Deep Learning-Based Control System Design for Emergency Vehicles through Intersections

This paper addresses the challenge of integrating priority passage for emergency vehicles with optimal intersection control in modern urban traffic. It proposes an innovative strategy based on deep learning to enable emergency vehicles to pass through intersections efficiently and safely. The research aims to develop a deep learning model that utilizes intersection violation monitoring cameras to identify emergency vehicles in real time. This system adjusts traffic signals to ensure the rapid passage of emergency vehicles while simultaneously optimizing the overall efficiency of the traffic system. In this study, OpenCV is used in combination with Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN) to jointly complete complex image processing and analysis tasks, to realize the purpose of fast travel of emergency vehicles. At the end of this study, the principle of the You Only Look Once (YOLO) algorithm can be used to design a website and a mobile phone application (app) to enable private vehicles with emergency needs to realize emergency passage through the application, which is also of great significance to improve the overall level of urban traffic management, reduce traffic congestion and promote the development of related technologies.

Fractional order PID control for steer-by-wire system of emergency rescue vehicle based on genetic algorithm

Aiming at dealing with the difficulty for traditional emergency rescue vehicle(ECV)to enter into limited rescue scenes,the electro-hydraulic steer-by-wire(SBW)system is introduced to achieve the multi-mode steering of the ECV.The overall structure and mathematical model of the SBW system are described at length.The fractional order proportional-integral-derivative(FOPID)controller based on fractional calculus theory is designed to control the steering cylinder’s movement in SBW system.The anti-windup problem is considered in the FOPID controller design to reduce the bad influence of saturation.Five parameters of the FOPID controller are optimized using the genetic algorithm by maximizing the fitness function which involves integral of time by absolute value error(ITAE),peak overshoot,as well as settling time.The time-domain simulations are implemented to identify the performance of the raised FOPID controller.The simulation results indicate the presented FOPID controller possesses more effective control properties than classical proportional-integral-derivative(PID)controller on the part of transient response,tracking capability and robustness.

Dynamic Routing for Emergency Vehicle by Collecting Real-Time Road Conditions

When a natural disaster such as earthquake strikes, people go away to safety areas by cars. Some roads are broken and impenetrable by buildings falling down. Furthermore, some fixed infrastructures for radio communication may be broken. In order to quickly bring ambulances and fire trucks to their destinations, it is necessary to provide real-time road conditions to these emergency vehicles via ad-hoc networks. In this paper, we propose a method to periodically reconstruct a route for an emergency vehicle by collecting real-time road conditions via vehicle ad-hoc networks. As simulation results, we confirmed that the proposed method collects 12% more road conditions than existing method. We also confirmed that the proposed method achieves 10% faster arrival than the existing method.

A New Type of Flat Vehicle for Emergency Patient Transfer

The utility model discloses a new type of flat vehicle for emergency patient transfer, comprising a support frame, a bed board, an infusion stand and a transfer assembly;the transfer assembly comprises a trapezoidal base fixed on the upper part of the support frame, and a trapezoid mounted on the bottom or side of the bed board. A sliding sleeve, a limit pin, a fixing cylinder and a spring;the trapezoidal sliding sleeve is matched on the trapezoidal base, a pin shaft hole is arranged on the trapezoidal base, the fixing cylinder is fixed on the trapezoidal sliding sleeve, and the limit pin is sleeved in the fixing cylinder, The bottom of the limit pin protrudes from the trapezoidal sliding sleeve, and the upper part is provided with a traction rod;the spring is sleeved on the traction rod, and a limiting plate is arranged at intervals on both sides of the trapezoidal base, and the limiting plate is wrapped in the trapezoidal sliding sleeve. The outer end: by setting the transfer component, the bed board is allowed to be fixed, slid and completely disengaged from the support frame, which is convenient for transferring the bed board together with the patient on it during the patient transfer process. It provides convenience for medical staff.

