Toward Trustworthy Decision-Making for Autonomous Vehicles:A Robust Reinforcement Learning Approach with Safety Guarantees

While autonomous vehicles are vital components of intelligent transportation systems,ensuring the trustworthiness of decision-making remains a substantial challenge in realizing autonomous driving.Therefore,we present a novel robust reinforcement learning approach with safety guarantees to attain trustworthy decision-making for autonomous vehicles.The proposed technique ensures decision trustworthiness in terms of policy robustness and collision safety.Specifically,an adversary model is learned online to simulate the worst-case uncertainty by approximating the optimal adversarial perturbations on the observed states and environmental dynamics.In addition,an adversarial robust actor-critic algorithm is developed to enable the agent to learn robust policies against perturbations in observations and dynamics.Moreover,we devise a safety mask to guarantee the collision safety of the autonomous driving agent during both the training and testing processes using an interpretable knowledge model known as the Responsibility-Sensitive Safety Model.Finally,the proposed approach is evaluated through both simulations and experiments.These results indicate that the autonomous driving agent can make trustworthy decisions and drastically reduce the number of collisions through robust safety policies.

Default rules in investment decision-making:trait anxiety and decision-making styles

This study investigates the role of default options in the relationship between trait anxiety,and decision-making styles and financial decisions.One hundred and ninety-four participants were divided into three groups and subjected to three different conditions.Under each experimental condition,they had to decide whether to accept or reject investment proposals.In the first group,they had been enrolled in investment plans by default(opt-out condition),in the second group,they had not been automatically enrolled in these plans(opt-in condition),and in the third group they had to choose whether to enroll or not(control condition).The results showed that the investment decisions of anxious,avoidant,rational and dependent individuals could be facilitated by default options.In conclusion,using default options as a“nudge”can support specific groups of people to improve their financial decisions.

Application of PPC Model Based on RAGA in Real Estate Investment Decision-Making

According to the size of the projector function to evaluate the merits of the program, Projection Pursuit method is applied to real estate investment decision-making by using the real coding based on Accelerating Genetic Algorithm (RAGA) to optimize the Projection Pursuit Classification (PPC) process and a wide range of indicators value was projected linearly. The results are reasonable and verified with an example. At the same time, the subjective of the target weight can be avoided. It provides decision-makers with comprehensive information on all the indicators of new ideas and new

A group consensus model for evaluating real estate investment alternatives

Background:Individual decision-making largely influences the effectiveness of decisions and benefits of investments.Methods:In this article,a consensus model for group decision-making(GDM),based on the analytic hierarchy process(AHP),is developed to gather group ideas and analyze the real estate investment environment under multi-criteria problems.Twelve evaluation procedures of the developed model,which increase the convergence of the opinions of multiple experts,are proposed.Results:An empirical case about the real estate investment environment is applied to certify the feasibility of this developed model.Conclusions:the evaluation procedures have been fully observed with several rounds of discussions,and have manifested the experiences of experts.Besides,the evaluation results are in accordance with real-world situations,which demonstrates that our developed model is a feasible analysis tool for real estate investors to obtain better profits and lower risk.

Probabilistic Evaluation for Commercial Real Estate Investments

Throughout the decision-making process, prudent investors must address questions regarding the probabilities of future profit gain. In this study, the probability-based discounted cash flow （DCF） method with net present value （NPV） as the indicator was adopted as an analysis tool. A probabilistic framework for measuring exceeding probability of annual rate of return on a commercial real estate investment under a specified holding period was developed. Based on the framework, the relation curves of annual rate of return versus the corresponding exceeding probability of return for available financing schemes were constructed. These curves were used as a tool to prioritize the schemes and inform decision-making. An example case is presented to demonstrate the decision-making process developed in this study. Through the proposed process, investors are given basic information on the return, probability that profit gain will occur, and feasibility of financial schemes for commercial real estate investments.

Fuzzy-logic Method for Global Quality Optimization Problem of the Programmed Action Investment

In order to analyze the planning of a transport linear infrastructure(railway or ordinary road),in order to optimize a relationship work-environment after-work,the study team(engineers,architects,economists,etc),realize a careful prearranged analysis about the characteristic of the site and the large area which are involved by the work project and,once one found all possible alternative solutions,he should compare them through the use of suitable technical,economical and environmental parameters,choosing that one which maximize the global utility of the public investment.In this paper we study a fuzzy-logic method in order to help the decision maker in the analysis of the programmed action public investment.

