Macroscopic Modelling of Predicted Automated Vehicle Emissions

Mohammed Obaid, Arpad Torok


This paper studies the effect of automated vehicle implementation on transport system emission from a macroscopic point of view. The paper considers several scenarios differing in passenger car unit (PCU) and the penetration share percent of automated vehicles in the system using PTV Visum software. The study presents that automated vehicles reduce total emission by both the effect of smooth driving of each automated vehicle independently and the spread of automated vehicles in the network. Furthermore, apart from considering the effect of different PCU values and penetration levels, the developed model takes into account three different types of emissions and seven different vehicle classes.


automated vehicles; emissions; macroscopic; modelling; passenger car unit; penetration

Full Text:



Aradi, S., Becsi, T., & Gaspar, P. (2014). Design of predictive optimization method for energy-efficient operation of trains. 2014 European Control Conference, ECC 2014, Strasbourg, France, 2490–2495.

Árpád, T., Zsolt, S., Gábor, U., & Bence, V. (2018). Modelling urban autonomous transport system in Budapest. 8th International Scientific Conference, CMDTUR 2018, Žilina, Slovakia.

Barth, M., & Boriboonsomsin, K. (2009). Energy and emissions impacts of a freeway-based dynamic eco-driving system. Transportation Research. Part D: Transport and Environment, 14(6), 400–410.

Bartolini, C., Tettamanti, T., & Varga, I. (2017). Critical features of autonomous road transport from the perspective of technological regulation and law. Transportation Research Procedia, 27, 791–798.

Bernhard, F. (2016). The effect of autonomous vehicles on traffic. In M. Maurer, J. Gerdes, B. Lenz, & H. Winner (Eds), Autonomous Driving (pp. 317–334). Springer.

Csiszár, C., Csonka, B., Földes, D., Wirth, E., & Lovas, T. (2019). Urban public charging station locating method for electric vehicles based on land use approach. Journal of Transport Geography, 74, 173–180.

Esteves-Booth, A., Muneer, T., Kubie, J., & Kirby, H. (2002). A review of vehicular emission models and driving cycles. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 216(8), 777–797.

European Environment Agency. (2020). European Union emission inventory report 1990-2018 (Issue EEA, Report No. 5/2020). https://www.eea.europa. eu//publications/european-union-emission-inventory-report-1990-2018

European Union. (2016). EU Transport in Figures. Statistical Pocketbook 2016. Directorate-General for Mobility and Transport (European Commission).

Fagnant, D. J., & Kockelman, K. (2015). Preparing a nation for autonomous vehicles: Opportunities, barriers and policy recommendations. Transportation Research. Part A: Policy and Practice, 77, 167–181.

Fallahshorshani, M., André, M., Bonhomme, C., & Seigneur, C. (2012). Coupling traffic, pollutant emission, air and water quality models: Technical review and perspectives. Procedia – Social and Behavioral Sciences, 48, 1794–1804.

Green, M. (2000). “How long does it take to stop?” Methodological analysis of driver perception-brake times. Transportation Human Factors, 2(3), 195–216.

Heinzelmann, B., Indinger, T., Adams, N., & Blanke, R. (2012). Taxonomy and definitions for terms related to driving automation systems for on-road motor vehicles. SAE International Journal of Commercial Vehicles, 5(1), 42–56.

Iacobucci, R., McLellan, B., & Tezuka, T. (2018). Modeling shared autonomous electric vehicles: Potential for transport and power grid integration. Energy, 158, 148–163.

Igliński, H., & Babiak, M. (2017). Analysis of the potential of autonomous vehicles in reducing the emissions of greenhouse gases in road transport. Procedia Engineering, 192, 353–358.

Jos G. J. Olivier, & Peters J.A.H.W. (2018). Trends in global CO2 and total greenhouse gas emissions: 2018 report. PBL Netherlands Environmental Assessment Agency.¬bal-co2-and-total-greenhouse-gas-emissions-2018-report

Kirby, A. (2008, December). CCCC kick the habit, A UN guide to climate neutrality. UNT Digital Library.

Knez, M. (2013). A review of vehicular emission models. Pre-Conference Proceedings of the 10th International Conference on Logistics & Sustainable Transport 2013, Celje, Slovenia.

Liu, J., Kockelman, K. M., & Nichols, A. (2017). Anticipating the emissions impacts of smoother driving by connected and autonomous vehicles, using the MOVES model. International Journal of Sustainable Transportation, December, 1–22.

Ma, J., & Zhang, L. (2018). A deploying method for predicting the size and optimizing the location of an electric vehicle charging stations. Information, 9(7).

MacKenzie, D. W. (2013). Fuel economy regulations and efficiency technology improvements in U.S. cars since 1975. [Doctoral dissertation, Massachusetts Institute of Technology]. beforeh2/files/MacKenzie dissertation final.pdf

Ntziachristos, L., et al. (2019). 1.A.3.b.i-iv Road transport 2019. EMEP/ EEA air pollutant emission inventory guidebook 2019. European Environment Agency. emep-eea-guidebook-2019/part-b-sectoral-guidance-chapters/1-energy/1-a-combustion/1-a-3-b-i/view

Obaid, M., & Szalay, Z. (2019). A novel model representation framework for cooperative intelligent transport systems. Periodica Polytechnica Transportation Engineering, 48(1), 39–44.

Obaid, M., & Torok, A. (2021). Macroscopic traffic simulation of autonomous vehicle effects. Vehicles, 3(2), 187–196.

Obaid, M., Torok, A., & Ortega, J. (2021). A comprehensive emissions model combining autonomous vehicles with park and ride and electric vehicle transportation policies. Sustainability, 13(9).

Paton-Walsh, C., Guérett`e, É. A., Emmerson, K., Cope, M., Kubistin, D., Humphries, R., Wilson, S., Buchholz, R., Jones, N. B., Griffith, D. W. T., Dominick, D., Galbally, I., Keywood, M., Lawson, S., Harnwell, J., Ward, J., Griffiths, A., & Chambers, S. (2018). Urban air quality in a coastal city: Wollongong during the MUMBA campaign. Atmosphere, 9(12).

Piatkowski, B., & Maciejewski, M. (2013). Comparison of traffic assignment in visum and transport simulation in MATSim. Transport Problems, 8(2), 113–1 20. traffic_assignment_in_VISUM_and_transport_simulation_in_MATSim

Szalay, Z., Nyerges, A., Hamar, Z., & Hesz, M. (2017). Technical specification methodology for an automotive proving ground dedicated to connected and automated vehicles. Periodica Polytechnica Transportation Engineering, 45(3), 168–174.

Tettamanti, T., Varga, I., & Szalay, Z. (2016). Impacts of autonomous cars from a traffic engineering perspective. Periodica Polytechnica Transportation Engineering, 44(4), 244–250.

Tsugawa, S. (2013). An overview on an automated truck platoon within the energy ITS project. IFAC Proceedings Volumes, 46(21), 41–46.

Vimmerstedt, L., Brown, A., Newes, E., Markel, T., Schroeder, A., Zhang, Y., Chipman, P., & Johnson, S. (2015). Transformative reduction of transportation greenhouse gas gmissions: Opportunities for change in technologies and systems (Report No. NREL/TP-5400-62943). National Renewable Energy Laboratory.

World Energy Counsil. (2016). World Energy Resources 2016. https://www. SummaryReport_2016.10.03.pdf

DOI: 10.7250/bjrbe.2022-17.550


  • There are currently no refbacks.

Copyright (c) 2022 Mohammed Obaid, Arpad Torok

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.