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Definition of a Python script for the micro-simulation of the truck platooning system

    Serio Agriesti Affiliation
    ; Marco Ponti Affiliation
    ; Luca Studer Affiliation
    ; Roberto Maja Affiliation
    ; Ornella Aleccia Affiliation
    ; Jochen Lohmiller Affiliation
    ; Isaac Vargas Gordillo Affiliation

Abstract

Truck platooning is, by now, one of the major topics in transport science and freight transport. The benefits arising from the system explain the growing interest of the involved stakeholders and the many field-tests planned in the next years. This run towards truck platooning saw an abrupt acceleration but there are risks that should be accounted for. Even though field-tests are fundamental for the implementation of a new transport system, they will hardly cover all the traffic scenarios that a platoon of trucks will face on the European network. Therefore, there is the need for many more studies based on traffic simulation and for tools enabling traffic simulation software to reproduce truck platooning. In this framework, the paper has two aims, the first one being to report and describe a Python script to reproduce truck platooning with a common commercial simulation software. The second one is to apply said script to analyse what is the best driving strategy for a platoon of truck to limit the hindrance on the surrounding traffic while approaching a critical highway segment such as the on-ramp one. At the end of the paper, a comparison between three different strategies (driving as usual, dissolution and headway adaptation) is carried out and commented.


First published online 11 November 2020

Keyword : truck platooning, Python script, impact assessment, C-Roads, traffic efficiency, traffic modelling

How to Cite
Agriesti, S., Ponti, M., Studer, L., Maja, R., Aleccia, O., Lohmiller, J., & Gordillo, I. V. (2021). Definition of a Python script for the micro-simulation of the truck platooning system. Transport, 36(1), 84-97. https://doi.org/10.3846/transport.2020.13784
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Mar 30, 2021
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This work is licensed under a Creative Commons Attribution 4.0 International License.

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