Intelligent Vehicle Platoon Lane Change Evaluation via Kalman Filter
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Solution Overview
Problem
Current methods lack a comprehensive, accurate, and reliable quantitative evaluation system for intelligent vehicle platoon lane change performance, which is crucial for ensuring safety and efficiency in intelligent driving technologies.
Innovation Solution
An intelligent vehicle platoon lane change performance evaluation method is proposed, involving the establishment of a three-degree of freedom nonlinear dynamics model and an improved adaptive unscented Kalman filter algorithm to estimate vehicle motion state parameters, enabling the quantification of performance indexes such as lane change yaw stability, velocity consistency, safety distance margin, and average vehicle clearance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing evaluation methods (hazard analysis, stochastic models, car-following models) are used for platoon safety evaluation, then safety assessment can be performed, but there is no quantitative evaluation method for platoon lane change performance
Solution Approach 1:
The evaluation system segments lane change performance into four distinct dimensional indexes: lane change smoothness, lane change time, safety distance margin, and velocity consistency. This segmentation allows each aspect to be measured and evaluated independently using specific algorithms and parameters, enabling precise quantitative evaluation without requiring an overly complex unified evaluation framework.
2Reliability
If a comprehensive quantitative evaluation system is established for platoon lane change performance, then accurate performance measurement is achieved, but the system complexity and implementation difficulty increase
Solution Approach 1:
The evaluation system incorporates feedback mechanisms by continuously monitoring platoon vehicles' motion state parameters (position, velocity, acceleration) during lane changes and comparing them against expected performance thresholds. The four dimensional indexes provide feedback on different aspects of lane change performance, enabling reliable assessment and identification of performance deficiencies without requiring excessively complex system architecture.
Solution Approach 2:
The system evaluates lane change performance by monitoring and analyzing changes in key parameters including position coordinates, velocity vectors, acceleration profiles, and inter-vehicle distance margins. By focusing on parameter changes rather than requiring complex system transformations, the evaluation achieves high reliability while maintaining manageable system complexity.
3Productivity
If multi-dimensional performance indexes are quantified for platoon lane change, then comprehensive evaluation is achieved, but the computational requirements and data processing complexity increase
Solution Approach 1:
The system performs preliminary data collection and preprocessing by continuously acquiring motion state parameters (position, velocity, acceleration) from platoon vehicles before and during lane change maneuvers. Evaluation data is prepared and organized in advance, allowing the four dimensional indexes to be calculated efficiently when needed without requiring complex real-time processing of raw sensor data.
Solution Approach 2:
The evaluation system uses copied and simplified representations of vehicle motion data, creating standardized data structures for position, velocity, and acceleration that can be efficiently processed. By working with copied and normalized data rather than raw sensor outputs, the system reduces computational complexity while maintaining evaluation comprehensiveness.
Data Source
AI summary
The present invention discloses an intelligent vehicle platoon lane change performance evaluation method. First, an intelligent vehicle platoon lane change performance test scenario is established; secondly, a three-degree of freedom nonlinear dynamics model is established according to motion characteristics of intelligent vehicles in a platoon lane change process; further, an improved adaptive unscented Kalman filter algorithm is utilized to perform filter estimation on state variables of positions and velocities of platoon vehicles; and finally, based on accurately recursive vehicle motion state parameters, evaluation indexes for platoon lane change performance are proposed and quantified, and an evaluation system for platoon lane change performance is constructed. According to the method proposed in the present invention, the problem of lacking platoon lane change performance quantitative evaluation at present is solved, vehicle motion state parameters can be measured in a high-precision and comprehensive manner, multi-dimensional platoon lane change performance evaluation indexes are quantified and output, and comprehensive, accurate, and reliable scientific quantitative evaluation for platoon lane change performance is achieved.