Optimization of Group Multiattribute Decision-Making Model in Commercial Space Investment

A group multiattribute decision-making model was proposed by implementing prospect theory,multi-attribute decision-making,group decision-making and entropy methods for the optimization in commercial space investment.First,the decision-making function was decided using prospect theory by the preference of each expert to reach the comprehensive prospect value based on different investment options;second,expert decision weights were reached according to entropy method;third,the expert group decision-making information was congregated according to the group decision-making congregation algorithm to reach the most optimized investment option;finally,an example was given to demonstrate the feasibility and effectiveness of the method.This model com-prehensively takes the advantages of many methods to congregate experts'experiences and avoid the subjective influences,thus providing a scientific decision-making approach for the commercial space investment.

个体与情境因素如何促成员工低频安全违规行为?——基于个体-情境互动理论的组态分析

为了揭示社会人口统计学因素和情境因素之间复杂的交互关系如何促成员工低频安全违规行为,结合组态思想和个体-情境互动理论,采用模糊集定性比较分析(fsQCA)方法分析1294份员工调查数据,探究个体(雇佣形式和性别)和情境(同事安全违规频率、企业安全投入、企业员工规模和行业危险程度)因素构成的不同条件组态对员工低频安全违规行为的影响。研究发现:任何单一因素均不构成员工低频安全违规行为的必要条件。员工低频安全违规行为存在3种不同驱动模式:非高危行业同事低频安全违规模式、高安全投入与同事低频安全违规共驱模式以及非高危行业大型企业高安全投入模式。同事低频安全违规行为在4种组态解中均是实现员工低频安全违规行为的核心条件。本研究引入fsQCA探究个体与情境因素对员工低频安全违规行为的组态效应,不仅拓展了对员工低频安全违规行为驱动模式的理解,还有助于倡导组态方法在行为安全领域的应用。

中吉乌铁路吉国境内段限制坡度方案研究

研究目的:中吉乌铁路吉尔吉斯斯坦境内段位于天山山系南天山的西部,穿越莫尔多套山、费尔干纳山,线路跨越吐尔尕特高山区、阿尔帕高原盆地区等10个地貌单元,线路附近最高点贾曼达万山高程4 205 m,最低点贾拉拉巴德高程722 m,相对高差3 483 m,地形高差巨大,工程地质条件复杂,吐尔尕特至马克马尔段采用1 435 mm标准轨距、马克马尔至贾拉拉巴德南段采用1 520 mm宽轨距,线路限制坡度的选择是项目研究的重点和难点。研究结论:(1)结合线路沿线地形地质条件、承担运输货物特点、列车牵引质量、机车选型、工程投资和综合经济性,对限制坡度分段进行研究;(2)标轨段重点对18‰、20‰、24‰、25‰四个方案,宽轨段重点对18‰、20‰、24‰、27‰四个方案进行了分析研究,为降低工程投资、提高项目经济性、匹配运输组织、优化运输条件、保障运营安全性,推荐中吉乌铁路吉国境内段限制坡度采用20‰方案;(3)本研究思路和方法可为境外铁路工程建设提供参考和借鉴。

高海拔季节冻土区完全融化期土壤水分特征曲线适用性

以怒江源区那曲流域为例,基于4个试验场完全融化期(6—9月)的土壤体积含水量(0.15~0.51 cm^(3)/cm^(3))和土壤基质势数据(0~200 kPa)实测数据,选择Van Genuchten(VG)、Brooks-Corey(BC)和Campbell 3个模型进行拟合,以均方根误差ERMS和决定系数R2为评价指标,分析3个模型对高海拔季节冻土区不同土层和不同土壤质地的适用性。结果表明:从整体上看,VG模型(平均R2为0.992,平均ERMS为0.006 cm^(3)/cm^(3))的拟合效果优于BC模型(平均R2为0.972,平均ERMS为0.019 cm^(3)/cm/3)和Campbell模型(平均R2为0.984,平均ERMS为0.014 cm^(3)/cm^(3));但是在不同土层和不同土壤质地情况下模型的适用性有所区别,VG模型更适用于壤土和壤质砂土(平均R2为0.987,平均ERMS为0.008 cm^(3)/cm^(3))以及土壤深层(10~35 cm土层,平均R2为0.990,平均ERMS为0.007 cm^(3)/cm^(3)),Campbell模型更适用于砂质壤土(平均R2为0.985,平均ERMS为0.009 cm^(3)/cm^(3))以及土壤表层(5 cm土层,平均R2为0.993,平均ERMS为0.006 cm^(3)/cm^(3)),BC模型在不同条件下都不是最优模型;参数θr取值大小会显著影响土壤水分特征曲线的形状。本研究可为深入研究高海拔季节冻土区的土壤水分运动特性以及中华水塔区的水源涵养作用提供支持。

