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Introducing Road Surface Conditions into a Microscopic Traffic Simulation

15 pagesPublished: August 13, 2019

Abstract

The introduction of highly automated driving functions is one of the main research and development efforts in the automotive industry worldwide. In the early stages of the development process, suppliers and manufacturers often wonder whether and to what extend the potential of the systems under development can be estimated in a cheap and timely manner. In the context of a current research project, a sensor system for the detection of the road surface condition is to be developed and it is to be investigated how such a system can be used to improve higher level driving functions. This paper presents how road surface conditions are introduced in various elements of the microscopic traffic simulation such as the actual network, the network editor, a device for detection, and an adaptation of the standard Krauß car following model. It is also shown how the adaptations can subsequently affect traffic scenarios. Furthermore, a summary is given how this preliminary work integrates into the larger scope of using SUMO as a tool in the process of analyzing the effectiveness of a road surface condition sensor.

Keyphrases: driver model, road surface conditions, traffic simulation

In: Melanie Weber, Laura Bieker-Walz, Robert Hilbrich and Michael Behrisch (editors). SUMO User Conference 2019, vol 62, pages 172-186.

BibTeX entry
@inproceedings{SUMO2019:Introducing_Road_Surface_Conditions,
  author    = {Thomas Weber and Patrick Driesch and Dieter Schramm},
  title     = {Introducing Road Surface Conditions into a Microscopic Traffic Simulation},
  booktitle = {SUMO User Conference 2019},
  editor    = {Melanie Weber and Laura Bieker-Walz and Robert Hilbrich and Michael Behrisch},
  series    = {EPiC Series in Computing},
  volume    = {62},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-7340},
  url       = {/publications/paper/3S4X},
  doi       = {10.29007/cqps},
  pages     = {172-186},
  year      = {2019}}
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