A genetic programming approach to explore the crash severity on multi-lane roads

Created by W.Langdon from gp-bibliography.bib Revision:1.4221

  author =       "Abhishek Das and Mohamed Abdel-Aty",
  title =        "A genetic programming approach to explore the crash
                 severity on multi-lane roads",
  journal =      "Accident Analysis \& Prevention",
  volume =       "42",
  number =       "2",
  pages =        "548--557",
  year =         "2010",
  ISSN =         "0001-4575",
  DOI =          "doi:10.1016/j.aap.2009.09.021",
  URL =          "http://www.sciencedirect.com/science/article/B6V5S-4XFXSWB-3/2/d3dd6df818f461070f758ebe4fb9f1f3",
  keywords =     "genetic algorithms, genetic programming, Crash
                 severity, Multi-lane roads, Genetic algorithm,
  abstract =     "The study aims at understanding the relationship of
                 geometric and environmental factors with injury related
                 crashes as well as with severe crashes through the
                 development of classification models. The Linear
                 Genetic Programming (LGP) method is used to achieve
                 these objectives. LGP is based on the traditional
                 genetic algorithm, except that it evolves computer
                 programs. The methodology is different from traditional
                 non-parametric methods like classification and
                 regression trees which develop only one model, with
                 fixed criteria, for any given dataset. The LGP on the
                 other hand not only evolves numerous models through the
                 concept of biological evolution, and using the
                 evolutionary operators of crossover and mutation, but
                 also allows the investigator to choose the best models,
                 developed over various runs, based on classification
                 rates. Discipulus software was used to evolve the
                 models. The results included vision obstruction which
                 was found to be a leading factor for severe crashes.
                 Percentage of trucks, even if small, is more likely to
                 make the crashes injury prone. The [`]lawn and curb'
                 median are found to be safe for angle/turning movement
                 crashes. Dry surface conditions as well as good
                 pavement conditions decrease the severity of crashes
                 and so also wider shoulder and sidewalk widths.
                 Interaction terms among variables like on-street
                 parking with higher posted speed limit have been found
                 to make injuries more probable.",

Genetic Programming entries for Abhishek Das Mohamed A Abdel-Aty