Safety

This paper investigates the effects of the colors of pavement and lane marking on the
performance of a lane departure warning system.  The performance of the system was tested on
highway sections of different facility types and with pavements and markings of varying types
and attributes in Texas and Florida.  The results presented in this paper indicate that the tested
lane departure warning system was not able to detect the yellow markings for some highway
segments with light concrete and asphalt pavement colors in daylight conditions.  It was found,
based on analyses of the digital images taken of the pavement markings and the background
pavement surfaces, that the inability to detect the yellow markings can be related to measures of
the marking and pavement colors.

Florida International University

ARCADIS US INC.

Yildiz Technical University

Presented at the ITS America Annual Conference and Exposition, November 16-20, 2008, New York, New York

COOPERS, an EC FP6 funded IP deals with Co-operative Systems, enabling the
communication of real time data between infrastructure and vehicle. The main objective of
this undertaking is to increase road safety and road efficiency. Value Chain activities and the
building of an appropriate business model are key elements in the project.  

This paper shows the main actors for a Value Chain in the Co-operative Systems context. It
reveals that besides traditional roles, such as content provider, content aggregator, service
provider, and data distributor also new roles, such the role of a data clearance body is needed.  
In the example analysed in this paper, a differentiation is made between a Value Chain for
Safety Critical Services, and Convenience Services is made. In the Safety Critical Services
case, a Traffic Control Centre plays the leading role, whereas in the case of the Convenience
Services a Telco takes over the lead.

Vereinigung High Tech Marketing

Presented at the ITS America Annual Conference and Exposition, November 16-20, 2008, New York, New York

Over time, the National Institute of Standards and Technology (NIST) has refined the
4Dimension / Real-time Control System (4D/RCS) architecture for use in Unmanned Ground
Vehicles (UGVs). This architecture, when applied to passenger or commercial vehicles, can
greatly assist in the process of saving time and lives by creating a more intelligent vehicle that
can act, or assist a human in acting, in a safer and more efficient manner. Southwest Research
Institute (SwRI®) has undertaken the Southwest Safe Transport Initiative (SSTI) aimed at
investigating the development and commercialization of vehicle autonomy as well as vehiclebased
telemetry systems to improve safety and facilitate traffic flow. This paper will discuss the
approach and lessons learned from applying the 4D/RCS architecture to the SSTI autonomous
vehicle, a 2006 Ford Explorer.

Southwest Research Institute

Presented at the ITS America Annual Conference and Exposition, November 16-20, 2008, New York, New York

Environment-understanding technology is vital for intelligent vehicles that are expected to automatically respond to fast-changing environments and dangerous situations. Achieving perceptual abilities requires automatic detection of static and dynamic obstacles and estimation of their related information. Conventional methods independently detect individual pieces of overall information. Each process is computationally heavy and often produces noisy results without high reliability. Here we propose a fusion-based and layered-based methodology to systematically detect dynamic and static obstacles and obtain their location/timing information for visible and infrared sequences. The proposed obstacle-detection methodology takes advantage of connections among different data and increases the estimation accuracy of information about obstacles, yet reduces computing time, thus improving environment-understanding abilities and driving safety.

Massachusetts Institute of Technology

Presented at the ITS America Annual Conference and Exposition, November 16-20, 2008, New York, New York

A driver fatigue detection system has been developed under test-driving conditions that include 24 hours of driving on a test track at Nihon University and 12 hours of driving on a national highway in Japan. The level of driver fatigue is shown as a Driver Fatigue Index (DFI). After the detection system was installed in the heavy trucks used in this study, various experiments aimed at establishing practical usage parameters for the system were conducted under actual operating conditions. Truck positioning data was verified by GPS. Three-dimensional acceleration levels, the vehicle’s operating speed, the driver’s heart rate, body surface temperature, and DFI were monitored, with the collected data transmitted automatically to the researchers by a mobile packet transmission system. The results of the study were displayed on a web page used to manage driver fatigue levels for road safety purposes.

Nihon University

Presented at the ITS America Annual Conference and Exposition, November 16-20, 2008, New York, New York