V2I Based Environment Perception for Autonomous Vehicles at Intersections

In recent years,autonomous driving technology has made good progress,but the noncooperative intelligence of vehicle for autonomous driving still has many technical bottlenecks when facing urban road autonomous driving challenges.V2I(Vehicle-to-Infrastructure)communication is a potential solution to enable cooperative intelligence of vehicles and roads.In this paper,the RGB-PVRCNN,an environment perception framework,is proposed to improve the environmental awareness of autonomous vehicles at intersections by leveraging V2I communication technology.This framework integrates vision feature based on PVRCNN.The normal distributions transform(NDT)point cloud registration algorithm is deployed both on onboard and roadside to obtain the position of the autonomous vehicles and to build the local map objects detected by roadside multi-sensor system are sent back to autonomous vehicles to enhance the perception ability of autonomous vehicles for benefiting path planning and traffic efficiency at the intersection.The field-testing results show that our method can effectively extend the environmental perception ability and range of autonomous vehicles at the intersection and outperform the PointPillar algorithm and the VoxelRCNN algorithm in detection accuracy.

Development Status and Application Analysis of Vehicle to Grid (V2G)

With the shortages of resources,environmental pollution,climate change,and other issues becoming more and more serious,it is extremely urgent to vigorously develop new energy vehicles.As the cost of batteries decrease year by year,the production and quantity of sales of electric vehicles(EVs)in the world,especially in China,increased substantially.In order to make vehicles to grid(V2G)technology better developed and applied in China.The brief introduction to V2G is given at first.Then the development status and specific cases of V2G at home and abroad are summarized.Finally,the problems that V2G may encounter during promotion and application in China are analyzed.Based on the development of the United States and Japan,specific policy recommendations are given in line with the basic national conditions of China.

A Comprehensive Analysis of Plug in Hybrid Electric Vehicles to Commercial Campus (V2C)

Vehicle to grid is an emerging technology that utilizes plug in hybrid electric vehicle batteries to benefit electric utilities during times when the vehicle is parked and connected to the electric grid. In its current form however, vehicle to grid implementation poses many challenges that may not be easily overcome and many existing studies neglect critical aspects such as battery cost or driving profiles. The goal of this research is to ease some of these challenges by examining a vehicle to grid scenario on a university campus, as an example of a commercial campus, based on time of use electricity rates. An analysis of this scenario is conducted on a vehicle battery as well as a stationary battery for comparison. It is found that vehicle to campus and a stationary battery both have the potential to prove economical based on battery cost and electricity rates.

Misbehavior Detection Method by Time Series Change of Vehicle Position in Vehicle-to-Everything Communication

In recent years, research has been conducted on connected vehicles (CVs) that are equipped with communication devices and can be connected to networks. CVs share their own position information and surrounding information with other vehicles using Vehicle-to-Everything (V2X) communication. CVs can recognize obstacles on non-line-of-sight (NLoS), which cannot be recognized by autonomous vehicles, and reduce travel time to a destination by cooperative driving. Therefore, CVs are expected to provide safe and efficient transportation. On the other hand, problems of security of V2X communication by CVs have been discussed. Safe and efficient transportation by CVs is on the basis of the assumption that correct vehicle information is shared. If fake vehicle information is shared, it will affect the driving of CVs. In particular, vehicle position faking has been shown that it can induce traffic congestion and accidents, which is a serious problem. In this study, we define position faking by CV as misbehavior and propose a method to detect misbehavior on the basis of changes in vehicle position time series data composed of vehicle position information. We evaluated the proposed method using four different misbehavior models. F-measure of misbehavior models that CV sends random position information detected by the proposed method is higher than one by a related method. Therefore, the proposed method is suitable for detecting misbehavior in which the position information changes over time.

