Safety

We describe recent work and a demonstration to intersection collision warning / decision
support that primarily addresses the left turn across path / opposite direction collision
type.   We are currently engineering this approach, to include all facets needed for
implementation:  hardware and software technologies, laboratory and field tests, and in
the end, a field operational test in a real-world setting.  It is this real-world setting which
we emphasize:  we have conducted a demonstration of research in progress that provides
drivers with infrastructure- and vehicle-based alternatives to left turn collision warning.

University of California, Berkeley

Presented at the ITS America Annual Conference and Exposition, April 26 - 28, 2004 San Antonio, Texas

Although the death rate of traffic accidents is decreasing in Japan, the number of people
injured remains at a high level. While on-board mechanism have been developed and
actualized, there are still collision types which are difficult to solve by the vehicle alone. To
solve this difficulty, Vehicle-Infrastructure communication safety support, the DSSS (Driving
Safety Support System), using Infrared Beacon is taking an active role in Japan. Here, we will
introduce the progress of FOT (Field Operational Test) taken by the Kanagawa DSSS
Analysis WG. which is one of the DSSS activities.

Universal Traffic Management Society of Japan

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

The most significant federal investment in intelligent vehicle R&D in the U.S. is being conducted by the US Department of Defense (DOD) through the Demo III autonomous scout vehicle program. Demo III is an aggressive development effort in autonomous tactical ground vehicle technology R&D.

Robotics has been identified by numerous DOD studies as a key enabling technology for future military operational concepts. The Demo III program is a multiyear effort encompassing technology development and demonstration on testbed platforms, together with modeling, simulation, and experimentation directed toward optimization of operational concepts to employ this technology. The primary program focus is the advancement of capabilities for autonomous mobility through unstructured environments, concentrating on both perception and intelligent control technology. The program has developed the Experimental Unmanned vehicle (XUV), a small technology testbed vehicle. The XUV design couples multisensor perception with intelligent control to permit autonomous cross-country navigation at speeds of up to 32 kph during daylight and 16 kph during hours of darkness. The system design also encompasses onroad operations at up to 64 kph, including the capability to respond intelligently to other traffic and obstacles. When it concludes in 2002, Demo III will provide the military with both the technology and the initial experience required to develop and field the first generation of semiautonomous tactical ground vehicles for combat, combat support, and logistics applications.

The Demo III program has a high potential for technology spinoffs to civilian transportation, particularly in the area of obstacle detection and intelligent machine perception. This paper includes a description of the program approach, the sensor suite, progress in the last year; and potential spinoff areas to ITS.

Richard Bishop Consulting

General Dynamics Robotic Systems

Presented at the 11th ITS Annual Conference and Exposition, June 4-7, 2001 Miami Beach, Florida

For probabilistic analysis, we used the system reliability engineering method to model
rear-end and right-turn collisions. This model integrates driver’s evasive reaction time to
dangerous events with fluctuating driving performance caused by state transition of driver
consciousness. Results show that the probability of a driver being inattentive can be estimated
quantitatively by analyzing the state transitions of consciousness. In dangerous situations, the
frequency of rear-end collisions caused by average drivers is about 6.7×10-5/h, and the
probability of right-turn collisions is about 3.7×10-6.

Japan Automobile Research Institute

Daido Institute of Technology

Tokyo University of Marine Science & Technology

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

The overall objective of the study is to understand the occurrence of
primary and secondary incidents and relevant incident management strategies, as
well as to understand how primary incident duration and secondary incident
occurrence are related. Specifically, secondary incidents are more likely to occur
if the primary incident lasts long; at the same time, the durations of primary
incidents are expected to be longer if secondary incidents occur. The work will
allow State Departments of Transportation to estimate the chances of a secondary
incident based on the characteristics of the primary incident, evaluate associated
delays, and aid in identifying incident management strategies to mitigate the
impacts of both primary and secondary incidents. Freeway incident and roadway
inventory data from the Hampton Roads area in Virginia were used in this study.
Modeling and simulation techniques were applied to develop primary incident
duration and secondary incident occurrence/duration prediction models. Models
for primary incident durations and whether or not a secondary incident occurs are
estimated. The interdependence is modeled by using the incident duration as
endogenous variable in secondary incident occurrence models. The results show
statistical evidence for interdependence, but when it is taken into account, no
substantial differences in the magnitudes and statistical significance for the
estimated independent variables are found (compared to when the
interdependence is not accounted for). Statistically significant correlations are
found between secondary incident occurrence and other variables, allowing us to
recommend aggressive incident clearance procedures on qualifying high-volume
roadways to avoid secondary incidents.

Old Dominion University

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