Combining optimal low emission zones scheduling and electric vehicle purchase incentives for transport policy backcasting
Abstract
Achieving greenhouse gas reduction targets in the mobility sector requires well-designed policies. Low emission zones (LEZ) and electric vehicle (EV) purchase incentives are widely used across Europe, yet they are usually decided separately. This study combines them in a backcasting approach, which entails setting environmental, budgetary and societal targets first, then seeking the optimal combination of policies that achieves these predefined targets. Using a passenger car fleet dynamics model, the LEZ schedule and the income-differentiated EV purchase incentives are taken as decision variables and optimised together against three objectives: CO2 emissions, the public budget spent on incentives, and the number of vehicles households replace because of LEZ implementation, which reflects social acceptability. NOx and PM are computed from the circulating fleet but left out of the optimisation. The environmental objective is written in two ways and compared: on the emissions of the final year, and on those accumulated over the horizon. The resulting multi-objective optimal control problem is solved with the Non-dominated Sorting Genetic Algorithm II (NSGA-II) and applied to the Île-de-France region from 2026 to 2050. Each formulation yields the set of achievable combinations of emissions, budget and replaced vehicles, together with the schedules that reach them. The framework itself is not tied to these two measures or to this region: other instruments and other objectives can be substituted, and other regions studied, provided the required data are available.
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BibTeX
@misc{alami2026combining,
title = {{Combining optimal low emission zones scheduling and electric vehicle purchase incentives for transport policy backcasting}},
author = {Asmae Alami and Vinith Lakshmanan and Antonio Sciarretta},
howpublished = {HAL},
year = {2026},
month = oct,
url = {https://ifp.hal.science/hal-05710781v2},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Combining optimal low emission zones scheduling and electric vehicle purchase incentives for transport policy backcasting
AU - Asmae Alami
AU - Vinith Lakshmanan
AU - Antonio Sciarretta
PY - 2026
DA - 2026/10/13
PB - HAL
UR - https://ifp.hal.science/hal-05710781v2
AB - Achieving greenhouse gas reduction targets in the mobility sector requires well-designed policies. Low emission zones (LEZ) and electric vehicle (EV) purchase incentives are widely used across Europe, yet they are usually decided separately. This study combines them in a backcasting approach, which entails setting environmental, budgetary and societal targets first, then seeking the optimal combination of policies that achieves these predefined targets. Using a passenger car fleet dynamics model, the LEZ schedule and the income-differentiated EV purchase incentives are taken as decision variables and optimised together against three objectives: CO2 emissions, the public budget spent on incentives, and the number of vehicles households replace because of LEZ implementation, which reflects social acceptability. NOx and PM are computed from the circulating fleet but left out of the optimisation. The environmental objective is written in two ways and compared: on the emissions of the final year, and on those accumulated over the horizon. The resulting multi-objective optimal control problem is solved with the Non-dominated Sorting Genetic Algorithm II (NSGA-II) and applied to the Île-de-France region from 2026 to 2050. Each formulation yields the set of achievable combinations of emissions, budget and replaced vehicles, together with the schedules that reach them. The framework itself is not tied to these two measures or to this region: other instruments and other objectives can be substituted, and other regions studied, provided the required data are available.
ER -