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.
Highlights
The truck platooning system exploits the Cooperative Adaptive Cruise Control (CACC) in order to compose a platoon of heavy vehicles, travelling almost with the same speed and the same driving regime
Aim of this paper is to provide a tool to prevent at least the risk of implementing the system without having examined in deep the potential impacts of truck platooning on the overall traffic flow
The paper is structured as follows: in Section 1 a short bibliographical review is carried out to identify the current capabilities of traffic simulation software and all the behaviours that should be included in a traffic simulation; in Section 2 an overview of the input parameters to be inserted through the COM interface and of how this interface is exploited is presented; in Section 3 the main scripted functions are reported and explained in their operational logics; in Section 4 the developed tool is exploited to evaluate three platooning driving strategies and their impacts on traffic efficiency, in the last section the conclusions are presented
Summary
The truck platooning system exploits the Cooperative Adaptive Cruise Control (CACC) in order to compose a platoon of heavy vehicles, travelling almost with the same speed and the same driving regime. In the short time horizon (2019–2025) the human driver will still be entrusted with the lateral driving task, while the longitudinal control will be granted to the on-board L1 system (Ricardo UK Ltd 2014; Bishop 2017; EC 2018) This solution should allow the heavy vehicles to travel with a strongly reduced time gap between them, keeping a value that can range between 0.3 and 1 s. The paper is structured as follows: in Section 1 a short bibliographical review is carried out to identify the current capabilities of traffic simulation software and all the behaviours that should be included in a traffic simulation; in Section 2 an overview of the input parameters to be inserted through the COM interface and of how this interface is exploited is presented; in Section 3 the main scripted functions are reported and explained in their operational logics; in Section 4 the developed tool is exploited to evaluate three platooning driving strategies and their impacts on traffic efficiency, in the last section the conclusions are presented
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