浅议云南省公路养护与环境保护对策

对公路养护施工中产生的环境影响进行了分析,提出了缓解措施和加强施工管理的建议。     

基于神经网络的闸阀模糊可靠度计算

为提高闸阀可靠度计算准确性,将模糊准则引入闸阀可靠性设计,将闸阀应力与阀体通径、内压之间隐式关系显式化,并基于神经网络构建地震工况下闸阀数学模型;利用蒙特卡洛法,计算闸阀在常规方法下的可靠度;利用正态型隶属函数描述闸阀强度的模糊性,计算闸阀在考虑模糊强度时的可靠度;对比强度的模糊性对可靠度计算结果的影响,分析不同隶属函...     

A transportation network assessment tool for hazardous material cargo routing: Weighing exposure health risks,proximity to vulnerable areas,delay costs and trucking expenses

The inherent risks associated with accidental releases of hazardous materials during transport have drawn attention and concerns in the recent decades. The aim of this study is to propose a tool for evaluation and comparison of the transportation networks which can be used to assess the routing options between origins and destinations of the cargos for their suitability for transporting hazardous material cargos by tanker trucks and to identify routes which provide lower accidental release risks, lower public exposure risks, and offer economical benefits. Each route segment of transportation networks were evaluated using specific criteria which included health risk and cost of delay in case of an accidental release of materials, trucking cost and proximity to vulnerable areas. Since, the health impact of hazardous materials differ depending on the characteristics of the material being transported as well as release quantities and atmospheric conditions; this paper aimed in providing a tool that can be used to estimate the impact radius (for health risks) after accidental release of hazardous materials by taking into account different atmospheric conditions based on the meteorological data and solar elevation angle. The Gaussian air dispersion model paired with ArcGIS using Python programming were employed to estimate the health risk impact zones by considering the meteorological data, and accordingly to analyze road segments for cost impacts (delay and trucking costs), and the proximity to vulnerable areas. The route assessment tool was demonstrated with a case study. The results of this study can efficiently aid decision makers for transportation of hazardous materials.     

基于BP神经网络的上市公司CEO报酬实证研究

近年来的研究表明,CEO报酬不仅受公司业绩的影响,还受到其他诸多因素的影响,而且,CEO报酬与其决定因素之间往往存在着非线性关系。本文以2003-2005年沪深股市的A股上市公司为样本,采用BP神经网络对CEO总报酬、CEO年薪、CEO持股价值及其决定因素分别进行训练和学习,结果表明：（1）网络训练输出值与实际值的拟合度分别达到91.09%、97.23%和78.44%;（2）网络的预测能力相对于传统的线性回归模型分别提高了92.72%、92.08%和53.89%。因此,本文认为在分析和确定CEO报酬水平时引入神经网络模型是可行的。     

Perceptions of safety on a shared road: Driving,cycling, or walking near an autonomous vehicle

Introduction: While improved safety is a highly cited potential benefit of autonomous vehicles (AVs), at the same time a frequently cited concern is the new safety challenges that AVs introduce. The literature lacks a rigorous exploration of the safety perceptions of road users who will interact with AVs, including vulnerable road users. Addressing this gap is essential because the successful integration of AVs into transportation systems hinges on an understanding of how all road users will react to their presence. Methods: A stated preference survey of the Phoenix, Arizona, metropolitan statistical area (Phoenix MSA) was conducted in July 2018. A series of ordered probit models was estimated to analyze the survey responses and identify differences between various population groups with respect to the perceived safety of driving, cycling, and walking near AVs. Results: Greater exposure to and awareness of AVs are not uniformly associated with increases in perceived safety. Various attitudinal factors, level of AV automation, and other intrinsic and extrinsic factors are related to safety perceptions of driving, walking, and cycling near AVs. Socioeconomic and demographic characteristics, such as gender, age, income, employment, and automobile usage and ownership, have various relationships with perceived safety. Conclusions: Cycling near an AV was perceived as the least safe activity, followed by walking and then driving near an AV. Both similarities and differences were observed among the factors associated with the perceived safety of different travel alternatives. Practical Applications: Public perception will guide the development and adoption of AVs directly and indirectly. To help maintain control of public perception, transportation planners, decision makers, and other stakeholders should consider more deliberate and targeted messaging to address the concerns of different road users. In addition, more careful pilot testing and more direct attention to vulnerable road users may help avoid a backlash that could delay the rollout of this technology.     

