Personal Mobility

 
This paper outlines the innovative work being undertaken to deliver improvements to road users
across  the  road  network,  in  the  county  of  Essex.  The  paper  shows  the  links  that  have  been
established with the private sector to make innovative use of data sources, and the work with the
County  Council’s  partnered  consultant  to  develop  sound  statistical  analysis  of  data  and  the
development of interventions to control and manage the road network. These activities combine
to form the basis of the delivery of targets agreed with central government which, when achieved,
will deliver over £3 million of reward funding to Essex County Council.

 Essex County Council

SA2000/Atkins

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

This paper presents an algorithm to predict an individual’s real-time travel path and destination using
data from a Global Positioning System (GPS) enabled mobile phone. The algorithm uses spatiallyaware,
geometric representations of a user’s historical trip data in its comparisons thus eliminating the
need for taxing calculations. This technique also promotes scalability through the use of enterprise
spatial database systems. Multiple modes of transportation are supported since the algorithm does
not rely on road network information. This Path Prediction algorithm can enable a variety of services
such as real-time localized traffic incident reporting, location-based advertising, and live traffic
management.

University of South Florida

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

Finnish Road Administration (later Finnra) is strongly improving the quality of real-time
traffic information in Finland. Finnra provides real-time traffic data free of charge to its
partners, but it does not participate in the development of actual end user services or value
added services. Finnra’s contribution to development is made through a private-public
partnership (PPP) as a provider of information.
In 2005 Finnra started a project for developing a travel time information system. This system
has been in production since June 2008. It is based on two parts: 1) detection of real-time
travel times, and 2) real-time traffic database called Digitraffic. In the future Digitraffic is the
only interface for real time traffic and road weather data from Finnra to the service providers.

Finnish Road Administration (Finnra), South-Eastern District

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

This paper presents problems identified in the conventional traffic information boards and
the implementation of cellular based traffic information system. We have just started to
implement the cellular phone system in order to provide our customers with timely,
accurate and reliable information as a responsibility of a road administrator, while the
traffic information service by the use of cellular phone had started among private sectors a
few years ago in Japan. The system will be expected to have ubiquitous coverage for
information services and enable advanced traffic management.
The latest results of the evaluation and more gained experiences will be presented at New
York since the system is now under development and to be launched into the market this
summer.

West Nippon Expressway Company Limited (NEXCO West)

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

As part of the Freight Performance Measures (FPM) initiative, the Federal Highway
Administration (FHWA) and the American Transportation Research Institute (ATRI) are
currently investigating research methods that will determine the usefulness of wireless truck
position data in identifying and improving truck parking deficiencies on U.S. interstate
highways. This report describes a new research methodology for measuring demand for truck
parking through the use of vehicle position data. The analysis described in this report also
demonstrate the application of position data for mapping truck parking supply to demand, and
subsequently identifying where truck parking facilities may be needed.

American Transportation Research Institute (ATRI)

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