influencing abnormal trip length frequency distribution (travel distances)influencing abnormal trip length frequency distribution (travel distances) by incorporating land use strategiesby incorporating land use strategies bottleneck eliminationbottleneck elimination

41. 8. Using Emme/2 in a Predictive Mode TDM measuresTDM measures rationalising PT network - using operating costs and fare income as a measure of improvementrationalising PT network - using operating costs and fare income as a measure of improvement Use of PT 57% now 80% target Refinement and Extension of PT network Future demographics 2.6m - 2.9m AIDS

42. Existing Trip Length Frequency Distribution

43. Preferred Trip Length Frequency Distribution

44. I n d I a n O c e a n Durban CBD Proposed Nodes and Corridors City of Durban

45. 9. Concluding Remarks b Use of Emme/2 has been the backbone in terms of determining the HPPTN b Model simplified to replicate current transport situation b In a firm position to test land use strategies b In a position to influence outcomes b Monitoring of particular parameters within Emme/2 is now easily achievable b Main tool in developing long range and short term plans for the City

46. City of Durban