Eurotunnel Flow Management and Parking

Final Customer:
Eurotunnel

Location:
Calais, France

Dates:
July 2019 – August 2019

Eurotunnel Flow Management and Parking

Eurotunnel wanted to improve the management of private vehicle flow: at the heart of the study was the issue of access to the P3 parking lot: Eurotunnel wanted to use modeling to guide a decision on whether or not to develop the parking access area and what outcomes this would have on user behavior.


Location Characteristics

The Eurotunnel Le Shuttle Passenger 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 Solution

The Aimsun modeling team fully automated the import of the real-time data supplied by Eurotunnel 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 team then used programming in the Aimsun Next Parking API to manage each vehicle’s waiting time for entering the parking lot.

Eurotunnel Flow Management and Parking

Benefit to Customer

By simulating the new parking lot access solution, the modeling team was able to show that Eurotunnel’s proposal was feasible: the new 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, Eurotunnel went ahead with the infrastructure work, which should be completed in 2020.

Reason for Success

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.