Objectives: Nationally, animal–motor vehicle crashes (AVCs) account for 4.4% of all types of motor vehicle crashes (MVCs). AVCs are a safety risk for drivers and animals and many National Park Service (NPS) units (e.g., national park, national monument, or national parkway) have known AVC risk factors, including rural locations and substantial animal densities. We sought to describe conditions and circumstances involving AVCs to guide traffic and wildlife management for prevention of AVCs in select NPS units.
Methods: We conducted an analysis using NPS law enforcement MVC data. An MVC is a collision involving an in-transit motor vehicle that occurred or began on a public roadway. An AVC is characterized as a collision between a motor vehicle and an animal. A non-AVC is a crash between a motor vehicle and any object other than an animal or noncollision event (e.g., rollover crash). The final data for analysis included 54,068 records from 51 NPS units during 1990–2013. Counts and proportions were calculated for categorical variables and medians and ranges were calculated for continuous variables. We used Pearson’s chi-square to compare circumstances of AVCs and non-AVCs. Data were compiled at the park regional level; NPS parks are assigned to 1 of 7 regions based on the park’s location.
Results: AVCs accounted for 10.4% (5,643 of 54,068) of all MVCs from 51 NPS units. The Northeast (2,021 of 5,643; 35.8%) and Intermountain (1,180 of 5,643; 20.9%) regions had the largest percentage of the total AVC burden. November was the peak month for AVCs across all regions (881 of 5,643; 15.6%); however, seasonality varied by park geographic regions. The highest counts of AVCs were reported during fall for the National Capital, Northeast/Southeast, and Northeast regions; winter for the Southeast region; and summer for Intermountain and Pacific West regions.
Conclusions: AVCs represent a public health and wildlife safety concern for NPS units. AVCs in select NPS units were approximately 2-fold higher than the national percentage for AVCs. The peak season for AVCs varied by NPS region. Knowledge of region-specific seasonality patterns for AVCs can help NPS staff develop mitigation strategies for use primarily during peak AVC months. Improving AVC data collection might provide NPS with a more complete understanding of risk factors and seasonal trends for specific NPS units. By collecting information concerning the animal species hit, park managers can better understand the impacts of AVC to wildlife population health. 相似文献
Objective: To conduct near-side moving deformable barrier (MDB) and pole tests with postmortem human subjects (PMHS) in full-scale modern vehicles, document and score injuries, and examine the potential for angled chest loading in these tests to serve as a data set for dummy biofidelity evaluations and computational modeling.Methods: Two PMHS (outboard left front and rear seat occupants) for MDB and one PMHS (outboard left front seat occupant) for pole tests were used. Both tests used sedan-type vehicles from same manufacturer with side airbags. Pretest x-ray and computed tomography (CT) images were obtained. Three-point belt-restrained surrogates were positioned in respective outboard seats. Accelerometers were secured to T1, T6, and T12 spines; sternum and pelvis; seat tracks; floor; center of gravity; and MDB. Load cells were used on the pole. Biomechanical data were gathered at 20 kHz. Outboard and inboard high-speed cameras were used for kinematics. X-rays and CT images were taken and autopsy was done following the test. The Abbreviated Injury Scale (AIS) 2005 scoring scheme was used to score injuries.Results: MDB test: male (front seat) and female (rear seat) PMHS occupant demographics: 52 and 57 years, 177 and 166 cm stature, 78 and 65 kg total body mass. Demographics of the PMHS occupant in the pole test: male, 26 years, 179 cm stature, and 84 kg total body mass. Front seat PMHS in MDB test: 6 near-side rib fractures (AIS = 3): 160–265 mm vertically from suprasternal notch and 40–80 mm circumferentially from center of sternum. Left rear seat PMHS responded with multiple bilateral rib fractures: 9 on the near side and 5 on the contralateral side (AIS = 3). One rib fractured twice. On the near and contralateral sides, fractures were 30–210 and 20–105 mm vertically from the suprasternal notch and 90–200 and 55–135 mm circumferentially from the center of sternum. A fracture of the left intertrochanteric crest occurred (AIS = 3). Pole test PMHS had one near-side third rib fracture. Thoracic accelerations of the 2 occupants were different in the MDB test. Though both occupants sustained positive and negative x-accelerations to the sternum, peak magnitudes and relative changes were greater for the rear than the front seat occupant. Magnitudes of the thoracic and sternum accelerations were lower in the pole test.Conclusions: This is the first study to use PMHS occupants in MDB and pole tests in the same recent model year vehicles with side airbag and head curtain restraints. Injuries to the unilateral thorax for the front seat PMHS in contrast to the bilateral thorax and hip for the rear seat occupant in the MDB test indicate the effects of impact on the seating location and restraint system. Posterolateral locations of fractures to the front seat PMHS are attributed to constrained kinematics of occupant interaction with torso side airbag restraint system. Angled loading to the rear seat occupant from coupled sagittal and coronal accelerations of the sternum representing anterior thorax loading contributed to bilateral fractures. Inward bending initiated by the distal femur complex resulting in adduction of ipsilateral lower extremity resulted in intertrochanteric fracture to the rear seat occupant. These results serve as a data set for evaluating the biofidelity of the WorldSID and federalized side impact dummies and assist in validating human body computational models, which are increasingly used in crashworthiness studies. 相似文献
Objective: Derive lower leg injury risk functions using survival analysis and determine injury reference values (IRV) applicable to human mid-size male and small-size female anthropometries by conducting a meta-analysis of experimental data from different studies under axial impact loading to the foot–ankle–leg complex.Methods: Specimen-specific dynamic peak force, age, total body mass, and injury data were obtained from tests conducted by applying the external load to the dorsal surface of the foot of postmortem human subject (PMHS) foot–ankle–leg preparations. Calcaneus and/or tibia injuries, alone or in combination and with/without involvement of adjacent articular complexes, were included in the injury group. Injury and noninjury tests were included. Maximum axial loads recorded by a load cell attached to the proximal end of the preparation were used. Data were analyzed by treating force as the primary variable. Age was considered as the covariate. Data were censored based on the number of tests conducted on each specimen and whether it remained intact or sustained injury; that is, right, left, and interval censoring. The best fits from different distributions were based on the Akaike information criterion; mean and plus and minus 95% confidence intervals were obtained; and normalized confidence interval sizes (quality indices) were determined at 5, 10, 25, and 50% risk levels. The normalization was based on the mean curve. Using human-equivalent age as 45 years, data were normalized and risk curves were developed for the 50th and 5th percentile human size of the dummies.Results: Out of the available 114 tests (76 fracture and 38 no injury) from 5 groups of experiments, survival analysis was carried out using 3 groups consisting of 62 tests (35 fracture and 27 no injury). Peak forces associated with 4 specific risk levels at 25, 45, and 65 years of age are given along with probability curves (mean and plus and minus 95% confidence intervals) for PMHS and normalized data applicable to male and female dummies. Quality indices increased (less tightness-of-fit) with decreasing age and risk level for all age groups and these data are given for all chosen risk levels.Conclusions: These PMHS-based probability distributions at different ages using information from different groups of researchers constituting the largest body of data can be used as human tolerances to lower leg injury from axial loading. Decreasing quality indices (increasing index value) at lower probabilities suggest the need for additional tests. The anthropometry-specific mid-size male and small-size female mean human risk curves along with plus and minus 95% confidence intervals from survival analysis and associated IRV data can be used as a first step in studies aimed at advancing occupant safety in automotive and other environments. 相似文献