主成分分析法和德尔菲结合法的影响驾驶行为指标构建

为了构建影响驾驶行为的指标,统计了影响驾驶行为的41项因素。针对这些因素,制作了调查问卷,并对各个行业的120名驾驶员发放问卷。对收回的有效问卷结果进行统计,并采用主成分分析法和模糊德尔菲与灰色德尔菲法结合两种方法对问卷结果进行分析。主成分分析与德尔菲结合法都能有效地将驾驶员观点定量化,进而得到对驾驶员行为相对影响较大的指标。比较两种方法的分析结果,运用交叉法得到了19个主要影响驾驶行为的指标。     

Safety assessment of automated vehicles: how to determine whether we have collected enough field data?

Abstract

Objective: The amount of collected field data from naturalistic driving studies is quickly increasing. The data are used for, among others, developing automated driving technologies (such as crash avoidance systems), studying driver interaction with such technologies, and gaining insights into the variety of scenarios in real-world traffic. Because data collection is time consuming and requires high investments and resources, questions like “Do we have enough data?,” “How much more information can we gain when obtaining more data?,” and “How far are we from obtaining completeness?” are highly relevant. In fact, deducing safety claims based on collected data—for example, through testing scenarios based on collected data—requires knowledge about the degree of completeness of the data used. We propose a method for quantifying the completeness of the so-called activities in a data set. This enables us to partly answer the aforementioned questions.

Method: In this article, the (traffic) data are interpreted as a sequence of different so-called scenarios that can be grouped into a finite set of scenario classes. The building blocks of scenarios are the activities. For every activity, there exists a parameterization that encodes all information in the data of each recorded activity. For each type of activity, we estimate a probability density function (pdf) of the associated parameters. Our proposed method quantifies the degree of completeness of a data set using the estimated pdfs.

Results: To illustrate the proposed method, 2 different case studies are presented. First, a case study with an artificial data set, of which the underlying pdfs are known, is carried out to illustrate that the proposed method correctly quantifies the completeness of the activities. Next, a case study with real-world data is performed to quantify the degree of completeness of the acquired data for which the true pdfs are unknown.

Conclusion: The presented case studies illustrate that the proposed method is able to quantify the degree of completeness of a small set of field data and can be used to deduce whether sufficient data have been collected for the purpose of the field study. Future work will focus on applying the proposed method to larger data sets. The proposed method will be used to evaluate the level of completeness of the data collection on Singaporean roads, aimed at defining relevant test cases for the autonomous vehicle road approval procedure that is being developed in Singapore.     

国内关于旅游发展动力机制研究述评

旅游发展是一项系统工程,涉及到经济、社会、文化以及发展政策、旅游资源、消费趋势、旅游产品等方面的因素而不断发展.从旅游发展动力机制的角度,着重对我国旅游发展动力机制研究的理论框架、动力机制类型、区域旅游发展动力机制以及相关的案例进行述评,并结合当前我国旅游发展动力机制研究的趋势和重点,对旅游发展动力机制研究进行展望.     

辽宁省城市化发展水平区域差异及驱动力研究

采用复合指标方法对辽宁省14个省辖市的城市化发展水平进行了测度.结果表明,辽宁省内城市化发展水平呈现高低落差大的格局.根据测度结果进行城市化发展水平类型划分,探讨了影响城市化发展水平区域差异的驱动力,主要包括资源禀赋因素、经济因素、经济全球化因素、城市基础设施因素、历史和政策因素.     

美军核生化个体防护装备发展现状与趋势

美军认为,在核生化污染区域采取行动中,个体防护装备性能的高低和救治程序是否得当,直接关系到作战行动的成败。经过多年的不断发展,目前,美军士兵已配备了从防护面具到防护靴的全套防护装备,能够为士兵在核生化沾染区域作战提供全身有效防护,可有效防止士兵受到核生化战剂的侵害,从而保证了部队的战斗力。目前已呈现出了标准化、系列化程度高,防护性能好,生理负担低,舒适性高等发展特点。深入研究美军个体防护装备的发展现状与趋势,对于今后我军个体防护装备的发展具有十分重要的启示和借鉴意义。     

美英联军在伊拉克和阿富汗战场的伤害与防护

本文归纳总结了美英联军在伊拉克和阿富汗战场的主要伤害类型,分析了现代局部战争的主要伤害因素,指出了美英联军针对新的战场伤害特点所采取的防护措施。     

Adolescent, and their parents, attitudes towards graduated driver licensing and subsequent risky driving and crashes in young adulthood

Problem

Although Graduated Driver Licensing Systems (GDLS) have helped reduce young driver crash rates, they remain significantly over-represented in crash statistics. To be effective GDLS rely heavily on support for the legislation by those directly involved; parents to enforce the restrictions and adolescents to comply. There is some evidence that practices regarding GDLS restrictions influence adolescent driving outcomes in the early stage of licensure. However there has been no examination undertaken on the influence of parent and adolescent attitudes toward GDLS on adolescents’ driving behavior and crash experiences as they move into their young adult years. The aim of this research was to examine these relationships.

Method

This investigation was based on a longitudinal study of a birth cohort, and uses data collected when the cohort members were aged 15, 18, and 21 years. At age 15 both adolescent and their parent attitudes toward GDLS were measured. At age 18 adolescent GDLS attitudes were measured again. The association between these measures and self-reported risky driving behavior and crash involvement at age 21 were examined.

Results

Negative attitudes toward the learner supervisor restriction for males, and negative attitudes toward a GDLS for females were strongly associated with risky driving and crash involvement as young adults.

Impact on industry

Targeting interventions to improve adolescents and parents understanding of the reasons for graduated licensing and the specific restrictions may improve attitudes and views and thereby contribute to a reduction in risky driving behaviors and crash risk among young adults.     

真实条件下长时间作业的驾驶安全性影响研究

为研究长时间单调驾驶对驾驶员疲劳、嗜睡、反应时间和驾驶速度的确切影响,以合作企业3系重卡为操作对象进行了一组真实驾驶条件试验。在自愿的基础上随机地从合作企业物流公司选择12名经验丰富的驾驶员作为试验的驾驶员样本。试验采用主观评分方法记录试验者的嗜睡和疲劳状况,所有数据分析基于统计学软件PASW Statistic 18.0。试验结果表明长时间单调驾驶会导致驾驶员疲劳和嗜睡,而疲劳和嗜睡在一定的程度上会导致驾驶速度的加快,却没有导致驾驶员反应时间的显著变化。在持续驾驶3 h之后驾驶员的疲劳和驾驶绩效发生了明显劣化,故从安全的角度考虑应以2~3 h为界合理安排司机的作业负荷和绩效考评。     

基于多通道信息融合的疲劳驾驶行为分析研究

为了克服单一通道信息在驾驶疲劳行为判定中的局限性,提出了综合运用多通道信息融合共同判定驾驶疲劳行为的方法。该方法在充分考虑各信息源相关性和互补性的基础上,优化采用驾驶人疲劳特征ECD、车道偏离程度SAAE、方向盘转动程度SWA等疲劳判别指标,运用MVAR进行多维特征向量提取,以有向无环支持向量机为融合算法,建立了基于多分类支持向量机的驾驶疲劳行为判定模型。结果表明,运用DAG-SVM进行多通道信息决策提高了疲劳驾驶行为检测的准确性和可靠性。