调水工程建设期安全-进度-投资系统风险分析——以引江济淮工程(河南段)为例

以引江济淮工程(河南段)为例,在确定安全-进度-投资系统风险评价指标体系的基础上,基于层次分析-模糊综合评价方法分析安全、进度、投资的单项风险;在考虑工程建设期安全、进度、投资的相互影响后,基于改进的综合风险评价方法分析安全-进度-投资系统风险。结果表明:当分析单项风险时,安全、进度和投资风险的评价结果均为一般风险;当分析系统风险时,得到安全风险>进度风险>投资风险;进一步分析指标体系中的准则层和指标层,安全风险的现场风险中施工技术方案风险排序第一,是后续风险管控的重点。本研究为提高工程建设期安全-进度-投资系统风险的可靠性、降低风险事件的发生提出了理论和技术参考。

基于组合赋权和SPA-TOPSIS的煤矿安全投入决策模型

为解决煤矿安全投入结构和决策方案不合理的问题,首先基于安全价值的视角,考虑安全功能与安全产出关系,选取8个评价指标,构建煤炭企业安全投入评价体系;其次采用熵权法与层次分析法(AHP),综合确定指标权重;最后采用集对分析(SPA)理论改进逼近理想解排序法(TOPSIS),建立决策模型,用以分析评价某煤矿2012—2022年的决策方案,优选评价方案,并针对实际问题提出改善意见。研究表明:该煤矿企业应更注重安全教育和工业卫生指标的投入;煤矿企业在安全投入决策时应综合考虑安全功能需要与安全产出效益,借鉴最佳投入配置,合理调整未来安全投入决策重点。

安全和环保投入管理情况审计研究

对安全和环保投入管理情况审计的背景和内涵进行回顾,以某特大型石油石化公司为例,从审计角度出发,分析其安全和环保投入管理的现状,阐述了开展专项审计的必要性和科学性,并总结目前存在的主要风险和问题表现,提出了加强安全和环保投入管理的建议措施,以期为夯实安全环保基础、促进高质量发展提供有益借鉴。

基于AHP-DEMATEL-ISM的煤矿安全投入结构研究

为改善煤矿安全投入结构状况,更好地为煤矿安全生产服务,研究了煤矿安全投入结构影响因素的相互关系。采用m-IHEL理论分析煤矿企业安全结构,将其划分为人—机—环境—信息4个子系统,构建煤矿安全投入结构评价指标体系,并使用AHP-DEMATEL-ISM模型进行分析评价。研究表明:安全教育培训、采掘安全设备、信息管理系统、安全监控系统是影响煤矿安全投入结构的关键因素,企业应该加强人员投入,重视环境和信息在煤矿系统的作用,以提高煤矿智能化水平。

基于调节效应模型分析煤矿企业安全投入对经济效益的影响

为合理有效地引导上市煤矿企业强化安全管理进而提高经济效益,选取了29家上市煤矿企业,基于2013—2022年的安全投入数据,运用固定效应模型和调节效应模型,探讨上市煤矿企业安全投入与经济效益之间的关系,并引入内部控制变量研究其调节作用。结果表明:我国上市煤矿企业安全投入与经济效益具有显著的正向关系,并且内部控制在上市煤矿企业安全投入与经济效益之间存在显著的负向调节作用。为进一步促进我国上市煤矿企业持续、高效发展,根据研究结果提出了相应的对策建议。

