新疆兵团垦区风积砂碾压技术的研究

基于农八师古新干线公路的筑路实践，提出了风积砂干压—湿压混合碾压施工方法及路面底基层的特殊施工工艺，解决了利用风积砂筑路粒料类结构层中砂石料的嵌入难题，有利于风积砂的应用，降低筑路成本。     

基于蚁群算法和群决策理论的动态路径优化研究

文章针对城市交通信号控制中的动态路径优化问题,综合考虑相邻交叉口间距和路段交通饱和度两个参数的影响,提出了一种基于蚁群算法和群决策理论的动态路径优化算法模型,并通过仿真实验,对比分析了该算法模型的有效性。     

轨道交通车站节能检测判定坐标系研究与应用

从轨道交通车站项目设计、技术要求、检测参数、检测方法及结果判定的角度,文章阐述了轨道交通车站系统节能检测的主要内容和检测方法。为了快速方便地判定检测结果,提出了检测结果坐标系的二维可视化评判方法,并给出了合格判定的点集数学表达式。以某车站系统节能性能检测项目为案例,运用检测结果判定坐标系法对主要参数包括室内温度、风系统总风量与风口风量、水系统水流量、平均照度与照明功率密度等进行了检测结果分析,实现了节能检测结果的快速和二维可视化判定。     

The price of uncertainty in pavement infrastructure management planning: An integer programming approach

Currently there is a true dichotomy in the pavement maintenance and rehabilitation (M&R) literature. On the one hand, there are integer programming-based models that assume that parameters are deterministically known. On the other extreme, there are stochastic models, with the most popular class being based on the theory of Markov decision processes that are able to account for various sources of uncertainties observed in the real-world. In this paper, we present an integer programming-based alternative to account for these uncertainties. A critical feature of the proposed models is that they provide – a priori – probabilistic guarantees that the prescribed M&R decisions would result in pavement condition scores that are above their critical service levels, using minimal assumptions regarding the sources of uncertainty. By construction of the models, we can easily determine the additional budget requirements when additional sources of uncertainty are considered, starting from a fully deterministic model. We have coined this additional budget requirement the price of uncertainty to distinguish from previous related work where additional budget requirements were studied due to parameter uncertainties in stochastic models. A numerical case study presents valuable insights into the price of uncertainty and shows that it can be large.     

Exploring active transportation investments and associated benefits for municipal budgets: a scoping review

Municipalities play an important role in the planning and development of communities that support active transportation (AT), which refers to human-powered modes of travel, such as walking and cycling. Municipal-level stakeholders involved in land-use and transportation infrastructure planning consider multiple social, environmental and economic considerations to inform decision-making and investments in AT. Evidence around the fiscal benefits of AT investment for local governments has not been systematically identified. This scoping review sought to explore the existing evidence regarding investments in AT and opportunities for savings on municipal expenditures and revenue generation. In total, 7060 records were located and screened; of which 162 full-text articles were reviewed. Ultimately, 23 articles met our inclusion criteria and were included in this review. The available evidence focuses on potential economic benefits of AT in the areas of tax revenues, property values, consumer spending and employment, all of which are relevant sources of revenue generation in municipal operating budgets. An evidence gap was identified regarding AT infrastructure investments and benefits corresponding to municipal expenditures (e.g. maintenance cost savings). Notably, a large portion of literature was published after 2009, suggesting that municipal-level evidence on the fiscal benefits of AT investments may just be emerging.     

两级模糊优选模型及非结构性模糊决策理论在桥梁方案比选中的应用

选择桥梁设计方案,涉及诸多因素,这些因素在某些情况下相容,在某些情况下又相斥。为了协调这些复杂关系,并降低人为因素的影响,本文引入两级模糊优选模型及非结构性模糊决策理论。并运用此模型,进行一桥梁的设计选型优化,得到了比较理想的结果,证明了此模型在桥梁方案比选中的实用性。     

基于梯度提升决策树模型的铁路货运装卸时间预测技术

铁路货运装卸时间的精准预测可提升铁路货运系统的调度合理性和服务质量,但装卸时间受多种因素影响。文章针对铁路货运装卸时间预测问题,从铁路货运运单全流程信息中挖掘运单属性与货运装卸时间的关系,以分类与回归树为基础模型,在LightGBM框架下构建梯度提升决策树模型;对铁路货运运单全流程信息中的相关数据进行整合、对数变换、增加特征等预处理,形成运单数据集;采用该数据对构建的模型进行训练,结果表明,构建的模型对货运装卸时间的预测性能优于与其对比的其他机器学习模型。将该模型应用在实际货运装卸业务场景时,实际准确率依旧高于其他对比模型。     

面向智慧原油管道建设的运行方案快速智能决策

为解决智慧原油管道建设实时优化的难题,从节能降耗和运行安全2个角度出发构建了以能耗和不安全系数最小为优化目标的运行方案智能决策模型;基于差分进化算法,从变异决策变量越界处理方法和离散决策变量变异算子2个算法角度提出了提高优化算法可靠性和优化效率的改进设想;结合算法计算流程和并行计算框架,提出了4种并行计算策略;以近900 km长的仪征-长岭原油管线(仪长线)作为测试管道来验证和进一步分析算法改进设想与并行计算策略。研究结果表明：结合智能决策模型和优化算法的运行方案智能决策方法可在保证管道安全运行的前提下使仪长线的能耗费用下降7.22%,节能效果明显;改进的变异决策变量越界处理方法和用于离散决策变量变异的浮点数圆整变异算子均能提高原油管道运行方案优化结果的可靠性,前者可使优化计算耗时至少缩短一半,后者可使优化计算耗时至少缩短2/3;在不同的计算机配置下,不同并行计算策略的优劣存在一定的差异,而在最优并行计算策略下,在服务器上优化计算耗时从220 s下降为10 s,加速比可达到22倍。可见,综合算法改进设想和并行计算策略的运行方案快速智能决策方法可使优化计算的加速比超过130倍,显著缩短了优化计算耗时,说明了该智能决策方法对于原油管道快速运行优化的有效性。     

基于决策场理论的出行者动态决策行为研究

为了研究出行者进行路径选择时的动态决策过程,本文采用决策场理论,研究 了多属性条件下,机动车出行者的微观和宏观动态决策行为.分析了决策场理论的基本模 型,构建了出行者动态决策行为场景和框架,以历史出行时间、预测出行时间和两者综合 值作为出行者决策的路径属性,并根据属性与实际出行时间的差值为依据,提出了出行 者注意力权重矩阵计算方法.通过算例分析发现,自由流出行时间对出行者决策影响较 大,出行者对路径属性的依赖性非常强,决策过程中存在路径偏好反转的现象,表明出行 者动态决策过程是随时间不断变化的,路径选择是时间累计的结果.     

基于驾驶人决策机制的换道意图识别模型

依据驾驶人换道决策的产生机制,提出速度期望满足度、危险感知系数和换道 可行性系数作为换道决策的识别指标并确定其量化方法.通过实车试验数据的分析表明： 量化指标与换道决策存在不同程度的相关性;同时在换道初期、车道保持及过渡状态阶 段存在显著差异.以速度期望满足度、危险感知系数和换道可行性系数为特征输入参数, 建立基于模糊神经网络的驾驶人换道意图识别模型,进行驾驶人换道意图的识别.结果表 明,该模型在换道初期的预测准确率达到89.93%,虚警率为9.52%,优于以碰撞时间TTC 为输入指标的BP神经网络模型,以及以RV、RP、RS为变量的Logistic 模型,说明模型具 有较好的预测准确性.