As groundbreaking vehicle and infrastructure technologies are deployed, and massive new data sources emerge, experts believe our traffic management systems will be revolutionised.

Leading transport experts have outlined a range of data sources and cutting-edge technologies that, if fully harnessed, can steer the nation towards the ambitious goals of reducing road fatalities by half by 2030 and ultimately attaining zero road deaths by 2050.

These key insights from leading government and industry specialists are explored in a Progress Report from the collaborative research initiative ‘Integrated connected data for safer, more efficient traffic management operations’ from ITS Australia, in partnership with the University of Melbourne, Victorian Department of Transport & Planning, Transport for NSW, Transport & Main Roads QLD, Main Roads Western Australia, Transport Accident Commission, and iMOVE Australia.

“Following our successful Connectivity in C-ITS project, better understanding how data can improve safety and efficiency on our networks now was the crucial next investigation, and the insights from our stakeholder interviews and literature review have proven enlightening,” says lead researcher Professor Majid Sarvi from University of Melbourne.

“The wealth of data coming from different sources such as connected vehicles present an enormous opportunity to enhance how we manage transport networks, reducing congestion and emission, and enhancing safety for all modes of travel.”

Four key traffic management domains

The research focused on four key traffic management domains: intersection management; network and freeway optimisation; incident management, and micro-mobility enablement. According to the evidence, current traffic management systems often react to problems, but advancements in machine learning, artificial intelligence, and access to automated data offer great potential for predictive capabilities.

An important step was to understand how data was currently being used in each domain with a focus on identifying current limitations that could be overcome through data enhancements. In the area of intersection management, metrics such as queue length, delay, pedestrian trajectory prediction, public transport priority, and bicycle volumes are used for intersection optimisation.

Better leveraging probe vehicle data is a significant opportunity in this area, with high-frequency and real-time GPS data to improve adaptive control strategies and enhance public transport priority schemes. Data used for network and freeway optimisation focuses on estimating and predicting traffic volume, speed, and vehicle travel time with probe vehicle data emerging as a cost-effective and flexible alternative to fixed installed road sensors.

Nevertheless, challenges persist, including oversaturated traffic conditions, noise, and the accessibility of lane specific information. Emerging solutions, such as high-resolution maps, may overcome these limitations. In incident management, data such as video, crowdsourced information from social media, and vehicle speeds extracted from GPS data can be used to understand incident locations in real-time. However, reliance on supplementary data, such as historical incident records and crash risk factors remains.

Video processing methods and machine learning analysis can identify incident locations and near-miss conflicts while artificial intelligence is increasingly being used for predictive crash modelling and real-time conflict prediction.

Micro-mobility enablement uses density and volume metrics to determine high-demand areas for corridors and parking locations; however, these methods are still emerging, and the review indicates a need for more research in this domain, especially for real-time application to adaptive control systems.

What the experts say

According to key leaders from industry and government consulted for the research, there are two big opportunities presented by new data and technology: greater efficiency in the transport network; and safety improvements that aim to drive down the number of road fatalities.

Experts highlight the transformative power of various data sources and technologies, ranging from vehicle probe data, camera-based video analytics, vehicle Bluetooth data, in-vehicle safety sensor data, and location app data.

Importantly, experts recognised the need to expand beyond conventional traffic modes like cars, trucks and buses, to incorporate information from micromobility, active transport, and pedestrians within our traffic management ecosystem.

Stakeholders point to a vast range of scenarios where integrated connected data could be harnessed more effectively including congestion performance measurement, heavy vehicle movement, improved coordinated corridors and speed compliance enforcement.

Beware the risks

The opportunities stemming from integrated connected data are vast, spanning areas including congestion performance measurement, speed compliance enforcement, and the development of vehicle priority and pre emption systems. However, along with the great possibilities, there are risks that must be addressed before we can fully harness the benefits of the data and technology.

Privacy and security management stood out as critical concerns amongst experts. While vehicle probe data is considered a game changer, stakeholders stressed the need to comprehend data aggregation, anonymisation methods, and the verification process before integrating new data streams into existing systems.

Furthermore, policy makers must address several crucial considerations including adapting traffic control systems to accommodate diverse data forms, scaling up complex algorithms, fostering data-sharing across agencies and jurisdictions, and navigating cost constraints.

“ITS Australia is proud to be supporting this research that brings traffic management into the digital age, using data and technology that can improve our traffic systems and save lives,” said ITS Australia CEO Susan Harris. “As the stakeholders have identified in the study, it’s imperative that we put the effort in now to get the privacy settings right to ensure that the community’s reasonable expectations for privacy and security are built in at the outset.”

Moving forward, the project team will delve deeper into the analysis of connected vehicle data, specifically focusing on traffic efficiency at intersections. They will investigate a range of metrics including queue length information, midblock speeds, delay measurements, and stop-and-go traffic states. The final report will be published in 2024.

Read the full progress report at:

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