Autonomous Driving Trajectory Optimization Using Motor Efficiency Maps
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Solution Overview
Problem
Existing autonomous vehicles (AVs) face challenges in optimizing energy consumption, with conventional steering systems being slow and unsafe, and there is a need for improved energy-efficient navigation and maneuverability, especially in complex driving scenarios.
Innovation Solution
An autonomous driving system with a three-layer framework that includes path smoothing, speed trajectory optimization, and path tracking, utilizing differential speed steering to enhance maneuverability and energy efficiency by analyzing human driving trajectories and employing motor efficiency maps for optimal steering angles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional steering systems are used in autonomous vehicles, then the system structure is simple, but the steering response is slow and safety is compromised
Solution Approach 1:
The steering control is segmented into multiple independent wheel motor controllers, each capable of independent speed and rotational angle control. This allows parallel processing of steering commands and enables faster response times while maintaining system reliability through distributed control architecture.
Solution Approach 2:
The system transitions from static, centralized steering control to dynamic, distributed wheel-level control. Each wheel motor can independently adjust speed and angle in real-time, enabling adaptive steering responses that improve safety while managing complexity through modular design.
2Ease of operation
If traditional path tracking methods are used, then the navigation is stable, but the vehicle cannot execute sharp turns or navigate confined spaces effectively
Solution Approach 1:
The differential speed steering system enables dynamic adjustment of each wheel's speed and angle independently, allowing the vehicle to execute sharp turns, U-turns, and navigate confined spaces while maintaining navigation stability through real-time feedback control.
Solution Approach 2:
The system changes steering parameters at the wheel level rather than through centralized mechanical linkage. By independently controlling wheel speeds and rotational angles, the vehicle achieves enhanced maneuverability for sharp turns and confined space navigation while maintaining stable path tracking.
3Use of energy by moving object
If energy-efficient speed and acceleration intervals are optimized, then energy consumption is reduced, but the driving performance may be limited
Solution Approach 1:
The system pre-optimizes speed and acceleration intervals based on motor efficiency maps before execution. By planning energy-efficient trajectories in advance while considering path constraints and vehicle dynamics, the system achieves reduced energy consumption without significantly compromising driving performance.
Solution Approach 2:
The optimization adjusts speed and acceleration parameters within efficient intervals derived from motor efficiency maps. By operating within these optimized parameter ranges, the system reduces energy consumption while maintaining acceptable driving performance through intelligent parameter selection.
Data Source
AI summary
An autonomous driving system having a three-layer framework to optimize energy consumption in autonomous driving by utilizing the driving trajectory of human drivers. The first layer involves smoothing out the driving path to reduce its curvature, thereby avoiding sudden changes in acceleration and velocity caused by abrupt path changes. The second layer is a trajectory optimization stage, where a relationship between speed and time in the human driving trajectory is assigned to the smoothed path. The acceleration is calculated at each moment based on the motor torque-rotational speed efficiency diagram and the corresponding output efficiency of the motor. A best efficiency interval is then determined based on a reference motor efficiency, which is then converted into an optimal speed and acceleration interval of each of the wheels. On the smooth path, the optimal speed and acceleration interval are jointly optimized to obtain the best driving trajectory in order to ensure that the motor operates in the high-efficiency interval. In the third layer, the generated optimal trajectory is combined with the model predictive control (MPC) method to generate the optimal steering angle to achieve accurate trajectory tracking.