Vehicle Gap Measurement Using Radar-GPS Lead Vehicle Tracking
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing vehicle platooning systems face challenges in reliably identifying and tracking the lead vehicle using radar due to ambiguous radar reflections and constantly changing conditions, particularly in scenarios where the lead vehicle is not directly within the radar's field of view or has varying effective lengths.
Innovation Solution
A method involving a bounding box around the estimated position of the lead vehicle, relative velocity filtering, and clustering algorithms is used to identify and track the lead vehicle, utilizing radar data and GPS information to maintain a desired gap between vehicles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If radar systems are used to determine distance between vehicles in platooning, then distance measurement capability is provided, but reliable identification and tracking of the lead vehicle becomes difficult due to ambiguous radar reflections and changing conditions
Solution Approach 1:
The patent introduces an intermediary processing system that receives radar reflections and GPS data, then processes this information through clustering algorithms and bounding box analysis to reliably identify the lead vehicle. This intermediary layer transforms ambiguous raw radar data into reliable vehicle identification by filtering and correlating multiple data sources.
Solution Approach 2:
The system combines multiple independent mechanisms (radar, GPS, clustering algorithms, bounding box analysis) into a universal identification system. This multi-functional approach allows the system to handle various challenging conditions (varying effective lengths, vehicles outside direct field of view) by leveraging the complementary strengths of different sensing and processing methods.
2Productivity
If the lead vehicle is not directly within the radar's field of view, then convoying can continue, but accurate tracking and identification become more difficult
Solution Approach 1:
The system performs preliminary actions by establishing a bounding box around the estimated position of the lead vehicle before direct radar detection is available. This predictive approach allows the system to maintain tracking continuity by anticipating where the lead vehicle should be based on previous positions and motion patterns, then confirming detection when the vehicle enters the predicted region.
Solution Approach 2:
The system uses feedback from GPS data and previous radar measurements to continuously update the estimated position and bounding box of the lead vehicle. This feedback loop allows the system to maintain accurate tracking even when the lead vehicle temporarily exits the direct radar field of view, by using the updated estimate to guide subsequent detection efforts.
3Adaptability or versatility
If the lead vehicle has varying effective lengths, then real-world conditions are accommodated, but consistent identification and gap maintenance become more challenging
Solution Approach 1:
The system dynamically adapts to varying lead vehicle effective lengths by using clustering algorithms that analyze the distribution of radar reflection points. Instead of assuming a fixed vehicle length, the system identifies clusters of reflections that correspond to the actual vehicle boundaries in each measurement cycle, allowing it to accurately identify the lead vehicle regardless of its current effective length.
Solution Approach 2:
The system changes its identification parameters based on the observed radar reflection patterns. By analyzing the spatial distribution and intensity of reflections, the system adjusts its understanding of the lead vehicle's effective length and position, maintaining accurate identification even as the vehicle's effective length varies due to different loading conditions, attachments, or environmental factors.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Effectively identifies and tracks the lead vehicle under changing conditions, ensuring safe and efficient vehicle platooning by maintaining a consistent gap, even when the lead vehicle is not directly within the radar's field of view.
Implementation Method 1
A challenge that occurs when using radar in platooning type applications is that the partner vehicle must be reliably identified from a potentially ambiguous set of radar reflections
Implementation Method 2
transmitting absolute or relative position data between vehicles (e.g., GPS or other GNSS data)
Data Source
AI summary
A variety of methods, controllers and algorithms are described for identifying the back of a particular vehicle (e.g., a platoon partner) in a set of distance measurement scenes and/or for tracking the back of such a vehicle. The described techniques can be used in conjunction with a variety of different distance measuring technologies including radar, LIDAR, camera based distance measuring units and others. The described approaches are well suited for use in vehicle platooning and/or vehicle convoying systems including tractor-trailer truck platooning applications. In another aspect, technique are described for fusing sensor data obtained from different vehicles for use in the at least partial automatic control of a particular vehicle. The described techniques are well suited for use in conjunction with a variety of different vehicle control applications including platooning, convoying and other connected driving applications including tractor-trailer truck platooning applications.