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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.

Modern vehicles record dynamic data from a number of on-board sensors for events that could precede a crash. These data can be used to reconstruct the behavior of a vehicle, although the accuracy of these reconstructions has not yet been quantified. Here, we evaluated various methods of reconstructing the vehicle kinematics of a 2017 and a 2018 Toyota Corolla based on Vehicle Control History (VCH) data from overlapping events generated by the pre-collision system (PCS), sudden braking (SB) and anti-lock brake (ABS) activation. The vehicles were driven towards a stationary target at 32-64 km/h (20-40 mph) and then after the pre-collision alarm sounded the vehicle was steered sharply right or left and braked rapidly to rest. VCH data for PCS event were recorded at 2 Hz and for the sudden braking and ABS activation events at 6.7 Hz.

Newer Toyota vehicles store information about more than 50 parameters for 5 s before and after non-collision events in the Vehicle Control History (VCH) records. The goals of this study were to assess the accuracy of VCH data acquired during Autonomous Emergency Braking (AEB) events and to investigate the effects of speed, acceleration, and system settings on AEB performance. A 2017 Toyota Corolla with Safety Sense P Pre-Collision System (PCS) was driven in a straight line towards a car-like target at different combinations of four speeds (20, 25, 30, and 40 km/h; or 12, 15, 19, and 25 mph) and three accelerator pedal positions (constant 30%, 40%, and 50% accelerator opening ratios) until the AEB system activated. The vehicle speed, vehicle acceleration, radar target closing speed, and radar target distance recorded in the VCH were compared to a reference 5th wheel. We found that errors in the VCH distance, speed, and acceleration data varied with the test conditions.

The Pre-Collision System (PCS) in Toyota’s Safety Sense package includes an autonomous emergency braking feature that can stop or slow a vehicle independent of driver input if there is an impending collision. The goals of this study were to determine how hazard characteristics, specifically radar reflector size and degree of target edge contrast, affect the response of the PCS, as well as to scrutinize tests wherein the PCS failed to stop the vehicle before impact. We conducted 80 tests with a 2017 Toyota Corolla driven towards a car-like target in a straight line and under constant accelerator pedal position, reaching about 30 km/h at the PCS alarm. Vehicle speed and distance to target at the alarm flag (ALM) and at times corresponding to three other system flags (PBA, FPB, and PB) were read from the Vehicle Control History records. Time to impact (TTI) at each flag was calculated and the distance between the stopped vehicle and the target was measured for each test.

Collision related data stored in the airbag control modules (ACM's) of Toyota vehicles can provide useful information to collision investigators, including both front and rear collision severity. Previous studies of ACM's from other manufacturers found that the devices underestimated the actual speed change in low speed frontal collisions. To quantify the accuracy and sensitivity of select 2005 to 2008 Toyota ACM's, in-vehicle crash tests and linear sled tests were performed in both front and rear impact orientations. A 2005 Toyota Corolla with five extra ACM's mounted in the right front seat position underwent a series of vehicle-to-barrier collisions with speed changes of up to 10 km/h. Next, the same six Toyota ACMs underwent a range of crash pulses using a linear sled. In all in-vehicle tests, the speed change reported by the ACM underestimated the actual speed change for frontal collisions, and overestimated the actual speed change for rear-end collisions.

Quantifying the energy associated with vehicle damage is the basis of common methods used to reconstruct car crashes. This study sought to characterize the relationship between crush and energy for the front and rear surfaces of a passenger car. Nine stationary barrier crash tests and one aligned car-to-car test were conducted using several cars of the same model with impact speeds ranging from 4.3 to 15.2 m/s generating as much as 0.47 m of crush. The results revealed a linear speed-crush relationship for front and rear car surfaces and a restitution coefficient that decreased from a maximum of 0.33 at low speed to a relatively constant value of 0.15 for crush levels above 0.2 m. Crush coefficients derived from the crash tests were compared to the coefficients from three other sources: i) default values from the CRASH3 computer program, ii) values from a published database and iii) values derived from an assumed damage threshold value and an NHTSA high-speed crash test.

The sampling rate and synchronization of the pre-impact data stored by General Motors (GM) sensing and diagnostic modules (SDMs) have not been experimentally determined. The goals of this study were to measure the time shift between the SDM-reported data times and algorithm enable, sampling rate variation and the synchronization of the sensor data. In this study, two experiments were performed. First, the SDM of a 2002 Pontiac Sunfire was artificially triggered while the throttle position, engine speed, vehicle speed and brake signals were also being monitored at their source sensors. Second, the throttle and vehicle speed sensors were replaced with artificially generated inputs so the timing of the SDM recorded values could be compared to that of the known inputs. Sampling rate and data synchronization were determined by fitting the SDM recorded values to the measured sensor outputs.

The Vetronix Crash Data Retrieval (CDR) system can download information recorded by the restraint control module (RCM) of newer Ford vehicles. In an earlier study, a 2003 Ford Crown Victoria and a 2003 Ford Windstar were exposed to 84 staged collisions with speed changes up to 13.5 km/h. After each test, crash data was downloaded from the RCM using version 2.1 of the Vetronix CDR software. In this study, the crash data was re-analyzed using the current version 2.4 of the software. Unlike version 2.1, version 2.4 did not report duplicate data points. Version 2.4 reported more accurate speed changes for the Windstar (average underestimate of 0.23 km/h) RCM but less accurate speed changes for the Crown Victoria (average underestimate of 0.73 km/h).

