Quantification of Platooning Fuel Economy Benefits across United States Interstates Using Closed-Loop Vehicle Model Simulation

2021-01-5028

02/25/2021

Features
Event
Automotive Technical Papers
Authors Abstract
Content
Evaluation of the platooning legislative space suggests a limited near-term opportunity for autonomous vehicles as currently only nine states have platooning and autonomous favorable legislations. An extensive closed-loop vehicle model simulation was conducted to quantify two-truck platooning fuel economy entitlement benefits across all United States (US) interstate routes (I-xx) spanning over 40,000 miles as compared to a single truck. A simultaneous study was carried out to identify the density of Class 8 heavy-duty trucks on these interstates, using the Freight Analysis Framework (FAF) 4 database. These two studies were combined to ascertain interstates that foresee the least fuel consumption due to platooning and thus identifying states with the most platooning benefits. Identification of states with most platooning benefits provides realistic data to push for autonomous driving and platooning legislations. The US heatmap was developed ranking states according to fuel conserved and thus recognizing states with maximum impact on US carbon footprint. Texas and California were found to have the most platooning fuel economy benefits due to high truck volumes. The analysis also predicted that 40% of total platooning benefits can be realized with only nine states. Further, I-20 and I-80 were recognized to have the most platooning benefits due to terrain characteristics and truck density. Thus, it is recommended that legislative efforts can be focused around limited states through which these interstates pass.
Meta TagsDetails
DOI
https://doi.org/10.4271/2021-01-5028
Pages
9
Citation
Chadha, P., and Sujan, V., "Quantification of Platooning Fuel Economy Benefits across United States Interstates Using Closed-Loop Vehicle Model Simulation," SAE Technical Paper 2021-01-5028, 2021, https://doi.org/10.4271/2021-01-5028.
Additional Details
Publisher
Published
Feb 25, 2021
Product Code
2021-01-5028
Content Type
Technical Paper
Language
English