Alternative Approaches for Real-Time Estimation and Prediction of Time-Dependent Origin-Destination Flows

By Kalidas Ashok, Moshe E. Ben-Akiva, J. Sussman. Transportation Science, 2000

359 citations recorded by the source corpus.

Subfields: Building and Construction, Transportation

View Paper: https://www.semanticscholar.org/paper/1f9d6a748eb52079e7af0cc6cd12b8a3a5a5876c

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. Srinivas Peeta
2. H. Koutsopoulos
3. Qi Yang
4. Moshe E. Ben-Akiva
5. Xuan Di
6. Henry X. Liu

In Transportation

1. Srinivas Peeta
2. H. Koutsopoulos
3. Qi Yang
4. Moshe E. Ben-Akiva
5. Fosca Giannotti
6. Dino Pedreschi
7. W. Jin
8. Henry X. Liu

Citations in the corpus

• Trajectory pattern mining (2007, background): “destination matrices are a common tool for the analysis of urban mobility flows, and both origins and destinations are usually given as background knowledge or they are the results of some preliminary study [2].”
• Foundations of Dynamic Traffic Assignment: The Past, the Present and the Future (2001, background): “(1997), Ashok and Ben-Akiva (2000), and Hu et al. (2001) belong to the non-DTA based category, while Cascetta et al. (1993) and Chang and Tao (1999) are representative of DTA based O-D demand models.”
• A novel approach for the structural comparison of origin-destination matrices: Levenshtein distance (2020, neutral): “…high density residential zones and destinations from high density work zones) in order to identify latent structure within the OD matrix; and (b) Ashok (1996) preserved the structural integrity of OD flows (both estimated and predicted) by introducing deviations of OD flows from historical OD…”
• Simulation Laboratory for Evaluating Dynamic Traffic Management Systems (2000, methodology): “The dynamic OD estimation model and the data used in the analysis are detailed by Ashok ( 40 ).”