Community-aware transport management
Mónica Domínguez
Scientific Researcher
A new concept of mobility is emerging where cities are starting to see a shift from an individualistic culture of private vehicle ownership to more efficient and sustainable means of transport.
Developing and testing cooperative management strategies was the main goal of the H2020 EU research project, ‘FRONTIER’. The FRONTIER project ran from May 2021 to April 2024 and involved 19 partners, including Aimsun, looking at ways to optimize cooperation between transport network stakeholders. FRONTIER promoted the adoption of the latest technological advances to cope with emerging mobility trends: data-driven techniques to analyze recurrent and non-recurrent patterns, computer vision algorithms to substitute traditional loop detectors, demand and supply forecasting, and hybrid solutions combining artificial intelligence with simulation frameworks.
From separation to cooperation
To illustrate the problem of siloed transport management, let us look at an example of a typical situation in a transport network: it is 7:56 a.m. in the traffic control center. Unexpected congestion on a major route into the city center triggers an alert, so a patrol is sent to the affected area and confirms that a broken-down truck is blocking a lane of traffic. A problem that could have caused long tailbacks all morning is resolved within half an hour, thanks to the ground crew and the automatic alert raised by the incident detection component.
However, that’s not the end of the story: taxi drivers trapped in the traffic jam had alerted their colleagues to the incident via their internal communication platform, which caused other taxi drivers to avoid heading out to the airport. Consequently, many travelers heading to the airport shifted to public transport, but the trains and buses couldn’t cope with the sudden avalanche of people. To cut a long story short, what was perceived as a successful intervention in the traffic control center in fact had a dramatic negative effect on other areas and users of the city’s transport network.
The point of the story is that a partial vision of the transport network is rarely enough to solve a complex situation involving multiple stakeholders, decisions, modes of travel, communication devices and technologies. Overarching management strategies, vision and information exchange are needed to provide coordinated and comprehensive network management.
Together, the FRONTIER project consortium researched and developed a platform capable of bridging the gap between data processing and decision making in complex mobility scenarios involving different key stakeholders.
The main tangible outcome of FRONTIER is this interactive platform known as the Autonomous Network and Traffic Management Engine (ANTME). ANTME facilitates an integrated, holistic vision and provides a shared communication platform where multiple stakeholders can discuss and agree on long- and short-term strategies based on data-driven quantitative analysis.
Three pilot cases
Cooperation and communication in FRONTIER were based on key performance indicators derived from simulation, data analysis and prediction within the ANTME interactive platform. Stakeholders from Athens, Antwerp, and Oxford tested specific cooperative strategies for more efficient global mobility at various levels, including future scenarios with connected and autonomous vehicles (CAVs).
In the Athens pilot case, an analysis of CAVs was carried out on penetration effects on traffic conditions along a section of the Attiki Odos corridor, with a penetration rate of almost 20% resulting in an 11% improvement to average Total Time Spent and 59% on the Average Vehicle Delay compared to the no-control scenario.
For the Antwerp pilot case, a modal shift from roadway to waterway was simulated, using a freight demand model to calculate cost and time values. The outputs from the pilot provide valuable insights for shaping strategies and interventions on the future of sustainable and efficient freight logistics practices in the Antwerp region and beyond.
For the Oxfordshire pilot case, response actions were developed and applied to use cases including road closures due to planned events, such as long-term roadwork, and road closures due to a collision. The response plans were coordinated with the Traffic Management & Control and the Traffic Signal teams within the Operational Network Management group and consist of tools, available to them – VMS and VVMS signs to redirect traffic to Park and Ride stations and traffic signal changes. Results from applying response actions overall show improved network performance when several operational teams worked together.
In a world of eight billion inhabitants, future mobility technologies need to adapt not only to handling big data feeds, but also to enhancing collaboration. The challenge is shifting from data centricity to focusing on how multidisciplinary teams use new technology, including data and artificial intelligence, to communicate efficiently and achieve a common goal.
Acknowledgements
This publication was funded by the European Union’s Horizon 2020 research and innovation program under grant agreement no. 955317.
