Traffic digital twins for managing toll roads and ferry terminal checkpoints
Published on July 31, 2023
Gavin Bailey
Regional Head of Business Development
Aimsun traffic digital twins are powerful tools that provide a high fidelity representation of current-and future, on-street traffic conditions, in real time.
These digital twins are typically driven by traffic data coming from a range of automatic traffic counters including:
- SCOOT / MOVA loops
- Computer-vision-based camera detection, and
- Floating vehicle data.
The value of these models can be significantly increased when private sector data from key trip origins and destinations are blended into the system.
Our previous work for the Channel Tunnel, and a toll-road operator in Spain demonstrate this, as illustrated below.
Channel Tunnel Terminals
Channel Tunnel operators, Getlink, wanted to improve the management of private vehicle flow at their terminals.
Aimsun was commissioned to simulate the impacts of anticipated EU Customs processes on the flow and queuing of departures at the Channel Tunnel terminal in Calais, France.
The terminal in Calais, France hosts very large volumes of vehicles (up to 10,000 a day) and is complex to manage, with flow limits imposed by the UK and French customs control points and up to 4 shuttle departures per hour.
The Aimsun modeling team fully automated the import of the real-time data supplied by GetLink in order to simulate an entire 24-hour period of operations. The quality of the data allowed for a precise emulation of traffic demand in 1-minute time slices.
The Aimsun traffic digital twin guides the Channel Tunnel operators on adapting infrastructure to future vehicle and passenger flows and, now, optimizing operations.
Parking feasibility study
In a previous study, Aimsun had assisted on the issue of access to the P3 parking lot at the ferry terminal in Calais, guiding a decision on whether or not to develop the parking access area and what outcomes this would have on user behavior.
Aimsun used programming in the Aimsun Next Parking API to manage each vehicle’s waiting time for entering the parking lot. By simulating the new parking lot access solution, the modeling team was able to show that the new proposed access plan would increase usage (with a rate of more than 90% over much of the afternoon) and this would have several positive effects: rather than idling in traffic jams, customers would wait in the carpark or in the terminal’s shops and restaurants, which made the experience more comfortable for the customer and more profitable for the businesses. More cars in the parking lot would mean reduced congestion downstream and faster travel time between the customs checkpoints. Improving parking access also acted as a cushion for peak arrivals, especially for vehicles that arrived well in advance of their shuttle reservation.
On the basis of this feasibility study, the terminal operators went ahead with the suggested plan and it worked successfully.
The strength of this solution was flexibility and integration: not only could Aimsun Next adapt to a wide range of behavior, from doubleparking to pedestrians alighting from vehicles, but using the API was a powerful way to combine dynamic assignment modeling with specific vehicle behavior, all in the same model. This meant that instead of dealing separately with parking management and road traffic assignment, the modeling team could directly assess the impact of one upon the other and ensure accurate results.
C-32 Highway outside Barcelona
Aimsun’s real-time traffic management tools can blend public and private operator traffic data and operations data to facilitate better management of traffic in real-time.
By combining data from multiple data sources within a single platform Aimsun can provide a comprehensive situational view of the live traffic network.
In addition to this, Aimsun’s predictive tools provide 1-hour forecasts on network traffic state enabling for proactive management of traffic networks.
Aimsun real-time solutions show traffic managers exactly what is happening on the network at any time, even looking forward into the future (up to 1-hour ahead).
A single interface combines public and private sector data to give a comprehensive understanding of the current and future state of the traffic network is. The system can also set up automated alerts and advisories to mitigate recurrent congestion, and monitor and manage multiple impacts on the network, whether it is traffic flow, incidents, or air quality.
Providing decision support to operators
AI- and simulation-driven analytics can provide useful insights into how the network is likely to respond to an intervention.
Thanks to the live real-time data connections, the impacts of any traffic intervention are instantaneously measured and can be compared against the expected outcomes to enable continuous improvement for traffic management strategies and actions.
