Environmental-sensitive Generation of Street Networks for Traffic Simulations

Manuel Lindorfer, Christian Backfrieder, Christoph Kieslich, Jens Krösche, Gerald Ostermayer

Research output: Chapter in Book/Report/Conference proceedingsConference contribution

5 Citations (Scopus)

Abstract

Traffic simulations aim to reveal the bottlenecks in street networks in order to find ways to improve the network structure in terms of traffic density or occupancy rates. Simulating traffic on real-world road networks is one possibility to expose weaknesses in existing network structures, however it's not always the real-world road networks which are of interest to traffic planners. Virtual road networks have gained importance since they allow to create scenarios which are not easily re-adjustable in the real world. We provide a mechanism to generate such virtual road networks in order to investigate how e.g. different road patterns affect the development of traffic congestions or traffic behavior in general. We use an environmental-sensitive Linden Mayer System for the generation of virtual road networks which allows us to actively interfere the network generation process by changing the system's environment. Our system automatically detects illegal areas within the environment such as forestal areas or river courses and adjusts the structure of the generated road network so that it fits into the environment.

Original languageEnglish
Title of host publicationProc. of the 7th European Symposium on Computer Modeling and Simulation, Manchester
Pages457-462
Number of pages6
DOIs
Publication statusPublished - 2013
Event7th European Symposium on Computer Modeling and Simulation - Manchester, United Kingdom
Duration: 20 Nov 201322 Nov 2013

Workshop

Workshop7th European Symposium on Computer Modeling and Simulation
Country/TerritoryUnited Kingdom
CityManchester
Period20.11.201322.11.2013

Keywords

  • L-System
  • street modeling
  • street networks
  • traffic simulation

Fingerprint

Dive into the research topics of 'Environmental-sensitive Generation of Street Networks for Traffic Simulations'. Together they form a unique fingerprint.

Cite this