Cross-cutting Issues

While extensive ITS technology is being deployed in the field, it remains difficult to perform formal evaluation of the benefits obtained from the implementation of the technology due to the lack of available evaluation tools. We propose a methodology that uses a simulation/optimization approach to develop a performance versus cost tradeoff analysis curve. In particular, we are evaluating ITS sensor and control technologies such as cameras, ramp metering, loop detectors, etc. Employing CORSIM, a traffic simulation tool, we determine the “optimal” ITS deployment and implementation strategy for a particular budget using a pseudo random search technique. This analysis is repeated over a range of budgets to determine the nature of the cost/performance tradeoff curve. We demonstrate this approach with a six-mile section of interstate in the Hampton Roads region of Virginia.

University of Virginia - Department of Systems Engineering

Presented at the 10th ITS Annual Conference and Exposition, May 1-4, 2000 Boston, MA

Integrating individual intelligent transportation systems into
comprehensive platforms is a key challenge faced by transport authorities in the provision
of optimal services to users. The use of an ITS architecture encourages structured
development and integration of ITS systems that leads to maximization of benefits by
minimizing redundancies and maximizing capabilities. This paper presents a distributed
framework for a multi-layered ITS architecture that has been designed for integrating
information generated and used by future as well as existing intelligent transportation
systems and applications. The iTransIT framework provides a data model that allow
complex ITS domains to be successfully decomposed into a number of data layers. This
multi-layered data model may be distributed across multiple systems and exploits the
overlapping temporal and spatial aspects of traffic information to allow the federation of
data from diverse ITS systems. Moreover, the abstractions used to compose the data
model combined with the range of interaction paradigms supported by the iTransIT
architecture allow interoperation between systems based on different communication
technologies. This provides the framework with the flexibility to enable a gradual
integration of systems over time thereby reducing integration restrictions on previously
deployed systems while catering for the as yet unknown requirements of future and novel
systems.

Trinity College Dublin, Ireland

Presented at the 12th World Congress on Intelligent Transport Systems, November 6-10, 2005, San Francisco, California

Improving intermodal transport management across modes, company responsibilities and
national borders is a complex undertaking. This paper discusses the challenges to achieve a
collaborative, advanced transport chain management system responding to the European
Commission`s recent Freight Transport Logistics Action Plan. The paper outlines a practical
solution based on a case of inland waterway transport of heavy cargo along the river Elbe for
export via Hamburg. The case is one of nine business cases which are participating in
FREIGHTWISE, an EU-sponsored project in the 6 Framework Programme.

BMT Group Ltd

Presented at the 15th World Congress on Intelligent Transport Systems, November 16-20, 2008, New York, New York

This paper presents a framework and tools developed to study the sensitivity of traffic data
quality to detectors location and spacing. Our ultimate objective is to formulate generalized
detector deployment guidelines that are based on the functional needs of practitioners, and for which funding can be objectively justified. Our approach consists in using trajectory sets obtained from field experiments and traffic simulation models as ground truth, and to run a traffic detector model from which we extract information that would normally be available to practitioners. Ground truth information and detector-generated information are compared through selected quality benchmark measures, and we search detector configurations that optimize this comparison. We test both model-based and so-called naïve traffic estimation techniques, and find that while the former is superior, the difference becomes negligible as detector density increases. ½ mile spacing seems to always yield reasonably good information, but no such analysis should overlook detector failure rates. We conclude that those must be taken into account in the formulation of deployment guidelines, a step we defer to further studies.

University of California, Berkeley

University of Minnesota

Rensselaer Polytechnic Institute

Presented at the 15th World Congress on Intelligent Transport Systems, November 16-20, 2008, New York, New York

It is a truism that new technology-driven applications often fail for institutional
reasons that have nothing to do with the technology. Yet, weaknesses within the technology
itself may hinder successful deployment. Accordingly, it has been proposed that to predict
whether a new application will succeed in the marketplace, it must pass three tests of feasibility:
technical, operational, and economic. The authors report the result of applying these three tests
to an application that is gaining widespread interest in the U.S. following its acceptance in
Europe: red light cameras. The three tests may be described as whether the system meets legal
standards, performs with sufficient accuracy to be accepted, and enjoys the support of the public
(technical feasibility), whether system costs are in line with revenue (fiscal feasibility), and
whether the system improves safety through reductions in violations and crash severity
(operational feasibility). The study found that cameras as applied in Virginia largely pass the
first test of technical feasibility: they are legally sound, technologically accurate, and supported
by the public. They pass a limited fiscal analysis: they do not generate revenue to the extent
critics suggest; however, data quality prevents a full economic feasibility test from being
undertaken. In terms of operational feasibility, the cameras potentially reduce crashes related to
red light running; however, because they are correlated with an increase in total injury crashes, a
better understanding of crash severity—e.g., the degree of injury—is required.

University of Virginia, USA

Virginia Transportation Research Council, USA

Presented at the 12th World Congress on Intelligent Transport Systems, November 6-10, 2005, San Francisco, California