Cross-cutting Issues

Today available (or under development) technologies enable the improvement of not only
sensing systems, but also the way these systems share information. Smarter systems demand
smarter sensors and at the same time cooperative systems require cooperative sensors.
One of the strategic goals for existing traffic control systems is to develop new systems for
cooperative sensing and predicting flow, infrastructure and environmental conditions
surrounding traffic, with a view to improve road transport operations safety and efficiency.
In order to achieve this objective, there is a need to improve existing sensing technologies,
providing them with knowledge sharing capabilities to share information.
Transforming the existing sensors into knowledge sharing sensors allows obtaining added
value information with the minimum investment from the administrations.

ETRA I+D

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

Based on traffic data measured on American freeways in Chicago with detector
measurements of vehicle speed and flow rates from NAVTEQ’S traffic service centres,
recognition and tracking of congested traffic patterns at freeway bottlenecks are
performed through the use of the FOTO and ASDA models based on Three-Phase
traffic theory by Kerner. These models reconstruct and track the “synchronized flow”
and “wide moving jams” traffic phases in congested traffic. A qualitative comparison of
ASDA/FOTO model results and archives of traffic messages (RDS/TMC) is shown. In
addition, a probable integration path into vehicles is presented.

IT Designers GmbH

Daimler AG

NAVTEQ

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

Global Positioning Systems (GPS) is widely used in tracking vehicles and is superior to conventional technologies based on certain important criteria. This article investigates the feasibility of tracking vehicles with regular GPS devices. Since downtown is generally the “heart” of a city with high density of vehicles and activities, locating vehicles precisely there is extremely important. Our field tests, however, find that GPS cannot efficiently track vehicles in downtown streets, although it works well on freeways. In this paper, we specifically analyze errors of GPS measured positions and the availability of satellite signals in both freeway and downtown scenarios

University of Washington - Department of Civil and Environmental Engineering

Presented at the ITS America Annual Conference and Exposition, May 19-22, 2003 Minneapolis, Minnesota

Transportation professionals strive to gain a deeper understanding of household travel behavior patterns for the purposes of modeling, planning, and maintaining transportation systems. Decision-makers also strive to utilize these patterns for educating, promoting and encouraging the use of alternatives to driving in general and to driving alone in particular. This paper focuses on using innovative technology in travel data collection. The ubiquity of portable devices, such as mobile phones and personal digital assistants (PDAs) in today’s world, provides opportunities to revolutionize travel surveys.  In the past, data have been obtained through labor intensive paper and/or telephone interviews then input into computers for analyses.  While mobile devices can be utilized as modern survey replacements, the requirement of constant user interaction presents many challenges.  This paper discusses the design and field tests of TRAC-IT, a smart application for mobile devices that interrelates real-time user input with global positioning system (GPS) data, while adapting to user behavior to create a comprehensive tool that improves the quality and quantity of collected data.  Initial limited field tests show a mean of 6.2 reported daily trips per individual.  More comprehensive travel behavior data are anticipated when TRAC-IT is used by a larger number of households for longer durations.Transportation professionals strive to gain a deeper understanding of household travel behavior patterns for the purposes of modeling, planning, and maintaining transportation systems. Decision-makers also strive to utilize these patterns for educating, promoting and encouraging the use of alternatives to driving in general and to driving alone in particular.  This paper focuses on using innovative technology in travel data collection. The ubiquity of portable devices, such as mobile phones and personal digital assistants (PDAs) in today’s world, provides opportunities to revolutionize travel surveys.  In the past, data have been obtained through labor intensive paper and/or telephone interviews then input into computers for analyses.  While mobile devices can be utilized as modern survey replacements, the requirement of constant user interaction presents many challenges.  This paper discusses the design and field tests of TRAC-IT, a smart application for mobile devices that interrelates real-time user input with global positioning system (GPS) data, while adapting to user behavior to create a comprehensive tool that improves the quality and quantity of collected data.  Initial limited field tests show a mean of 6.2 reported daily trips per individual.  More comprehensive travel behavior data are anticipated when TRAC-IT is used by a larger number of households for longer durations.

University of South Florida

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

Under the premise that relatively near-term and passive vehicle and roadway markings can enhance the effectiveness of otherwise autonomous driver-assist sensing systems, alternative candidate vehicle and roadway feature marking concepts have been explored within a project with scope that encompasses analytical and experimental investigations of cooperative markings or systems on the highway and on vehicles to enhance target signals detected by intelligent vehicle sensing systems. The pacing assumption is that driver-assist safety services will at least initially be implemented in autonomous vehicles; hence, it these services cannot be dependent on special highway or roadside features. With that in mind, the intent of the work is not to make sensing systems dependent on any special infrastructure or Federally-mandated vehicle markings; rather, the intent to understand how to provide supplemental infrastructure as an independent measure to improve the performance of autonomous intelligent vehicle sensing systems. In that manner, the default operating mode would be in the absence of cooperative markings, but if they do exist, system effectiveness could be enhanced. Within these boundaries, a broad set of concepts were considered, from which four promising “sensor-friendly” candidates under consideration for further analytical and experimental work are described: passive reflectors, traffic striping, fluorescent paint, and passive amplifiers on license plates. In selecting specific candidates, our primary criteria are that they must be inexpensive, reliable and interoperable in a variety of highway environments and vehicle platforms. To cull the list further, we have additionally imposed criteria that concepts must be passive, and minimize the need for new in-vehicle sensing systems (although software modifications such as additional processing is recognized to be essential). This is not to say that other "sensor-friendly" candidates are less viable or are not being investigated (e.g., LED messaging). We do say, however, that the four candidates above are the most likely near-term implementations of passive cooperative concepts that we have thus far considered, and that we will concentrate performance and benefits analyses and experiments on them.

California PATH - University of California at Berkeley

Robotics Institute - Carnegie Mellon University

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