A Comprehensive Eco-Driving Strategy for CAVs with Microscopic Traffic Simulation Testing Evaluation

In this paper, a comprehensive deterministic Eco-Driving strategy for Connected and Autonomous Vehicles (CAVs) is presented. In this setup, multiple driving modes calculate speed profiles that are ideal for their own set of constraints simultaneously to save fuel as much as possible, while a High-Le...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2023-10, Vol.23 (20), p.8416
Main Authors: Kavas-Torris, Ozgenur, Guvenc, Levent
Format: Article
Language:English
Subjects:
Algorithms
Automation
Connectivity
Control algorithms
Design
Driverless cars
dynamic programming
eco-driving
ecological cooperative adaptive cruise control
Electric vehicles
Energy consumption
Energy efficiency
Energy management
Infrastructure
Infrastructure (Economics)
Simulation
Simulation methods
traffic simulation
velocity trajectory
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Summary:In this paper, a comprehensive deterministic Eco-Driving strategy for Connected and Autonomous Vehicles (CAVs) is presented. In this setup, multiple driving modes calculate speed profiles that are ideal for their own set of constraints simultaneously to save fuel as much as possible, while a High-Level (HL) controller ensures smooth and safe transitions between the driving modes for Eco-Driving. This Eco-Driving deterministic controller for an ego CAV was equipped with Vehicle-to-Infrastructure (V2I) and Vehicle-to-Vehicle (V2V) algorithms. This comprehensive Eco-Driving strategy and its individual components were tested by using simulations to quantify the fuel economy performance. Simulation results are used to show that the HL controller ensures significant fuel economy improvement as compared to baseline driving modes with no collisions between the ego CAV and traffic vehicles, while the driving mode of the ego CAV was set correctly under changing constraints. For the microscopic traffic simulations, a 6.41% fuel economy improvement was observed for the CAV that was controlled by this comprehensive Eco-Driving strategy.
ISSN:1424-8220
1424-8220
DOI:10.3390/s23208416