NOMA-Based UAV-Aided Networks for Emergency Communications

High spectrum efficiency(SE)requirement and massive connections are the main challenges for the fifth generation(5G)and beyond 5G(B5G)wireless networks,especially for the case when Internet of Things(IoT)devices are located in a disaster area.Non-orthogonal multiple access(NOMA)-based unmanned aerial vehicle(UAV)-aided network is emerging as a promising technique to overcome the above challenges.In this paper,an emergency communications framework of NOMA-based UAV-aided networks is established,where the disasters scenarios can be divided into three broad categories that have named emergency areas,wide areas and dense areas.First,a UAV-enabled uplink NOMA system is established to gather information from IoT devices in emergency areas.Then,a joint UAV deployment and resource allocation scheme for a multi-UAV enabled NOMA system is developed to extend the UAV coverage for IoT devices in wide areas.Furthermore,a UAV equipped with an antenna array has been considered to provide wireless service for multiple devices that are densely distributed in disaster areas.Simulation results are provided to validate the effectiveness of the above three schemes.Finally,potential research directions and challenges are also highlighted and discussed.

Dynamic performance of heavy-haul combined train applying emergency braking on straight line

A heavy-haul train-track coupled model is developed. Taking the emergency braking of the 2×104 t combined train as example, the train longitudinal impulse, the coupler dynamic behaviors and wheel-rail interactions of vehicles distributing in the different positions are analyzed. The results indicate that under the coupler compressing forces, the couplers of middle locomotives may tilt to the free swing limits, which induces the unidirectional tilt of their connected wagon couplers. Consequently, the coupler longitudinal forces produce the lateral components, and then affect the wheel-rail dynamic interaction. The performance of the middle locomotive and their neighboring freight wagons deteriorate significantly, becoming the most dangerous parts in the combined train. The wagons disconnecting with the locomotives can basically keep their couplers to stabilize in the centering positions, even though the maximum coupler longitudinal force acts on it. And its corresponding running safety also has little changes.

Unmanned aerial vehicle based intelligent triage system in mass-casualty incidents using 5G and artificial intelligence

BACKGROUND:Rapid on-site triage is critical after mass-casualty incidents(MCIs)and other mass injury events.Unmanned aerial vehicles(UAVs)have been used in MCIs to search and rescue wounded individuals,but they mainly depend on the UAV operator’s experience.We used UAVs and artificial intelligence(AI)to provide a new technique for the triage of MCIs and more efficient solutions for emergency rescue.METHODS:This was a preliminary experimental study.We developed an intelligent triage system based on two AI algorithms,namely OpenPose and YOLO.Volunteers were recruited to simulate the MCI scene and triage,combined with UAV and Fifth Generation(5G)Mobile Communication Technology real-time transmission technique,to achieve triage in the simulated MCI scene.RESULTS:Seven postures were designed and recognized to achieve brief but meaningful triage in MCIs.Eight volunteers participated in the MCI simulation scenario.The results of simulation scenarios showed that the proposed method was feasible in tasks of triage for MCIs.CONCLUSION:The proposed technique may provide an alternative technique for the triage of MCIs and is an innovative method in emergency rescue.

The Buffering analysis to identify common geographical factors within the vicinity of severe injury related to motor vehicle crash in Malaysia

BACKGROUND:The main objective was to identify common geographical buildup within the100-meter buffer of severely injured based on injury severity score(ISS) among the motor vehicle crash(MVC) victims in Malaysia.METHODS:This was a prospective cohort study from July 2011 until June 2013 and involved all MVC patients attending emergency departments(ED) of two tertiary centers in a district in Malaysia.A set of digital maps was obtained from the Town Planning Unit of the district Municipal Office(local district map).Vector spaces were spanned over these maps using GIS software(ARCGIS 10.1licensed to the study center),and data from the identified severe injured cases based on ISS of 16 or more were added.Buffer analysis was performed and included all events occurring within a 100-meter perimeter around a reference point.RESULTS:A total of 439 cases were recruited over the ten-month data collection period.Fifty two(11%) of the cases were categorized as severe cased based on ISS scoring of 16 and more.Further buffer analysis looking at the buildup areas within the vicinity of the severely injured locations showed that most of the severe injuries occurred at locations on municipal roads(15,29%),straight roads(16,30%) and within villages buildup(suburban) areas(18,35%).CONCLUSION:This study has successfully achieved its objective in identifying common geographical factors and buildup areas within the vicinity of severely injured road traffic cases.

