Managing Traffic Incidents - University of Queensland

Publications
Dia, H (2000a) A conceptual framework for modelling
the environmental impacts of intelligent transport
systems, Proceedings of the XI Pan American
Conference in Traffic and Transportation Engineering,
19-23 November 2000, Gramado, Rio Grande do
Sul, Brazil.
The work reported in this paper is part of an ongoing
research project which aims to evaluate a
modelling framework that can be used to assess
the environmental impacts of Intelligent Transportation
Systems (ITS).
These systems aim to reduce traffic congestion
and enhance air quality through the application
of advanced communications, electronics
and computing technologies. It is still not clear,
however, whether the potential environmental
benefits of improved system efficiencies could
be partially offset by the induced travel associated
with ITS services. The techniques currently
available to evaluate the impacts of ITS on the
environment are not capable of addressing this
question because they do not take the induced
travel, demographics, land use and growth-indemand
changes into consideration. As a result,
a number of new techniques aimed at evaluating
the full traffic and environmental implications
of ITS deployment have been proposed in the
literature.
This research will contribute to progressions
in the needed methodologies by evaluating a
number of modelling platforms that address the
short and long-term potential deployment
outcomes, including induced travel effects, for
specific ITS components. Emissions and fuel
consumption models can then be linked to these
modelling frameworks to assess the effects of
ITS deployment.
This paper first highlights the limitations of
using conventional transportation and emissions
models to assess the environmental impacts of
ITS services. It also describes the modelling
approaches needed to capture the short and
long-term impacts of ITS deployment. A
generic modelling framework for assessing the
environmental impacts of ITS, based on techniques
that integrate travel demand and traffic
simulation models, is then presented. In this
modelling approach, the travel demand models
are used to assess the impacts of ITS services
that affect traveller behaviour, while traffic
simulation models are used to analyse the
effects of specific ITS services on network
performance.
The paper then describes how this generic
approach will be applied to develop and evaluate
modelling frameworks suitable for addressing
the short and long-term impacts of two
specific ITS components: incident management
and traveller information systems. The paper
also discusses a number of challenges related to
the implementation of feedback mechanisms
between traffic simulation and travel demand
models, the limitations of the approach and data
collection requirements.
Dia, H (2000b) A conceptual framework for modelling
dynamic driver behaviour using intelligent agents,
Proceedings of the 6th International Conference on
Applications of Advanced Technologies in Transportation
Engineering, 28-30 June 2000, Singapore.
This paper presents a dynamic driver behaviour
modelling framework based on Intelligent
Agents. This is a relatively recent computing
paradigm comprising autonomous software
components that can each be assigned a set of
goals to achieve (e.g. travel between points A
and B in a network) and a database of knowledge
comprising certain beliefs, intentions and
preferences concerning the task under consideration.
The characteristics of Intelligent Agents
suggest that they have the potential for successful
implementation in modelling dynamic driver
behaviour and driver response to information.
The work reported in this paper is part of an
ongoing research project which aims to demonstrate
the feasibility of using Intelligent Agents
to model travel behaviour on a congested traffic
commuting corridor based on a behavioural
survey of drivers. The Intelligent Agents
modelling framework represents a departure
from the classical view of route choice as an
individual issue and attempts to study the
collective behaviour of individual drivers as
more than rational decision makers who react
only according to pre-defined rules.
The modelling approach proposed in this
study allows for modelling the interaction
between drivers, co-ordination of their goals
and updating of their decisions on a real-time
and day-today basis. The Intelligent Agents
model developed in this study will be used in
conjunction with a traffic simulation component
to evaluate the impacts of providing drivers
with real-time information. The proposed
models will provide road authorities with a
valuable tool to evaluate and design effective
traveller information systems aimed at influencing
travel behaviour, reducing congestion and
enhancing the performance of the road network.
24 DECEMBER 2001