Autonomous Vehicle Speed Profiling for Fuel-Efficient Arrival Times
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Solution Overview
Problem
Autonomous vehicles face challenges in optimizing fuel economy due to varying road conditions, traffic, and regulatory constraints, which affect their ability to meet arrival times while minimizing fuel consumption.
Innovation Solution
A method and system that identify fuel-efficient speed values for each segment of a route, calculate an estimated arrival time, and adjust speed profiles based on correlation metrics to optimize fuel economy while meeting arrival times, incorporating regulatory and historical speed limits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If the autonomous vehicle travels at higher speeds to meet the threshold arrival time, then the arrival time constraint is satisfied, but fuel consumption increases
Solution Approach 1:
The system dynamically adjusts the speed profile across different route segments rather than maintaining a constant speed. The processing device determines optimal speed values for each segment based on fuel economy data, allowing the vehicle to accelerate in favorable conditions and decelerate when necessary, thereby optimizing the trade-off between arrival time and fuel consumption
Solution Approach 2:
The system changes the speed parameter across different spatial segments of the route. By determining a fuel-efficient speed value for each segment and computing correlation metrics between speed changes and fuel economy changes, the system optimizes the speed parameter to minimize fuel consumption while ensuring the vehicle arrives by the threshold time
2Ease of operation
If the autonomous vehicle maintains constant speed to simplify control, then ease of operation is improved, but fuel economy deteriorates due to inability to exploit road conditions
Solution Approach 1:
The route is divided into multiple segments, and the system determines a fuel-efficient speed value for each segment independently. This segmentation allows the vehicle to adapt its speed to local road conditions, traffic patterns, and terrain characteristics, improving fuel economy while maintaining manageable control complexity through automated segment-based optimization
3Loss of time
If the autonomous vehicle increases speed in all segments to ensure on-time arrival, then the arrival time constraint is met, but fuel consumption increases excessively
Solution Approach 1:
The system applies different speed strategies to different segments of the route based on local conditions. By computing correlation metrics for each segment and identifying only those segments where speed increase would significantly improve fuel economy, the system locally optimizes speed rather than applying a blanket speed increase across the entire route, thereby minimizing overall fuel consumption while ensuring on-time arrival
Data Source
AI summary
A method includes identifying route data including a threshold arrival time for a route for an autonomous vehicle (AV) and calculating, based on the route data and a fuel-efficient speed value for each segment of the route, an estimated arrival time. Responsive to the estimated arrival time not meeting the threshold arrival time, the method includes identifying at least a subset of segments that each represent a candidate for speed increase, computing, for each segment in the subset and based on the fuel economy data, a correlation metric that indicates a correlation between a change in fuel economy and a change in speed for a corresponding segment in the subset, and increasing, for at least one segment from the subset and based on a respective correlation metric, a fuel-efficient speed value of the corresponding segment from the subset to provide a speed profile reflecting the increased fuel-efficient speed value.