Automated platoon manipulation in merging scenarios using trajectory estimation of connected vehicles

Rory Alston; Daniel Pierce; Patrick Smith; David Bevly; Scott Heim

doi:10.1117/12.2523994

2 May 2019 Automated platoon manipulation in merging scenarios using trajectory estimation of connected vehicles

Rory Alston, Daniel Pierce, Patrick Smith, David Bevly, Scott Heim

Proceedings Volume 11009, Autonomous Systems: Sensors, Processing, and Security for Vehicles and Infrastructure 2019; 110090N (2019) https://doi.org/10.1117/12.2523994
Event: SPIE Defense + Commercial Sensing, 2019, Baltimore, MD, United States

Abstract

A method of integrating non-automated vehicles into a platoon of Cooperative Adaptive Cruise Control (CACC) Class 8 Heavy Duty Trucks was developed and tested at the National Center for Asphalt Technology (NCAT) test track. As CACC platooning becomes more commonplace, the interaction between automated and non-automated vehicles increases. This work explores this interaction during a highway merging scenario. Merging of vehicles occurs when a vehicle enters the highway system where an automated platoon is operating at that time. This scenario is handled by predicting the trajectories of the automated platoon and the non-automated vehicle entering the highway. Based on these trajectories, the automated platoon decides to create a gap for the merging vehicle if necessary. In this work, the non-automated vehicle is assumed to be a passive, connected vehicle, i.e. the platoon has knowledge of the merging vehicle’s position and velocity. The merging scenarios are handled by a CACC platooning system with Dedicated Short Range Communication (DSRC) for Vehicle to Vehicle (V2V) communication. This algorithm was implemented as an addition to Auburn University’s CACC system and was able to successfully complete automated merging scenarios. The merging scenarios in the front, middle, and back of the platoon were completed at the NCAT test track.

Conference Presentation

Citation Download Citation

Rory Alston, Daniel Pierce, Patrick Smith, David Bevly, and Scott Heim "Automated platoon manipulation in merging scenarios using trajectory estimation of connected vehicles", Proc. SPIE 11009, Autonomous Systems: Sensors, Processing, and Security for Vehicles and Infrastructure 2019, 110090N (2 May 2019); https://doi.org/10.1117/12.2523994

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