Lane Change Risk Weighting for Multi-Vehicle Traffic Assessment
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Solution Overview
Problem
Current lane change control systems for vehicles do not adequately consider the influence of other vehicles, leading to unsafe or uncomfortable maneuvers during lane changes.
Innovation Solution
A vehicle-mounted device that calculates and processes data to determine collision times and risk factors for surrounding vehicles, adjusting lane change weights and vehicle operations to ensure safer and more comfortable lane changes by considering multiple vehicles' positions, velocities, and accelerations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional lane change control is used, then the lane change operation is simple, but the safety and comfort during lane change deteriorate due to insufficient consideration of surrounding vehicles
Solution Approach 1:
The patent segments the surrounding vehicle environment into multiple discrete targets, each with calculated collision time and risk factor. This allows the system to individually assess and respond to each vehicle's influence on the lane change maneuver, improving safety through comprehensive evaluation while maintaining manageable complexity through systematic processing of segmented data
Solution Approach 2:
The system performs preliminary calculations of collision time and risk factors for all surrounding vehicles before executing the lane change maneuver. By pre-assessing the safety environment and identifying potential conflicts in advance, the system can make informed decisions about lane change feasibility and timing, thereby improving reliability without requiring complex real-time adjustments during execution
2Reliability
If the system considers all surrounding vehicles, then the safety improves, but the calculation complexity and processing time increase
Solution Approach 1:
The system continuously monitors surrounding vehicles and dynamically updates collision time and risk factor calculations based on changing vehicle positions, velocities, and accelerations. This feedback mechanism ensures accurate collision risk assessment while optimizing calculation time by focusing computational resources on vehicles that pose actual threats to the lane change maneuver
Solution Approach 2:
The patent changes the assessment parameters from simple distance-based metrics to physics-based collision time and risk factor calculations that incorporate velocity and acceleration. This allows the system to accurately assess collision risk by evaluating the dynamic state of surrounding vehicles, improving reliability while the systematic parameter selection keeps calculation time manageable
3Ease of operation
If the lane change weight is adjusted dynamically, then the comfort improves, but the control complexity increases
Solution Approach 1:
The system dynamically adjusts the lane change weight parameter based on real-time assessment of surrounding vehicle conditions and calculated risk factors. This dynamic adjustment allows the vehicle to optimize lane change comfort by adapting the maneuver profile to current traffic conditions, while the systematic approach to weight calculation based on pre-determined risk factors keeps the control algorithm complexity manageable
Data Source
AI summary
A lane change control method applied to a vehicle-mounted device is provided. The method includes calculating a first risk factor of a preceding vehicle based on a first vehicle data and a second vehicle data, calculating a second risk factor of an adjacent preceding vehicle based on the first vehicle data and a third vehicle data. A risk weight is obtained according to the first risk factor and the second risk factor. A lane-change weight is calculated based on a target lane line. A collective weight is obtained according to the lane-change weight and the risk weight. Once a plurality of reference vehicle values is obtained, the host vehicle is controlled to change lanes based on the plurality of reference vehicle values, the lane-change weight, and the first vehicle data.