Evolving Driving Agent for Remote Control of Scaled Model of a Car

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{tanev:2005:GECCOLB,
  author =       "Ivan Tanev and Michal Joachimczak and 
                 Hitoshi Hemmi and Katsunori Shimohara",
  title =        "Evolving Driving Agent for Remote Control of Scaled
                 Model of a Car",
  booktitle =    "Late breaking paper at Genetic and Evolutionary
                 Computation Conference {(GECCO'2005)}",
  year =         "2005",
  editor =       "Franz Rothlauf",
  address =      "Washington, D.C., USA",
  month =        "25-29 " # jun,
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://www.cs.bham.ac.uk/~wbl/biblio/gecco2005lbp/papers/50-tanev.pdf",
  abstract =     "We present an approach for automatic design via
                 genetic programming of the functionality of driving
                 agent, able to remotely operate a scale model of a car
                 running in a fastest possible way. The agent's actions
                 are conveyed to the car via standard radio control
                 transmitter. The agent perceives the environment from a
                 live video feedback of an overhead camera. In order to
                 cope with the inherent video feed latency we propose an
                 approach of anticipatory modelling in which the agent
                 considers its current actions based on anticipated
                 intrinsic (rather than currently available, outdated)
                 state of the car and its surrounding. The driving style
                 of the agent is first evolved offline on a software
                 simulator of the car and then adapted online to the
                 real world. Experimental results demonstrate that on
                 long runs the agent's-operated car is only marginally
                 (about 5%) slower than a human-operated one, while the
                 consistence of lap times posted by the evolved driving
                 agent is better than that of a human. Presented work
                 can be viewed as a step towards the development of a
                 framework for automated design of the controllers of
                 remotely operated vehicles capable to find an optimal
                 solution to various tasks in different traffic
                 situations and road conditions",
  notes =        "Distributed on CD-ROM at GECCO-2005",
}

Genetic Programming entries for Ivan T Tanev Michal Joachimczak Hitoshi Hemmi Katsunori Shimohara

Citations