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排序方式: 共有397条查询结果,搜索用时 15 毫秒
1.
高速公路浓雾监测预警系统 总被引:1,自引:0,他引:1
为研究浓雾对高速公路运营的影响,通过建设高速公路环境气象监测站以获取与浓雾发生密切相关的气象要素和能见度实测值,并结合高速公路沿线历史浓雾个例研究形成浓雾的环流形势特征和局地监测站气象要素演变与能见度值变化规律和特征,由此建成了高速公路浓雾监测预警系统。系统通过多种通讯传输和显示手段,将自动监测站的实况和预报中心制作的浓雾预警、预报结论传送至公路运营指挥中心,供采取决策措施时应用。该系统目前已由无锡段扩展到常州至苏州段,在试验应用期,沪宁高速公路在试验路段未发生因浓雾而造成的重大交通事故。 相似文献
2.
公路特大型泥石流研究及防治新理念 总被引:13,自引:1,他引:13
作为我国一种严重的公路水毁类型,公路特大型泥石流灾害至今尚未解决,本文建构了该类泥石流研究及防治新理念,对于公路建筑物的安全与稳定、确保公路交通有序进行具有重要意义。研究认为,公路泥石流研究及防治的主要对象是具有大冲大淤性能、毁损作用强烈的特大型泥石流;必须遵循以泥石流发育机理研究为基础、防治技术研究为手段、防治工程研究为目的的研究原则;详细分析了公路泥石流水毁模式,概化分析了冲淤变动型沟谷泥石流的发育特性;开发了防治效果极佳的速流结构,运用运动状态函数法建构了速流结构设计理念,运用动力学建构了泥石流最大抛程计算理论。 相似文献
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This study determines the optimal electric driving range of plug-in hybrid electric vehicles (PHEVs) that minimizes the daily cost borne by the society when using this technology. An optimization framework is developed and applied to datasets representing the US market. Results indicate that the optimal range is 16 miles with an average social cost of $3.19 per day when exclusively charging at home, compared to $3.27 per day of driving a conventional vehicle. The optimal range is found to be sensitive to the cost of battery packs and the price of gasoline. When workplace charging is available, the optimal electric driving range surprisingly increases from 16 to 22 miles, as larger batteries would allow drivers to better take advantage of the charging opportunities to achieve longer electrified travel distances, yielding social cost savings. If workplace charging is available, the optimal density is to deploy a workplace charger for every 3.66 vehicles. Moreover, the diversification of the battery size, i.e., introducing a pair and triple of electric driving ranges to the market, could further decrease the average societal cost per PHEV by 7.45% and 11.5% respectively. 相似文献
4.
本文归纳总结了车站能力查定计算过程中存在的多种影响因素,深入分析了其产生原因和不可避免性。然后利用层次分析法的区间估计方法计算得出各种误差因子对计算结果的影响权重大小,并对比不同误差因子的权重区间,筛选出强误差因子,剔除弱误差因子,为精确计算车站能力值提供依据。 相似文献
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Fuel-switching personal transportation from gasoline to electricity offers many advantages, including lower noise, zero local air pollution, and petroleum-independence. But alleviations of greenhouse gas (GHG) emissions are more nuanced, due to many factors, including the car’s battery range. We use GPS-based trip data to determine use type-specific, GHG-optimized ranges. The dataset comprises 412 cars and 384,869 individual trips in Ann Arbor, Michigan, USA. We use previously developed algorithms to determine driver types, such as using the car to commute or not. Calibrating an existing life cycle GHG model to a forecast, low-carbon grid for Ann Arbor, we find that the optimum range varies not only with the drive train architecture (plugin-hybrid versus battery-only) and charging technology (fast versus slow) but also with the driver type. Across the 108 scenarios we investigated, the range that yields lowest GHG varies from 65 km (55+ year old drivers, ultrafast charging, plugin-hybrid) to 158 km (16–34 year old drivers, overnight charging, battery-only). The optimum GHG reduction that electric cars offer – here conservatively measured versus gasoline-only hybrid cars – is fairly stable, between 29% (16–34 year old drivers, overnight charging, battery-only) and 46% (commuters, ultrafast charging, plugin-hybrid). The electrification of total distances is between 66% and 86%. However, if cars do not have the optimum range, these metrics drop substantially. We conclude that matching the range to drivers’ typical trip distances, charging technology, and drivetrain is a crucial pre-requisite for electric vehicles to achieve their highest potential to reduce GHG emissions in personal transportation. 相似文献
7.
Due to the difficulty of obtaining accurate real-time visibility and vehicle based traffic data at the same time, there are only few research studies that addressed the impact of reduced visibility on traffic crash risk. This research was conducted based on a new visibility detection system by mounting visibility sensor arrays combined with adaptive learning modules to provide more accurate visibility detections. The vehicle-based detector, Wavetronix SmartSensor HD, was installed at the same place to collect traffic data. Reduced visibility due to fog were selected and analyzed by comparing them with clear cases to identify the differences based on several surrogate measures of safety under different visibility classes. Moreover, vehicles were divided into different types and the vehicles in different lanes were compared in order to identify whether the impact of reduced visibility due to fog on traffic crash risk varies depending on vehicle types and lanes. Log-Inverse Gaussian regression modeling was then applied to explore the relationship between time to collision and visibility together with other traffic parameters. Based on the accurate visibility and traffic data collected by the new visibility and traffic detection system, it was concluded that reduced visibility would significantly increase the traffic crash risk especially rear-end crashes and the impact on crash risk was different for different vehicle types and for different lanes. The results would be helpful to understand the change in traffic crash risk and crash contributing factors under fog conditions. We suggest implementing the algorithms in real-time and augmenting it with ITS measures such as VSL and DMS to reduce crash risk. 相似文献
8.
针对仅使用槽道推进器提供横向推力的动力定位船舶路径跟踪控制问题,建立慢变环境干扰影响下的非线性船舶数学模型,设计带有自适应干扰补偿的反步控制算法来消除环境干扰的影响。引入平行目标接近(CB)导引算法为跟踪控制生成期望速度矢量信号,通过与所提出的自适应反步控制算法相结合,得到不受船舶驱动特性限制的全速度范围动力定位船舶导引跟踪控制算法,应用李雅普诺夫稳定性理论证明系统跟踪误差渐进收敛到零。仿真结果表明通过调整导引算法参数可以调节船舶跟踪过程表现,并可以得到较好的控制精度。 相似文献
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针对目前一些船舶在恶劣海况下遇到的加速问题,以及通过转速禁区时间过长的问题,从螺旋桨匹配和主机内部设计两方面进行原因分析。围绕转速禁区功率裕度,结合相关案例,从轻螺旋桨裕度、转速禁区及MAN主机输出扭矩能力等方面入手,提出改进措施。 相似文献