摘要
"互联网+"使各行各业每天都产生了海量数据,针对交通数据的爆炸式增长,传统的交通规划与管制已经不能满足复杂的交通需求,交通管理的难度不断增加这一问题,提出一种智能交通大数据处理框架;通过该框架及相关技术进行交通大数据的数据采集、数据同步与传输、数据存储、数据分析与处理和结果展现等应用研究,将起到助力交通违法与环境监测、为相关业务部门提供决策依据、提高交通运行效率与交通安全水平、提升城市交通规划等作用,使交通管理真正地智能起来;大数据研究与应用下的智能交通将成为解决诸多交通城市病的有力手段,其发展将导致各种新技术的不断诞生,使人们的出行方式和生活模式产生巨大变革,人们的生活将更加美好。
'The Internet +' produces an ocean of data in all walks of life every day.In view of the explosive growth of traffic data,traditional traffic planning and control can’t meet the complex traffic demand no longer,and traffic management has become increasingly difficult. An intelligent transportation big data processing framework is proposed. Through this framework and related technologies, applied research on data collection,data synchronization and transmission,data storage,data analysis and processing,result presentation of traffic big data is conducted. It will facilitate traffic violations monitoring and environmental monitoring,provide decision-making basis for relevant business departments,improve traffic operation efficiency and traffic safety level,and enhance urban traffic planning and so on,It will make traffic management truly intelligent. Intelligent transportation under the research and application of big data will become a powerful means to solve many traffic urban diseases. Its development will lead to the constant birth of new technologies. It has brought great changes to people ’s way of travel and life style,and people’s life will be better.
作者
杨永斌
李笑扬
YANG Yong-bin;LI Xiao-yang(School of Computer Science and Information Engineer,Chongqing Technology and Business University Chongqing 400067,China;Key Laboratory of Chongqing Test and Control Integrated System Engineering,Chongqing 400067,China;Chongqing No.29 Middle School)
出处
《重庆工商大学学报(自然科学版)》
2019年第2期73-79,共7页
Journal of Chongqing Technology and Business University:Natural Science Edition
基金
教育部产学合作协同育人项目(201702097010)
重庆工商大学项目(2017234)
关键词
大数据分析
智能交通
决策依据
发展趋势
感知体系
数据资源标准化
big data analysis
intelligent traffic
decision basis
developing trend
perception system
data resources standardization