Eco-driving training of professional bus drivers – Does it work?

The drive to reduce fuel consumption and greenhouse gas emissions is one shared by both businesses and governments. Although many businesses in the European Union undertake interventions, such as driver training, there is relatively little research which has tested the efficacy of this approach and that which does exist has methodological limitations. One emerging technology employed to deliver eco-driving training is driver training using a simulator. The present study investigated whether bus drivers trained in eco-driving techniques were able to implement this learning in a simulator and whether this training would also transfer into the workplace. A total of 29 bus drivers attended an all-day eco-driving course and their driving was tested using a simulator both before and after the course. A further 18 bus drivers comprised the control group, and they attended first aid courses as well as completing the same simulator drives (before-after training). The bus drivers who were given the eco-driving training significantly improved fuel economy figures in the simulator, while there was no change in fuel economy for the control group. Actual fuel economy figures were also provided by the bus companies immediately before the training, immediately after the training and six months after the training. As expected there were no significant changes in fuel economy for the control group. However, fuel economy for the treatment group improved significantly immediately after the eco-driving training (11.6%) and this improvement was even larger six months after the training (16.9%). This study shows that simulator-based training in eco-driving techniques has the potential to significantly reduce fuel consumption and greenhouse gas emissions in the road transport sector.     

A context aware system for driving style evaluation by an ensemble learning on smartphone sensors data

There are many systems to evaluate driving style based on smartphone sensors without enough awareness from the context. To cover this gap, we propose a new system namely CADSE system to consider the effects of traffic levels and car types on driving evaluation. CADSE system includes three subsystems to calibrate smartphone, to classify the maneuvers, and to evaluate driving styles. For each maneuver, the smartphone sensors data are gathered in three successive time intervals referred as pre-maneuver, in-maneuver, and post-maneuver times. Then, we extract some important mathematical and experimental features from these data. Afterwards, we propose an ensemble learning method on these features to classify the maneuvers. This ensemble method includes decision tree, support vector machine, multi-layer perceptron, and k-nearest neighbors. Finally, we develop a rule-based fuzzy inference system to integrate the outputs of these algorithms and to recognize dangerous and safe maneuvers. CADSE saves this result in driver’s profile to consider more for dangerous driving recognition. The experimental results show that accuracy, precision, recall, and F-measure of CADSE system are greater than 94%, 92%, 92%, and 93%, respectively that prove the system efficiency.     

The impact of airport noise as part of a Strategic Environmental Assessment,case study: The Tivat (Montenegro) Airport expansion plan

Strategic Environmental Assessment (SEA) is one of the most important instruments for making relevant decisions on the basis of which spatial planning is aligned with the tenets and principles of sustainable spatial development. Its primary application is in spatial (strategic) and urban planning, as well as in the planning and design of sectoral policies in the areas of energy, water management, waste management, transport, etc. The implementation of SEA allows developers to establish the benefits and implications of the proposed spatial changes, taking into account the capacity of the space to sustain the planned development, and to determine the degree of acceptability of the proposed spatial changes. This paper presents a specific method of assessing the impact of airport noise as part of a particular SEA. The particularity of this method is that it integrates the objectives, indicators and criteria for assessing the impact of airport noise on the population using the method of multi-criteria evaluation, applied in the preparation of the SEA for the Urban development plan regarding the expansion of Tivat Airport, Montenegro. The changes in noise intensity within the planning horizon to 2030 were predicted taking into account the following factors: physical, geographic and demographic characteristics of the space, the projected increase in the number and nature of the flights operated within the planning period, as well as the types of aircraft. On the basis of these data noise dispersion modelling was carried out using the IMMI model, and the results obtained were used in a multi-criteria evaluation as part of the SEA. The results of the research do not indicate any significant increase in noise intensity within the planning period to 2030 and they represent a good basis for making relevant decisions regarding the future development of Tivat Airport.     

