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.

Automation 5.0: The Key to Systems Intelligence and Industry 5.0

AUTOMATION has come a long way since the early days of mechanization,i.e.,the process of working exclusively by hand or using animals to work with machinery.The rise of steam engines and water wheels represented the first generation of industry,which is now called Industry Citation:L.Vlacic,H.Huang,M.Dotoli,Y.Wang,P.Ioanno,L.Fan,X.Wang,R.Carli,C.Lv,L.Li,X.Na,Q.-L.Han,and F.-Y.Wang,“Automation 5.0:The key to systems intelligence and Industry 5.0,”IEEE/CAA J.Autom.Sinica,vol.11,no.8,pp.1723-1727,Aug.2024.

基于.net的党建工作平台的设计与实现

数字化、信息化技术在机关部门日常事务中发挥重要作用。本平台基于.net技术及oralce数据库技术,采用B/S互联网模式,实现了机关内部党建的日常工作,将各项事务流程化、规范化;记录每项工作的办理时间,以数据的方式进行归档,方便查询和考核检查。将日常事务信息化、数字化,可对部门党建工作起到积极促进作用,提高办公效率。

Towards Energy-Efficient Autonomous Driving: A Multi-Objective Reinforcement Learning Approach

Dear Editor, With the development of automobile industry and artificial intelligence(AI) domains, autonomous vehicles(AVs) are becoming a reality and promise to revolutionize human mobility [1]–[3]. The decision-making system of AVs is crucial, which is typically required to trade off multiple competing objectives. For example,when determining driving policies.

制约农产品电商直播发展的原因与对策研究

随着网络直播平台的兴起,农产品直播销售成为农民脱贫致富、推动乡村振兴的新方式。通过分析农产品电商直播发展动因,并在指出农产品电商直播发展过程中遇到的缺乏行业规范,缺乏行业监管,农民电商知识不足,直播经济效益不高,农产品标准化低,购买反馈不一等阻碍的基础上,探索农产品电商直播发展路径:加强培训,提升农产品电商直播经济效益;优质内容策划,打造良好私域流量;重视产品及服务,提高用户满意度。

对《市场营销》课程在线开放建设的思考——基于教学工作诊断与改进制度视角

以我校课程层面质量保证子系统为基础,诊断出市场营销课程建设存在教学资源质量不高、课程成绩优秀率低及网络平台访问量低等问题,进而提出相关改进对策:多方参与讨论,优化课程内容;发挥学习平台,强化课程知识;充分运用平台,提高访问量;及时跟踪访问,检查学习效果。

超分子水凝胶软反应器制备钯纳米催化剂的研究

金属纳米颗粒(NPs)因其具有独特的物理和化学性质而在传感器、能源储存材料、生物成像、环保材料以及催化等领域得到广泛应用。超分子水凝胶具有的网络和多孔结构能赋予NPs高分散稳定性、易回收、自修复等性能。以超分子水凝胶为模板和软反应器,通过原位还原制备了负载纳米钯的复合催化剂。利用XRD、TGA、SEM及TEM等对催化剂进行了结构和性能表征,发现该复合催化剂具有良好的自修复能力。以Na BH4为还原剂、水为介质,在Pd/水凝胶中催化还原4-硝基苯酚,考察了温度对催化性能的影响。通过循环实验发现,该催化剂在重复使用6次后仍然保持了良好的催化性能。

Overexpression of microRNA-124 promotes the neuronal differentiation of bone marrow-derived mesenchymal stem cells

microRNAs （miRNAs） play an important regulatory role in the self-renewal and differentiation of stem cells. In this study, we examined the effects of miRNA-124 （miR-124） overexpression in bone marrow-derived mesenchymal stem cells. In particular, we focused on the effect of overexpression on the differentiation of bone marrow-derived mesenchymal stem cells into neurons. First, we used GeneChip technology to analyze the expression of miRNAs in bone marrow-derived mesen- chymal stem cells, neural stem cells and neurons, miR-124 expression was substantially reduced in bone marrow-derived mesenchymal stem cells compared with the other cell types. We con- structed a lentiviral vector overexpressing miR-124 and transfected it into bone marrow-derived mesenchymal stem cells. Intracellular expression levels of the neuronal early markers [3-III tu- bulin and microtubule-associated protein-2 were significantly increased, and apoptosis induced by oxygen and glucose deprivation was reduced in transfected cells. After miR-124-transfected bone marrow-derived mesenchymal stem cells were transplanted into the injured rat spinal cord, a large number of cells positive for the neuronal marker neurofilament-200 were observed in the transplanted region. The Basso-Beattie-Bresnahan locomotion scores showed that the motor function of the hind limb of rats with spinal cord injury was substantially improved. These re- sults suggest that miR-124 plays an important role in the differentiation of bone marrow-derived mesenchymal stem cells into neurons. Our findings should facilitate the development of novel strategies for enhancing the therapeutic efficacy of bone marrow-derived mesenchymal stem cell transplantation for spinal cord injury.

