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Event Data Recorder (EDR) technology has been incorporated into the Electronic Control Modules (ECMs) of many on-highway heavy trucks. One benefit of this technology is its applicability to vehicle collision investigation and reconstruction ( Goebelbecker & Ferrone, 2000 ; van Nooten & Hrycay, 2005 ). However, collisions that cause extensive damage to the truck may cause a loss of electrical power to the ECM, which might interrupt the data storage process. This research is an attempt to determine the effects of power loss on heavy vehicle ECMs 1 , and the associated effects on data collected by the EDR function. Controlled testing was conducted with Detroit Diesel, Mercedes, Mack, Cummins, and Caterpillar engines, and power failures were created by artificially interrupting power between the vehicle's battery and ECM at predetermined intervals. EDR data from the test vehicles were extracted after each test, and the presence or absence of new data was examined.

The most common trigger for event data collection in Heavy Vehicle1 ECMs is a sudden decrease in the calculated vehicle speed. The calculated vehicle speed is a by-product of programmed calibrations and measured wheel speed data. In some cases, as is the case with Detroit Diesel ECMs, event data are recorded when the vehicle transitions from a driving state to a stopped state. Event data are reported with respect to time when the calculated vehicle speed change exceeds the preset threshold value or the first recorded 0 mph value. Because the data are not necessarily centered on the collision event itself, determination of impact speed and analysis of driver response can be problematic. A statistical evaluation of crash and non-crash related Heavy Vehicle Event Data Recorder (HVEDR) reports was conducted to identify specific measurable characteristics that can be used to identify the time of impact within reported event data.

Several previous studies report driver response times when responding to a lead vehicle. There have also been other studies that examined and measured the ability of drivers to detect the relative velocity of a lead vehicle. This study attempts to determine how the relative velocity detection threshold and driver response times fit together. There may be a significant difference between the times at which a lead vehicle is visible versus when it is perceivable as an immediate hazard. This research involved two parts; the first analyzes the raw data reported in previous research. The second part involved measuring responses of subjects using a laptop simulator. The goal of both parts of this research was to compare the subtended angular velocity [SAV] with the response times of drivers to determine if there is a point (threshold) at which response times level off at a fast rate.