A combined frequency-severity approach for the analysis of rear-end crashes on urban arterials

Created by W.Langdon from gp-bibliography.bib Revision:1.4549

  author =       "Abhishek Das and Mohamed A. Abdel-Aty",
  title =        "A combined frequency-severity approach for the
                 analysis of rear-end crashes on urban arterials",
  journal =      "Safety Science",
  year =         "2011",
  volume =       "49",
  number =       "8-9",
  pages =        "1156--1163",
  ISSN =         "0925-7535",
  DOI =          "doi:10.1016/j.ssci.2011.03.007",
  URL =          "http://www.sciencedirect.com/science/article/B6VF9-52T1BCG-2/2/dbc605442a050a3d5a59a825025f0f40",
  keywords =     "genetic algorithms, genetic programming, Arterial
                 safety, Injury severity, Crash frequency, Sensitivity
  abstract =     "Analysis of both the crash count and the severity of
                 injury are required to provide the complete picture of
                 the safety situation of any given roadway. The
                 randomness of crashes, the one-way dependency of injury
                 on crash occurrence and the difference in response
                 types have typically led researchers into developing
                 independent statistical models for crash count and
                 severity classification. The Genetic Programming (GP)
                 methodology adopts the concepts of evolutionary biology
                 such as crossover and mutation in effectively giving a
                 common heuristic approach to model the development for
                 the two different modelling objectives. The chosen GP
                 models have the highest hit rate for rear-end crash
                 classification problem and the least error for function
                 fitting (regression) problems. Higher Average Daily
                 Traffic (ADT) is more likely to result in more crashes.
                 Absence of on-street parking may result in diminished
                 severity of injuries resulting from crashes as they may
                 provide soft crash barrier in contrast to fixed road
                 side objects. Graphical presentation of the frequency
                 of crashes with varying input variables shed new light
                 on the results and its interpretation. Higher friction
                 coefficient of roadways result in reduced frequency of
                 crashes during the morning peak hours, with the trend
                 being reversed during the afternoon peak hours. Crash
                 counts have been observed to be at a maximum at a
                 surface width of 30 ft. Sensitivity analysis results
                 reflect that ADT is responsible for the largest
                 variation in crash counts on urban arterials.",

Genetic Programming entries for Abhishek Das Mohamed A Abdel-Aty