Dynamic travel time prediction using data clustering and genetic programming

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@Article{Elhenawy:2014:TRPCET,

• author = "Mohammed Elhenawy and Hao Chen2 and Hesham A. Rakha",
• title = "Dynamic travel time prediction using data clustering and genetic programming",
• journal = "Transportation Research Part C: Emerging Technologies",
• volume = "42",
• pages = "82--98",
• year = "2014",
• month = may,
• ISSN = "0968-090X",
• DOI = "doi:10.1016/j.trc.2014.02.016",
• URL = "http://www.sciencedirect.com/science/article/pii/S0968090X14000588",
• keywords = "genetic algorithms, genetic programming, Travel time prediction, Clustering, Sampling with replacement, Probe data",
• abstract = "The current state-of-practice for predicting travel times assumes that the speeds along the various roadway segments remain constant over the duration of the trip. This approach produces large prediction errors, especially when the segment speeds vary temporally. In this paper, we develop a data clustering and genetic programming approach for modelling and predicting the expected, lower, and upper bounds of dynamic travel times along motorways. The models obtained from the genetic programming approach are algebraic expressions that provide insights into the spatio-temporal interactions. The use of an algebraic equation also means that the approach is computationally efficient and suitable for real-time applications. Our algorithm is tested on a 37-mile freeway section encompassing several bottlenecks. The prediction error is demonstrated to be significantly lower than that produced by the instantaneous algorithm and the historical average averaged over seven weekdays (p-value <0.0001). Specifically, the proposed algorithm achieves more than a 25percent and 76percent reduction in the prediction error over the instantaneous and historical average, respectively on congested days. When bagging is used in addition to the genetic programming, the results show that the mean width of the travel time interval is less than 5 minutes for the 60-80 min trip.",

}

Genetic Programming entries for Mohammed Elhenawy Hao Chen2 Hesham A Rakha

Citations