一种新的通用航空机载防撞逻辑设计方法

由于机载防撞系统(TCAS)是针对具有较大垂直高度变化率的大型飞机设计的，系统设定条件和与之相关的解脱建议并不能适用于通航飞机。针对通用航空的防撞问题，提出了一种基于马尔可夫决策过程(MDP)的防撞逻辑设计方法。首先，将飞机空中相遇过程的动态模型转换为离散转移函数；然后，基于防撞系统结果事件末端效用函数进行MDP建模，采用动态规划方法导出了最优防撞逻辑的迭代方程；最后，给出了通航飞机最优化防撞逻辑的设计流程并对最优防撞逻辑进行了计算机仿真。仿真结果表明，通过调整效用比参数可以在保证安全性能的同时有效降低系统告警率。在垂直相遇高度小于30 m的相遇过程占比高达18〖WT《Times New Roman》〗%〖WTBZ〗的情况下，当告警率大于0.85时系统的碰撞概率仅为2.88×10-4左右。该设计方法对我国在低空空域通用飞机防撞系统的研究具有一定的参考价值。     

基于数据链的无人机空中自动防撞技术

分析了一种基于数据链的自动空中防撞技术，从空中自动防撞系统需求出发，描述了系统 基本工作原理和流程。采用二次曲线拟合方法，给出了最优控制数学模型，以求解无人机航 路间的最小距离，实现最优机动操作组合。仿真分析结果表明，空中自动防撞系统可在碰撞发 生前的最后时刻有效完成逃逸操作，避免发生飞行碰撞，可为无人机编队提供进近飞行的安 全防护。     

基于SSR和ADS-B混合监视的机载编队防撞系统设计

由于设备性能的限制,民航飞机目前使用的机载防撞系统TCASⅡ不能适用于编队飞 行防撞。为了解决飞机编队飞行防撞以及与民航飞机TCASⅡ兼容的问题,给出了一种基 于二次雷达(SSR)和ADS-B混合监视的机载编队防撞系统的设计方案。该方案采用了TCAS主动 监视和被动监 视相结合的方法,利用唯一的24位S模式地址来识别和归类目标飞机,将TCAS的监视数据和A DS-B的监视数据进行数据融合来完成对目标飞机的监视和跟踪。通过将大型编队划分为多个 编队单元的方法,由长机负责保持各个编队单元之间的安全间距。采用收发器将长机产生的 位置保持和碰撞避免的操纵指令通过高频数据链路传送给各个编队单元,各个编队成员按照 操纵指令调整自己飞机的位置,完成对整个编队的位置保持和碰撞避免的集中控制和分散执 行。该方案可以为机载编队防撞系统的设计和实现提供参考和帮助。     

机车车体防撞柱组焊工艺研究

机车车体防撞柱是在机车发生碰撞时，为了保护司机室乘员和部分设备安全而设计的装置。防撞柱板材采用Q420E、Q460E低合金高强度结构钢。由于防撞柱结构的限制，只能在车架组装完成后，在车架翻转台位进行组焊。为了控制焊接变形，尽量采用对称焊接，同时打底和盖面焊缝采用热输入较小的2G位置焊接。     

巴斯夫聚酰胺制品在中国发展前景巨大

用塑料来减轻车重，减少排放和降低成本是巴斯夫新品的特点。用巴斯夫Ultramid工程塑料制成的进气歧管对汽车金属制进气歧管进行替换后，该部件质量减轻了40％，功率提高超过3％，实现了节能减排。为提高车辆安全性，巴斯夫推出了以优化聚酰胺材料制成的Ultramid CR产品，适用于与碰撞相关的零部件，行人防撞保护（LBS）便是采用集成模拟设计部件的实例。     

基于实例的车削仿真中碰撞干涉检查研究

碰撞和干涉检查是加工过程仿真的主要内容,采用区域干涉检查法,将车削仿真过程中三维实体间的碰撞检查简化为二维多边形之间的碰撞检查,并以UG为平台对仿真过程中可能发生的碰撞干涉进行了实例分析,验证了算法的正确性和有效性。     

试述公路防撞护栏的具体施工过程

公路防撞护栏按设置位置可分为路侧护栏和中央分隔带护栏.路倜护栏,是指设置于高速公路路肩上的护栏.目的是防止失控车辆越出路外,避免碰撞路边其它设施和车辆翻出路外.中央分隔带护栏,是指设置于公路中央分隔带内的护栏.目的是防止失控车辆穿越中央分隔带闯入对向车道,并保护分隔带内的构造物.由于高速公路行车速度快,行车密度大,在高速公路上必须设置一套完整的安全设施.防撞护栏作为安全设施的组成部分对防止行车事故起着重要作用.本文主要论述了高速公路防撞护栏的具体施工过程.     

