Learning Risky Driver Behaviours from Multi-Channel Data Streams Using Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3963

@InProceedings{Xie:2013:AI,
  author =       "Feng Xie and Andy Song and Flora Salim and 
                 Athman Bouguettaya and Timos Sellis and Doug Bradbrook",
  title =        "Learning Risky Driver Behaviours from Multi-Channel
                 Data Streams Using Genetic Programming",
  booktitle =    "Proceedings of the 26th Australasian Joint Conference
                 on Artificial Intelligence (AI2013)",
  year =         "2013",
  editor =       "Stephen Cranefield and Abhaya Nayak",
  volume =       "8272",
  series =       "LNAI",
  pages =        "202--213",
  address =      "Dunedin, New Zealand",
  month =        "1-6 " # dec,
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming, smartphone",
  isbn13 =       "978-3-319-03679-3",
  URL =          "http://dx.doi.org/10.1007/978-3-319-03680-9_22",
  DOI =          "doi:10.1007/978-3-319-03680-9_22",
  size =         "12 pages",
  abstract =     "Risky driver behaviours such as sudden braking,
                 swerving, and excessive acceleration are a major risk
                 to road safety. In this study, we present a learning
                 method to recognise such behaviours from smart phone
                 sensor input which can be considered as a type of
                 multi-channel time series. Unlike other learning
                 methods, this Genetic Programming (GP) based method
                 does not require pre-processing and manually designed
                 features. Hence domain knowledge and manual coding can
                 be significantly reduced by this approach. This method
                 can achieve accurate real-time recognition of risky
                 driver behaviours on raw input and can outperform
                 classic learning methods operating on features. In
                 addition this GP-based method is general and suitable
                 for detecting multiple types of driver behaviours.",
}

Genetic Programming entries for Feng Xie Andy Song Flora Salim Athman Bouguettaya Timos Sellis Doug Bradbrook

Citations