Connected and autonomous vehicles are seeing their dawn at this moment.They provide numerous benefits to vehicle owners,manufacturers,vehicle service providers,insurance companies,etc.These vehicles generate a large a...Connected and autonomous vehicles are seeing their dawn at this moment.They provide numerous benefits to vehicle owners,manufacturers,vehicle service providers,insurance companies,etc.These vehicles generate a large amount of data,which makes privacy and security a major challenge to their success.The complicated machine-led mechanics of connected and autonomous vehicles increase the risks of privacy invasion and cyber security violations for their users by making them more susceptible to data exploitation and vulnerable to cyber-attacks than any of their predecessors.This could have a negative impact on how well-liked CAVs are with the general public,give them a poor name at this early stage of their development,put obstacles in the way of their adoption and expanded use,and complicate the economic models for their future operations.On the other hand,congestion is still a bottleneck for traffic management and planning.This research paper presents a blockchain-based framework that protects the privacy of vehicle owners and provides data security by storing vehicular data on the blockchain,which will be used further for congestion detection and mitigation.Numerous devices placed along the road are used to communicate with passing cars and collect their data.The collected data will be compiled periodically to find the average travel time of vehicles and traffic density on a particular road segment.Furthermore,this data will be stored in the memory pool,where other devices will also store their data.After a predetermined amount of time,the memory pool will be mined,and data will be uploaded to the blockchain in the form of blocks that will be used to store traffic statistics.The information is then used in two different ways.First,the blockchain’s final block will provide real-time traffic data,triggering an intelligent traffic signal system to reduce congestion.Secondly,the data stored on the blockchain will provide historical,statistical data that can facilitate the analysis of traffic conditions according to past behavior.展开更多
本文以美国常春藤大学图书馆研究数据管理服务(Research Data Management Services,RDMS)为例,通过网站调查、文献研究、电子邮件咨询、电话访谈等方法,从服务组织、服务内容、服务方式3个维度进行调查分析。同时,针对国内高校图书馆RDM...本文以美国常春藤大学图书馆研究数据管理服务(Research Data Management Services,RDMS)为例,通过网站调查、文献研究、电子邮件咨询、电话访谈等方法,从服务组织、服务内容、服务方式3个维度进行调查分析。同时,针对国内高校图书馆RDMS的现状与问题,提出一些思路和建议:提高RDMS意识,制定研究数据管理的服务政策;加大对RDMS基础设施的投入,打造RDMS平台;明确服务目标,扩大RDMS服务范围;组建专家团队,提升RDMS服务水平。展开更多
基金funded by the Deanship of Scientific Research at King Khalid University,Kingdom of Saudi Arabia for large group Research Project under grant number:RGP2/249/44.
文摘Connected and autonomous vehicles are seeing their dawn at this moment.They provide numerous benefits to vehicle owners,manufacturers,vehicle service providers,insurance companies,etc.These vehicles generate a large amount of data,which makes privacy and security a major challenge to their success.The complicated machine-led mechanics of connected and autonomous vehicles increase the risks of privacy invasion and cyber security violations for their users by making them more susceptible to data exploitation and vulnerable to cyber-attacks than any of their predecessors.This could have a negative impact on how well-liked CAVs are with the general public,give them a poor name at this early stage of their development,put obstacles in the way of their adoption and expanded use,and complicate the economic models for their future operations.On the other hand,congestion is still a bottleneck for traffic management and planning.This research paper presents a blockchain-based framework that protects the privacy of vehicle owners and provides data security by storing vehicular data on the blockchain,which will be used further for congestion detection and mitigation.Numerous devices placed along the road are used to communicate with passing cars and collect their data.The collected data will be compiled periodically to find the average travel time of vehicles and traffic density on a particular road segment.Furthermore,this data will be stored in the memory pool,where other devices will also store their data.After a predetermined amount of time,the memory pool will be mined,and data will be uploaded to the blockchain in the form of blocks that will be used to store traffic statistics.The information is then used in two different ways.First,the blockchain’s final block will provide real-time traffic data,triggering an intelligent traffic signal system to reduce congestion.Secondly,the data stored on the blockchain will provide historical,statistical data that can facilitate the analysis of traffic conditions according to past behavior.
文摘本文以美国常春藤大学图书馆研究数据管理服务(Research Data Management Services,RDMS)为例,通过网站调查、文献研究、电子邮件咨询、电话访谈等方法,从服务组织、服务内容、服务方式3个维度进行调查分析。同时,针对国内高校图书馆RDMS的现状与问题,提出一些思路和建议:提高RDMS意识,制定研究数据管理的服务政策;加大对RDMS基础设施的投入,打造RDMS平台;明确服务目标,扩大RDMS服务范围;组建专家团队,提升RDMS服务水平。
文摘大数据时代背景下,对车辆的GPS(global positioning system,全球定位系统)轨迹数据进行研究分析,能够帮助交通管理者充分了解交通态势及发展趋势,为精细化管理提供数据支撑。为通过货运车辆运行情况探索甘肃省货运规律,以甘肃省货运车辆GPS数据为例,充分关联区域内的相关产业分布,分析货运走行规律,探索区域货运态势,通过等时差抽取估算法得到产业分布情况、货运OD(Origin and destination,起讫点)情况、货运通道偏好情况、货运车辆停留点分布情况等4项交通分析结果。采取等时差抽取估算法省去了对所有车辆逐一进行轨迹重构的工作量,可直接估算出道路的单公里货运车辆流量值,并且最终结果显示误差率在5%以内,可为同类研究提供借鉴。
