Cooperative Intelligent Transport Systems (C-ITS)

Triggered by recent developments in vehicular safety, driverless vehicles etc., cooperative intelligent transport systems (C-ITS) has become a major research area. Over the past decade ACSER has developed a strong heritage in multi-sensor integration for land navigation, as evidenced by numerous high quality journal publications. ACSER has focussed on enhancing accuracy and resilience of GNSS-based navigation in vehicular applications by combining GNSS with other on-board sensors. The exploitation of channel parameters from vehicle-to-vehicle (V2V) communications has resulted in significant improvement in not only positioning accuracy but also availability, allowing resilient navigation in semi-urban environments where typical standalone GPS receivers will intermittently fail. Expanding this idea to networked vehicles enhances the overall positioning accuracy of the entire network of vehicles.

ACSER’s prominence in this field of research attracted the attention of Thales Alenia Space France (TAS), who approached us to study the benefits of integrating Inertial Measurement Unit (IMU), GNSS and V2V sensors, and how redundancy in such multi-sensor integrations mitigate the signal distortions due to multipath and Non-Line-of-Sight by rejecting measurements from effected signals. The study attracted a €40,000 consultancy fee from TAS and concluded that using non-conventional estimators can indeed significantly reduce positioning errors. It is hoped that further investigations using a modified particle-filter to improve capability in rejecting distorted signals can be carried out in the future.

A simulation of vehicles travelling in an urban environment  with high rise buildings of various shapes. A vehicle (red) can share  information with neighbouring vehicles (blue) in its vicinity, but not  vehicles (black) too far away

Modelling GPS signals that a vehicle (red box) sees from  two perspective, a top view (top) and side view (bottom). The vehicle  can simultaneously observe both good (blue lines) and misleading  (green and red lines) signals, resulting in poor positioning solution in  environments with high rise buildingsModelling GPS signals that a vehicle (red box) sees from  two perspective, a top view (top) and side view (bottom). The vehicle  can simultaneously observe both good (blue lines) and misleading  (green and red lines) signals, resulting in poor positioning solution in  environments with high rise buildings