A new statistical method of assigning vehicles to delivery areas for CO2 emissions reduction

Transportation CO₂ emissions are expected to increase in the following decades, and thus, new and better alternatives to reduce emissions are needed. Road transport emissions are explained by different factors, such as the type of vehicle, delivery operation and driving style. Because different cities may have conditions that are characterized by diversity in landforms, congestion, driving styles, etc., the importance of assigning the proper vehicle to serve a particular region within the city provides alternatives to reduce CO₂ emissions. In this article, we propose a new methodology that results in assigning trucks to deliver in areas such that the CO₂ emissions are minimized. Our methodology clusters the delivery areas based on the performance of the vehicle fleet by using the k-means algorithm and Tukey’s method. The output is then used to define the optimal CO₂ truck-area assignment. We illustrate the proposed approach for a parcel company that operates in Mexico City and demonstrate that it is a practical alternative to reduce transportation CO₂ emissions by matching vehicle type with delivery areas.     

Learning User Intention in Networked Mobile Robot Control

Teleoperated networked robot often has unpredictable behaviors due to uncertain time delay from data transmission over Internet. The robot cannot accomplish the desired actions of the remote operator in time, which severely impairs reliability and efficiency of the robot system. This paper investigated a novel approach, learning user intention, to compensate the uncertain time delay with the autonomy of a mobile robot. The user intention to control and operate the robot was modeled and incrementally inferred based on Bayesian techniques so that the desired actions could be recognized and completed by the robot autonomously. Thus the networked robot is able to fulfill the task assigned without frequent interaction with the user, which decreases data transmission and improves the efficiency of the whole system. Experimental results show the validity and feasibility of the proposed method.     

基于理性推理的观点演化模型

针对现实生活中个体观点形成中的理性推理过程,提出了一种基于DS（Dempster-Shafer）证据理论的观点更新规则,并在连续观点离散决策的框架下,对个体如何利用其他个体的意见和相关知识来形成自身意见的过程进行建模.实验仿真结果表明,群体中能够出现观点一致、分散等常见的舆论现象,观点演化过程中伴随着知识由确定性个体向不确定性个体的扩散,同时发现在规则网络中,意见领袖的观点的影响力在扩散过程中是逐渐减弱的,其影响范围与个体对知识不确定性的接受程度密切相关.     

大型油船和集装箱船静水弯矩的统计特性研究

本文介绍了国内外静水弯矩的研究现状，对Soares和Moan的经验回归公式进行了详细讨论，发现不同的研究人员对静水弯矩统计特征的认识存在相当大的差异。文中对静水弯矩均值和变异系数对船舶总纵强度安全指数的敏感度进行了分析，发现均值比变异系数更加重要。在分析和比较的基础上，根据简单可靠的原则，对集装箱船和油船的静水弯矩统计特征计算提出了如下建议：集装箱船，Cov=0．30；油船，满载（中垂）时，Cov＝0．4，压载（中拱）时，Cov=0．70。     

舰船材料疲劳统计分析中的贝叶斯方法

讨论了舰船材料疲劳统计分析中的贝叶斯方法,将疲劳模型中的未知参数作为随机变量处理,利用贝叶斯定理求出参数的后验分布密度,然后建立不同存活率下的贝叶斯疲劳曲线的求解方程;最后再编程进行计算,结果表明,贝叶斯方法既考虑了统计上的不确定性,又合理解决了疲劳试验数据中的越出问题。     

《汽车工程》论文及参考文献的统计分析

《汽车工程》１９９１－１９９５年共参表论文２３８篇,附参考谳３４２篇,本文针对《汽车工程》论文发表时差,论文作者情况,参考文献数量,语种,类型以及被引中文期刊,作者等有关信息进行定量统计,客观地对《汽车工程》论文及参考文献的一般规律进行了评价。     

