Loss Function Design for Data-Driven Predictors to Enhance the Energy Efficiency of Connected and Automated Vehicles

Article Automation & Control Systems

Ecological Adaptive Cruise Control of Plug-In Hybrid Electric Vehicle With Connected Infrastructure and On-Road Experiments

Sangjae Bae et al.

Summary: This paper examines the mathematical formulation and practical implementation of an ecological adaptive cruise controller (ECO-ACC) with connected infrastructure. The proposed ECO-ACC framework for plug-in hybrid electric vehicle (PHEV) and the demonstration results in a real-world setting show significant improvement in energy efficiency.

JOURNAL OF DYNAMIC SYSTEMS MEASUREMENT AND CONTROL-TRANSACTIONS OF THE ASME (2022)

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Article Automation & Control Systems

Data-Driven Forgetting and Discount Factors for Vehicle Speed Forecasting in Ecological Adaptive Cruise Control

Eunjeong Hyeon et al.

Summary: This paper investigates temporal correlations in human driving behavior and proposes a new prediction method to improve speed forecasting accuracy. The results show that the new method significantly improves energy saving compared to conventional speed predictors.

JOURNAL OF DYNAMIC SYSTEMS MEASUREMENT AND CONTROL-TRANSACTIONS OF THE ASME (2022)

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Article Engineering, Civil

Leveraging Human Driving Preferences to Predict Vehicle Speed

Sen Yang et al.

Summary: Accurate speed prediction is crucial for eco-safe driving of intelligent vehicles. This paper proposes a learning-based model that incorporates human driving preferences into speed prediction, achieving the best results compared to its counterparts in a 200 m prediction horizon.

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS (2022)

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Article Automation & Control Systems