Impacts of automated driving on energy demand and emissions in motorway traffic

Automated Vehicles (AVs) are expected to reduce CO2 emissions and energy demand of road transportation by mechanisms such as more stable vehicle control, but realisation of these benefits depends on AV deployment and use. Simulation studies have reported a wide range of potential impacts, depending...

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Main Authors: Elina Aittoniemi, Teemu Itkonen, Satu Innamaa
Format: Article
Language:English
Published: Elsevier 2024-11-01
Series:Transportation Research Interdisciplinary Perspectives
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2590198224002677
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author Elina Aittoniemi
Teemu Itkonen
Satu Innamaa
author_facet Elina Aittoniemi
Teemu Itkonen
Satu Innamaa
author_sort Elina Aittoniemi
collection DOAJ
description Automated Vehicles (AVs) are expected to reduce CO2 emissions and energy demand of road transportation by mechanisms such as more stable vehicle control, but realisation of these benefits depends on AV deployment and use. Simulation studies have reported a wide range of potential impacts, depending on the driver model and assumptions. Studies have focused on the total impact on CO2 emissions in specific traffic volume and speed limit conditions and have not separated impacts for different road users. Heavy-duty vehicles (HDVs) have often been omitted entirely. This study assessed the potential impacts of conditionally automated driving on the CO2 emissions and energy demand of equipped and unequipped passenger cars (MVs) and unequipped HDVs with a systematic approach, covering different speed limits, traffic volumes and AV penetration rates on motorways. The methodology incorporated traffic microsimulation, an emissions calculation tool, and a formula for tractive energy demand. Replacing passenger cars with AVs in traffic simulation affected emissions of all road users, and the magnitude and direction of impacts differed between vehicle types. Whereas average energy demand and CO2 emissions of AVs were lower in most conditions compared to MVs at baseline, benefits for all vehicle types were seen only at the highest traffic volumes. Changed traffic dynamics can lead to increases in energy demand and emissions of HDVs and MVs already at low AV penetration rates in moderate traffic. Thus, future studies on AV impacts should include more variation in simulated conditions and consider impacts on different vehicle types separately.
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spelling doaj-art-239ce4d115964a9fb9a80dca75082bb82025-08-20T02:37:05ZengElsevierTransportation Research Interdisciplinary Perspectives2590-19822024-11-012810128110.1016/j.trip.2024.101281Impacts of automated driving on energy demand and emissions in motorway trafficElina Aittoniemi0Teemu Itkonen1Satu Innamaa2Corresponding author.; VTT Technical Research Centre of Finland Ltd., P.O. Box 1000, FI-02044 VTT, Espoo, FinlandVTT Technical Research Centre of Finland Ltd., P.O. Box 1000, FI-02044 VTT, Espoo, FinlandVTT Technical Research Centre of Finland Ltd., P.O. Box 1000, FI-02044 VTT, Espoo, FinlandAutomated Vehicles (AVs) are expected to reduce CO2 emissions and energy demand of road transportation by mechanisms such as more stable vehicle control, but realisation of these benefits depends on AV deployment and use. Simulation studies have reported a wide range of potential impacts, depending on the driver model and assumptions. Studies have focused on the total impact on CO2 emissions in specific traffic volume and speed limit conditions and have not separated impacts for different road users. Heavy-duty vehicles (HDVs) have often been omitted entirely. This study assessed the potential impacts of conditionally automated driving on the CO2 emissions and energy demand of equipped and unequipped passenger cars (MVs) and unequipped HDVs with a systematic approach, covering different speed limits, traffic volumes and AV penetration rates on motorways. The methodology incorporated traffic microsimulation, an emissions calculation tool, and a formula for tractive energy demand. Replacing passenger cars with AVs in traffic simulation affected emissions of all road users, and the magnitude and direction of impacts differed between vehicle types. Whereas average energy demand and CO2 emissions of AVs were lower in most conditions compared to MVs at baseline, benefits for all vehicle types were seen only at the highest traffic volumes. Changed traffic dynamics can lead to increases in energy demand and emissions of HDVs and MVs already at low AV penetration rates in moderate traffic. Thus, future studies on AV impacts should include more variation in simulated conditions and consider impacts on different vehicle types separately.http://www.sciencedirect.com/science/article/pii/S2590198224002677Automated drivingHeavy-duty vehiclesMotorwayTraffic simulationCO2 emissionsEnergy demand
spellingShingle Elina Aittoniemi
Teemu Itkonen
Satu Innamaa
Impacts of automated driving on energy demand and emissions in motorway traffic
Transportation Research Interdisciplinary Perspectives
Automated driving
Heavy-duty vehicles
Motorway
Traffic simulation
CO2 emissions
Energy demand
title Impacts of automated driving on energy demand and emissions in motorway traffic
title_full Impacts of automated driving on energy demand and emissions in motorway traffic
title_fullStr Impacts of automated driving on energy demand and emissions in motorway traffic
title_full_unstemmed Impacts of automated driving on energy demand and emissions in motorway traffic
title_short Impacts of automated driving on energy demand and emissions in motorway traffic
title_sort impacts of automated driving on energy demand and emissions in motorway traffic
topic Automated driving
Heavy-duty vehicles
Motorway
Traffic simulation
CO2 emissions
Energy demand
url http://www.sciencedirect.com/science/article/pii/S2590198224002677
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AT teemuitkonen impactsofautomateddrivingonenergydemandandemissionsinmotorwaytraffic
AT satuinnamaa impactsofautomateddrivingonenergydemandandemissionsinmotorwaytraffic