Vegetation cover at right of way locations

This research evaluated the status of vegetation cover at right of way locations. Site factors that contributed to low and high ground cover along roadsides and medians were identified. Twenty-nine roadside and median study sites incorporated variability in soil type, elevation, vegetation establishment and cover, seed mixture, slope, aspect, time since planting, and climate. Vegetation cover was measured, and species distribution was identified. Slopes, aspects of the sloping face, and elevations were recorded. Soil samples were tested for nutrients, minerals, texture, and pH. Approximately 50% of the test sites met the 70% cover criteria. Locations of the worst cover (<50%) had soils with high soluble salt content (0.36–1.54 mmhos/cm) or low organic matter values (<1.7%). Vegetation cover was dominated by tall fescue (Festuca arundinacea) and crownvetch (Coronilla varia L.), two species that were included in the current seeding mixture and are considered invasive. To further promote revegetation success and persistence, both maintenance and site specific seed mixtures are needed.     

复合动力超长续航无人艇系统的设计与实现

为实现无人艇在海上追踪、搜救、巡逻、反潜等任务中的超长续航,避免因油料限制而被迫任务中断,设计了一套以风能、太阳能为动力的无人艇系统,利用风帆为无人艇推进,太阳能为船上电控设备提供电能。该系统由无人艇和岸基监控平台组成,无人艇可通过python开发的数据采集模块和算法模块实时采集环境数据、计算、生成并下达控制指令,在风区内可超长续航自主航行,实现全风向利用；岸基监控平台可实时监控无人艇状态,并进行自主/遥控模式切换。对系统进行了测试,通讯连接试验的可靠性高；无人艇航行试验验证了全风向自主航行的可行性,运行轨迹与仿真结果基本重合；太阳能供电分析理论上验证了风区超长续航的可实现性。     

基于ADRC的调距桨伺服控制系统设计

船舶调距桨推进系统具有典型的非线性和不确定性,以及柴油机、推进轴系和螺旋桨三者的强耦合性,并受到其执行能力的约束以及风、浪、流等的干扰,使得调距桨伺服控制系统的设计非常困难。本文建立了基于自抗扰控制器(Active Disturbance Rejection Control,ADRC)的调距桨伺服控制系统数学模型,对自抗扰控制器的原理及参数整定进行了分析,采用Matlab/Simulink完成仿真程序的设计和研究,ADRC螺距控制与传统的PID螺距控制相比,具有良好的鲁棒性和稳定性,尤其在抗扰性能方面具有良好的控制效果。     

存在饱和输入的欠驱动船舶航迹跟踪控制

针对控制输入存在饱和限制的欠驱动船舶的航迹跟踪问题,提出鲁棒饱和控制方法。以船舶纵向速度和艏向角速度为虚拟输入,设计饱和运动学控制器,并引入二阶滤波器形式对控制器进行简化;利用反步法并引入Nussbaum型函数,设计饱和动力学控制器,以实现对任意光滑航迹的跟踪控制,并保证跟踪误差收敛至零点附近的一个有界区域内。仿真算例验证了设计方法的有效性和鲁棒性。     

Dynamic traffic metering in urban street networks: Formulation and solution algorithm

Traffic metering offers great potential to reduce congestion and enhance network performance in oversaturated urban street networks. This paper presents an optimization program for dynamic traffic metering in urban street networks based on the Cell Transmission Model (CTM). We have formulated the problem as a Mixed-Integer Linear Program (MILP) capable of metering traffic at network gates with given signal timing parameters at signalized intersections. Due to the complexities of the MILP model, we have developed a novel and efficient solution approach that solves the problem by converting the MILP to a linear program and several CTM simulation runs. The solution algorithm is applied to two case studies under different conditions. The proposed solution technique finds solutions that have a maximum gap of 1% of the true optimal solution and guarantee the maximum throughput by keeping some vehicles at network gates and only allowing enough vehicles to enter the network to prevent gridlocks. This is confirmed by comparing the case studies with and without traffic metering. The results in an adapted real-world case study network show that traffic metering can increase network throughput by 4.9–38.9% and enhance network performance.     