Reduction of global effects on vehicles after IED detonations

Global effects caused by the detonation of an IED near a military vehicle induce subsequent severe acceleration effects on the vehicle occupants.Two concepts to minimize these global effects were developed,with the help of a combined method based on a scaled experimental technology and numerical simulations.The first concept consists in the optimization of the vehicle shape to reduce the momentum transfer and thus the occupant loading.Three scaled V-shaped vehicles with different ground clearances were built and compared to a reference vehicle equipped with a flat floor.The second concept,called dynamic impulse compensation(DIC),is based on a momentum compensation technique.The principal possibility of this concept was demonstrated on a scaled vehicle.In addition,the numerical simulations have been performed with generic full size vehicles including dummy models,proving the capability of the DIC technology to reduce the occupant loading.

Big Wave of the Intelligent Connected Vehicles

Internet of things is deemed as the one of the great revolution after the age of Industrial Revolution.With the development of the communication technology,more and more entities are connected to the communication network and become one of the elements in the network.Over recent decades,in the area of intelligent transportation,pedestrian and transport infrastructure are connected to the communication network to improve the driving safety and traffic efficiency which is known as the ICV(Intelligent Connected Vehicle).This paper summarizes the global ICV progresses in the past decades and the latest activities of ICV in China,and introduces various aspects regarding the recent development of the ICV,including industry development,spectrum and standard,at the same time.

A Multi-Objective Coordinated Charging and Discharging Strategy for Electric Vehicles Based on Stackelberg Game

For the negative impact of large-scale electric vehicles (EVs) disorderly charging on the power grid, a multi-objective optimization strategy for coordinated charging and discharging of EVs based on Stackelberg game is proposed. As the leader, the grid company aims to stabilize load fluctuations and formulate a reasonable electricity price strategy to guide EVs to participate in vehicle-to-grid (V2G);As followers, EV users optimize their charging plans based on electricity price information with the objective of reducing costs and obtaining good comfort. This paper uses the MOPSO algorithm to solve the proposed multi-objective Stackelberg problem, and calculates the optimization results under various preferences, which proves the effectiveness of the proposed model and method.

Charging infrastructure planning for electric vehicle in India:Present status and future challenges

The challenge to deal with environmental contamination along with national goals such as energy security,reliability,and self-dependency due to depleting fossil fuel resources has motivated researchers to find an alternate solution in the transport sector.Due to this,electrification of the transport sector has become an achievable solution that has caught attention with increasing penetration in the market share.India is a participant in the Paris Agreement which aims to curtail the production of greenhouse gases and limit the escalating temperature.Public intervention and changes in policy and regulations are the key aspects of technological transition.Compared to internal combustion engine(ICE)-based vehicles,the consumers’frame of mind concerns about adapting to e-mobility is anxiety over charging times and driving range.Thus,the development of charging stations plays a crucial role in promoting electric vehicles(EVs).This study investigates to identify different barriers that exist in the Indian context related to the adoption of e-mobility.Furthermore,this work emphasizes the recent developments in charging infrastructure planning in India.Also,the status of installed charging stations is examined.Developing appropriate charging stations are associated with several challenges,which are also highlighted to provide guidance to public and private entities that can be adopted in their respective business model.As India has the second largest population and is the seventh largest country in the world,the EV adoption rate of India is considerably low compared to other countries;for India,there is a long way to match the growth rate of EV adoption.Hence it becomes essential to develop a robust and suitable charging infrastructure to promote the sale and use of EVs in India.

V/STOL飞机建模与仿真分析

以原理验证机为背景,建立了无尾布局垂直/短距起降飞行器的数学模型,并通过智能自适应方法对其进行了闭环飞行控制,控制量通过控制分配合理的协调各操纵面,最后在MATLAB7.0/Simulink环境下通过数值仿真进行了验证。结果显示,该平台具备垂直/短距起降能力和较好的飞行性能。

800 V充电平台中SiC材料的应用及发展趋势

SiC功率器件具有优异的性能,已经成为高端新能源汽车的核心部件,并随着应用成本的降低在逐步取代传统的Si基器件。然而,SiC单晶生长的参数可控性差、成本高、扩径难度大,它的市场渗透受到制约。当前对于SiC材料的投资非常火热,国内也有大量产业项目开展,但是实际投产却相对较少,半导体材料行业准入门槛较高,也需警惕重复建设的风险。山西烁科晶体有限公司实现了6英寸(1英寸=25.4 mm)SiC衬底产业化,并推出了8英寸产品,计划在十四五期间内将年产能扩充至150万片以满足市场巨大的需求,同时不断提升产品的良率及性能,助力第三代半导体行业的发展,在实现“碳达峰碳中和”的目标道路上贡献力量。

