Title
User-driven cloud transportation system for smart driving
Abstract
Intelligent transportation systems (ITS) have emerged as an efficient and effective way of alleviating the traffic congestion and improving the performance of transportation systems. Key challenges of ITS in recent years include the pervasive data collection, data security, privacy preserving, large volume data processing, and intelligent analytics. These challenges lead to a revolution in ITS development by leveraging the crowdsourcing scheme and cloud computing architecture. In this paper, we propose a user-driven Cloud Transportation system (CTS) which employs a scheme of user-driven crowdsourcing to collect user data for traffic model construction and congestion prediction including data collection, filtering, modeling, intelligent computation and publish. We describe in details the application scenario, system architecture, and core CTS services model. To verify the feasibility of our approach, we have developed a prototype system which elaborated the cloud architecture and other implementation details. This paper aims to inspire further research of user-driven CTS on intelligent data processing model for smarter utilization of transportation infrastructure.
Year
DOI
Venue
2012
10.1109/CloudCom.2012.6427600
CloudCom
Keywords
Field
DocType
traffic model construction,user-driven,intelligent data processing,cloud transportation system,data privacy,cloud computing architecture,intelligent analytics,data publish,intelligent computation,data security,large volume data processing,information filtering,cloud trasoortation svstem (cts),data analysis,data processing,smart driving,data acquisition,data filtering,cts,data models,automated highways,traffic congestion prediction,user driven crowdsourcing,road traffic,its,cloud computing,data collection,user data,intelligent transportation system,pervasive data collection,user-driven cloud transportation system,transportation infrastructure,cloud architecture,data modeling,security of data,intelligent data,servers,computer architecture,computational modeling
Data modeling,Advanced Traffic Management System,Computer science,Crowdsourcing,Systems architecture,Intelligent transportation system,Traffic congestion,Cloud computing,Distributed computing,Cloud computing architecture
Conference
ISBN
Citations 
PageRank 
978-1-4673-4509-5
5
0.43
References 
Authors
14
4
Name
Order
Citations
PageRank
Meng Ma18212.29
Chao-Hsien Chu271148.98
Ping Wang31999.12
Yu Huang450.43