Learning-Based Driver Behavior Modeling and Delay Compensation to Improve the Efficiency of an Eco-Driving Assistance System
Author:
Affiliation:
1. University of Kaiserslautern,Institute of Electromobility,Germany
2. University of Kaiserslautern,Human Computer Interaction Group,Germany
3. University of Kaiserslautern,Institute for Mechanical and Automotive Engineering,Germany
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9945068/9945069/09945577.pdf?arnumber=9945577
Reference16 articles.
1. Driving Mode Advice for Eco-Driving Assistance System With Driver Reaction Delay Compensation
2. Eco-driving assistance system for electric vehicles based on speed profile optimization
3. Ecological Adaptive Cruise Control for Urban Environments using SPaT Information
4. A driver-in-the-loop co-simulation framework for testing predictive EDAS for commercial vehicles in urban environments
5. Driving Style Analysis Using Data Mining Techniques
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1. Enhancing Driving Behavior Analysis in Autonomous Systems: A Reservoir Computing and Temporal-Aware Machine Learning Approach;2024 IEEE International Conference on Mobility, Operations, Services and Technologies (MOST);2024-05-01
2. A Review of Driving Style Recognition Methods From Short-Term and Long-Term Perspectives;IEEE Transactions on Intelligent Vehicles;2023-11
3. Evaluation of the driving performance and user acceptance of a predictive eco-driving assistance system for electric vehicles;Transportation Research Part C: Emerging Technologies;2023-08
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