长江航道大型整治工程施工安全控制关键技术

长江航道大型整治工程施工河段长、工程量大且工序多,施工水域船舶通航密度大、船舶种类多,施工安全生产控制与河段通航安全面临巨大挑战。依托长江干线下、中、上游典型大型航道整治工程,围绕工程施工全过程风险管控及安全保障技术,采用理论分析、仿真模拟、现场试验、系统研发相结合的方法,提出了长江航道大型整治工程风险识别与评估方法,构建了通航安全与施工生产安全风险预测模型,研究了长江航道大型整治工程全方位、全过程、全要素施工安全保障与控制技术,并基于AIS和云技术开发了长江航道整治工程施工区安全综合信息平台,为保障大型航道整治工程生产及通航安全提供了理论依据和技术手段。     

Analysis of air traffic control operational impact on aircraft vertical profiles supported by machine learning

The Air Traffic Management system is under a paradigm shift led by NextGen and SESAR. The new trajectory-based Concept of Operations is supported by performance-based trajectory predictors as major enablers. Currently, the performance of ground-based trajectory predictors is affected by diverse factors such as weather, lack of integration of operational information or aircraft performance uncertainty.Trajectory predictors could be enhanced by learning from historical data. Nowadays, data from the Air Traffic Management system may be exploited to understand to what extent Air Traffic Control actions impact on the vertical profile of flight trajectories.This paper analyses the impact of diverse operational factors on the vertical profile of flight trajectories. Firstly, Multilevel Linear Models are adopted to conduct a prior identification of these factors. Then, the information is exploited by trajectory predictors, where two types are used: point-mass trajectory predictors enhanced by learning the thrust law depending on those factors; and trajectory predictors based on Artificial Neural Networks.Air Traffic Control vertical operational procedures do not constitute a main factor impacting on the vertical profile of flight trajectories, once the top of descent is established. Additionally, airspace flows and the flight level at the trajectory top of descent are relevant features to be considered when learning from historical data, enhancing the overall performance of the trajectory predictors for the descent phase.     

Fractional-order-based ACC/CACC algorithm for improving string stability

Traffic flow optimization and driver comfort enhancement are the main contributions of an Adaptive Cruise Control (ACC) system. If communication links are added, more safety and shorter gaps can be reached performing a Cooperative-ACC (CACC). Although shortening the inter-vehicular distances directly improves traffic flow, it can cause string unstable behavior. This paper presents fractional-order-based control algorithms to enhance the car-following and string stability performance for both ACC and CACC vehicle strings, including communication temporal delay effects. The proposed controller is compared with state-of-the-art implementations, exhibiting better performance. Simulation and real experiments have been conducted for validating the approach.     

Predictive power of inspection outcomes for future shipping accidents – an empirical appraisal with special attention for human factor aspects

This paper investigates whether deficiencies detected during port state control (PSC) inspections have predictive power for future accident risk, in addition to other vessel-specific risk factors like ship type, age, size, flag, and owner. The empirical analysis links accidents to past inspection outcomes and is based on data from all around the globe of PSC regimes using harmonized deficiency codes. These codes are aggregated into eight groups related to human factor aspects like crew qualifications, working and living conditions, and fatigue and safety management. This information is integrated by principal components into a single overall deficiency index, which is related to future accident risk by means of logit models. The factor by which accident risk increases for vessels with above average compared to below average deficiency scores is about 6 for total loss, 2 for very serious, 1.5 for serious, and 1.3 for less-serious accidents. Relations between deficiency scores and accident risk are presented in graphical format. The results may be of interest to PSC authorities for targeting inspection areas, to maritime administrations for improving asset allocation based on prediction scenarios connected with vessel traffic data, and to maritime insurers for refining their premium strategies.     

斜拉索-磁流变阻尼器多性能约束下的减振控制算法

提出一种极点和方差指标约束下的斜拉索-磁流变减振控制算法。基于Halmiton原理与切比雪夫级数求解方法建立斜拉索-阻尼器减振控制系统状态空间方程。以极点表达减振控制快速性和稳定性约束,以方差表达小振幅和振速约束,基于凸优化理论,给出满足相容快速性、稳定性、小振幅以及振速指标约束下的磁流变半主动减振控制算法。最后,以某斜拉桥C20号斜拉索为例进行仿真验证。结果表明,给出的减振控制算法能保证斜拉索在随机外界激励下的快速性稳定性,且有效抑制拉索的振幅,减振效果良好。