How predictable are macroscopic traffic states: a perspective of uncertainty quantification

Author:

Li Guopeng1,Knoop Victor L.1,van Lint Hans1

Affiliation:

1. Department of Civil Engineering and Geoscience, Delft University of Technology, Delft, Netherlands

Publisher

Informa UK Limited

Reference75 articles.

1. A review of uncertainty quantification in deep learning: Techniques, applications and challenges

2. Amini, Alexander, Wilko Schwarting, Ava Soleimany, and Daniela Rus. 2020. “Deep Evidential Regression.” In Neural Information Processing Systems. Vancouver.

3. Water quality modeling: A review of the analysis of uncertainty

4. Ben-Akiva Moshe. 1998. “Dynamit A Simulation-Based System for Traffic Prediction and Guidance Generation.”

5. Online-SVR for short-term traffic flow prediction under typical and atypical traffic conditions

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