机载防撞系统非线性高度跟踪器的设计与实现

高度跟踪器对于机载防撞系统(TCAS)能否可靠工作至关重要。传统的高度跟踪器采用线性α-β跟踪器,高度报告的“粗量化”精度将导致线性α-β跟踪器的性能劣化。为此,设计了一种对30 m量化精度高度报告的非线性跟踪器。核心思想是利用多次高度层穿越占用时间以及穿越高度层数来计算高度率,并将飞行过程划分为5个不同状态,不同状态采用不同高度率修正公式。仿真结果及误差分析显示非线性高度跟踪器在跟踪精度和响应时间两方面均优于线性α-β跟踪器,有效提高了TCAS做出防撞决策的可靠性。     

机载防撞系统垂直防撞的物理模型

如何准确预测和估算本机与入侵飞机相遇时在最接近点的垂直间隔距离,是机载防 撞系统（TCAS）在垂直方向上选择防撞措施的关键问题。采用空间相遇几何学的方法,建立 了本机与入侵飞机相遇时垂直防撞的两种物理模型,基于该模型推导出了预测两机之间垂直 间隔距离的计算公式,并且进行了计算机仿真。仿真结果表明,该模型能够准确预测本机 与入侵飞机相遇时在最接近点的垂直间隔距离。最后,给出了本机在垂直方向上选择防撞措 施的决策咨询条件和逻辑处理流程。     

跳频通信电台组网的建模与仿真

随着跳频通信在无线通信中日益广泛的应用,跳频电台的组网也就成为一个重要的课题。跳频碰撞作为跳频电台组网的关键技术,但这方面可见的研究文献却很少。本文首先介绍了跳频电台组网理论容限的数学模型,然后以53个有效频点为例,设计出了非重复碰撞的跳频图案。最后,对异步组网时跳频图案的性能和碰撞问题进行了仿真。     

A study of factors affecting intersection crash frequencies using random-parameter multivariate zero-inflated models

Recent research demonstrates the appropriateness of multivariate regression models in crash count modelling when one specific type of crash counts needs to be analysed, since they can better handle the correlated issues in multiple crash counts. In this paper, a random-parameter multivariate zero-inflated Poisson (RMZIP) regression model is proposed as an alternative multivariate methodology for jointly modelling crash counts simultaneously. Using this RMZIP model, we are able to account for the heterogeneity due to the unobserved roadway geometric design features and traffic characteristics. Our formulation also has the merit of handling excess zeros in correlated crash counts, a phenomenon that is commonly found in practice. The Bayesian method is employed to estimate the model parameters. We use the proposed modelling framework to predict crash frequencies at urban signalized intersections in Tennessee. To investigate the model performances, three models – a fixed-parameter MZIP model, a random-parameter multivariate negative binomial (RMNB) model, and a random-parameter multivariate zero-inflated negative binomial (RMZINB) model – have been employed as the comparison methods. The comparison results show that the proposed RMZIP models provide a satisfied statistical fit with more variables producing statistically significant parameters. In other word, the RMZIP models have the potential to provide a fuller understanding of how the factors affect crash frequencies on specific roadway intersections. A variety of variables are found to significantly influence the crash frequencies by varying magnitudes. These variables result in random parameters and thereby their effects on crash frequencies are found to vary significantly across the sampled intersections.     

The effect of natural and built environmental characteristics on pedestrian-vehicle crash severity in Ghana

Despite the benefits of walking as a means of travelling, walking can be quite hazardous. Pedestrian-vehicle crashes remain a major concern in Ghana as they account for the highest percentage of fatalities. The objective of this study is to determine the effect of both natural and built environmental features on pedestrian-vehicle crash severity in Ghana. The study is based on an extensive pedestrian-vehicle crash dataset extracted from the National Road Traffic Accident Database at the Building and Road Research Institute (BRRI) of the Council for Scientific and Industrial Research (CSIR), Ghana. Using a multinomial logit modelling framework, possible determinants of pedestrian-vehicle crash severity were identified. The study found that fatal crashes are likely to occur during unclear weather conditions, on weekends, at night time where there are no lights, on curved and inclined roads, on untarred roads, at mid-blocks and on wider roads. The developed model and its interpretations will make important contributions to road crash analysis and prevention in Ghana with the possibility of extension to other developing countries. These contributing factors could inform policy makers on road design and operational improvements.     

Exploring the factors influencing pedestrian-vehicle crash severity in Dhaka,Bangladesh

Abstract

Although the rate of road crashes and their severity is relatively higher in developing countries, there is still a lack of research on pedestrian-vehicle crash severity in these contexts, particularly in Bangladesh. Therefore, this study aimed to identify the contributing environmental, road, and vehicular factors that influenced pedestrian—single-vehicle crash severity in Dhaka, a megacity and the capital of Bangladesh. A binary logistic regression model was developed in this study by analyzing a data set of pedestrian—single-vehicle crashes involving casualties in Dhaka from 2010 to 2015. The model identified seven significant factors influencing pedestrian-vehicle crash severity. Significant factors increasing the likelihood of fatal crashes included crashes during adverse weather, dawn/dusk period, night period (where street light was absent), off-peak period, crashes where road divider was unavailable, road geometry was straight and flat, and crashes those were occurred by heavier vehicles. Besides, crashes at three-legged intersections were less likely to be fatal. Both similarities and differences were found among the significant factors influencing pedestrian-vehicle crash severity in Dhaka from the findings of the developed countries. The findings of this study would help transport engineers and planners to design safer roadways for both pedestrians and vehicles.     

