8908

A multi-lane traffic simulation model via continuous cellular automata

Emanuele Rodaro, Oznur Yeldan
Centro de Matematica, Faculdade de Ciencias, Universidade do Porto, R. Campo Alegre 687, 4169-007 Porto, Portugal
arXiv:1302.0488 [cs.MA], (3 Feb 2013)
@article{2013arXiv1302.0488R,

   author={Rodaro}, E. and {Yeldan}, {"O}.},

   title={"{A multi-lane traffic simulation model via continuous cellular automata}"},

   journal={ArXiv e-prints},

   archivePrefix={"arXiv"},

   eprint={1302.0488},

   primaryClass={"cs.MA"},

   keywords={Computer Science – Multiagent Systems, Nonlinear Sciences – Cellular Automata and Lattice Gases},

   year={2013},

   month={feb},

   adsurl={http://adsabs.harvard.edu/abs/2013arXiv1302.0488R},

   adsnote={Provided by the SAO/NASA Astrophysics Data System}

}

Traffic models based on cellular automata have high computational efficiency because of their simplicity in describing unrealistic vehicular behavior and the versatility of cellular automata to be implemented on parallel processing. On the other hand, the other microscopic traffic models such as car-following models are computationally more expensive, but they have more realistic driver behaviors and detailed vehicle characteristics. We propose a new class between these two categories, defining a traffic model based on continuous cellular automata where we combine the efficiency of cellular automata models with the accuracy of the other microscopic models. More precisely, we introduce a stochastic cellular automata traffic model in which the space is not coarse-grain but continuous. The continuity also allows us to embed a multi-agent fuzzy system proposed to handle uncertainties in decision making on road traffic. Therefore, we simulate different driver behaviors and study the effect of various compositions of vehicles within the traffic stream from the macroscopic point of view. The experimental results show that our model is able to reproduce the typical traffic flow phenomena showing a variety of effects due to the heterogeneity of traffic.
VN:F [1.9.22_1171]
Rating: 0.0/5 (0 votes cast)

* * *

* * *

Like us on Facebook

HGPU group

194 people like HGPU on Facebook

Follow us on Twitter

HGPU group

1330 peoples are following HGPU @twitter

* * *

Free GPU computing nodes at hgpu.org

Registered users can now run their OpenCL application at hgpu.org. We provide 1 minute of computer time per each run on two nodes with two AMD and one nVidia graphics processing units, correspondingly. There are no restrictions on the number of starts.

The platforms are

Node 1
  • GPU device 0: AMD/ATI Radeon HD 5870 2GB, 850MHz
  • GPU device 1: AMD/ATI Radeon HD 6970 2GB, 880MHz
  • CPU: AMD Phenom II X6 @ 2.8GHz 1055T
  • RAM: 12GB
  • OS: OpenSUSE 13.1
  • SDK: AMD APP SDK 2.9
Node 2
  • GPU device 0: AMD/ATI Radeon HD 7970 3GB, 1000MHz
  • GPU device 1: nVidia GeForce GTX 560 Ti 2GB, 822MHz
  • CPU: Intel Core i7-2600 @ 3.4GHz
  • RAM: 16GB
  • OS: OpenSUSE 12.2
  • SDK: nVidia CUDA Toolkit 6.0.1, AMD APP SDK 2.9

Completed OpenCL project should be uploaded via User dashboard (see instructions and example there), compilation and execution terminal output logs will be provided to the user.

The information send to hgpu.org will be treated according to our Privacy Policy

HGPU group © 2010-2014 hgpu.org

All rights belong to the respective authors

Contact us: