Investigation of seat belt use among the drivers of different education levels

Seat belt use habit has been investigated according to the education level of drivers. Copies of a questionnaire were distributed to 1000 participants of four different education levels. Factors such as seat belt usage habit, restricting factors and crash data have been investigated. Data have been analyzed with SPSS 15.0 software. Increased level of education leads to increased seat belt usage, lower numbers of crashes and crash severities. The factors restricting seat belt use are lack of habit, discomfort and short distance driving. The use of precaution signal and increases in comfort can increase seat belt usage. The primary and high school education on traffic safety and seat belt usage has been serving the purpose.     

我国危险化学品道路运输的现状与对策研究

随着我国工业和经济的发展,危险化学品的需求量越来越大,危险化学品的道路运输也越来越频繁,由危险化学品道路运输而引发的事故也越来越多。为此,必须基于我国危险化学品道路运输的现状,借鉴发达国家在危险化学品道路运输方面较成熟的经验,提出符合我国国情的危险化学品道路运输安全管理的对策,以达到减少危险化学品道路运输事故发生的目的,最大限度地降低由危险化学品道路运输事故引起的生命财产的损失。     

地震灾害紧急救援可支配交通链路选择研究

如何通过科学的算法提前获取决定路网通达性的关键链路,即可支配链路,从而可通过各方面养护措施提高可支配链路的抗震能力,保证震后救援运输的顺利进行。提出可支配链路的相关概念,基于矩阵结构的计算方法与原理,并应用算例进行验证。通过选取云南省保山市隆阳区的部分目标区域来进行震后救援路网的支配性链路计算,同时针对地震发生后的特点,综合考虑医疗救援、火灾救援及紧急物资救援3方面的综合救援需求,获得该区域路网的可支配链路。研究结果表明:结合震后实际救援需求,将需求点扩展为多个需求点,能够进一步获得在多个需求点基础上的可支配链路。因此,利用矩阵结构获得可支配链路的方法,能够综合需求点数量和概率临界值的进一步调整,进一步优化计算结果。     

环保多功能沥青除冰路面一体化设计研究

依托湖北杭瑞高速公路工程,为降低沿线行车通过居民区带来的噪音污染,解决冬季路面积雪薄冰带来的行车安全问题,以具有一定结构除冰性能的高连通孔隙沥青路面材料为基体,选用橡胶高黏度改性沥青,并掺入环保型化学抑冰剂,开发设计具有除冰、降噪、抗滑功能材料路面。以不牺牲路用性能为前提,通过测试动稳定度、冻融劈裂强度比、飞散损失、抗剪强度等,确定环保型化学抑冰剂的掺量。同时利用驻波管法、手工铺砂法及轮碾法测定空隙率分别为16%、20%、24%、28%的路面材料除冰性能、降噪性能和抗滑性能。测试结果表明,当环保型融雪除冰剂的掺量为2%,空隙率控制在20%左右时,高连通孔隙沥青材料的路面使用性能最佳,具有较好的除冰性能、降噪性能和抗滑性能。     

Permeability of Roads to Movement of Scrubland Lizards and Small Mammals

A primary objective of road ecology is to understand and predict how roads affect connectivity of wildlife populations. Road avoidance behavior can fragment populations, whereas lack of road avoidance can result in high mortality due to wildlife‐vehicle collisions. Many small animal species focus their activities to particular microhabitats within their larger habitat. We sought to assess how different types of roads affect the movement of small vertebrates and to explore whether responses to roads may be predictable on the basis of animal life history or microhabitat preferences preferences. We tracked the movements of fluorescently marked animals at 24 sites distributed among 3 road types: low‐use dirt, low‐use secondary paved, and rural 2‐lane highway. Most data we collected were on the San Diego pocket mouse (Chaetodipus fallax), cactus mouse (Peromyscus eremicus), western fence lizard (Sceloporus occidentalis), orange‐throated whiptail (Aspidoscelis hyperythra), Dulzura kangaroo rat (Dipodomys simulans) (dirt, secondary paved), and deer mouse (Peromyscus maniculatus) (highway only). San Diego pocket mice and cactus mice moved onto dirt roads but not onto a low‐use paved road of similar width or onto the highway, indicating they avoid paved road substrate. Both lizard species moved onto the dirt and secondary paved roads but avoided the rural 2‐lane rural highway, indicating they may avoid noise, vibration, or visual disturbance from a steady flow of traffic. Kangaroo rats did not avoid the dirt or secondary paved roads. Overall, dirt and secondary roads were more permeable to species that prefer to forage or bask in open areas of their habitat, rather than under the cover of rocks or shrubs. However, all study species avoided the rural 2‐lane highway. Our results suggest that microhabitat use preferences and road substrate help predict species responses to low‐use roads, but roads with heavy traffic may deter movement of a much wider range of small animal species.     

北京市25种公路绿化植物及配置模式的绿量

计量研究公路绿地的生态服务功能有助于科学评估公路绿化的无形价值。以北京市顺义区顺平路(S305)的绿化植物群落为研究对象,运用WinScanopy For Canopy Analysis冠层分析仪采集数据,研究了公路绿化常见植物及配置模式的绿量率,并建立了25种公路绿化常见植物的绿量率模型,以期为公路绿化树种选择和群落配置提供基础分析与参考。结果表明:阔叶乔木的绿量率在3.02~4.80之间,针叶乔木的绿量率集中在4~6之间,灌木植物的绿量率较小,种植紧凑的绿篱绿量率达到3.94;不同配置模式的群落绿量率大小顺序依次为:针阔混交林>阔叶林>针叶林>灌木群落。其研究结果为公路绿化建设和绿地生态效益的计量提供了科学依据。     

基于ARIMA-LOESS模型的危化品道路运输事故起数预测

文章针对危化品道路运输事故预测问题,运用差分自回归移动平均模型(Autoregressive Integrat-ed Moving Average,ARIMA)与局部加权回归模型(Locally Estimated Scatterplot Smoothing,LOESS)的组合模型,对我国危化品道路运输事故发生起数进行...     

An in-depth analysis of self-reported cycling injuries in single and multiparty bicycle crashes in Denmark

Introduction: Cycling is one of the main forms of transportation in Denmark. However, while the number of traffic crash fatalities in the country has decreased over the past decade, the frequency of cyclists killed or seriously injured has increased. The high rate of serious injuries and fatalities associated with cycling emphasizes the increasing need for mitigating the severity of such crashes. Method: This study conducted an in-depth analysis of cyclist injury severity resulting from single and multiparty bicycle-involved crashes. Detailed information was collected using self-reporting data undertaken in Denmark for a 12-month period between 1 November 2012 and 31 October 2013. Separate multilevel logistic (MLL) regression models were applied to estimate cyclist injury severity for single and multiparty crashes. The goodness-of-fit measures favored the MLL models over the standard logistic models, capturing the intercorrelation among bicycle crashes that occurred in the same geographical area. Results: The results also showed that single bicycle-involved crashes resulted in more serious outcomes when compared to multiparty crashes. For both single and multiparty bicycle crash categories, non-urban areas were associated with more serious injury outcomes. For the single crashes, wet surface condition, autumn and summer seasons, evening and night periods, non-adverse weather conditions, cyclists aged between 45 and 64 years, male sex, riding for the purpose of work or educational activities, and bicycles with light turned-off were associated with severe injuries. For the multiparty crashes, intersections, bicycle paths, non-winter season, not being employed or retired, lower personal car ownership, and race bicycles were directly related to severe injury consequences. Practical Applications: The findings of this study demonstrated that the best way to promote cycling safety is the combination of improving the design and maintenance of cycling facilities, encouraging safe cycling behavior, and intensifying enforcement efforts.     

Investigating factors affecting severity of large truck-involved crashes: Comparison of the SVM and random parameter logit model

Introduction: Reducing the severity of crashes is a top priority for safety researchers due to its impact on saving human lives. Because of safety concerns posed by large trucks and the high rate of fatal large truck-involved crashes, an exploration into large truck-involved crashes could help determine factors that are influential in crash severity. The current study focuses on large truck-involved crashes to predict influencing factors on crash injury severity. Method: Two techniques have been utilized: Random Parameter Binary Logit (RPBL) and Support Vector Machine (SVM). Models have been developed to estimate: (1) multivehicle (MV) truck-involved crashes, in which large truck drivers are at fault, (2) MV track-involved crashes, in which large truck drivers are not at fault and (3) and single-vehicle (SV) large truck crashes. Results: Fatigue and deviation to the left were found as the most important contributing factors that lead to fatal crashes when the large truck-driver is at fault. Outcomes show that there are differences among significant factors between RPBL and SVM. For instance, unsafe lane-changing was significant in all three categories in RPBL, but only SV large truck crashes in SVM. Conclusions: The outcomes showed the importance of the complementary approaches to incorporate both parametric RPBL and non-parametric SVM to identify the main contributing factors affecting the severity of large truck-involved crashes. Also, the results highlighted the importance of categorization based on the at-fault party. Practical Applications: Unrealistic schedules and expectations of trucking companies can cause excessive stress for the large truck drivers, which could leads to further neglect of their fatigue. Enacting and enforcing comprehensive regulations regarding large truck drivers’ working schedules and direct and constant surveillance by authorities would significantly decrease large truck-involved crashes.     

大型公园道路网络关键节点脆弱性评价

为更加科学有效地辨识景区道路网络中的客流关键节点,以节点脆弱性为度量指标,提出1种基于FIM模型的关键节点脆弱性评价方法.以某大型公园为例,首先通过ArcGIS软件将该公园的道路网络信息转换成可编译的文本信息,经过Java枚举可行路径,然后利用嵌入FIM算法的Lingo进行优化,得出网络节点的重要度.最后综合节点容量、...