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Video evidence in collision reconstruction has become a common foundation for vehicle position and speed analyses. The goal of this study was to explore how the uncertainty of these position/speed analyses is affected by various camera-, scene-, and vehicle-related properties. To achieve this goal, we quantified how the size and aspect ratio of pixels in the pixel grid change as a result of correcting for lens distortion and projecting the pixel grid onto a real-world surface captured by the image. Relying on both general and case-specific examples, we used Monte Carlo analyses to explore how uncertainty can be calculated and how it varies for different measurements and different camera-, scene-, and vehicle-related properties.

Bicycle computers record and store global position data that can be useful for forensic investigations. The goal of this study was to estimate the absolute error of the latitude and longitude positions recorded by a common bicycle computer over a wide range of riding conditions. We installed three Garmin Edge 530 computers on the handlebars of a bicycle and acquired 9 hours of static data and 96 hours (2214 km) of dynamic data using three different navigation modes (GPS, GPS+GLONASS, and GPS+Galileo satellite systems) and two geographic locations (Vancouver, BC, Canada and Orange County, CA, USA). We used the principle of error propagation to calculate the absolute error of this device from the relative errors between the three pairs of computers. During the static tests, we found 16 m to 108 m of drift during the first 4 min and 1.4 m to 5.0 m of drift during a subsequent 8 min period. During the dynamic tests, we found a 95th percentile absolute error for this device of ±8.04 m.

This paper describes the instrumentation used to study how the control inputs of 17 long-haul truck drivers were affected by fatigue. The task required outfitting a test vehicle to accurately measure the following control inputs and resulting vehicle behavior: Vehicle speed, Steering wheel angle and angular velocity, Accelerator pedal angle and angular velocity, Perception/response time, Driver EEG and heart rate, Clinical assessment of driver fatigue, Vehicle lateral lane position, and Car-following distance. The location and mounting procedure of each instrument as well as the sampling requirements for each device are discussed. Also discussed are the methods of data handling and storage.

The driving performance of 17 heavy-truck drivers was monitored under alert and fatigued conditions on a closed-circuit track to determine whether driver fatigue could be indirectly measured in the vehicle control inputs or outputs. Data were recorded for various potential physiological indicators of fatigue (EEG, heart rate and a subjective evaluation of drowsiness), for vehicle speed, steering, and accelerator pedal movements, and for vehicle position on the track. The objective was to determine whether a simple set of vehicle-based control measures correlated with the fatigue indicators. Correlations between other vehicle-based measures reported in the literature and the fatigue indicators were also calculated. The results indicate that there are measures which correlate sufficiently well with driver fatigue that they could potentially be used for an unobtrusive vehicle-based fatigue-detection algorithm.

The accuracy of collision severity data recorded by event data recorders (EDRs) has been previously measured primarily using barrier impact data from compliance tests and experimental low-speed impacts. There has been less study of the accuracy of EDR-based collision severity data in real-world, vehicle-to-vehicle collisions. Here we used 189 real-world front-into-rear collisions from the Crash Investigating Sampling System (CISS) database where the EDR from both vehicles recorded a severity to examine the accuracy of the EDR-reported speed changes. We calculated relative error between the EDR-reported speed change of each vehicle and a speed change predicted for that same vehicle using the EDR-reported speed change of the other vehicle and conservation of momentum. We also examined the effect of vehicle-type, mass ratio, and pre-impact braking on the relative error in the speed changes.