Analysis of Autopilot Disengagements Occurring During Autonomous Vehicle Testing

In present-day highly-automated vehicles, there are occasions when the driving system disengages and the human driver is required to take-over. This is of great importance to a vehicle's safety and ride comfort. In the U.S state of California, the Autonomous Vehicle Testing Regulations require every manufacturer testing autonomous vehicles on public roads to submit an annual report summarizing the disengagements of the technology experienced during testing. On 1 January 2016,seven manufacturers submitted their first disengagement reports:Bosch, Delphi, Google, Nissan, Mercedes-Benz, Volkswagen, and Tesla Motors. This work analyses the data from these disengagement reports with the aim of gaining abetter understanding of the situations in which a driver is required to takeover, as this is potentially useful in improving the Society of Automotive Engineers(SAE) Level 2 and Level 3 automation technologies.Disengagement events from testing are classified into different groups based on attributes and the causes of disengagement are investigated and compared in detail. The mechanisms and time taken for take-over transition occurred in disengagements are studied. Finally, recommendations for OEMs, manufacturers, and government organizations are also discussed.

Advances in Vision-Based Lane Detection：Algorithms,Integration,Assessment,and Perspectives on ACP-Based Parallel Vision

Lane detection is a fundamental aspect of most current advanced driver assistance systems(ADASs). A large number of existing results focus on the study of vision-based lane detection methods due to the extensive knowledge background and the low-cost of camera devices. In this paper, previous visionbased lane detection studies are reviewed in terms of three aspects, which are lane detection algorithms, integration, and evaluation methods. Next, considering the inevitable limitations that exist in the camera-based lane detection system, the system integration methodologies for constructing more robust detection systems are reviewed and analyzed. The integration methods are further divided into three levels, namely, algorithm, system,and sensor. Algorithm level combines different lane detection algorithms while system level integrates other object detection systems to comprehensively detect lane positions. Sensor level uses multi-modal sensors to build a robust lane recognition system. In view of the complexity of evaluating the detection system, and the lack of common evaluation procedure and uniform metrics in past studies, the existing evaluation methods and metrics are analyzed and classified to propose a better evaluation of the lane detection system. Next, a comparison of representative studies is performed. Finally, a discussion on the limitations of current lane detection systems and the future developing trends toward an Artificial Society, Computational experiment-based parallel lane detection framework is proposed.

Vehicle Dynamic State Estimation： State of the Art Schemes and Perspectives

Next-generation vehicle control and future autonomous driving require further advances in vehicle dynamic state estimation. This article provides a concise review, along with the perspectives, of the recent developments in the estimation of vehicle dynamic states. The definitions used in vehicle dynamic state estimation are first introduced, and alternative estimation structures are presented. Then, the sensor configuration schemes used to estimate vehicle velocity, sideslip angle, yaw rate and roll angle are presented. The vehicle models used for vehicle dynamic state estimation are further summarized, and representative estimation approaches are discussed. Future concerns and perspectives for vehicle dynamic state estimation are also discussed.

Blood perfusion of the contralateral testis evaluated with contrast-enhanced ultrasound in rabbits with unilateral testicular torsion

The changes of blood perfusion of contralateral testis after unilateral testicular torsion remain controversial.In this study,28 New Zealand white male rabbits were randomly divided into five groups.Group A(n=8),the control group,underwent a sham operation on the unilateral testis without inducing testicular torsion.In groups B,C,and D(n=5 each),unilateral testicular torsion was induced,and,after 3,6 or 24 h,respectively,detorsion was performed.In group E(n=5),permanent unilateral testicular torsion was applied.Contrast-enhanced ultrasound was used to observe the blood perfusion of the contralateral testis at the following stages:pre-torsion(preopration),immediately post-torsion(postopration),pre-detorsion,immediately post-detorsion,and late-stage post-detorsion(6-12 h post-detorsion in groups B-D)or at a similar time point(15-21 h post-torsion in group E).Time-intensity curves were generated,and the following parameters were derived and analyzed:arrival time,time to peak intensity,peak intensity,and half-time of the descending peak intensity.The analysis revealed that blood perfusion of the contralateral testis increased immediately after testicular torsion on the opposite side(P<0.05),which increased with prolonged testicular torsion of the other testis.This research demonstrated that contrast-enhanced ultrasound was valuable in evaluating blood perfusion of the contralateral testis after unilateral testicular torsion.

