Improving a Travel-Time Estimation Algorithm by Using Dual Loop Detectors

By J. Van Lint, N. J. van der Zijpp. 2003

161 citations recorded by the source corpus.

Subfields: Building and Construction, Control and Systems Engineering, Transportation

View Paper: https://www.semanticscholar.org/paper/c2dc49e9fdaca2f22f2338d235ad6122bc2ec8fe

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Building and Construction

1. Feiyue Wang
2. Henk J. van Zuylen
3. J. V. Lint
4. Yanjie Duan
5. Serge P. Hoogendoorn
6. Yisheng Lv
7. Yinhai Wang
8. Ruimin Ke

In Control and Systems Engineering

1. Feiyue Wang
2. Henk J. van Zuylen
3. J. V. Lint
4. Yanjie Duan
5. Serge P. Hoogendoorn
6. Yisheng Lv
7. Yinhai Wang
8. Daniel Hsu

In Transportation

1. Feiyue Wang
2. Henk J. van Zuylen
3. J. V. Lint
4. Yanjie Duan
5. Serge P. Hoogendoorn
6. Yisheng Lv
7. Yinhai Wang
8. Daniel Hsu

Citations in the corpus

• Travel time prediction with LSTM neural network (2016, methodology): “the PCSB method and the PLSB method [21].”
• Accurate freeway travel time prediction with state-space neural networks under missing data (2005, background): “Travel time estimation pertains to deducing travel times from ''known'' (i.e. historic) traffic conditions such as speeds or flows (see e.g. Van Lint and Van der Zijpp, 2003).”