2014/04/12 by Borhan M. Sanandaji, Sanandaji, Borhan M., Pravin Varaiya +1 · 1 citation
Computer Science · Engineering · #Blind Source Separation Techniques #Distributed Sensor Networks and Detection Algorithms #Dynamical Systems (math.DS) #FOS: Electrical engineering #FOS: Mathematics #Sparse and Compressive Sensing Techniques #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.1404.3263
openalex publication_date 2014/04/12 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01
The paper presents an approach to estimate Origin-Destination (OD) flows and their path splits, based on traffic counts on links in the network. The approach called Compressive Origin-Destination Estimation (CODE) is inspired by Compressive Sensing (CS) techniques. Even though the estimation problem is underdetermined, CODE recovers the unknown variables exactly when the number of alternative paths for each OD pair is small. Noiseless, noisy, and weighted versions of CODE are illustrated for synthetic networks, and with real data for a small region in East Providence. CODE's versatility is suggested by its use to estimate the number of vehicles and the Vehicle-Miles Traveled (VMT) using link counts.