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Journal Article
Sam Kodsi, Jeffrey Muttart
A primary goal of crash reconstruction (or collision avoidance system) is to determine whether a crash is avoidable or not. A prerequisite for the determination of avoidance is knowledge of the time that is available to a driver. In a path intrusion crash scenario, a method to determine the time available for a major road driver is to know the time a minor road driver accelerated before impact. This research is an attempt to model the time based upon acceleration distance. The current study involved two parts. Part one was a naturalistic study of driver acceleration behavior at two-way-stop controlled intersections. In part two, ten drivers with instrumented vehicles were asked to drive a route that included four acceleration runs at two-way-stop sign control intersections. In the naturalistic study, the accelerations were measured using video recordings and videogrammetry at known distances.
Journal Article
William F. Messerschmidt, Jeffery W. Muttart
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.
Technical Paper
Jeffrey W. Muttart, William F. Messerschmidt, Larry G. Gillen
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.
Technical Paper
Jeffrey W. Muttart
The goal of this research was to develop mathematical equations that would estimate the response times of drivers in various situations. This research involved two studies. The first study involved the development of a series of equations that predict driver response times [DRTs]. Compiling a database of over 130 studies that measured DRT and coding for over 20 methodology and substantive variables was the source from which the equations were developed. Multiple Stepwise Linear Regression analysis was performed on the database. The analysis produced an empirical equation that revealed which variables and methods were statistically significant predictors of DRTs. The analysis showed that when all research data was analyzed together an accurate predictor could not be developed. However, when the database was divided into smaller sets based upon where the target emerged, empirical equations were developed. Each of six equations reached statistical significance.
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