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
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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
                                                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