Crash data stored in the airbag sensing and diagnostic modules (SDMs) of General Motors vehicles can provide useful information for accident investigators. To quantify the accuracy and sensitivity of select 2003 to 2004 SDMs, two types of tests were performed. First, three 2004 vehicles underwent 136 vehicle-to-barrier and vehicle-to-vehicle collisions with speed changes up to 8 km/h. Second, 2003 and 2004 model year SDMs underwent a range of crash pulses using a linear sled. In all of the tests the speed change reported by the SDM underestimated the actual speed change. The speed change underestimates ranged from 0.2 to 2.9 km/h except for several anomalous tests in which the underestimate was as high as 12.3 km/h. The magnitude of this error varied with crash pulse shape. Increasing crash pulse duration and decreasing peak acceleration increased the difference between the actual and SDM reported speed change. The threshold accelerations for the SDMs tested ranged from 1.1 to 2.7g.

Two methods for calculating speed from curved tire marks were investigated. The commonly used critical speed formula and a computer simulation program were evaluated based on their ability to reproduce the results of full-scale yaw tests. The effects of vehicle braking and friction coefficient were studied. Twenty-two yaw tests were conducted at speeds between 70 and 120 km/h. For half of the tests, about 30% braking was applied. Using the measured sliding coefficient of friction, both the critical speed formula and the computer simulations under-predicted the actual speed of the vehicle. Using the measured peak coefficient of friction, both methods over-estimated the actual speed. There was less variance in the computer simulation results. Braking tended to increase the speeds calculated by the critical speed formula.

Crash data recorded by the restraint control module (RCM) installed in newer Ford passenger vehicles have recently become available to investigators. To quantify the accuracy of the crash data in low-speed collisions, two RCM-equipped vehicles were exposed to 84 aligned frontal barrier collisions with speed changes up to 13.5 km/h. The accuracy of the speed change reported by the RCM ranged from an underestimate of 1.8 km/h to an overestimate of 0.3 km/h. The error varied with speed change. The RCMs were mounted on a linear sled to investigate their sensitivity to specific collision pulse parameters. For both RCMs, the first eight acceleration data points were duplicated at the end of the data and the record of the crash pulse was often incomplete. Based on the results of this study, crash investigators need to carefully interpret the RCM-reported acceleration and speed change data before using it to reconstruct low-speed collisions involving Ford vehicles.

Most 1999 and newer General Motors (GM) vehicles have an event data recorder (EDR) that can record pre-crash speed incorporated into the airbag sensing and diagnostic module (SDM). The accuracy of the SDM-reported pre-crash speed over a wide range of speeds has not been previously tested and reported. In this study, the SDMs of three late-model GM passenger cars were artificially triggered while driving at a constant speed between 1 and 150 km/h. The SDM-reported pre-crash speeds were compared to speeds measured by a calibrated 5th-wheel of known accuracy. The results showed that the accuracy of the SDM-reported pre-crash speed varied with both speed and vehicle. The overall uncertainty associated with all three SDMs tested varied from a 1.5 km/h overestimation of vehicle speed at low speeds to a 3.7 km/h underestimation of vehicle speed at high speeds.

Adrian's visibility model is a useful tool for assessing the visibility of an object at night. However, it was developed under laboratory conditions. Thus, it is necessary to determine the visibility levels which are required for detection under nighttime driving conditions. Experimental data from Olson et al were applied to the Adrian visibility model to determine visibility levels at target detection for alerted drivers. The data has been modified to account for experimental delay in the recorded detection points and a correction has been applied to assess driver expectation. Driver age, headlight beam pattern, and target reflectivity were all found to have a significant effect on visibility level at target detection. For alerted drivers, 50th-percentile threshold visibility levels between 1 and 23 were calculated. For unalerted drivers, 50th-percentile threshold visibility levels between 13 and 210 were calculated.

Collision data stored in the airbag sensing and diagnostic module (SDM) of 1996 and newer GM vehicles have become available to accident investigators through the Vetronix Crash Data Retrieval system. In this study, two experiments were performed to investigate the accuracy and sensitivity of the speed change reported by the SDM in low-speed crashes. First, two SDM-equipped vehicles were subjected to 260 staged frontal collisions with speed changes below 11 km/h. Second, the SDMs were removed from the vehicles and exposed to a wide variety of collision pulses on a linear motion sled. In all of the vehicle tests, the speed change reported by the SDM underestimated the actual speed change of the vehicle. Sled testing revealed that the shape, duration and peak acceleration of the collision pulse affected the accuracy of the SDM-reported speed change. Data from the sled tests were then used to evaluate how the SDM-reported speed change was calculated.

The purpose of this paper was to compare the damage to pickup truck bumpers produced by vehicle-to-barrier and vehicle-to-vehicle collisions of a similar severity, in order to determine whether vehicle-to-barrier tests can serve as surrogates for vehicle-to-vehicle tests in accident reconstruction. Impact tests were conducted on the front and rear bumpers of five pickup trucks. Each truck was subjected to an impact with a fixed barrier and with a passenger vehicle. All impacts resulted in pickup truck speed changes of about 8 km/h. Damage produced in the barrier and vehicle-to-vehicle collisions was similar if both collisions resulted in bumper mount damage on the pickup truck. If there was no bumper mount damage, then the bumper beam deformation depended on the shape of the impactor.