Parallel Traffic Micro-Simulation by Cellular Automata and Application for Large Scale Transportation Modeling

Details

• Creators:
  Nagel, Kai ; Barrett, Christopher L. ; Rickert, Marcus
• Corporate Creators:
  Los Alamos National Laboratory
• Corporate Contributors:
  United States. Federal Highway Administration ; United States. Department of Transportation. Bureau of Transportation Statistics ; United States. Federal Transit Administration ; United States. Environmental Protection Agency ; Travel Model Improvement Program (U.S.)
• Subject/TRT Terms:
  • Traffic simulation
  • Microsimulation
  • Traffic models
  • Cellular automata
  • Networks
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States
• Corporate Publisher:
  United States. Department of Transportation. Federal Highway Administration
• Abstract:
  A set of very simple driving rules for single lane roadway traffic gives surprisingly realistic results. This observation can be backed up by theory, showing relations both to fluid-dynamical models for traffic, and to control system approaches to driving. Extensions to multi-lane traffic are straightforward and work well. Because of its simplicity, it is easy to implement the model on supercomputers (vectorizing and parallel), where we have achieved real time limits of more than 4 million kilometers (or more than 53 million vehicle sec/sec). The model can be used for applications where both high simulation speed ad individual vehicle resolution are needed. We describe results of freeway network simulations of the German land Northrhine-Westfalia, where drivers have individual route plans which they adapt according to the delays they experience. Finally, we discuss the TRANSIMS microsimulation design, where such a simple high-speed microsimulation will be used s one microsimulation option.
• Format:
  PDF
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/57245/dot_57245_DS1.pdf
• File Type:
  [PDF - 1.74 MB]
• Collection(s):
  Federal Highway Administration
• Main Document Checksum:
  urn:sha-512:f225ff29aebe1dfeaf39cb46eb7d026c7a7dcb92af80c0cf4bc9d553bb919a4f64eb91e927ec9ddca7518970e025b132d7c89936d6cf2e7e4d19b9a208a3440c