基于时空GPSO-SVM的短时交通流预测

为了提高城市道路短时交通流预测的精度,提出了一种基于时空遗传粒子群支持向量机的短时交通流预测模型.通过主成分分析法对路网原始交通流量进行时空相关性分析,用较少的主成分代替原始交通流量并作为预测因子,在粒子群算法中引入遗传算法的交叉和变异因子,避免粒子群算法陷入局部最优.利用改进后的粒子群算法优化支持向量机参数,得到最优的支持向量机模型,并实现城市道路的短时交通流预测.以长春市路网的实测数据为基础进行了实例验证,结果表明,优化支持向量机参数时,遗传粒子群算法不会陷入局部最优,优化效果更好;与粒子群支持向量机模型和遗传粒子群支持向量机模型相比,所提出预测模型的相对误差波动较稳定,平均预测精度分别提高了4.96%和3.41%.     

单向复合材料高应变率下材料特性的研究

在船舶领域,复合材料及夹芯复合材料板梁结构已大量应用在舰船结构中,尤其游艇及复合材料高速艇上.在运行过程中,这些结构有时很可能会受到如砰击、碰撞等动态载荷或高速冲击载荷.然而到目前为止,大多数的结构设计所用到的材料特性仍基于低应变率情况下的准静态测试结果.该文研究了高速艇等结构中的纤维增强复合材料高应变率情况下的材料特性,通过引入一种粘弹性模型来模拟并分析研究对象.并在世界先进的INSTRON高应变率材料试验机上设计并完成了相关试验,验证了该枯弹性模型、确定了模型中的材料参数.该粘弹性模型然后被用来研究分析应变率对单向复合材料机械特性的影响.     

沥青混合料抗车辙性能的分形描述方法

为了准确模拟沥青混合料抗车辙性能, 采用分形理论分析了沥青混合料微观结构, 研究了粗细集料不同级配分形维数对沥青混合料抗车辙性能的影响, 并根据级配分形维数公式计算了沥青混合料的分形值, 进行了沥青混合料车辙试验和微观结构的电子扫描。分析结果表明: 4.75 mm通过率是集料尺度的分界点, 集料分形维数与抗车辙性能有一致相关性, 分形值越大, 抗车辙能力越高; 根据路用性能设计集料级配可以定量地分析沥青混合料的级配差异和路面性能, 及路面微观结构与宏观路用性能的关系。     

基于目标级联分析法的车下设备悬挂参数优化设计

为改善高速列车运行舒适度和车下悬挂设备的振动水平,建立了车辆-设备系统垂向动力学模型,推导了车辆系统振动加速度频率响应函数;结合轨道不平顺激励谱函数计算了车下悬挂设备振动加速度均方根,联合人体舒适度加权滤波函数计算了车体振动参考点的垂向舒适度指标;引入目标级联分析(ATC)法逐层分解车辆-设备系统振动指标,构建了车辆-设备系统两层指标分解数学模型,采用指数罚函数策略协调两层振动指标之间的耦合问题;提出了以车辆运行舒适度和车下悬挂设备振动加速度为指标的多目标优化方法,建立了以车下设备悬挂刚度和阻尼为设计变量的优化模型;联合车下设备悬挂参数动力吸振器(DVA)设计法对比探讨了ATC法在复杂车辆系统参数优化设计中的应用效果。分析结果表明：与DVA设计法相比,ATC法优化后车辆中部舒适度在300 km·h^-1工况下提高了8.5%,设备振动水平减小了约20%;在全速域区间,ATC法对车体中部的振动衰减是DVA设计法的2倍,且对设备的振动衰减比DVA设计法大4.5 dB;与优化前相比,ATC法优化后车辆中部舒适度指标最大提升了15%,设备振动加速度减小了0.18 m·s^-2。由此可见,ATC法可以运用于复杂轨道车辆结构参数优化设计中,能有效改善车辆系统的振动水平,也可为车下设备悬挂参数优化设计提供指导。     

肋拱桥关键截面箱型转换加固技术试验研究

以重庆丰都庙包大桥为原型,制作了2片钢筋混凝土肋拱模型,首先采用"肋拱桥关键截面箱型转换加固技术"对其中1片进行加固处治,然后对加固前、后肋拱模型实施全过程破坏试验。通过对比分析加固前、后肋拱模型的应变、挠度、横向分布比率、裂缝及破坏模式等指标,得到以下结论:肋拱桥关键截面箱型转换加固后,新增设的钢筋混凝土箱型封闭层能与原肋拱协调变形、共同承担活载。     

