Spatial and Temporal Patterns in Large-Scale Traffic Speed Prediction
The ability to accurately predict traffic speed in a large and heterogeneous road network has many useful applications, such as route guidance and congestion avoidance. In principle, data-driven methods, such as support vector regression (SVR), can predict traffic with high accuracy because traffic...
Main Authors: | Asif, Muhammad Tayyab, Dauwels, Justin, Oran, Ali, Fathi, Esmail, Dhanya, Menoth Mohan, Mitrovic, Nikola, Jaillet, Patrick, Goh, Chong Yang, Xu, Muye |
---|---|
Other Authors: | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science |
Format: | Article |
Language: | en_US |
Published: |
Institute of Electrical and Electronics Engineers (IEEE)
2015
|
Online Access: | http://hdl.handle.net/1721.1/100436 https://orcid.org/0000-0003-0064-6568 https://orcid.org/0000-0002-8585-6566 |
Similar Items
-
Low-Dimensional Models for Compressed Sensing and Prediction of Large-Scale Traffic Data
by: Mitrovic, Nikola, et al.
Published: (2016) -
Low-Dimensional Models for Compressed Sensing and Prediction of Large-Scale Traffic Data
by: Mitrovic, Nikola, et al.
Published: (2016) -
Near-Lossless Compression for Large Traffic Networks
by: Muhammad Tayyab Asif, et al.
Published: (2016) -
Near-Lossless Compression for Large Traffic Networks
by: Asif, Muhammad Tayyab, et al.
Published: (2016) -
Unsupervised learning based performance analysis of v-support vector regression for speed prediction of a large road network
by: Jaillet, Patrick, et al.
Published: (2014)