Trip-Based Explanatory Variables For Estimating Vehicle Fuel Consumption and Emission Rates

The current state-of-practice in the US for estimatingvehicle emissions is based on a single traffic-relatedexplanatory variable, namely average speed. Research,however, has demonstrated that the use of average speed asa single traffic-related variable is insufficient for theestimation of vehicle emissions. For example, although theEnvironmental Protection Agency (EPA) MOBILE5 model wouldindicate that a slowing of traffic typically increasesemissions, empirical research indicates the opposite inmany cases.The objective of this paper is to identify criticalaggregate trip variables as potential explanatory variablesfor the estimation of a vehicle's fuel consumption andemissions. Subsequently, statistical models for estimatingfuel consumption and emissions of hydrocarbon (HC), carbonmonoxide (CO), and oxides of nitrogen (NO_x) aredeveloped using these critical variables that include theaverage speed, speed variability, the level ofdeceleration, and the level of acceleration. The proposedmodels are demonstrated to be consistent with microscopicenergy and emission model estimates that are based on thevehicle's instantaneous speed and acceleration levels(coefficient of determination ranges from 0.88 to 0.96).     

Short-term wind speed forecasting based on random forest model combining ensemble empirical mode decomposition and improved harmony search algorithm

ABSTRACT

Wind speed forecasting plays an important role in power grid dispatching management. This article proposes a short-term wind speed forecasting method based on random forest model combining ensemble empirical modal decomposition and improved harmony search algorithm. First, the initial wind speed data set is decomposed into several ensemble empirical mode functions by EEMD, then feature extraction of each sub-modal IMF is performed using fast Fourier transform to solve the cycle of each sub-modal IMF. Next, combining the high-performance parameter optimization ability of the improved harmony search algorithm, two optimal parameters of random forest model, number of decision trees, and number of split features are determined. Finally, the random forest model is used to forecast the processing results of each submodal IMF. The proposed model is applied to the simulation analysis of historical wind data of Chaoyang District, Liaoning Province from April 27, 2015 to May 22, 2015. To illustrate the suitability and superiority of the EEMD-RF-IHS model, three types of models are used for comparison: single models including ANN, SVM, RF; EMD combination models including EMD-ANN, EMD-SVM, EMD-RF; EEMD combination models including EEMD-ANN, EEMD-SVM, EEMD-RF. The analysis results of evaluation indicators show that the proposed model can effectively forecast short-term wind data with high stability and precision, providing a reference for forecasting application in other industry fields.     

流动危险源毒气泄漏事故伤害模型研究

笔者介绍了危险货物道路运输的现状和特点，阐述了进行流动危险源事故后果分析的必要性，提出了流动危险源运动时毒气泄漏事故伤害模型，并利用该模型进行了数值模拟，证明该模型分析流动危险源运动时毒气泄漏事故的后果是可行的。     

公路运输化学事故应急救援体系研究

以动态源的定义为基础 ,结合危化品公路运输特殊性 ,阐述了危化品在公路运输过程中发生化学事故后应急救援的原则、工作特点与基本要求 ;提出化学事故应急救援中的基本任务是控制危险源 ,抢救受害人员 ,指导并组织群众疏散、自救和做好事故现场清理洗消工作 ,消除危害后果 ;提出公路运输化学事故应急救援预案系统建设的总体目标是 ,在应用ITS智能交通系统对动态源精确定位的基础上 ,建立公路运输化学事故应急救援预案动态库及应急救援组织保障系统和应急救援技术支持系统 ,一旦事故发生 ,能够做到尽快有效处理 ,最大限度地减小或消除事故损失。     

化工装置爆炸事故模式及预防研究

对建国以来我国已经发生的典型化工装置爆炸事故原因进行了统计分析 ,总结了爆炸危险性的影响因素。结合对已经发生的事故案例的剖析 ,提取并建立了装置内爆炸事故模式 ,对各种模式的爆炸机理和发生条件进行了初步的研究分析 ,并提出事故的预防措施 ,以期指导安全生产     

交通系统智能决策的算法研究

遗传算法是近年来迅速发展起来的一种全新的随机搜索与优化算法，但由于其自身固有的缺陷，通常优化过程的收敛速度较慢，局部搜索能力不足，而且算法稳定性较差。而蚁群算法广泛应用在旅行商问题计算中，目前是较好的求解最短路由问题的算法之一。就其自身来说有很多优点，如正反馈性、鲁棒性和智能性，但是在寻优过程中容易陷入局部最佳的缺点。针对上述情况，将遗产算法与蚁群算法相结合，用于实际交通系统寻找最优路径的问题中，并定义了目标函数，以路径可靠性和路径长度为优化目标，寻找最合适的救灾路线。最后通过实际计算结果的对比验证，说明了该方法的有效性。     

车辆事故紧急呼救技术发展综述

综述了车辆事故紧急呼救技术的原理,从车辆事故检测识别技术、移动车辆定位技术、无线通信技术和地理信息系统几方面概述车辆事故紧急呼救技术的研究内容。进一步介绍车辆事故紧急呼救技术的国内外研究和应用现状,并从车辆事故识别技术、地图匹配及组合导航、集群通信及通信网络几方面总结并指出车辆事故紧急呼救技术的关键技术和难点。展望了车辆事故紧急呼救技术的发展趋势,并就我国发展车辆事故呼救技术的可行性和发展方向进行探讨。     

基于事故理论的城市轨道交通风险评价模型研究

笔者分析了城市轨道交通事故,在分析我国其他行业事故分类的基础上,确定城市轨道交通事故分类标准,即重大事故、大事故、险性事故和一般事故,并将不同事故分类情况及专家判断评分,按事故的大小不同换算成可以计算的计算尺度,根据事故种类不同计算出事故折算因子,根据风险理论的评价方法,建立了地铁风险评价模型,对地铁的危险性进行量化定级,并通过具体实例进行综合分析评价,该风险评价模型具有一定的工程意义。     

危险货物道路运输系统的风险评价

分析了危险货物道路运输系统的风险影响因素,在此基础上建立了风险评价指标体系,并采用专家咨询法确定了各指标的权重,提出了使用模糊数学综合评价法对危险货物道路运输系统进行风险评价,并通过实例对评价模型进行了验证.结果表明,利用模糊综合评价的方法对危险货物道路运输系统的风险进行研究,可以为危险货物道路运输企业和交通安全监管部门对危险货物道路运输采取有效的安全控制措施,提供有益的参考.     

FACTORS AFFECTING WATERWAY INVESTMENT DECISIONS1

ABSTRACT: There are many factors, other than economic efficiency, which must be considered in judging the merits of proposed investments in the inland navigation system. No satisfactory formula exists for deciding the net worth of public investments in water resources projects. Such a measure would not be accepted because these investments can serve conflicting goals. Political, rather than technical, judgments are required to resolve these goal conflicts.