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This report describes the system capability assessment for the
Cooperative Intersection Collision Avoidance System for Violations
(CICAS-V) based on data collected from objective tests and a pilot
test. The CICAS-V is a vehicle-to-infrastructure system that
provides visual, audio, and haptic (brake pulse) warnings when a
vehicle is in danger of violating a traffic signal or stop sign at
an intersection. A series of objective tests were conducted at the
Virginia Tech Transportation Institute. Each test was defined by an
initial geometry, a set of validity constraints (such as the
sufficient GPS accuracy), and a set of pass/fail criteria. The test
series investigated the ability to appropriately warn or not warn
at various speeds, in appropriately discerned lanes, under dynamic
lane changes, under changing signal conditions, and in the presence
of multiple equipped intersections. A pilot test was run with
nearly 100 naive drivers on a two-hour prescribed course in the
Blacksburg, VA area.
This report documents the process required for data exchange
between a conductor of a field operational test (FOT) and an
independent evaluator based on the experience of the Cooperative
Intersection Collision Avoidance System for Violations (CICAS-V)
FOT project. This report also describes lessons learned from the
data exchange in this project and proposes improvements to the
process going forward. The main implementation of these
improvements will be to design and maintain a Relational Database
Management System (RDBMS).
This report identifies crash imminent test scenarios based on
common pre-crash scenarios for integrated vehicle-based safety
systems that alert the driver of a light vehicle or a heavy truck
to an impending rear-end, lane change, or run-off-road crash.
Pre-crash scenarios describe vehicle movements and critical events
immediately prior to the crash. The General Estimates System (GES)
crash database was queried to distinguish common pre-crash
scenarios for light vehicles (2003 GES) and heavy trucks (2000-2003
GES) in terms of their frequency of occurrence. Analysis of
two-vehicle rear-end crashes revealed four dominant scenarios that
accounted for 97 percent of light-vehicle crashes and 95 percent of
heavy-truck crashes in which the subject vehicle was striking. Four
scenarios were also identified from an analysis of two-vehicle lane
change crashes, comprising 65 percent of light-vehicle crashes and
76 percent of heavy-truck crashes in which the subject vehicle was
encroaching onto another vehicle in adjacent lanes. There were five
single-vehicle, run-off-road scenarios representing 63 percent of
light-vehicle crashes and 83 percent of heavy-truck crashes,
excluding crashes caused by vehicle failure or evasive maneuver. An
additional set of scenarios is proposed to address multiple threats
from near simultaneous critical events. This report also provides a
statistical description of individual scenarios in terms of their
environmental factors, roadway geometry, and speed conditions.
This report presents results from an analysis of about 47,000 red
light violation records collected from 11 intersections in the City
of Sacramento, California, by red light photo enforcement cameras
between May 1999 and June 2003. The goal of this analysis is to
understand the correlation between red light violations and various
driver, intersection, and environmental factors.
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