碱激发煤制气残渣地质聚合物的制备及性能

煤制天然气残渣（CSNGS）是一种可用于制备地质聚合物的潜在新原料，然而关于用该工业废渣制备地质聚合物的报道却很少。采用机械球磨手段对煤制天然气残渣进行活化改性，分别以氢氧化钠（NaOH）溶液和氢氧化钾（KOH）溶液为激发剂，在不同条件下制备煤制气残渣地质聚合物，并对其强度进行对比。然后，通过X射线粉末衍射仪（XRD）、扫描电镜（SEM）、能谱分析（EDS）以及红外光谱（FT-IR）等微观试验手段对比研究了2种煤制气残渣地质聚合物的微观结构和强度形成机理，并分析了激发剂中不同碱金属阳离子对地质聚合物性能的影响。研究发现，随着热养护温度的升高，2种煤制气残渣中晶体峰强降低，地质聚合物的硅铝比（Si/Al）升高，地质聚合物的强度增加。研究还发现，在适当的热养护条件下，当激发剂浓度在6~9 mol·L^-1时，2种煤制气残渣地质聚合物均可以获得较高的力学强度。由SEM分析可知，较高的热养护温度和适当的激发剂浓度可以生成大量的水化硅铝酸钠凝胶（N-A-S-H）或水化硅铝酸钾凝胶（K-A-S-H），使地质聚合物的微观结构变得更加致密，从而使试件具备良好的力学性能。此外，NaOH溶液对煤制气残渣的碱激发效果要优于KOH溶液，这不仅是因为钠离子与负离子的结合能力强于钾离子，更有效地保证了地质聚合物骨架中的电荷平衡；而且与钾离子相比，钠离子更容易形成具有2个或3个SiO₄四面体桥接单个AlO₄四面体的地聚合物凝胶，这使材料形成了更加致密均匀的微观结构。研究结果表明：地质聚合物最高强度分别为36.1 MPa（NaOH）和27.8 MPa（KOH），因此，以煤制天然气残渣为原料制备地质聚合物具有很高的研究和应用价值。     

钢纤维-水泥石基体界面粘结性能研究进展综述

钢纤维与混凝土水泥石基体界面性能直接决定纤维对复合材料的增强效果，对界面性能的改善已经成为钢纤维混凝土性能提高的主要途径。从界面区的结构与特征着手，总结国内外界面区力学性能与微观结构的测试方法和评价指标，阐述常用的纤维混凝土理论及一些有限元模拟分析方法，并对钢纤维混凝土发展方向进行归纳。     

东南沿海地区全季节预制箱梁混凝土配合比设计

针对70 m预制箱梁混凝土早期抗压强度及耐久性的需求，通过调整胶凝材料的用量以及掺合料的掺配比例，进行多次试配、试验，配制出满足东南沿海地区不同季节气候条件下箱梁混凝土施工工艺需求的海工耐久混凝土配合比。     

城市水下道路隧道驾驶安全影响因素分析和改善思路

总结城市水下道路隧道事故分布规律，从驾驶人、隧道光环境及道路条件3方面分析隧道驾驶安全影响因素，对现有安全改善措施及其优缺点进行剖析，并指出城市水下道路隧道驾驶安全优化研究趋势： 应以提升隧道光环境质量为主，考虑交通事故形态、事故致因及影响因素，在确保交通安全的基础上，考虑不同隧道路段驾驶人差异化视觉需求。驾驶人视觉需求可以分为功能性、安全性与舒适性需求，对应的隧道行车环境可分为基本型、安全型与舒适型视觉参照系。提出以构建城市水下道路隧道舒适型视觉参照系为目标，通过隧道照明与隧道视线诱导技术相结合，缓解隧道出入口参照系的剧烈过渡，加强中间段弱视觉参照的城市水下道路隧道驾驶安全优化方法。构建基于空间路权、人因与驾驶任务、差异性与韵律性的隧道驾驶安全优化评价指标体系，为城市水下道路隧道驾驶安全优化提供新思路。     

浅谈混凝土桥梁火灾后检测评估要点

结合某座桥梁火灾后的情况,具体阐述了火灾后桥梁的检测评估内容、过程及注意要点,为规范类似桥梁结构火灾后的检测鉴定工作提供借鉴及参考.     

甘肃省农产品冷链物流系统评价研究

如何构建高效运作的农产品冷链物流系统对于农产品毁损率、减少不必要的经济损失进而提高农民的收入意义重大。文章建立了多层次综合评价体系，应用模糊层次分析法（F_AHP）的原理及算法综合评价了甘肃省农产品冷链物流系统的绩效，验证了F．AHP法在这一领域应用的有效性，并进一步剖析了该省农产品冷链物流系统存在的诸多问题。     

交通建设项目招投标阶段造价控制研究

综述交通建设项目招投标对工程造价的影响，并从实际出发分析当前招投标阶段造价控制中存在的问题，最后提出相应的解决措施，可为同行提供一定的参考与借鉴。