Autonomous Vehicle Load Distribution Control for Safer Handling
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Solution Overview
Problem
Autonomous vehicles lack effective methods to optimize their driving strategies based on the mass distribution of loads, leading to inefficient fuel use, increased wear-and-tear, and potential safety risks due to conservative or dangerous maneuvers.
Innovation Solution
The implementation of mass distribution-informed optimization systems that identify sensor data from axles to determine mass distribution data, allowing for corrective actions such as route adjustments and handling maneuver limits to improve fuel efficiency and safety.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If autonomous vehicles use conservative driving maneuvers to ensure safety, then safety is improved, but fuel efficiency deteriorates
Solution Approach 1:
The system dynamically adjusts driving maneuvers based on real-time mass distribution data from sensors. The autonomous vehicle transitions from static conservative driving to dynamic adaptive driving, where acceleration, braking, and steering actions are optimized according to current load conditions, resolving the contradiction between safety and fuel efficiency
Solution Approach 2:
The system changes driving parameters (speed, acceleration, steering angle) based on mass distribution parameters detected by sensors. By continuously monitoring and adjusting these parameters according to actual vehicle loading conditions, the system achieves both safety and fuel efficiency
2Use of energy by moving object
If autonomous vehicles use aggressive driving maneuvers to improve fuel efficiency, then fuel efficiency is improved, but safety deteriorates
Solution Approach 1:
The system adjusts driving parameters within safe boundaries based on mass distribution. Rather than using fixed aggressive maneuvers, the system optimizes parameters dynamically according to actual vehicle conditions, achieving fuel efficiency without compromising safety
Solution Approach 2:
The system uses sensor feedback on mass distribution to continuously monitor and adjust driving maneuvers. This closed-loop control ensures that fuel-efficient maneuvers remain within safety boundaries by adapting to real-time vehicle conditions
3Ease of operation
If autonomous vehicles apply uniform driving strategies regardless of load, then ease of operation is improved, but fuel efficiency deteriorates
Solution Approach 1:
The autonomous vehicle performs self-assessment of its mass distribution using onboard sensors and automatically adjusts its driving strategy accordingly. This self-service capability eliminates the need for external input while achieving fuel-efficient operation adapted to current load conditions
Solution Approach 2:
The system automatically changes driving parameters based on detected mass distribution parameters, providing adaptive fuel efficiency without requiring manual intervention or complex external control
4Use of energy by moving object
If autonomous vehicles monitor mass distribution in real-time, then fuel efficiency is improved, but device complexity increases
Solution Approach 1:
The system uses existing multi-functional sensors (accelerometers, gyroscopes, load cells) already present in autonomous vehicles for navigation and stability control to also determine mass distribution. This universal use of existing components achieves fuel efficiency improvement without adding dedicated complex hardware
Solution Approach 2:
The system replaces complex mechanical weighing mechanisms with electronic sensor-based mass distribution determination. By using electronic sensors and computational algorithms instead of mechanical scales, the system achieves real-time monitoring with reduced mechanical complexity
Data Source
AI summary
A method includes identifying sensor data associated with corresponding distal ends of one or more axles of an autonomous vehicle (AV). The method further includes determining, based on the sensor data, mass distribution data of the AV. The mass distribution data is associated with a first load proximate a first distal end of a first axle of the AV and a second load proximate a second distal end of the first axle of the AV. The method further includes causing, based on the mass distribution data, performance of a corrective action associated with the AV.