Research on the construction of smart city railvehicle technical standards system

With the rapid development and application of cloud computing,big data,artificial intelligence,5G,satellite communication,blockchain and other emerging information technologies,conditions have been provided for the intelligent development of urban rail vehicles.With the development of smart urban rail vehicles,the standards system of traditional urban rail vehicle cannot meet the development requirements,so it is necessary to study and reconstruct the standards system.To embody the intelligent level of urban rail vehicles,the paper conducts the research on the standards for the urban rail vehicle train control system,monitoring and diagnosis system,passenger service system,and then proposes the overall architecture and standard list of smart city rail vehicle technical standards system,providing reference for the planning and establishment of China's smart city rail standards system.

Epidemiology and Challenges of Neurotraumas Care in the Emergency Department of a Semi-Urban Hospital in Guinea, West Africa

Trauma is one of the most common surgical emergencies admitted in the acute care departments of hospitals in Guinea, West Africa. We carried a study to assess the epidemiological pattern and clinical care of neurotrauma in the emergency department of the Kindia regional hospital, a rural secondary hospital catering to the needs of western Guinea and nearby districts. Data were prospectively collected from December 2019 to March 2020 after receiving the required hospital authorization and informed consent from the patients or relatives. We recorded two hundred cases of neurotraumas (64.5% of traumatic brain injury cases and 14.5% of spinal cord injury). Neurotraumas represented 17.7% of all admitted patients in the department in the study period. The mean age was 25.34 ± 16.73, and the age range 16 to 30 was the most affected. The predominance was male, with a sex ratio of 3.43. Motor Vehicle Accident was the leading cause 68.5%, and 73.2% of them involved a motorcycle. Motorcycle-to-motorcycle collision was responsible for more than a third of neurotraumas. We classified the majority of the cases as mild and low risk neurotrauma representing 62.08%. All patients benefited from medical treatment, and 30.7% of patients received surgical treatment for associated abdominal, orthopedic, and minor procedures for scalp dilacerations. No patient was referred to a Neurosurgery department, and all living patients were discharged home during the study period with minimal disability. The mortality was 16.3%. Our results could be biased by the lack of interhospital networking and the fact that severe traumatic brain-injured patient dies before seeking medical attention.

Overview of Vehicle AEB

With the rapid development of China's economy and the continuous improvement of people's living standards,people pay more attention to the safety of cars.China's car sales and ownership is also rising,but also led to a lot of traffic accidents.With the continuous promotion of intelligent,electric and networked automobiles,Autonomous Emergency Braking system has become the focus of automobile enterprises in the active safety of automobiles.The overall scheme of auto emergency braking includes information acquisition module,control module and execution module.This paper briefly introduces the application status of this field at home and abroad,and discusses the function and implementation method of each module respectively.

Chip Design for In-Vehicle System Transmitter

This paper presents embedded system design of the In-Vehicle System (IVS) for the European Union (EU) emergency call (eCall) system. The IVS transmitter modules are designed, developed and implemented on a field programmable gate array (FPGA) device. The modules are simulated, synthesized, and optimized to be loaded on a reconfigurable device as a system-on-chip (SoC) for the IVS electronic device. All the modules of the transmitter are designed as a single embedded module. The bench-top test is completed for testing and verification of the developed modules. The hardware architecture and interfaces are discussed. The IVS signal processing time is analyzed for multiple frequencies. A range of appropriate frequency and two hardware interfaces are proposed. A state-of-the-art FPGA design is employed as a first implementation approach for the IVS prototyping platform. This work is used as an initial step to implement all the modules of the IVS on a single SoC chip.

