Intersection Lane Weighting for Vehicle Route Prediction
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Solution Overview
Problem
Current vehicle route prediction methods, especially in complex scenarios like intersections, suffer from low accuracy due to reliance on simplistic strategies such as defaulting to straight routes, leading to inefficiencies and reduced computational accuracy.
Innovation Solution
A vehicle travel control method that determines the weight of each lane based on intersection and vehicle information, allowing for a more accurate prediction of the intended travel route by calculating angular and distance parameters, and using these to determine a target lane.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the vehicle route prediction defaults to straight routes at intersections, then the prediction process is simple and fast, but the prediction accuracy deteriorates
Solution Approach 1:
The patent changes the prediction parameters from simple geometric center prediction to multi-parameter analysis including lane direction angles, vehicle position, and distance to intersection. By calculating angular parameters between vehicle trajectory and lane directions, the system achieves higher prediction accuracy while maintaining computational efficiency through parameter-based decision making
Solution Approach 2:
The patent introduces dynamic prediction that adapts to different scenarios based on real-time vehicle state and intersection characteristics. The prediction model dynamically adjusts weights for different lanes based on vehicle position, approach direction, and distance to intersection, enabling accurate prediction of non-straight routes while maintaining fast processing through conditional logic
2Measurement precision
If the vehicle route prediction considers multiple lanes and angular parameters, then the prediction accuracy improves, but the computational complexity increases
Solution Approach 1:
The patent segments the intersection area into multiple discrete lanes with defined geometric centers and directions. By dividing the complex intersection into manageable lane segments, the system can calculate angular parameters and distances for each lane independently, improving prediction accuracy through detailed analysis while controlling computational complexity through structured segmentation
Solution Approach 2:
The patent applies partial action by focusing computational resources on the most relevant lanes based on vehicle position and approach direction. Instead of equally processing all possible routes, the system calculates parameters for likely candidate lanes first, achieving high accuracy for the actual route while avoiding unnecessary computations for improbable alternatives
Data Source
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AI summary
The present disclosure provides a vehicle travel control method and apparatus, which are related to the field of computer technologies and, in particular, to the field of autonomous driving and intelligent transportation. A specific implementation lies in: acquiring a distance between a vehicle and a first intersection, where the first intersection is an intersection for the vehicle to go across on a first road which the vehicle is currently on; acquiring, on a determination that the distance is less than or equal to a preset distance, intersection information of the first intersection and travelling information of the vehicle, where the intersection information includes lane information of at least two lanes on the first road; determining, according to the intersection information and the travelling information, a target weight of each of the lanes for the vehicle to travel into; and determining, according to the target weight of each of the lanes for the vehicle to travel into, an intended travel route of the vehicle. By means of determining, in a lane-by-lane manner, the target weight of each of the lanes for the vehicle to travel into, and then determining the intended travel route of the vehicle according to the target weight, prediction on a travelling route of the vehicle can be effectively improved in accuracy.