OPTImising Motorway control Algorithms (OPTIMA) – New insights from emerging technologies and data

Motorways are critical infrastructures for efficient transportation, but long queues pose safety and
productivity challenges. Traffic management agencies like the Queensland Department of Transport
and Main Roads (TMR) use different Variable Speed Limit (VSL) algorithms like Queue Detection (QD),
Queue Protection (QP), and High Flow (HF) algorithms, to manage queues and ensure smooth
operations. However, optimising the parameters of these algorithms is complex due to traffic flow
dynamics and data limitations from traditional data sources. This research aims to optimise motorway
control algorithms by leveraging emerging technologies and data-driven methodologies. The
objectives include sensitivity analysis of algorithm parameters, integration of loop detector and
connected vehicle data, and optimisation of control algorithm parameters. By exploring the
relationship between parameters and traffic flow theory, the study seeks to enhance algorithm
effectiveness and efficiency.
The project conducts sensitivity analyses of QD, QP, and HF algorithm parameters and integrates loop
detector and vehicle trajectory data for improved traffic state identification. Methodologies for
algorithm parameter optimisation are developed based on comprehensive diagnostics of TMR’s
motorway control algorithms. The study identifies shortcomings in current practices and recommends
enhancements. By exploring the potential of connected vehicle data, real-time insights into traffic
states are obtained, facilitating algorithm optimization with minimal human intervention.
Through the integration of emerging technologies and data-driven approaches, the project contributes
to safer and more efficient motorway operations. By optimizing motorway control algorithms, it
addresses challenges related to queue and congestion management, leading to improved safety,
operational efficiency, and environmental sustainability on motorways.