Objective: Powered mobility devices (PMDs) are commonly used as aids for older people and people with disabilities, subgroups of vulnarable road users (VRUs) who are rarely noted in traffic safety contexts. However, the problem of accidents involving PMD drivers has been reported in many countries where these vehicles have become increasingly popular.The aim of this study is to extract and analyze national PMD-related accident and injury data reported to the Swedish Traffic Accident Data Acquisition (STRADA) database. The results will provide valuable insight into the risks and obstacles that PMD drivers are exposed to in the traffic environment and may contribute to improving the mobility of this group in the long term.Methods: The current study is based on data from 743 accidents and 998 persons. An analysis was performed on a subset of data (N?=?301) in order to investigate the development of accidents over a period of 10 years. Thereafter, each accident in the whole data set was registered as either single (N?=?427) or collision (N?=?315).Results: The results show that there was a 3-fold increase in the number of PMD-related accidents reported to STRADA during the period 2007–2016.With regard to single accidents, collisions, as well as fatalities, the injury statistics were dominated by males. Single accidents were more common than collisions (N?=?427 and N?=?316, respectively) and the level of injury sustained in each type of accident is on par. The vast majority of single accidents resulted in the PMD driver impacting the ground (87%), due to either PMD turnover (71%) or the driver falling out of the PMD (16%). The reason for many of the single accidents was a difference in ground level (34%, typically a curb).Cars, trucks, or buses were involved in 67% of collision events; these occured predominantly at junctions or intersections (70%).Abbreviated Injury Scale (AIS) 3+ injuries were dominated by hip and head injuries in both single accidents and collision events.Conclusions: The present study shows that further research on PMD accidents is required, with regard to both single accidents and collision events. To ensure that appropriate decisions are made, future work should follow up on injury trends and further improve the quality of PDM-related accident data. Improved vehicle stability and design, increased usage of safety equipment, proper training programs, effective maintenance services, and development of a supporting infrastructure would contribute to increased safety for PMD drivers. 相似文献
A Pb-Zn tailings pond, abandoned for approximately 90 years, has been naturally colonized by Glyceria fluitans and is an excellent example of long-term metal retention in tailings ponds under various water cover and vegetation conditions. Shallow/intermittently flooded areas (dry zone) were unvegetated and low in organic matter (OM) content. Permanently flooded areas were either unvegetated with low OM, contained dead vegetation and high OM, or living plants and high OM. It was expected that either water cover or high OM would result in enhanced reducing conditions and lower metal mobility, but live plants would increase metal mobility due to root radial oxygen loss. The flooded low OM tailings showed higher As and Fe mobility compared with dry low OM tailings. In the permanently flooded areas without live vegetation, the high OM content decreased Zn mobility and caused extremely high concentrations of acid-volatile sulfides (AVS). In areas with high OM, living plants significantly increased Zn mobility and decreased concentrations of AVS, indicating root induced sediment oxidation or decreased sulfate-reduction. This is the first study reporting the ability of wetland plants to affect the metal mobility and AVS in long-term (decades), unmanaged tailings ponds. 相似文献
In this paper, we present a three-step methodological framework, including location identification, bias modification, and out-of-sample validation, so as to promote human mobility analysis with social media data. More specifically, we propose ways of identifying personal activity-specific places and commuting patterns in Beijing, China, based on Weibo (China’s Twitter) check-in records, as well as modifying sample bias of check-in data with population synthesis technique. An independent citywide travel logistic survey is used as the benchmark for validating the results. Obvious differences are discerned from Weibo users’ and survey respondents’ activity-mobility patterns, while there is a large variation of population representativeness between data from the two sources. After bias modification, the similarity coefficient between commuting distance distributions of Weibo data and survey observations increases substantially from 23% to 63%. Synthetic data proves to be a satisfactory cost-effective alternative source of mobility information. The proposed framework can inform many applications related to human mobility, ranging from transportation, through urban planning to transport emission modeling.
