Traffic Management Actions in Aimsun
May 2017: Dimitris Triantafyllos and Sergi Pujadas explain how to alleviate traffic congestion using a variety of traffic management actions.
November 2022 — Technical note #75
Dimitris Triantafyllos
Senior Product Specialist at Aimsun
Geline Canayon
Product Specialist at Aimsun
Road transport accounts for a significant amount of air pollutant emissions. Although monitoring and regulations have produced a downward trend in total pollutant emissions, a significant part of the population is still exposed to air pollutant concentrations above the air quality standards set by the EU and the World Health Organization (WHO). According to the European Environment Agency (EEA), road transport is responsible for up to 9.9% of all PM2.5 emissions in the European Union, 7.7% of PM10, 28.1% of NOX, 7.6 of NMVOC1 , and 18% of CO [1].
This effect is magnified in urban centers, where higher traffic volumes and congestion produce a concentration of pollutants in short time peaks. Low Emission Zones (LEZ) has been an important approach for cities and governments to tackle air quality to meet the EU Air Quality Standards. by setting restrictions on the operation of more polluting, typically older vehicles. Low Emission Zones can reduce emissions of fine particles, nitrogen and carbon dioxide and (indirectly) ozone, the four main air pollutants of concern in Europe.
Simulation is a valuable tool to support the definition of LEZ policies as it allows comparing the effectiveness of different measures and assessing any other related impacts, such as the change in travel times and flows.
Let’s assume that we have to evaluate the following policy:
Based on recent data, for this case study, the vehicle fleet and the EURO category for each type are:
The London Emission Model (LEM) is included in the Aimsun Next microscopic, mesoscopic, and hybrid simulators. This estimates the CO2 and NOx emissions for a vehicle, using a calibrated average speed emissions model developed in collaboration with Transport for London (TfL) in 2017.
The LEM then uses one of two polynomial relationships, derived by regression analysis, to estimate the CO2 and NOx produced by that vehicle using that micro-trip.
Here, y is the emission (grams/km); a, b, c, and z are derived constants which are defined for each vehicle and euro type, x is the average speed in the micro-trip.
For more info, check Aimsun Next Users Manual – London Emission Model (LEM)
The vehicle types in the model are setup using the fleet information provided.
For example, for vehicle type car, the emission vehicle type is car and the Euro Standard Emissions are set for Petrol engine type.
The planned Low Emission Zone and buffer zone are shown in the map of the model. 100% of cars, vans and trucks without an environmental label will be prohibited from entering or circulating within the Low Emission Zone. Drivers now must find other means of reaching a destination inside the LEZ. The figure below shows the full network, LEZ and buffer zone.
The location of the parking areas at the boundaries of the LEZ is shown in blue. These are new destinations in the model where a new centroid has been placed and connected to entrance sections of the LEZ. The speed on the centroid connections was set up to 10km/h to better model the driving behaviour of the vehicles inside the parking area.
As a result, there’s an expected shift in the traffic demand. The assumptions we made were based on previous LEZ schemes:
A. Outside-LEZ to LEZ
Actions:
B. LEZ to Outside-LEZ
Actions:
C. LEZ to LEZ
Actions:
D. Outside-LEZ to Outside-LEZ
No Action
The changes to the traffic demand and OD matrices can be done inside Aimsun Next by applying factors and using the operations available inside OD matrices. To process trips between the different zones (LEZ, buffer zone, rest of the network), we created different Groupings where the centroids of each zone were defined.
In the future scenario, the new centroids are used as new destinations in Destination Change traffic management actions. The Destination Change is applied at each of the entrances to the LEZ that prohibits Euro 0, I, II, and III from entering. A vehicle class containing vehicles that are Euro 0, I, II, and III is used as a filter so that the traffic management action does not affect the vehicles permitted in the LEZ.
Groupings are created for the LEZ and the buffer zone so that statistics can be extracted for those areas only.
As expected, the emissions inside the LEZ area are much lower in the future scenario when the LEZ is implemented. Although, the decrease in CO2 and NOx inside the buffer zone and globally are slightly reduced.
CO2 emissions comparison:
NOx emissions comparison
Aside from the LEM, there are two additional emissions models in Aimsun Next that can be used in microsimulation, the Panis et al Pollutant Emission Model and the QUARTET Pollutant Emission Model.
For Panis et al, the emissions for each pollutant are measured at each time step and considers the different factors according to vehicle type, fuel type and instant acceleration/deceleration measures. The model provides outputs for sections, nodes, turns and the replication for CO2, NOx, VOC and PM in g and g/km.
The QUARTET Pollutant Emissions Model requires more inputs from the user, particularly the emission rates for accelerating, decelerating and idling vehicles to name a few. These values are typically collected from an instrumented vehicle. The outputs from QUARTET are the kilograms of each pollutant emitted and are produced for the entire network, each section and turn and for each route.
More details can be found in the Environmental Models section of the Aimsun Next User Manual.
It is also possible to calculate emissions based on different models in a postprocess. For example, you can code a python script in Aimsun Next to calculate emissions from simulation outputs retrieved by a macroscopic simulation (i.e: based on the average speeds and flows for different vehicle types). You can also use Aimsun Next API to calculate any pollutant per any object for any time interval based on driving behavior parameters (acceleration, deceleration, delay time etc.).
[1] European Environment Agency, “Emissions and Air Pollutants from Transport,” EEA, Copenhagen, 2021.
May 2017: Dimitris Triantafyllos and Sergi Pujadas explain how to alleviate traffic congestion using a variety of traffic management actions.
October 2020: Tessa Hayman reveals how to set different speed limits for different vehicle types in dynamic models.
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