@inproceedings{fdc17c407d014fe2b9ffc854f62e6464,
title = "An improved model for short-term traffic forecasting considering weather impacts",
abstract = "Accurate short-term prediction of traffic conditions on freeways has recently become increasingly important because of its vital role in the basic traffic management functions and trip decision making processes. The objective of this research is to utilize traffic and weather data from multiple data sources to develop an integrated model to predict traffic conditions under different rainfall conditions. A set of prediction models are compared and their performances using data from case studies are investigated and reported. The model performance was valuated using prediction errors, which are measured by the relative length of the distance between the predicted state and the observed state.",
author = "Xinchao Chen and Si Qin and Jian Zhang and Huachun Tan and Yunxia Xu and Guanchen Dai and Xiaoxuan Chen",
note = "Publisher Copyright: {\textcopyright} ASCE.; 17th COTA International Conference of Transportation Professionals: Transportation Reform and Change - Equity, Inclusiveness, Sharing, and Innovation, CICTP 2017 ; Conference date: 07-07-2017 Through 09-07-2017",
year = "2018",
doi = "10.1061/9780784480915.080",
language = "English",
series = "CICTP 2017: Transportation Reform and Change - Equity, Inclusiveness, Sharing, and Innovation - Proceedings of the 17th COTA International Conference of Transportation Professionals",
publisher = "American Society of Civil Engineers (ASCE)",
pages = "784--792",
editor = "Haizhong Wang and Jian Sun and Jian Lu and Lei Zhang and Yu Zhang and ShouEn Fang",
booktitle = "CICTP 2017",
address = "United States",
}