File(s) under permanent embargo

Reason: Under embargo until December 2021. After this date a copy can be supplied under Section 51(2) of the Australian Copyright Act 1968 by submitting a document delivery request through your library or by emailing document.delivery@monash.edu

Estimating Time-Dependent Origin-Destination Demand in a Large-Scale Congested Network Using Multi-Source Traffic Data

thesis
posted on 13.12.2018, 03:23 by MOHAMMAD SAJJAD SHAFIEI
Traffic simulation models are capable of replicating traffic network conditions and providing accurate forecasts. These models involve a number of parameters that need to be calibrated based on the available archived traffic data. Time-Dependent Origin-Destination (TDOD) demand is a crucial input for traffic simulations. The reliability of the traffic simulations is highly dependent on the accuracy of the TDOD demand. Since the demand data cannot be observed directly, a common approach to obtain TDOD demand is to use a priori demand matrix and traffic count data in some parts of the network. The broad aim of this research is to develop a TDOD estimation model using multi-source traffic data applied to a large-scale congested urban network (Melbourne).

History

Campus location

Australia

Principal supervisor

Hai Vu

Additional supervisor 1

Meead Saberi

Year of Award

2018

Department, School or Centre

Civil Engineering

Additional Institution or Organisation

Department of Civil Engineering, Institute of Transport Studies

Course

Doctor of Philosophy

Degree Type

DOCTORATE

Faculty

Faculty of Engineering