Eco-Autonomous Driving Control for Energy Efficiency
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Solution Overview
Problem
Current automated driving systems in vehicles lack efficient energy management and adaptive control capabilities, particularly in varying roadway conditions, which affects energy efficiency, occupant comfort, and collision avoidance.
Innovation Solution
The Info-Rich Eco-Autonomous Driving (iREAD) system architecture integrates eco-driving protocols into connected and automated vehicles, using a universal canonical data-exchange architecture to fuse preview information with vehicle energy efficiency, occupant security, and comfort data for multi-layer co-optimization, enabling real-time eco-routing and vehicle dynamics and powertrain control without additional sensors or hardware.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If traditional navigation systems are used to determine routes, then route guidance is provided, but energy efficiency optimization is not achieved
Solution Approach 1:
The patent combines traditional navigation routing functionality with eco-driving energy optimization into a unified system. The route determination module integrates map data, traffic data, and energy consumption models to simultaneously provide route guidance and energy efficiency optimization without requiring separate independent systems.
Solution Approach 2:
The route determination module serves multiple functions: it provides traditional navigation routing, calculates energy consumption for different routes, determines eco-routes optimized for energy efficiency, and adapts to various driving conditions. This multi-functional approach eliminates the need for separate dedicated eco-routing hardware.
2Use of energy by moving object
If real-time data processing is implemented for eco-routing, then energy efficiency is optimized, but computational load increases
Solution Approach 1:
The system pre-calculates energy consumption values for different routes and stores them in advance using the energy consumption model. By performing these computations beforehand rather than in real-time during driving, the system reduces the instantaneous computational load while still providing real-time eco-routing guidance.
Solution Approach 2:
The route determination module uses previously stored energy consumption data and traffic information to quickly determine optimal eco-routes without requiring intensive real-time calculations. The system serves itself by leveraging pre-processed data and models rather than performing all computations from scratch during operation.
3Measurement precision
If multiple data sources are integrated for comprehensive routing, then routing accuracy improves, but data processing complexity increases
Solution Approach 1:
The patent segments the data processing into distinct functional modules: a map data module for geographic information, a traffic data module for real-time traffic conditions, and an energy consumption model for efficiency calculations. This modular segmentation allows each module to process specific data types independently, reducing overall processing complexity while maintaining comprehensive routing accuracy.
Data Source
AI summary
A method for controlling automated driving operations of a vehicle includes determining vehicle origin and destination data, and generating a graphical representation of a road network with multiple candidate routes between the vehicle's origin and destination. Road-level data, including speed, turn angle, and/or gradient data, is received for each candidate route, and respective total energy uses are estimated for the vehicle to traverse across the candidate routes. Multiple candidate driving strategies, each having respective speed and acceleration profiles, are determined for the candidate route with the lowest estimated total energy use. An optimal candidate driving strategy is selected through a cost evaluation of the associated speed and acceleration profiles and forward movement simulations of the vehicle over a prediction horizon. Command signals are transmitted to the vehicle's steering and/or powertrain systems to execute control operations based on the optimal driving strategy and the candidate route with the lowest energy use.