77 citations · 158 across the 6 of their papers we have counts for
3 papers · 1 filter
Scalable Dynamic Mixture Model with Full Covariance for Probabilistic Traffic Forecasting
Seongjin Choi, Nicolas Saunier, Vincent Zhihao Zheng +2
Deep learning-based multivariate and multistep-ahead traffic forecasting models are typically trained with the mean squared error (MSE) or mean absolute error (MAE) as the loss fun…
Bayesian calibration of traffic flow fundamental diagrams using Gaussian processes
Zhanhong Cheng, Xudong Wang, Xinyuan Chen +2
Modeling the relationship between vehicle speed and density on the road is a fundamental problem in traffic flow theory. Recent research found that using the least-squares (LS) met…
Probabilistic forecasting of bus travel time with a Bayesian Gaussian mixture model
Xiaoxu Chen, Zhanhong Cheng, Jian Gang Jin +2
Accurate forecasting of bus travel time and its uncertainty is critical to service quality and operation of transit systems; for example, it can help passengers make better decisio…