黄土地区公铁涵洞病害特征及其差异性对比研究

为了对比研究黄土地区铁路涵洞和公路涵洞出现的病害特征及其差异性,以青海省境内黄土区的高等级公路408座涵洞和兰西铁路59座涵洞为调查实例,对其病害类型、发育特征等进行统计分析。结果表明:青海东部黄土地区高等级公路涵洞出现的病害类型主要有8类,分别是涵洞下沉、涵顶路面开裂、翼墙沉降开裂或倾斜错位、涵节错位或填缝脱落、基础开裂、内部积水淤塞、进出口积水淤塞、涵背填土塌陷等。相对于公路涵洞病害,青海东部黄土地区兰西铁路涵洞病害类型比较单一,出现的病害类型主要是涵洞内部积水和进出口积水等。发育程度以轻微居多,中等病害的比例很小,严重病害的比例极其少有,基本没有出现涵顶路(轨)面开裂或沉降的情况。公铁涵洞病害差异性是由涵洞结构自身特征、荷载及受力特征、地基岩土体特性、施工因素、管养模式等综合因素导致的,应对公铁涵洞病害类型及其发育程度的划分标准区别对待,同时应考虑特殊岩土体地基特性的影响。     

An integrated solution for lane level irregular driving detection on highways

Global Navigation Satellite Systems (GNSS) has been widely used in the provision of Intelligent Transportation System (ITS) services. Current meter level system availability can fulfill the road level applications, such as route guide, fleet management and traffic control. However, meter level of system performance is not sufficient for the advanced safety applications. These lane level safety applications requires centimeter/decimeter positioning accuracy, with high integrity, continuity and availability include lane control, collision avoidance and intelligent speed assistance, etc. Detecting lane level irregular driving behavior is the basic requirement for these safety related ITS applications. The two major issues involved in the lane level irregular driving identification are accessing to high accuracy positioning and vehicle dynamic parameters and extraction of erratic driving behaviour from this and other related information. This paper proposes an integrated solution for the lane level irregular driving detection. Access to high accuracy positioning is enabled by GNSS and Inertial Navigation System (INS) integration using filtering with precise vehicle motion models and lane information. The detection of different types of irregular driving behaviour is based on the application of a Fuzzy Inference System (FIS). The evaluation of the designed integrated systems in the field test shows that 0.5 m accuracy positioning source is required for lane level irregular driving detection algorithm and the designed system can detect irregular driving styles.     

An integrated Bayesian approach for passenger flow assignment in metro networks

This paper proposes an integrated Bayesian statistical inference framework to characterize passenger flow assignment model in a complex metro network. In doing so, we combine network cost attribute estimation and passenger route choice modeling using Bayesian inference. We build the posterior density by taking the likelihood of observing passenger travel times provided by smart card data and our prior knowledge about the studied metro network. Given the high-dimensional nature of parameters in this framework, we apply the variable-at-a-time Metropolis sampling algorithm to estimate the mean and Bayesian confidence interval for each parameter in turn. As a numerical example, this integrated approach is applied on the metro network in Singapore. Our result shows that link travel time exhibits a considerable coefficient of variation about 0.17, suggesting that travel time reliability is of high importance to metro operation. The estimation of route choice parameters conforms with previous survey-based studies, showing that the disutility of transfer time is about twice of that of in-vehicle travel time in Singapore metro system.     

120km／h重载货车摇枕载荷谱最大载荷的统计推断研究

高速铁路货车在实际运行中最大载荷虽然极少出现，但会引起零部件较大的损伤，对其疲劳强度有较大影响。由于实际测试样本有限，最大载荷不一定能实测得到。为了使编制出的载荷谱能够全面反映摇枕的载荷分布特征，对实测的载荷谱进行统计分析，确定可能出现的最大值。采用线性相关系数为目标函数的优化算法，对实测摇枕载荷的理论分布进行了统计拟合，然后利用概率计算的方法求出了相应的最大载荷。