基于长/短视距多模型自适应交互的高速无人车避障规划研究

在低附着、高速紧急避障工况下无人驾驶车辆需要充分考虑到路径规划效率和车辆动力学特性,以保障规划的路径满足车辆高速行驶跟踪精度要求.文中针对无人车紧急避障中路径规划与跟踪控制之间存在的耦合干预问题,提出一种基于长/短视距多层融合的高速紧急避障局部路径规划算法.根据不同风险值障碍物分布的密集程度细化障碍物的风险值,分别设计了可跨/绕障碍物群的风险势场和环境风险状态采样空间,从而构建一种基于偏向性采样的长视距局部路径规划算法.提出了一种基于交互式多模型预测控制的短视距局部路径重规划,建立模型概率实时在线更新规则,实现了极限工况下车辆快速行驶的局部路径规划,同时满足计算实时性、避障安全性和跟踪稳定性的路径规划设计需求.仿真试验验证了所提多层融合局部路径规划方法的有效性和优越性.

汽车新污染物识别清单、风险特征和管控建议

对比国内外相关管控清单,识别出汽车潜在的20大类共55种新污染物。按汽车材料分析,塑料材质零部件可能含有的新污染物种类最多,其次为橡胶、涂料和纺织品;涉及材料种类最多的新污染物为邻苯二甲酸酯(PAEs),其次为全氟和多氟烷基化合物(PFASs)、氯化石蜡(CPs)、壬基酚(NPs)和多环芳烃(PAHs)。风险特征分析结果显示,汽车内空气环境PAEs类的邻苯二甲酸二(α-乙基己基)酯(DEHP)的致癌风险值和PFASs类的全氟辛酸(PFOA)的非致癌风险值最高,DEHP的致癌风险最大值为9.45×10^(−7),略低于美国国家环境保护局(US EPA)规定的基本值1×10^(−6),PFOA的非致癌风险最大值为0.11,低于US EPA规定的基本值1。通过对国内外汽车有害物质管控的法规进行对比分析,总结了国内相关法规存在的不足。建议开展替代技术研究、制定无意痕量新污染物标准体系、制定汽车行业新污染物管控指南和建立汽车新污染物检测指标体系。

基于BERTopic的新兴技术主题识别研究

[目的/意义]识别并预见新兴技术,为企业和政府带来技术先发优势,及时把握技术发展趋势。[方法/过程]本研究采用BERTopic的主题建模方法获取领域主题分布,依据主题向量的余弦相似度合并论文和专利主题,实现新兴主题的识别。[结果/结论]运用BERTopic主题建模方法结合指标评价,能够实现新兴主题与新兴术语的有效识别。以新能源汽车领域为例开展实证研究,使用划分验证期和资料验证法2种方式进行验证,在识别出的16项主题中有12项通过验证,证实了本研究方法的有效性。

运用无人机提升海事监管效能及搜救应急能力研究

通过分析无人机的技术优势和实际应用案例,发现无人机在提高海事监管效率和增强搜救应急响应方面具有显著潜力。将无人机技术应用于通航环境监控、违法行为取证、危险品监管和应急处置等多个方面,不仅提高了监管效率,还增强了应对复杂海况和有毒气体环境的能力。探讨了漳州辖区在监管和搜救领域的需求,以及面临的挑战,并提出了相应的解决方案。

Bibliometric analysis and system review of vehicle routing optimization for emergency material distribution