山区公路水灾害评价体系框架的研究

为了提高山区公路抗水灾能力,在实地调查、研究基础之上,详细阐明了山区公路水灾害评价中危险性、易损性、损失、风险、减灾效益等基本概念。提出了山区公路水灾害评价系统应由危险性评价、易损性评价、风险评价及减灾效益评价4部分构成,而对于路网水灾害评价应由点、线、面构成,首次建立了完整的三维评价体系。指出对已有公路的防排水与抗水毁能力的工程评价,是水毁防治工程投资决策的重要依据,应作为重点进行研究。对于路网水灾害评价,应侧重于点(点单元)评价,适当考虑线评价。最后,从致灾因子、承灾体、灾情及防灾减灾4个方面构建了公路水灾害评价基本模型。     

电控汽油机喷油脉宽与燃油消耗质量关系试验研究

针对目前电喷汽油机油耗测量带来的新问题,根据喷油器喷油量控制原理,研究利用测量喷油脉宽来测量燃油消耗质量的方法;开发了喷油器喷油脉宽测量仪,通过试验分析了发动机在不同负荷、不同转速时喷油脉宽与燃油消耗质量之间的关系,为随车油耗快速检测设备的开发提供了基础。     

An application of a rank ordered probit modeling approach to understanding level of interest in autonomous vehicles

Surveys of behavior could benefit from information about people’s relative ranking of choice alternatives. Rank ordered data are often collected in stated preference surveys where respondents are asked to rank hypothetical alternatives (rather than choose a single alternative) to better understand their relative preferences. Despite the widespread interest in collecting data on and modeling people’s preferences for choice alternatives, rank-ordered data are rarely collected in travel surveys and very little progress has been made in the ability to rigorously model such data and obtain reliable parameter estimates. This paper presents a rank ordered probit modeling approach that overcomes limitations associated with prior approaches in analyzing rank ordered data. The efficacy of the rank ordered probit modeling methodology is demonstrated through an application of the model to understand preferences for alternative configurations of autonomous vehicles (AV) using the 2015 Puget Sound Regional Travel Study survey data set. The methodology offers behaviorally intuitive model results with a variety of socio-economic and demographic characteristics, including age, gender, household income, education, employment and household structure, significantly influencing preference for alternative configurations of AV adoption, ownership, and shared usage. The ability to estimate rank ordered probit models offers a pathway for better utilizing rank ordered data to understand preferences and recognize that choices may not be absolute in many instances.     

Exploring the impact of walk–bike infrastructure,safety perception,and built-environment on active transportation mode choice: a random parameter model using New York City commuter data

This study estimates a random parameter (mixed) logit model for active transportation (walk and bicycle) choices for work trips in the New York City (using 2010–2011 Regional Household Travel Survey Data). We explored the effects of traffic safety, walk–bike network facilities, and land use attributes on walk and bicycle mode choice decision in the New York City for home-to-work commute. Applying the flexible econometric structure of random parameter models, we capture the heterogeneity in the decision making process and simulate scenarios considering improvement in walk–bike infrastructure such as sidewalk width and length of bike lane. Our results indicate that increasing sidewalk width, total length of bike lane, and proportion of protected bike lane will increase the likelihood of more people taking active transportation mode This suggests that the local authorities and planning agencies to invest more on building and maintaining the infrastructure for pedestrians. Further, improvement in traffic safety by reducing traffic crashes involving pedestrians and bicyclists, will increase the likelihood of taking active transportation modes. Our results also show positive correlation between number of non-motorized trips by the other family members and the likelihood to choose active transportation mode. The model would be an essential tool to estimate the impact of improving traffic safety and walk–bike infrastructure which will assist in investment decision making.     

Visualisation of uncertainty in probabilistic traffic models for policy and operations

This study investigates different methods to visualise uncertainty in static representations of probabilistic traffic models predictions on road-networks. Although various graphical cues may be used to represent uncertainty it is not a priori clear which of them are most suited for this purpose, since their legibility, intelligibility and the degree to which they interfere with other graphical elements in a representation differ widely. Several graphical uncertainty representations were therefore developed and analysed in expert sessions. A selection of the initial set of uncertainty visualisations was further evaluated in a cognitive alternative task-switching experiment. The results show that graphical representations are able to convey uncertainty information relatively accurately, while some uncertainty visualisations outperform others. It depends on the model and scenario which representation is most suited for a given application. This paper presents an overview of possible graphic uncertainty representations and the considerations involved when applying them to uncertainty in traffic model visualisations.