TY - GEN
T1 - Big data analytics architecture for real-time traffic control
AU - Amini, Sasan
AU - Gerostathopoulos, Ilias
AU - Prehofer, Christian
PY - 2017/8/8
Y1 - 2017/8/8
N2 - The advent of Big Data has triggered disruptive changes in many fields including Intelligent Transportation Systems (ITS). The emerging connected technologies created around ubiquitous digital devices have opened unique opportunities to enhance the performance of the ITS. However, magnitude and heterogeneity of the Big Data are beyond the capabilities of the existing approaches in ITS. Therefore, there is a crucial need to develop new tools and systems to keep pace with the Big Data proliferation. In this paper, we propose a comprehensive and flexible architecture based on distributed computing platform for real-time traffic control. The architecture is based on systematic analysis of the requirements of the existing traffic control systems. In it, the Big Data analytics engine informs the control logic. We have partly realized the architecture in a prototype platform that employs Kafka, a state-of-the-art Big Data tool for building data pipelines and stream processing. We demonstrate our approach on a case study of controlling the opening and closing of a freeway hard shoulder lane in microscopic traffic simulation.
AB - The advent of Big Data has triggered disruptive changes in many fields including Intelligent Transportation Systems (ITS). The emerging connected technologies created around ubiquitous digital devices have opened unique opportunities to enhance the performance of the ITS. However, magnitude and heterogeneity of the Big Data are beyond the capabilities of the existing approaches in ITS. Therefore, there is a crucial need to develop new tools and systems to keep pace with the Big Data proliferation. In this paper, we propose a comprehensive and flexible architecture based on distributed computing platform for real-time traffic control. The architecture is based on systematic analysis of the requirements of the existing traffic control systems. In it, the Big Data analytics engine informs the control logic. We have partly realized the architecture in a prototype platform that employs Kafka, a state-of-the-art Big Data tool for building data pipelines and stream processing. We demonstrate our approach on a case study of controlling the opening and closing of a freeway hard shoulder lane in microscopic traffic simulation.
KW - Big Data
KW - Intelligent Transportation System
KW - Kafka
KW - Real-time traffic control
UR - http://www.scopus.com/inward/record.url?scp=85030213329&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85030213329&partnerID=8YFLogxK
U2 - 10.1109/MTITS.2017.8005605
DO - 10.1109/MTITS.2017.8005605
M3 - Conference contribution
AN - SCOPUS:85030213329
T3 - 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2017 - Proceedings
SP - 710
EP - 715
BT - 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2017 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2017
Y2 - 26 June 2017 through 28 June 2017
ER -