人工神经网络方法在拟建小区域环境质量评价中的应用

人工神经网络的评价方法用于小区域环境质量评价中,根据本地区特点因地制宜地选择环境质量参数,代入模型中进行环境质量评价及预测,对用于环境质量评价的BP人工神经网络模型进行了改进,即对网络模型的训练样本进行了扩充,从而提高了模型的抗干扰能力和准确性.将改进了的BP人工神经网络模型应用于四川省资阳市沱江二桥拟建项目小区域的大气、地表水环境质量评价中, 对该市小区域大气、地表水环境质量状况进行评价,评价结果表明,BP人工神经网络模型用于环境质量评价是可行的,且评价结论客观,评价模型普遍适用.     

人行横道危险时段的灰色聚类评价研究

人行横道是人车冲突的焦点地带,以行人违规率(RTI)为评价指标,采用灰色聚类的评价方法,对人行横道的安全状况进行分级评价,然后对单条人行横道的不同时间段的安全状况进行评价,找出危险时段.     

基于模糊神经网络的机动车驾驶教练员职业适宜性研究

提出应用模糊神经网络系统,建构教练员职业适宜性的3个要素(即心理素质、驾驶技能和知识的表达阐述能力)的学习样本,分析"三要素"的8项特征参数指标——场依存性、速度估计能力、交通安全意识、简单反应、选择反应、跟踪能力、行车注意力、表达阐述能力等,使用K-均值法对实验样本进行初始分类,形成标准学习样本,使用该样本对所构建系统进行训练和调试。利用经调试训练后的系统,依据所测教练员的心理、心理参数对其职业适宜性进行评价。试验表明:建立的教练员职业适宜性仿真模型能取得很好的评价效果。     

AHP-SWOT法在道路交通安全改善策略中的应用

针对交通事故的特点,探讨AHP-SWOT方法在道路交通事故评价中的具体应用。SWOT(优势—劣势,机会—威胁)分析法是一种综合考虑系统外部环境和内部条件的各种因素,对其进行系统评价并从中选择最佳策略的方法,但是它缺少定量分析的过程。AHP(层次分析法)具有定性分析和定量分析相结合的优势,采用SWOT和AHP相结合的方法进行评价更加合理和准确。将AHP-SWOT方法应用于道路交通安全评价系统,分析道路交通安全系统所面临的机会和威胁、所处的优势和劣势,可为正确评价道路安全水平、制定合理的道路交通安全改善策略提供理论指导。实例证明该方法可行有效。     

道路交叉口冲突仿真分析

针对基于事故的安全评价在数量、周期、均值、随机性等方面以及基于现场冲突观测识别在主观性、可靠性、成本、指标全面性等方面存在的问题,提出基于冲突仿真的交叉口安全预评价分析方法:研究利用安全间接分析(SSAM)模型分析冲突的基本原理和冲突时间(TTC)、遭遇时间(PET)等分析指标的计算方法;以及利用VISSIM仿真软件进行冲突仿真分析应注意的策略。以邢台市某道路交叉口安全改善方案为例,进行改善前后冲突仿真的比较分析。研究结果表明,改善后在通行效率显著提升的同时,交叉、追尾、车道变换冲突的数量均显著减少,TTC值有所增加,说明改善后安全程度有所提升。笔者提出的方法和案例应用为道路交叉口改善措施的安全预评价提供了一种分析途径和有益借鉴。