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.