A synthesis of emerging data collection technologies and their impact on traffic management applications
C Antoniou, R Balakrishna… - European Transport …, 2011 - Springer
Purpose The objective of this research is to provide an overview of emerging data collection
technologies and their impact on traffic management applications. Methods Several existing …
technologies and their impact on traffic management applications. Methods Several existing …
Exploiting floating car data for time-dependent Origin–Destination matrices estimation
M Nigro, E Cipriani, A del Giudice - Journal of Intelligent …, 2018 - Taylor & Francis
The study evaluates the added value generated by estimating dynamic demand matrices by
information gathered from Floating Car Data (FCD). Firstly, adopting a large dataset of FCD …
information gathered from Floating Car Data (FCD). Firstly, adopting a large dataset of FCD …
Origin-destination pattern estimation based on trajectory reconstruction using automatic license plate recognition data
Origin-destination (OD) pattern estimation is a vital step for traffic simulation applications and
active urban traffic management. Many methods have been proposed to estimate OD …
active urban traffic management. Many methods have been proposed to estimate OD …
A DBSCAN-based framework to mine travel patterns from origin-destination matrices: Proof-of-concept on proxy static OD from Brisbane
Limited studies exist in the literature on demand related travel patterns, the analysis of which
requires a rich database of Origin Destination (OD) matrices with appropriate clustering …
requires a rich database of Origin Destination (OD) matrices with appropriate clustering …
A novel approach for the structural comparison of origin-destination matrices: Levenshtein distance
Origin-Destination (OD) matrix is a tableau of travel demand distributed between different
zonal pairs. Essentially, OD matrix provides two types of information:(a) the individual cell …
zonal pairs. Essentially, OD matrix provides two types of information:(a) the individual cell …
Dynamic origin-destination demand estimation using automatic vehicle identification data
X Zhou, HS Mahmassani - IEEE Transactions on intelligent …, 2006 - ieeexplore.ieee.org
This paper proposes a dynamic origin-destination (OD) estimation method to extract
valuable point-to-point split-fraction information from automatic vehicle identification (AVI) …
valuable point-to-point split-fraction information from automatic vehicle identification (AVI) …
Nonlinear Kalman filtering algorithms for on-line calibration of dynamic traffic assignment models
C Antoniou, M Ben-Akiva… - IEEE Transactions on …, 2007 - ieeexplore.ieee.org
An online calibration approach that jointly estimates demand and supply parameters of
dynamic traffic assignment (DTA) systems is presented and empirically validated through an …
dynamic traffic assignment (DTA) systems is presented and empirically validated through an …
Calibration of microscopic traffic simulation models: Methods and application
R Balakrishna, C Antoniou… - Transportation …, 2007 - journals.sagepub.com
A mathematical framework and a solution approach are presented for the simultaneous
calibration of the demand and supply parameters and inputs to microscopic traffic simulation …
calibration of the demand and supply parameters and inputs to microscopic traffic simulation …
Dynamic demand estimation and prediction for traffic urban networks adopting new data sources
Nowadays, new mobility information can be derived from advanced traffic surveillance
systems that collect updated traffic measurements, both in fixed locations and over specific …
systems that collect updated traffic measurements, both in fixed locations and over specific …
An information-theoretic sensor location model for traffic origin-destination demand estimation applications
To design a transportation sensor network, the decision maker needs to determine what
sensor investments should be made, as well as when, how, where, and with what …
sensor investments should be made, as well as when, how, where, and with what …