- Projects
- Research Projects
RESEARCH PROJECTS
Reliable Multi-Agent Collaborative GNSS Positioning for Intelligent Transportation Systems
:
Traffic jams are one of the most frustrating experiences in daily life. Although intelligent transportation systems (ITSs) have helped alleviate traffic jams, the traffic situation remains fraught; thus, there is a need for further ITS development, especially for road transportation frameworks involving buses and minibuses. ITSs apply state-of-the-art sensors, technologies, and algorithms to improve the efficiency of overcrowded road networks. Most public buses are tracked using global navigation satellite systems (GNSSs). Based on the GNSS-determined location, an ITS can derive the estimated time of arrival of buses to improve user experience and increase public transport utilization. Additionally, the GNSS trace data of buses play a role in revealing the location and time of jams. Thus, GNSS data are used for the holistic design of traffic signaling plans, aiming to reduce traffic jams. However, traffic engineers may design ineffective algorithms if they have erroneous data. Thus, the accuracy and integrity of the GNSS data are important considerations.
This project aims to develop a collaborative GNSS positioning system to solve the problem of data inaccuracy and unreliability by effectively leveraging Hong Kong’s existing smart city digital infrastructure. The 3D city model developed by the Lands Department and the Internet of Things (IoT) connectivity of the buses developed by the Department of Transport are keys to developing the proposed collaborative GNSS positioning system. The 3D model can reveal how the GNSS signals are deflected and propagate inside the city, which can help mitigate the unfavorable multipath effects of the signals. The IoT connectivity introduces GNSS big data, which can enable us to develop an artificial intelligence (AI) algorithm to intelligently (that is, mathematically and statistically) improve the accuracy and reliability of the GNSS traces of all buses and minibuses.
In summary, we will develop a collaborative GNSS positioning algorithm that uses data from a centralized cloud server and that is based on 3D city models, AI, and IoT. The proposed system can play an irreplaceable role to provide accurate, reliable, and absolute position tags in the coming digital era.
:
Dr. Li-Ta Hsu and Prof. CHEN Wu
:
HKD $ 4.25M
:
1 JUN 2022 - 31 MAY 2025
:
RGC Research Impact Fund
:
Research Grants Council
BACK TO TOP