TY - GEN
T1 - User-driven cloud transportation system for smart driving
AU - Ma, Meng
AU - Huang, Yu
AU - Chu, Chao Hsien
AU - Wang, Ping
PY - 2012/12/1
Y1 - 2012/12/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84874283599&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84874283599&partnerID=8YFLogxK
U2 - 10.1109/CloudCom.2012.6427600
DO - 10.1109/CloudCom.2012.6427600
M3 - Conference contribution
AN - SCOPUS:84874283599
SN - 9781467345095
T3 - CloudCom 2012 - Proceedings: 2012 4th IEEE International Conference on Cloud Computing Technology and Science
SP - 658
EP - 665
BT - CloudCom 2012 - Proceedings
T2 - 2012 4th IEEE International Conference on Cloud Computing Technology and Science, CloudCom 2012
Y2 - 3 December 2012 through 6 December 2012
ER -