Correlation between Sensor Performance, Autonomy Performance and Fuel-Efficiency in Semi-Truck Platoons

2021-01-0064

04/06/2021

Features
Event
SAE WCX Digital Summit
Authors Abstract
Content
Semi-trucks, specifically class-8 trucks, have recently become a platform of interest for autonomy systems. Platooning involves multiple trucks following each other in close proximity, with only the lead truck being manually driven and the rest being controlled autonomously. This approach to semi-truck autonomy is easily integrated on existing platforms, reduces delivery times, and reduces greenhouse gas emissions via fuel economy benefits. Level 1 SAE fuel studies were performed on class-8 trucks operating with the Auburn Cooperative Adaptive Cruise Control (CACC) system, and fuel savings up to 10-12% were seen. Enabling platooning autonomy required the use of radar, global positioning systems (GPS), and wireless vehicle-to-vehicle (V2V) communication. Poor measurements and state estimates can lead to incorrect or missing positioning data, which can lead to unnecessary dynamics and finally wasted fuel. This is especially an issue if deceleration is applied in response to a bad measurement. In this study, a faulty radar was shown to cause a greater than 5% increase in fuel consumption. The mechanism of this fuel consumption increase is investigated and applied to other types of sensor failures to indicate their potential effects on fuel economy. This analysis indicates that poor GPS signals over short time can be largely filtered out, with no real gain or loss of fuel economy. V2V communications were intentionally limited by causing interference, which resulted in dropped communication packets over a small physical area, but not an appreciable impact on fuel economy.
Meta TagsDetails
DOI
https://doi.org/10.4271/2021-01-0064
Pages
10
Citation
Adam, C., Lakshmanan, S., Richardson, P., Stegner, E. et al., "Correlation between Sensor Performance, Autonomy Performance and Fuel-Efficiency in Semi-Truck Platoons," SAE Technical Paper 2021-01-0064, 2021, https://doi.org/10.4271/2021-01-0064.
Additional Details
Publisher
Published
Apr 6, 2021
Product Code
2021-01-0064
Content Type
Technical Paper
Language
English