Determining the optimal vehicle routing of emergency material distribution(VREMD)is one of the core issues of emergency management,which is strategically important to improve the effectiveness of emergency response and thus reduce the negative impact of large-scale emergency events.To summarize the latest research progress,we collected 511VREMD-related articles published from 2010 to the present from the Scopus database and conducted a bibliometric analysis using VOSviewer software.Subsequently,we cautiously selected 49 articles from these publications for system review;sorted out the latest research progress in model construction and solution algorithms;and summarized the evolution trend of keywords,research gaps,and future works.The results show that domestic scholars and research organizations held an unqualified advantage regarding the number of published papers.However,these organizations with the most publications performed poorly regarding the number of literature citations.China and the US have contributed the vast majority of the literature,and there are close collaborations between researchers from both countries.The optimization model of VREMD can be divided into single-,multi-,and joint-objective models.The shortest travel time is the most common optimization objective in the single-objective optimization model.Several scholars focus on multiobjective optimization models to consider conflicting objectives simultaneously.In recent literature,scholars have focused on the impact of uncertainty and special events(e.g.,COVID-19)on VREMD.Moreover,some scholars focus on joint optimization models to optimize vehicle routes and central locations(or material allocation)simultaneously.Solution algorithms can be divided into two primary categories,i.e.,mathematical planning methods and intelligent evolutionary algorithms.The branch and bound algorithm is the most dominant mathematical planning algorithm,while genetic algorithms and their enhancements are the most commonly used intelligent evolutionary algorithms.It is shown that the nondominated sorting genetic algorithmⅡ(NSGA-Ⅱ)can effectively solve the multiobjective model of VREMD.To further improve the algorithm’s performance,researchers have proposed improved hybrid intelligent algorithms that combine the advantages of NSGA-Ⅱand certain other algorithms.Scholars have also proposed a series of optimization algorithms for specific scenarios.With the development of new technologies and computation methods,it will be exciting to construct optimization models that consider uncertainty,heterogeneity,and temporality for large-scale real-world issues and develop generalized solution approaches rather than those applicable to specific scenarios.

Integrated multi-item packaging and vehicle routing with split delivery problem for fresh agri-product emergency supply at large-scale epidemic disease context

Fresh agri-product emergency supply is crucial to secure the basic livelihood of residents at large-scale epidemic disease context. Considering the massive demand and limited transportation resources, this study integrates multi-item packaging and vehicle routing with split delivery to improve the emergency supply capacity. Firstly, three specific objectives of fresh agri-product emergency supply at large-scale epidemic disease context are formulated, i.e., average response time, infectious risk possibility and transportation resource utilization. Then, a multi-item packaging strategy is proposed to consolidate different categories of fresh agri-products according to the food cold chain temperatures.An optimization model integrating multi-item packaging and vehicle routing with split delivery is developed to jointly decide the optimal packaging scheduling, vehicle assignment and delivery routing. Next, an improved genetic algorithm based on solution features (IGA-SF) is designed to solve the integrated model with multiple decision variables. Finally,a case on fresh agri-product emergency supply of Huangpi District, Wuhan in the context of the Corona Virus Disease 2019(COVID-19) is carried out to illustrate the efficiency and feasibility of the proposed model. The numerical results of medium-to-largescale cases demonstrate that the proposed IGA-SF could save 23.91% CPU time and 37.80% iteration number on average than genetic algorithm. This study could satisfy different emergency scenario requirements flexibly, and provide scientific decision support for provincial and national governments on fresh agri-product emergency supply.

基于离散混合蛙跳算法的地震应急物资调度

建立震后应急物资调度数学模型。该模型根据各灾区的受灾情况评估其救援紧急程度,并设计一种需求拆分供应的运输机制,提高车辆的利用效率。为求解该模型,提出一种多源信息学习的离散混合蛙跳算法。所提算法引入多种信息源以扩展算法的搜索方向,降低种群的同化速度。同时,让子组最差个体学习种群中的有效信息,提高算法的收敛精度。实验结果表明,所提算法能够搜索到精度更优的调度方案,对问题规模具有良好的可扩展性。