高压电气设备未来安全检修的趋势与挑战

随着电力系统规模的不断扩大和对供电可靠性要求的日益提高,高压电气设备的维护与安全检修成为确保电网稳定运行的关键环节。未来高压电气设备维护的发展趋势将侧重于智能化、预防性维护策略以及远程监测技术的应用,旨在提高检修效率、减少非计划停运并保障人员安全。然而,这一进程也面临着诸多挑战,包括技术升级的投资成本、数据安全与隐私问题、专业技能人才的培养,以及适应不断变化的电力市场需求。因此,本文将深入分析高压电气设备维护的未来趋势,如人工智能与大数据分析的融合应用、状态监测系统的普及,同时探讨面对这些趋势时,企业与行业需克服的主要障碍与解决方案,以促进高压电气设备维护领域的高质量发展。

DIMZAL:A Software Tool to Compute Acceptable Safety Distance

The scope of this work is to present a multidisciplinary study in order to propose a tool called DIMZAL. DIMZAL forecasts fuelbreak safety zone sizes. To evaluate a safety zone and to prevent injury, the Acceptable Safety Distance (ASD) between the fire and firefighters is required. This distance is usually set thanks to a general rule-of-thumb: it should be at least 4 times the maximum flame length. A common assumption considers an empirical relationship between fireline intensity and flame length. In the current work which follows on from an oral presentation held at the VII International Conference on Forest Fire Research in Coimbra in 2014, an alternative way is proposed: a closed physical model is applied in order to quantize the ASD. This model is integrated in a software tool, which uses a simulation framework based on Discrete EVent system Specification formalism (DEVS), a 3D physical real-time model of surface fires developed at the University of Corsica and a mobile application based on a Google SDK to display the

Dynamic probability evaluation of safety levels of earth-rockfill dams using Bayesian approach

In order to accurately predict and control the aging process of dams, new information should be collected continuously to renew the quantitative evaluation of dam safety levels. Owing to the complex structural characteristics of dams, it is quite difficult to predict the time-varying factors affecting their safety levels. It is not feasible to employ dynamic reliability indices to evaluate the actual safety levels of dams. Based on the relevant regulations for dam safety classification in China, a dynamic probability description of dam safety levels was developed. Using the Bayesian approach and effective information mining, as well as real-time information, this study achieved more rational evaluation and prediction of dam safety levels. With the Bayesian expression of discrete stochastic variables, the a priori probabilities of the dam safety levels determined by experts were combined wfth the likelihood probability of the real-time check information, and the probability information for the evaluation of dam safety levels was renewed. The probability index was then applied to dam rehabilitation decision-making. This method helps reduce the difficulty and uncertainty of the evaluation of dam safety levels and complies with the current safe decision-making regulations for dams in China. It also enhances the application of current risk analysis methods for dam safety levels.

The Impact of Human Misjudgment Psychology on Investing

Everyone responds to their psychological emotions,which affects all aspects of their lives.Therefore,psychology is not an independent discipline;it can react chemically with many other disciplines,such as finance and architecture.A person who is not careful and unconcerned about precision is more likely to fail a project.Investment decision-making always appears in people’s daily life and takes an important role.Through linking psychology to investment,people can learn a deep understanding on their investment decision.Human Misjudgment Psychology is a not widely taught discipline although it has great influence on the decision-making.As a result,the focus of this paper will be on the impact of Human Misjudgment Psychology on investment decisions.However,due to the limitation of time,only five biases from the Human Misjudgment Psychology will be covered,so further research and studies of the other biases will be looking forward to being finished.

采掘业上市企业安全投入对企业价值的影响--基于内部控制的调节作用

为科学客观地评价企业安全投入效果,提高安全管理水平,以2013—2019年我国采掘业上市企业为样本,建立面板数据多元回归模型,实证分析安全投入、内部控制与企业价值之间的关系,并进一步探讨企业内部控制对安全投入与企业价值关系的调节作用。结果表明:采掘业上市企业安全投入与企业价值呈显著正相关关系;企业的内部控制越好,企业的价值也越高;内部控制在安全投入与企业价值之间发挥调节效应,良好的内部控制可以增强安全投入对企业价值的正向影响。因此,采掘业上市企业不仅要注重安全投入,同时应建立有效的内部控制管理机制,促进企业价值不断提升。