Optimising motorway control algorithms: New technologies/data
Road agencies aim to improve safety and road network efficiency by applying intelligent technologies and advanced control algorithms such as Variable Speed Limits and Ramp Signalling. The effectiveness of these algorithms depends on the quality of the real time traffic data and optimal tuning of the control parameters.
This project aims to perform a comprehensive diagnostic of the Department of Transport and Main Roads Queensland’s (TMR) motorway control algorithms and explore opportunities for optimising the motorway control by leveraging emerging technologies and consideration of traffic flow fundamentals.
New models to automate the calibration of the control algorithms will be developed and thoroughly tested. The methodology to be developed in this research considers vehicle trajectories and is data agnostic. The project will also identify shortcomings in the current state of practice and recommend enhancements.
Project background
Long queues on motorways are a major hurdle in achieving a smooth, efficient, and the safe transport of vehicle, people, and goods. As motorways carry a large volume of traffic, delays occurring due to vehicular queues can result in significant loss of productivity and detrimental impacts on economy and environment.
Further, as vehicles travel at considerably high speeds on motorways, the sudden encountering of vehicular queues acts as a potential source of road traffic crashes. Due to high speeds, such crashes can be extremely dangerous and even fatal for the drivers and the passengers involved. Therefore, traffic management agencies such as TMR have various control mechanisms and algorithms in place to ensure minimal impact of vehicle queues on the safe and efficient operation of motorways.
TMR uses a Queue Detection (QD) algorithm which makes use of the real-time data from inductive loops to detect the onset and presence of queues on motorways. The output from QD is used as an input to another algorithm called the Queue Protection (QP) algorithm.
The QP uses the knowledge of the queue location to warn drivers through Variable Message Signs (VMS) about the presence of a downstream queue. In addition, QP algorithm helps to alter the speed limit on the upstream section using Variable Speed Limit (VSL) control. TMR also uses a High Flow (HF) algorithm to proactively intervene to delay the onset of congestion. These three algorithms play significant role in motorway management.
Other algorithms used to control traffic includes Ramp Metering (RM) and for optimal management of motorways all these algorithms should be integrated. For the current project the focus is on QD, QP and HF. RM and its integration with the other algorithms (such as VSL) will be discussed where needed but is outside the scope of the project.
An important input for the control algorithms is the identification of the Back of the Queue (BoQ). Conventional traffic data collection sources like inductive loops are location based and cover only specific points on the motorways and the BoQ estimates using the loops can have errors.
Connected vehicles capable of continually transmitting real-time information about their location, speed, acceleration, and heading are gaining prominence. Such connected vehicle data can provide rich insights about the spatial variation of traffic states on the motorways. This provides opportunities to perform reverse engineering on the traffic data from multiple sources and generate new insights on the current state of practice and the optimisation of its parameters.
For the current project, detailed vehicle trajectory data (such as through TMR’s CAVI program) on motorways will be used. It is proposed to exclusively collect trajectory data with controlled runs on the motorways (the design for which will be part of the research).
During the project if additional detailed trajectory data from other sources such as Compass IoT is available then the project will also explore the possibility of using such data sources. Nevertheless, the methodology to be developed in this research considers vehicle trajectories and is data-agnostic.
Project objectives
This project aims to perform a comprehensive diagnostic of TMR’s motorway control algorithms and explore opportunities for optimising the motorway control by leveraging emerging technologies and with minimal human intervention.
Specifically, the project has the following primary objectives:
- Explore the relationship between the motorway control algorithm parameters and the underlying traffic flow theory fundamentals.
- Perform sensitivity analysis of the various parameters used in Queue Detection, Queue Protection and high-flow algorithms.
- Integrate loop detector data and vehicle trajectory data for enhanced identification of traffic states and traffic state transition.
- Develop methodologies to optimise the parameters of these control algorithms for efficient management of the motorways.
- Identify shortcomings and recommend enhancements to the current practice.
Please note …
This page will be a living record of this project. As it matures, hits milestones, etc., we’ll continue to add information, links, images, interviews and more. Watch this space!
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