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picture1_Planning Ppt 69899 | Macro Transportation Modelling In Ethekwini


 223x       Filetype PPTX       File size 2.47 MB       Source: www.satc.org.za


File: Planning Ppt 69899 | Macro Transportation Modelling In Ethekwini
contents introduction background macro modeling in ethekwini data required review of the various plans key findings emanating from past plans implementation of the plans how has modeling influenced the landscape ...

icon picture PPTX Filetype Power Point PPTX | Posted on 29 Aug 2022 | 3 years ago
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                 CONTENTS
   • Introduction
   • Background
   • Macro modeling in eThekwini
   • Data required
   • Review of the various plans
   • Key findings emanating from past plans
   • Implementation of the plans
   • How has modeling influenced the landscape of SA cities
   • Future predictions
   • Conclusions
   • Recommendations
               INTRODUCTION
 • eThekwini has been at the forefront of transportation planning and macro 
  modeling has been underpinning much of the work
 • Paper explores the journey of transportation planning -highlighting the traffic 
  predictions
 • Commentary on the accuracy of the predictions, challenges and key 
  opportunities
 • Journey has been influenced by the political landscape , mode choice and 
  technology
 • Future landscape explored
                                                 INTRODUCTION
                                                       population grown fivefold 
                                                       to about 3.6 m
                               Shape and size of 
                               the city has grown                                Large volumes of data
                                           2
                               from 800 km  to 2200 
                                km2
                                                                                            C
                                                                                             i
                                                                                              t
                                                                                               y i
                                                                                                 n
                                                                                                   bet
                                                         Better prediction of                         te
                                                                                                       r
                                                                                                         po
                                                                                                           si
                                                                                                             t
                                                         traffic                                             io
                                                                                                               n to
                                                                                                                    
                             Many models developed                                     p
                                                                                         re
                                                                                           pa
                                                                                             r
                                                                                       a      e 
                                                                                        n       s
                                                                                         d       ho
                                                                                           l       r
                                                                                           o        t,
                                                                                            ng        m
                                                                                                ra     e
                                                                                                 n       d
                                                                                                          i
                                                                                                   g      u
                                                                                                    e       m 
                                                                                                      pl
                                                                                                       a
                                                                                                         ns
                 CONTENTS
   • Introduction
   • Background
   • Macro modeling in eThekwini
   • Data required
   • Review of the various plans
   • Key findings emanating from past plans
   • Implementation of the plans
   • How has modeling influenced the landscape of SA cities
   • Future predictions
   • Conclusions
   • Recommendations
                                                BACKGROUND
  • Transportation and City Development
  • Former Durban City boundary 
     transformed
        •   800 to 2500 km2
  • Political changes since 1994
  • Consolidation of  25 smaller local 
     authorities
  • Dramatic impact on service delivery – 
     low pop densities and underserviced 
     areas
  • Transport sector transition has been 
     seamless
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...Contents introduction background macro modeling in ethekwini data required review of the various plans key findings emanating from past implementation how has influenced landscape sa cities future predictions conclusions recommendations been at forefront transportation planning and underpinning much work paper explores journey highlighting traffic commentary on accuracy challenges opportunities by political mode choice technology explored population grown fivefold to about m shape size city large volumes km c i t y n bet better prediction te r po si io many models developed p re pa a e s d ho l o ng ra g u pl ns development former durban boundary transformed changes since consolidation smaller local authorities dramatic impact service delivery low pop densities underserviced areas transport sector transition seamless...

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