A cognitive framework to plan for the future of transportation

ABSTRACT

Automated, connected, electrified, and shared mobility will be cornerstones of the transportation future. Research to quantify the potential benefits and drawbacks of practice, and to identify barriers to adoption, is the first step in any strategic plan for their adoption. However, uncertainties, complexity, interdependence, and the multidisciplinary nature of emerging transportation technologies make it difficult to organize and identify focused research. The contribution of this work is a cognitive framework to help planners and policymakers organize broad topics, reveal challenges, discover ideas for solutions, quantify potential impacts, and identify implications to guide preparation strategies. The authors provide example cognitive frameworks for connected, automated, and electrified vehicles.     

Prediction of seasonal maximum wave height for unevenly spaced time series by Black Widow Optimization algorithm

The present study aimed to predict the maximum seasonal wave height by new integrative data driven methods. For this purpose, two data-driven techniques, that are, the Adaptive Neuro-Fuzzy Inference System (ANFIS) and the Support Vector Regression (SVR), were applied, and a BWO algorithm was used as an integrated method (ANFIS-BWO and SVR-BWO). In addition, the Particle Swarm Optimization (PSO) algorithm was used as a method integrated with SVR and ANFIS (SVR-PSO and ANFIS-PSO) to compare the performance of the newly developed methods (ANFIS-BWO and SVR-BWO). The wave data were collected in different seasons by a buoy station deployed in the southern Baltic Sea by the Institute of Hydro-Engineering of the Polish Academy of Sciences. Seasonal simulations were performed to investigate the effect of seasons on the maximum wave height. The wave data constituted an unevenly spaced time series. The maximum wave height was modeled using the maximum wave height period (T_max), the significant wave height (H_s), the significant wave period (T_s), and time steps (Δt). The results showed that the application of BWO and PSO algorithms increased the accuracy of ANFIS and SVR by about 18.45%. Moreover, the results show that PSO increased the accuracy of ANFIS and SVR by about 17.98% and 21.59%, respectively. The results of different runs indicated that the BWO is more stable to reach the global solution than PSO. The results also show that show that SVR-BWO is the most accurate model.     

道路路面现场冷再生技术探究

路面现场冷再生具有施工简便、充分利用旧路面废料、减少生态破坏和环境污染、不断行交通、缩短施工周期、降低工程费用等优点,在国外已经应用多年,而我国尚处于初级应用阶段,因此加快对路面现场冷再生技术的研究和应用,已成为当务之急。通过对路面现场冷再生设计、机械设备、施工工艺、质量控制等方面的简要介绍,可为类似工程提供一定的参考。     

公路沥青混凝土路面热再生技术研究

热再生技术作为一种快捷、环保、节能的沥青路面翻修技术,越来越受到公路行业的重视。与传统的路面修补技术相比,热再生技术在保证沥青路面维修质量的同时,能最大程度地节约时间、减小投入。总结公路沥青混凝土路面热再生技术的施工工艺流程,并结合实际公路沥青路面翻修工程实例对热再生技术进行评价,具有一定的参考价值。     

沥青路面再生养护分析

鉴于我国绝大多数沥青路面存在的病害问题,对沥青路面再生技术、微波加热再生技术在沥青路面中的应用进行分析,并对其未来发展进行展望,对沥青路面的再生养护有着积极意义.     

绿色包装技术PVA在纤维材料中的应用

当前,世界各国对包装的环保性能要求越来越高,对绿色包装技术提出新要求。可回收的新型绿色环保维纶水溶纱包装新材料及复合新技术的采用,能提高包装袋整体强度,降低包装成本,节约包装费用,提高车船利用率,减少环境污染。PVA材料的使用解决维纶复合包装袋的回收问题,改变传统塑编袋和纸塑复合袋回收难度大及污染严重的局面,消除对生态环境的威胁,具有重要环保意义。     

《弧焊电源》课程的教学改革浅析

《弧焊电源》是高职焊接技术及自动化专业的一门专业课,目的是让学生掌握各种常用弧焊电源的结构、特点、原理、以及调试和维护的方法,从而提高学生的职业岗位能力和职业素养。在此结合学院实际情况,从课程内容、学生和教学资源等方面分析了课程的教学现状;并从教材、教学方法和教学环境等方面提出了一些解决的方法。     

旧沥青混凝土路面现场冷再生技术及施工工艺研究

以山东临沂东红路的改建为例。介绍了旧沥青混凝土路面冷再生技术的原理特点以及应用前景。通过试验研究及施工实践。提出了适合北方地区的沥青混凝土冷再生施工技术。研究结果对今后旧沥青混凝土路面冷再生技术的推广应用及施工规范的制订有积极的作用。     

沥青路面再生利用技术综述

沥青路面再生利用技术是一项新的沥青路面修筑技术.目前世界各国非常重视.笔者阐述了沥青路面再生利用的可行性和必要性以及再生的机理,分析了旧沥青路面再生混合料配合比设计和施工工艺.     

冷再生沥青混合料设计方法概述

通过对国外有关研究与施工经验的总结,对冷再生混合料设计进行了讨论．即首先对代表性试样进行测试．确定再生沥青路面(RAP)混合料的组成(沥青含量和级配)。同时要测试RAP中复原沥青的粘度和针入度,然后根据再生料的目标级配和RAP料的级配确定是否有必要加入新料。目前选取的稳定剂多数是乳化沥青．利用乳化沥青进行再生．必须进行相关的实验室测试以确保乳化沥青和RAP料(包括新料)的相容性。乳化沥青的选择主要依赖于RAP料(包括新料)的级配和RAP料中老化沥青的稠度。乳化沥青和水的用量可以通过制备和测试含有这些不同含量组合的试件加以确定。最后对美国部分州公路局和单位有关冷再生设计方法进行了介绍。