Hazard-evaluation-oriented Moving Horizon Parallel Steering Control for Driver-Automation Collaboration During Automated Driving

Prompted by emerging developments in connected and automated vehicles, parallel steering control, one aspect of parallel driving, has become highly important for intelligent vehicles for easing the burden and ensuring the safety of human drivers. This paper presents a parallel steering control framework for an intelligent vehicle using moving horizon optimization.The framework considers lateral stability, collision avoidance and actuator saturation and describes them as constraints, which can blend the operation of a human driver and a parallel steering controller effectively. Moreover, the road hazard and the steering operation error are employed to evaluate the operational hazardous of an intelligent vehicle. Under the hazard evaluation,the intelligent vehicle will be mainly operated by the human driver when the vehicle operates in a safe and stable manner.The automated steering driving objective will play an active role and regulate the steering operations of the intelligent vehicle based on the hazard evaluation. To verify the effectiveness of the proposed hazard-evaluation-oriented moving horizon parallel steering control approach, various validations are conducted, and the results are compared with a parallel steering scheme that does not consider automated driving situations. The results illustrate that the proposed parallel steering controller achieves acceptable performance under both conventional conditions and hazardous conditions.

Collective Entity Alignment for Knowledge Fusion of Power Grid Dispatching Knowledge Graphs

Knowledge graphs(KGs)have been widely accepted as powerful tools for modeling the complex relationships between concepts and developing knowledge-based services.In recent years,researchers in the field of power systems have explored KGs to develop intelligent dispatching systems for increasingly large power grids.With multiple power grid dispatching knowledge graphs(PDKGs)constructed by different agencies,the knowledge fusion of different PDKGs is useful for providing more accurate decision supports.To achieve this,entity alignment that aims at connecting different KGs by identifying equivalent entities is a critical step.Existing entity alignment methods cannot integrate useful structural,attribute,and relational information while calculating entities’similarities and are prone to making many-to-one alignments,thus can hardly achieve the best performance.To address these issues,this paper proposes a collective entity alignment model that integrates three kinds of available information and makes collective counterpart assignments.This model proposes a novel knowledge graph attention network(KGAT)to learn the embeddings of entities and relations explicitly and calculates entities’similarities by adaptively incorporating the structural,attribute,and relational similarities.Then,we formulate the counterpart assignment task as an integer programming(IP)problem to obtain one-to-one alignments.We not only conduct experiments on a pair of PDKGs but also evaluate o ur model on three commonly used cross-lingual KGs.Experimental comparisons indicate that our model outperforms other methods and provides an effective tool for the knowledge fusion of PDKGs.

A Sensorless State Estimation for A Safety-Oriented Cyber-Physical System in Urban Driving:Deep Learning Approach

In today's modern electric vehicles,enhancing the safety-critical cyber-physical system(CPS)'s performance is necessary for the safe maneuverability of the vehicle.As a typical CPS,the braking system is crucial for the vehicle design and safe control.However,precise state estimation of the brake pressure is desired to perform safe driving with a high degree of autonomy.In this paper,a sensorless state estimation technique of the vehicle's brake pressure is developed using a deep-learning approach.A deep neural network(DNN)is structured and trained using deep-learning training techniques,such as,dropout and rectified units.These techniques are utilized to obtain more accurate model for brake pressure state estimation applications.The proposed model is trained using real experimental training data which were collected via conducting real vehicle testing.The vehicle was attached to a chassis dynamometer while the brake pressure data were collected under random driving cycles.Based on these experimental data,the DNN is trained and the performance of the proposed state estimation approach is validated accordingly.The results demonstrate high-accuracy brake pressure state estimation with RMSE of 0.048 MPa.

