@inproceedings{54036d4409924edb89950fa5da5be075,
title = "Analysing day-to-day and within-day changes of ramp-to-ramp traffic volume on urban expressway using Gaussian process",
abstract = "The analysis of the day-to-day and within-day changes of the ramp-to-ramp traffic volume of an urban expressway is important for efficient operation and management of vehicular traffic. A data-oriented approach is proposed in this investigation to estimate day-to-day and within-day changes of ramp-to-ramp traffic volume using three types of traffic data: ramp-to-ramp traffic volume, travel time between ramps, and section traffic volume data of arterial roads. In this regard, a negative binomial regression model and a Gaussian process regression model were developed and their accuracy was evaluated. It was determined that the latter generally yielded better accuracy and its characteristics were examined.",
keywords = "Gaussian process, Generalized linear model, Non-linear model",
author = "Kenji Ikeda and Shohei Yasuda and Takamasa Iryo and Masaaki Ishihara",
note = "Publisher Copyright: {\textcopyright} 2010 23th International Conference on Architecture of Computing Systems 2010, ARCS 2010 - Workshop Proceedings. All rights reserved.; 24th International Conference of Hong Kong Society for Transportation Studies: Transport and Smart Cities, HKSTS 2019 ; Conference date: 14-12-2019 Through 16-12-2019",
year = "2019",
language = "English",
series = "Proceedings of the 24th International Conference of Hong Kong Society for Transportation Studies, HKSTS 2019: Transport and Smart Cities",
publisher = "Hong Kong Society for Transportation Studies Limited",
pages = "99--106",
editor = "Chow, {Andy H.F.} and S.M. Lo and Lishuai Li",
booktitle = "Proceedings of the 24th International Conference of Hong Kong Society for Transportation Studies, HKSTS 2019",
}