Prediction, Expectation, and Surprise: Methods, Designs, and Study of a Deployed Traffic Forecasting Service
Abstract
We present research on developing models that forecast traffic flow and congestion in the Greater Seattle area. The research has led to the deployment of a service named JamBayes, that is being actively used by over 2,500 users via smartphones and desktop versions of the system. We review the modeling effort and describe experiments probing the predictive accuracy of the models. Finally, we present research on building models that can identify current and future surprises, via efforts on modeling and forecasting unexpected situations.
Cite
Text
Horvitz et al. "Prediction, Expectation, and Surprise: Methods, Designs, and Study of a Deployed Traffic Forecasting Service." Conference on Uncertainty in Artificial Intelligence, 2005.Markdown
[Horvitz et al. "Prediction, Expectation, and Surprise: Methods, Designs, and Study of a Deployed Traffic Forecasting Service." Conference on Uncertainty in Artificial Intelligence, 2005.](https://mlanthology.org/uai/2005/horvitz2005uai-prediction/)BibTeX
@inproceedings{horvitz2005uai-prediction,
title = {{Prediction, Expectation, and Surprise: Methods, Designs, and Study of a Deployed Traffic Forecasting Service}},
author = {Horvitz, Eric and Apacible, Johnson and Sarin, Raman and Liao, Lin},
booktitle = {Conference on Uncertainty in Artificial Intelligence},
year = {2005},
pages = {275-283},
url = {https://mlanthology.org/uai/2005/horvitz2005uai-prediction/}
}