电动汽车动力电池采用V2G的有序充放电策略研究

本文针对电动汽车充电站现状问题,介绍了动力V2G有序充放电技术的背景并提出了相应的控制方法。通过建立仿真模型,验证了本文提出的有序充放电控制方法的有效性。研究结果表明,该控制方法可以提高充电站的服务质量和效率,为电动汽车的普及和推广提供有力支持。

基于边缘计算的用户异常负荷识别方法

针对未知家电负荷背景下基于智能电表采样数据进行异常负荷识别问题,以电动车入户充电负荷为出发点,提出了一种基于边缘计算的用户异常负荷识别方法。首先通过Boruta-SHAP算法对非侵入式负荷数据的14种特征进行排序筛选,得到在秒级负荷数据下的辨识效果最佳的特征子集;然后采用改进的非平行支持向量机(v-non parallel support vector machine,v-NPSVM)模型进行异常负荷识别模型的训练;最后结合边缘计算技术将算法部署到边缘计算平台上,实现对典型电动车充电负荷的识别。实验基于低压台区中智能电表获取的真实负荷数据进行验证,并进一步对数据进行降频处理以验证更低频数据源下方法的有效性,实验结果表明针对降频后的异常负荷识别的正确辨识率仍在90%以上,证明了在未知家电负荷背景下方法具有较好的适用性和准确性。

基于系统工程V模型的课程思政教学探索与实践——以智能网联汽车技术概论课程为例

为了培养智能网联汽车专业高素质技术技能人才,以智能网联汽车技术概论课程为例,深入分析目前高职院校智能网联汽车技术专业课程思政建设存在的问题,以“提升职业能力、塑造价值观”为导向,构建了基于系统工程V模型的“分析设计、评价体系建立、目标验证”三位一体课程思政教学体系,并对课程思政元素挖掘与融入路径进行详细说明。探索将该课程思政教学体系在高职院校专业人才培养过程中实践落实,并在教学实践过程中根据“学生评教、效果评价、综合评价”三个维度的评价结果动态调整课程思政设计方案,以期解决智能网联汽车技术专业课程思政教学效果不突出的问题,为高职院校课程思政建设提供借鉴。

Interacting multiple model-based ETUKF for efficient state estimation of connected vehicles with V2V communication

Accurate prediction of the motion state of the connected vehicles,especially the preceding vehicle(PV),would effectively improve the decision-making and path planning of intelligent vehicles.The evolution of vehicle-tovehicle(V2V)communication technology makes it possible to exchange data between vehicles.However,since V2V communication has a transmission interval,which will result in the host vehicle not receiving information from the PV within the time interval.Furthermore,V2V communication is a time-triggered system that may occupy more communication bandwidth than required.On the other hand,traditional estimation methods of the PV state based on individual models are usually not applicable to a wide range of driving conditions.To address these issues,an event-triggered unscented Kalman filter(ETUKF)is first employed to estimate the PV state to strike a balance between estimation accuracy and communication cost.Then,an interactive multi-model(IMM)approach is combined with ETUKF to form IMMETUKF to further improve the estimation accuracy and applicability.Finally,simulation experiments under different driving conditions are implemented to verify the effectiveness of IMMETUKF.The test results indicated that the IMMETUKF has high estimation accuracy even when the communication rate is reduced to 14.84%and the proposed algorithm is highly adaptable to different driving conditions.

A Novel Bidirectional Interaction Model and Electric Energy Measuring Scheme of EVs for V2G with Distorted Power Loads

With the increasing demand for petroleum resources and environmental issues,new energy electric vehicles are increasingly being used.However,the large number of electric vehicles connected to the grid has brought new challenges to the operation of the grid.Firstly,A novel bidirectional interaction model is established based on modulation theory with nonlinear loads.Then,the electric energy measuring scheme of EVs for V2G is derived under the conditions of distorted power loads.The scheme is composed of fundamental electric energy,fundamental-distorted electric energy,distorted-fundamental electric energy and distorted electric energy.And the characteristics of each electric energy are analyzed.Finally,the correctness of the model and energy measurement method is verified by three simulation cases:the impact signals,the fluctuating signals,and the harmonic signals.