冲头对层合板低能量冲击损伤有限元模拟精度的影响

为探索冲头对低能量冲击损伤有限元模拟精度的影响,基于连续损伤力学模型,采用基于应变的Hashin失效准则,并利用VUMAT子程序实现刚度折减,建立了预测复合材料层合板低能量冲击损伤的数值模型;并选用圆形和锥形冲头进行了落锤低能量冲击试验,测量了冲击损伤形貌。研究结果表明:低能量冲击条件下,模型可以较为准确的预测损伤深度及面积,但相较于圆形冲头,锥形冲头的预测精确度更高,且在25J≥冲击能量≥15J时,模型预测精度更高。

遥感技术广东龙川县地质灾害调查的应用

广东省河源市龙川县地处粤东北部地质灾害高发区,是广东地质灾害重点防治区之一,尽快开展地质灾害详细调查非常必要。文章以SOPT.ETM+和GoogleEarth为遥感数据源结合现在已确定滑坡、地面塌陷、泥石流、地面沉降、地裂缝以及斜坡、崩塌等地质灾害点和实际野外踏勘,对广东省河源市龙川县3066km^2进行遥感地质灾害解译,利用遥感技术共解译出地灾点103处,其中滑坡48处,不稳定斜坡33处,崩塌13处,地质环境9处,为地质灾害详细调查提供了调查方向。

参麦注射液辅助紫杉醇联合卡铂化疗治疗非小细胞肺癌的疗效观察

目的分析参麦注射液辅助紫杉醇联合卡铂化疗方案治疗非小细胞肺癌的效果。方法以我院2016年1月-2021年3月收治的52例肺癌患者为研究对象,以单双号法随机分为单纯化疗组26例与辅助治疗组26例。单纯化疗组行紫杉醇联合卡铂化疗方案,辅助治疗组在单纯化疗组基础上予以参麦注射液辅助治疗,对比2组临床效果。结果疾病缓解率,辅助治疗组略高于单纯化疗组,但差异无统计学意义(P>0.05)。生活质量评分,化疗前差异无统计学意义(P>0.05);化疗后,辅助治疗组评分高于单纯化疗组,差异具有统计学意义(P<0.05)。不良反应发生率,化疗后辅助治疗组低于单纯化疗组(P<0.05)。化疗前,2组T细胞亚群及NK细胞对比无明显差异(P>0.05);化疗后,辅助治疗组的CD_(3)^(+)、CD_(4)^(+)、NK细胞水平较同组治疗前有明显提升(P<0.05)、CD_(8)^(+)较同组化疗前无明显差异(P>0.05),而单纯化疗组治疗后CD_(3)^(+)、CD_(4)^(+)较化疗前有所降低,CD8+较化疗前有所提高,但无统计学差异(P>0.05);而2组化疗后对比,辅助治疗组CD_(3)^(+)、CD_(4)^(+)、NK细胞水平均高于单纯化疗组,CD_(8)^(+)低于单纯化疗组,差异显著(P<0.05)。结论参麦注射液辅助紫杉醇联合卡铂化疗方案治疗非小细胞肺癌,具有明显增效减毒作用,利于提高患者免疫功能并改善生活质量。

超分子水凝胶原位制备纳米镍及其在对硝基苯酚催化还原中的应用

在超分子水凝胶中负载Ni^(2+),再添加NaBH_(4)原位还原制备得到纳米镍。利用EDS、SEM、TEM及流变等方法对复合催化剂进行结构和性能表征,结果发现纳米镍尺寸约为5~10 nm,均匀分散于水凝胶中,复合催化剂具有良好的自修复能力。利用UV-Vis研究了其在催化还原4-NP中的性能,通过对反应随时间的变化及在不同温度下的催化性能研究发现,该反应动力学数据符合一级反应特征,表观速率常数与反应温度呈线性关系,催化剂重复使用6次后仍然保持了良好的催化性能。

Research on Multi-Scale Modeling of Grid-Connected Distributed Photovoltaic Power Generation

The complexity of distribution network model mainly depends on the model scale of grid-connected distributed photovoltaic (PV) power generation. Therefore, the simulation performance of multi-scale PV model is the key factor of the simulation accuracy in the specific operating scenarios of distribution network. In this paper, a multi-scale model of grid connected PV distributed generation system is proposed based on the mathematical model of grid-connected distributed PV power generation. It is analyzed that differences of simulation performance, such as adaptability of simulation step size, accuracy of output and the effect on voltage profile of distribution network, between PV models with different scales in IEEE 33 node example. Simulation results indicate that the multi-scale model is effective in improving the accuracy and efficiency of simulation under different operating conditions of distribution network.