Collision-avoidance under COLREGS for unmanned surface vehicles via deep reinforcement learning

ABSTRACT

Collision avoidance for unmanned surface vehicles (USVs) is significant for the fulfillment of autonomous navigation. Generally, classical collision-avoidance algorithms are proposed for relatively simple encounter situation, in this scenario only two USVs are stressed. Furthermore, to generate the rational manoeuvre operations, it is necessary that USVs should abide by International Regulations for Preventing Collision at Sea (COLREGS). However, COLREGS has not paid attention to rules for multi-USV collision-avoidance problem. Furthermore, those collision-avoidance rules in COLREGS have not been quantified for USVs. Following that, this paper utilizes deep reinforcement learning (DRL) algorithm to resolve collision-avoidance for USVs even in complex encounter situations. Within our DRL algorithm, related COLREGS is quantified properly and integrated into the DRL model, and then encounter situation of USVs is formulated as environmental observation value, accordingly a set of decision making is reached by decision-making neural network, and the reward function is designed for updating network parameters iteratively. Consequently, collision avoidance for USVs can be achieved eventually. By employing our DRL algorithm, collision avoidance for USVs under generous complex scenarios are resolved with the aid of corresponding intelligent decision-making operations. Simulation results verify the effectiveness of our DRL algorithm.     

A random forests approach to prioritize Highway Safety Manual (HSM) variables for data collection

The Highway Safety Manual (HSM) recommends using the empirical Bayes method with locally derived calibration factors to predict an agency's safety performance. The data needs for deriving these local calibration factors are significant, requiring very detailed roadway characteristics information. Many of these data variables are currently unavailable in most of the agencies' databases. Furthermore, it is not economically feasible to collect and maintain all the HSM data variables. This study aims to prioritize the HSM calibration variables based on their impact on crash predictions. Prioritization would help to identify influential variables for which data could be collected and maintained for continued updates, and thereby reduce intensive data collection efforts. Data were first collected for all the HSM variables from over 2400 miles of urban and suburban arterial road networks in Florida. Using 5 years (2008–2012) of crash data, a random forests data mining approach was then applied to measure the importance of each variable in crash frequency predictions for five different urban and suburban arterial facilities including two‐lane undivided, three‐lane with a two‐way left‐turn lane, four‐lane undivided, four‐lane divided, and five‐lane with a two‐way left‐turn lane. Two heuristic approaches were adopted to prioritize the variables: (i) simple ranking based on individual relative influence of variables; and (ii) clustering based on relative influence of variables within a specific range. Traffic volume was found as the most influential variable. Roadside object density, minor commercial driveway density, and minor residential driveway density variables were the other variables with significant influence on crash predictions. Copyright © 2015 John Wiley & Sons, Ltd.     

反射隔热涂料对轨道板温度及应力的影响

为了降低无砟轨道板板温及板内应力，缓解夏季高温期无砟轨道胀板导致的各类病害，使用钛白粉、玻璃微珠等组份配置了一种无砟轨道用反射隔热涂料；探究了各组份使用量的合理性，并在红外光及自然光下测试了其降温性能；分析了轨道板板表及内部温度差对轨道板内部应力的影响. 研究结果表明:该种涂料可在夏季高温期降低轨道板板表温度最高达16 ℃，可使轨道板板表与180 mm深处温度差由24 ℃下降至12 ℃，降幅约50%，并可有效降低轨道板应力0.4 MPa；该种涂料可有效降低因温度应力产生的各种轨道病害风险.      

基于EMD-Wavelet模型的实时交通流噪声数据清洗方法

针对实时交通流数据的噪声污染,将具有处理非平稳非线性信号优势的经验模式分解方法(EMD)和小波变换(wavelet)相结合,构建EMD-Wavelet组合清洗模型.该模型首先将实时交通流序列进行经验模式分解,然后将含有噪声的高频分量用小波变换进行软阈值去噪,最后将去噪后的高频分量、未去噪的低频分量和残量进行重构,形成清洗后数据序列.通过实验表明:该方法的去噪效果要好于单独使用小波变换和EMD法,是一种有效可靠的实时交通量噪声数据清洗方法.     

铁路复线三线隧道双侧壁导洞法施工技术

在山岭地区修建铁路,因受地形限制,往往几条铁路穿越同一山脉,线路并行需要大断面隧道通过,例如在建的兰渝高铁(双线)就和遂渝二线(单线)穿越同一座山,形成三线大跨隧道.与其他双线铁路隧道相比,三线隧道具有跨度大、高度变化相对较小(即矢跨比变小)、结构形状更加扁平等特点.文章简要介绍了兰渝复线铁路唯一的一座三线隧道——新作坊隧道的“双侧壁导洞法”的施工工艺和关键技术,研究分析了施工方案优化及施工效果.     

论致病性大肠杆菌(EPEC)的致病机理

由于分子和细胞生物学方法的出现,对EPEC的致病机理有了更好的了解,EPEC侵入体外培养的组织细胞,但是一般认为这不会发生在体内主要是由一种超微损伤介导的,细菌通过这种超微损伤从而与原生质膜紧密接触,导致肠刷状缘局部破坏和原生质膜变形。     

区间拨线接触网过渡方案

根据京郑线第六次提速改造工程的线路拨移实际经验,提出了几种线路拨移方案,并总结了京郑线的不同线路拨移条件下所使用的拨移方案.     

纯电动汽车动力传动系统的匹配与仿真

纯电动汽车采用5挡变速器相比单挡、两挡变速器时的电机使用效率高,续驶里程长。按整车性能要求计算出所需电机的额定功率和峰值功率,确定电机参数后分别与单挡、两挡和5挡变速器进行动力性分析与匹配,计算表明采用5挡变速器与15kW电机最高车速能达到96km/h,高于采用单挡和两挡变速器时最高车速的12.9%和6.7%。最后,结合ADVISOR进行了5挡变速器与15kW电机续驶里程仿真,其续驶里程为121km,很好地满足了设计标准,为高效率、低成本的电动车动力系统概念设计指出了一个方向。     

中国连锁零售业RFID技术应用研究

本文分析了无线射频识别技术—RFID的工作原理以及连锁零售业RFID技术应用研究现状,最后探讨了该技术在国内连锁零售业的应用。     

长白山区几种野生浆果营养成分及延缓衰老作用

目的　研究越桔、山葡萄、软枣猕猴桃等长白山区主要野生浆果的营养成分及延缓衰老作用。方法　测定野果中维生素B1、B2 、C、烟酸、β 胡萝卜素及钙、铁、锌等矿物质含量。老年Wistar大鼠分别按 3g·kg-1、6g·kg-1以野果汁灌胃 30d,测定红细胞及肝脏SOD、全血GSH Px活性、血清MDA与脑、心组织中脂褐质含量。结果　野果中维生素B1、B2 、C、β 胡萝卜素及钙、铁、锌等含量显著高于常用栽培果品 ,老年大鼠按 6g·kg-1野果汁灌胃 30d后 ,红细胞及肝脏SOD、全血GSH Px活性显著增高 (P <0 .0 5或P <0 .0 1) ,血清MDA及脑、心组织中脂褐质含量则显著降低 (P <0 .0 5或P <0 .0 1)。结论　 3种野果中富含维生素和矿物质 ,其果汁能显著提高老年大鼠体内抗氧化酶类活性 ,降低脂质过氧化作用 ,延缓衰老进程