A Multi-Mode Public Transportation System Using Vehicular to Network Architecture

The number of accidents in the campus of Suranaree University of Technology(SUT)has increased due to increasing number of personal vehicles.In this paper,we focus on the development of public transportation system using Intelligent Transportation System(ITS)along with the limitation of personal vehicles using sharing economy model.The SUT Smart Transit is utilized as a major public transportation system,while MoreSai@SUT(electric motorcycle services)is a minor public transportation system in this work.They are called Multi-Mode Transportation system as a combination.Moreover,a Vehicle toNetwork(V2N)is used for developing theMulti-Mode Transportation system in the campus.Due to equipping vehicles with On Board Unit(OBU)and 4G LTE modules,the real time speed and locations are transmitted to the cloud.The data is then applied in the proposed mathematical model for the estimation of Estimated Time of Arrival(ETA).In terms of vehicle classifications and counts,we deployed CCTV cameras,and the recorded videos are analyzed by using You Only Look Once(YOLO)algorithm.The simulation and measurement results of SUT Smart Transit and MoreSai@SUT before the covid-19 pandemic are discussed.Contrary to the existing researches,the proposed system is implemented in the real environment.The final results unveil the attractiveness and satisfaction of users.Also,due to the proposed system,the CO_(2) gas gets reduced when Multi-Mode Transportation is implemented practically in the campus.

基于分段隔磁桥的V型转子永磁电机的振动噪声削弱方法

电动汽车用V型转子永磁电机中的电磁噪声是电动汽车噪声的主要来源,影响到乘车人的舒适度问题。本文以1台额定功率104 kW的电动汽车用V型永磁电机为研究对象,分析电机电磁噪声产生的原因,提出一种在转子中开设分段隔磁桥的方案以降低电机的振动噪声,并与不分段隔磁桥、双层分段隔磁桥方案进行比较。在Maxwell中建立仿真计算模型,并采用有限元法对多个优化方案的电机模型进行电磁性能、振动、噪声的分析比较,并通过样机的振动噪声试验证明了计算方法的正确性及准确性。结果表明,考虑到制作工艺等问题,采用单层分段隔磁桥能够在几乎不影响电磁性能的情况下,有效地减弱电机的电磁噪声。

无人机航拍在体育赛事中的应用

无人机(Unmanned Aerial Vehicle,UAV)航拍技术在体育赛事领域的应用已经成为一个备受瞩目的趋势。由于体育项目具有运动范围广、运动速度快、瞬间决胜等特点,无人机航拍不受限于传统摄影在高度以及移动速度上的局限,可以更好地提高体育赛事的观赏性,提供实时数据,增强运动员的表现分析。基于此,介绍无人机航拍技术在体育赛事中的应用技术要点、优势及领域,为无人机航拍在各领域的应用提供参考。

智能网联汽车计算卸载与边缘缓存联合优化策略

为了保障智能网联汽车的低时延通信,利用蜂窝车联网中V2X(vehicle to everything)信道模型、边缘计算技术,研究计算卸载与边缘缓存联合优化策略。设计了一种智能网联汽车计算卸载与边缘缓存协同模型L-DDPG(least-deep deterministic policy gradient),通过对车载本地与边缘计算资源的整合,支持V2X场景下对不同计算任务的分类处理。由边缘平台对车载计算请求进行预判决,确保对连续的计算任务快速响应;结合基于最近最少使用(least recently used,LRU)的边缘缓存策略,实现对新计算任务的高效管理;基于DDPG算法对计算卸载与边缘缓存进行联合卸载决策。仿真结果表明:L-DDPG模型性能优于传统模型,能够有效提升系统的工作效能,在保障业务服务质量的同时降低时延和系统资源消耗。