Semi-Autonomous Electric Vehicles in Platooning Mode and Their Effects on Travel Time: A Framework for Simulation Evaluation

TL;DR

This paper develops a simulation framework to evaluate how semi-autonomous electric vehicle platooning affects travel time, demonstrating the model's effectiveness through real-world trip data and use cases.

Contribution

It introduces a dynamic-flexible platooning model for electric vehicles, extending a simulation platform and validating its impact on travel efficiency.

Findings

Model effectively evaluates platooning impact on travel time

Dynamic-flexible platooning improves traffic efficiency

Simulation results support real-world applicability

Abstract

Connected and Automated Vehicles (CAVs) have received a lot of attention in recent years. However, there are still numerous challenges in this field. In this paper, we investigated the effects of dynamic-flexible platooning on travel time by considering real-world trips data. For this purpose we extended the platooning capabilities of the 3DCoAutosim simulation platform, and proposed a dynamic-flexible model that we validated by creating use cases on traffic efficiency. We studied our dynamic-flexible platooning case for three electric vans with an autonomous leader, a semi-autonomous first follower with a driver, and an autonomous last follower. Results showed that the model developed in this study is efficient to investigate the effects of dynamic-flexible platooning on travel time.