Institutional investors,selling pressure and crash risk: Evidence from China

Inconsistent with prior literature on the US stock market, our evidence shows the negative role of institutional investors who exacerbate subsequent crash risk in China. This is because institutional ownership amplifies the selling pressure in response to firm’s bad news, which in turn leads to higher stock price crash risk. The positive relation between institutional ownership and crash risk is more (less) pronounced for transient (dedicated) institutional investors, suggesting the selling pressure of short-term investors is heavier. Additionally, competition of institutional investors strengthens institutional selling pressure and hence exacerbates the effect of institutional ownership on crash risk.     

Corporate Philanthropy and Stock Price Crash Risk: Evidence from China

How to mitigate stock price crash risk has become a focus in the theoretical and practical fields. Building on the work of Kim et al. (J Bank Finance, 43:1–13, 2014b), this paper investigates the relation between corporate philanthropy and crash risk under the unique Chinese institutional background. The results show that both state ownership and the 2005 split share reform attenuate the mitigating effect of corporate philanthropy on crash risk. Specifically, the negative relation between corporate philanthropy and crash risk is less pronounced for state-owned enterprises than for non-state-owned enterprises, and it is also less pronounced after firms accomplish the split share reform. Further, this effect is more pronounced for firms with greater financial risks and poorer performance. Our paper contributes to the growing literature on the determinants of stock price crash risk and the economic consequences of corporate philanthropy. It also offers useful guidance to firms that are seeking to reduce stock price crash risk in emerging markets.     

Identifying the factors contributing to the severity of truck-involved crashes

To address the dilemma between the need for truck transportation and the costs related to truck-involved crashes, the key is to identify the risk factors that significantly affect truck-involved crashes. The objective of this research is to estimate the effects of the characteristics of traffic, driver, geometry, and environment on severity of truck-involved crashes. Based on four crash severity categories (fatal/incapacitating, non-incapacitating, possible injury, and no injury/property damage only), a multinomial logit model is conducted to identify the risk factors. The investigation of risk ratios indicates that lower traffic volume with higher truck percentage is associated with more serious traffic crash with fatal/incapacitating injury while a non-standard geometric design is the main cause of non-incapacitating crashes. The influences of weather are significant for the possible-injury crashes while driver condition is the principal cause of no-injury/property-damage-only crashes. In addition, the statistical results demonstrate that the influence of the truck percentage is significant. One-unit change in the truck percentage will cause more than one times probability of being in an injury.     

环境管理体系认证能够抑制股价崩盘风险吗？

近年来，随着环境政策日趋严格，环境负面消息累积导致的股价崩盘风险不断提高。文章基于2007-2019年中国沪深两市A股重污染企业的经验数据，探讨了环境管理体系认证对股价崩盘风险的影响。研究发现，环境管理体系认证能够显著抑制股价崩盘风险，且当媒体关注越高、分析师关注越高时，环境管理体系认证对股价崩盘风险的抑制作用更强。进一步探讨影响机制发现，环境管理体系认证主要通过治理机制和信息机制来影响股价崩盘风险，换言之，环境管理体系认证能够通过提高公司环境绩效和公司信息透明度来抑制股价崩盘风险。研究结论揭示了环境管理体系认证具有资本市场有效性，丰富了股价崩盘风险的影响因素研究，对于政府完善环境管理体系认证制度以提高资本市场稳定性、企业优化战略决策以提升企业价值具有重要的借鉴意义。     

Predictability and interpretability of hybrid link-level crash frequency models for urban arterials compared to cluster-based and general negative binomial regression models

Machine learning (ML) techniques have higher prediction accuracy compared to conventional statistical methods for crash frequency modelling. However, their black-box nature limits the interpretability. The objective of this research is to combine both ML and statistical methods to develop hybrid link-level crash frequency models with high predictability and interpretability. For this purpose, M5′ model trees method (M5′) is introduced and applied to classify the crash data and then calibrate a model for each homogenous class. The data for 1134 and 345 randomly selected links on urban arterials in the city of Charlotte, North Carolina was used to develop and validate models, respectively. The outputs from the hybrid approach are compared with the outputs from cluster-based negative binomial regression (NBR) and general NBR models. Findings indicate that M5' has high predictability and is very reliable to interpret the role of different attributes on crash frequency compared to other developed models.     

Data mining in road crash analysis: the context of developing countries

The recent advancements in the field of data mining have made vast progress in extracting new information and hidden patterns from large datasets which are often overlooked by the traditional statistical approaches. These methods focus on searching for new and interesting hypothesis which were previously unobserved. Road safety researchers working with the crash data from developed world have seen encouraging success in obtaining new insight into crash mechanism through data mining. An attempt was made in this study to apply these advance methods and evaluate their performance in manifesting crash causes for Bangladesh. The study applies hierarchical clustering to identify hazardous clusters, random forest to find important variables explaining each of these clusters, and classification and regression trees to unveil their respective crash mechanisms for the road crash data of Bangladesh. The results identified several new interesting relationships and acknowledged issues related to quality of data.