Search Results

The accuracy of the speed change reported by Generation 1 Toyota Corolla Event Data Recorders (EDR) in low-speed front and rear-end collisions has previously been studied. It was found that the EDRs underestimated speed change in frontal collisions and overestimated speed change in rear-end collisions. The source of the uncertainty was modeled using a threshold acceleration and bias model. This study compares the response of Generation 1, 2 and 3 Toyota EDRs from Toyota Corolla, Camry and Prius models. 19 Toyota airbag control modules (ACMs) were mounted on a linear sled. The ACMs underwent a series of frontal and rear-end haversine crash pulses of varying severity, duration and peak acceleration. The accuracy and trigger thresholds of the different models and generations of EDRs were compared. There were different accuracy trends found between the early Generation 1 and the more modern Generation 2 and 3 EDRs.

The goal of this study was to use naturalistic driving data to characterize the longitudinal and lateral accelerations of vehicles making a left turn from a stop at signalized intersections. Left turn maneuvers at 15 intersections were extracted from the Second Strategic Highway Research Program (SHRP2) database. A subset of 420 traversals for lead vehicles that were initially stopped and negotiated their left turns unimpeded by oncoming traffic was used for the analysis. For each traversal, we extracted information regarding the driver’s sex and age, the vehicle type, the vehicle’s longitudinal and lateral acceleration, and on-board forward-facing video. From the video, we further extracted information about whether the road was dry/wet and if it was day/night, and from aerial photographs of the intersections we extracted the radius of each left turn path through the intersection.

The goal of this study was to use naturalistic driving data to characterize the motion of vehicles making right turns at signalized intersections. Right-turn maneuvers from 13 intersections were extracted from the Second Strategic Highway Research Program (SHRP2) database and categorized based on whether or not the vehicle came to a stop prior to making its turn. Out of the vehicles that did stop, those that were the first and second in line at the intersection were isolated. This resulted in 186 stopped first-in-line turns, 91 stopped second-in-line turns, and 353 no stop turns. Independent variables regarding the maneuver, including driver’s sex and age, vehicle type, speed, and longitudinal and lateral acceleration were extracted. The on-board video was reviewed to categorize the road as dry/wet and if it was day/night. Aerial photographs of the intersections were obtained, and the inner radius of the curve was measured using the curb as a reference.

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.