Vehicle Trajectory Planning With Energy-Constrained Speed Mapping
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for determining vehicle travel trajectories in autonomous driving do not consider factors like path turning radius, ground conditions, and vehicle speed, leading to high energy consumption and potential safety hazards.
Innovation Solution
A method that determines an initial path information, optimizes it to generate a target optimized path information, establishes an optimized mapping relationship for velocity based on energy consumption constraints, and calculates an optimized trajectory for the vehicle.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Length of stationary object
If a shortest path method is used to determine vehicle travel trajectory, then the path length is minimized, but energy consumption increases and safety hazards occur due to ignoring turning radius, ground condition, and vehicle speed factors
Solution Approach 1:
The patent transforms the trajectory determination from a static shortest path problem to a dynamic optimization problem by introducing velocity as a variable parameter. The mapping relationship between velocity and trajectory points allows the system to adjust speed at different locations to minimize energy consumption while considering vehicle dynamics and environmental constraints
Solution Approach 2:
The system transitions from a static path planning approach to a dynamic trajectory optimization approach. By establishing a velocity mapping relationship that changes with position and considering factors like turning radius and ground conditions, the trajectory becomes adaptive and dynamic rather than fixed
2Length of stationary object
If a shortest path method is used to determine vehicle travel trajectory, then the path length is minimized, but safety hazards occur due to ignoring turning radius, ground condition, and vehicle speed factors
Solution Approach 1:
The patent incorporates safety-critical parameters such as turning radius, ground condition, and vehicle speed into the optimization framework. By making these parameters explicit constraints in the velocity mapping relationship, the system ensures that trajectory adjustments maintain safety margins while achieving energy efficiency
Solution Approach 2:
The system uses feedback from environmental sensors and vehicle state measurements to continuously update the velocity mapping relationship. This allows real-time adjustment of the trajectory to maintain safety under changing conditions while optimizing energy consumption
3Use of energy by moving object
If velocity optimization is performed based on energy consumption constraints, then energy efficiency improves, but computational complexity increases
Solution Approach 1:
The patent segments the trajectory into discrete path points and establishes a velocity mapping relationship for each segment independently. This segmentation allows the complex optimization problem to be broken down into manageable sub-problems that can be solved more efficiently
Solution Approach 2:
The system computes velocity optimization for critical segments of the trajectory where energy consumption is most significant, rather than optimizing every point uniformly. This partial action approach reduces computational burden while maintaining overall energy efficiency
Data Source
AI summary
A method of determining a vehicle travel trajectory, an electronic device, a storage medium and a vehicle, which relate to a field of an artificial intelligence technology, in particular to a field of autonomous driving and intelligent transportation. A specific implementation solution includes: determining an initial path information for a vehicle; optimizing the initial path information to generate a target optimized path information; determining an optimized mapping relationship for velocity according to the target optimized path information and a first energy consumption constraint parameter; and determining an optimized trajectory for the vehicle according to the target optimized path information and the optimized mapping relationship for velocity.