ORIGIN-DESTINATION-BASED PUBLIC TRANSPORT SERVICE GAP

Compressive Origin-Destination Estimation

The paper presents an approach to estimate OriginDestination (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 pa...

Compressive Origin-Destination Matrix Estimation

The paper presents an approach to estimate OriginDestination (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 pa...

Service Reliability and Urban Public Transport Design

An Agent-Based Model of Origin Destination Estimation (ABODE)

Abstract: is paper introduces ABODE, an agent-based model for Origin-Destination (OD) demand estimation, that can serve as a work trip distribution model. e model takes residential locations of workers and the locations of employers as exogenous and deals specifically with the interactions between firms and workers in creating a job-worker match and the commute outcomes. It is meant to illust...

ODCRep: Origin-Destination-Based Content Replication for Vehicular Networks

The evolving of vehicular network applications, from simple alert message exchanging to more elaborated and sophisticated systems, boosts the need for content delivery solutions. A useful technique, in such case, is the content replication, in which strategically selected vehicles replicate content and help on the delivery process. However, content replication is particularly challenging in veh...