Attached Object Tracking for Accurate Vehicle Boundary Control
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing vehicle control systems face challenges in accurately tracking and controlling vehicles when objects are attached to the rear of a second vehicle, leading to difficulties in determining the vehicle's rear boundary and potentially causing inadvertent braking or acceleration.
Innovation Solution
A method and system that utilize a combination of radar, camera, and lidar sensors to track attached objects on a second vehicle. The system determines if an object corresponds to an attached object type, calculates its region based on distance, and checks if its velocity matches the vehicle's velocity within a threshold, thereby accurately determining if the object is attached and adjusting the vehicle's control accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the vehicle control system tracks objects using sensors to determine vehicle boundaries, then the basic tracking function is achieved, but the system cannot accurately distinguish attached objects from the second vehicle itself, leading to incorrect vehicle boundary determination
Solution Approach 1:
The system segments the detection process into multiple stages: initial object detection, attached object region identification, velocity-based attachment determination, and final vehicle boundary calculation. This segmentation allows the system to separately analyze and identify attached objects before determining the complete vehicle boundary, resolving the inability to distinguish attached objects from the main vehicle.
Solution Approach 2:
The system introduces an intermediary attached object region and velocity threshold mechanism between raw sensor data and final vehicle boundary determination. By using velocity comparison as an intermediary criterion, the system can identify which detected objects are attached to the second vehicle, preventing loss of critical attachment information.
2Reliability
If the system includes all detected objects within a fixed region around the second vehicle as part of the vehicle boundary, then attached objects are included, but the system also incorrectly includes non-attached objects, leading to inaccurate control decisions
Solution Approach 1:
The system dynamically adjusts the vehicle boundary based on real-time velocity information. Instead of using a static fixed region, the boundary is continuously updated by comparing object velocities with the second vehicle's velocity. Objects whose velocities fall within the threshold are dynamically included in the boundary, while others are excluded, maintaining accuracy without excessive complexity.
Solution Approach 2:
The system changes the parameter used for boundary determination from purely spatial (fixed region) to a combination of spatial and temporal parameters (position plus velocity). By incorporating velocity as an additional parameter and using a velocity threshold, the system accurately distinguishes attached objects from non-attached objects, improving reliability while managing complexity through a clear decision criterion.
3Measurement precision
If the system uses multiple sensors and velocity threshold checks to accurately identify attached objects, then the identification accuracy is improved, but the processing time and computational load increase
Solution Approach 1:
The system performs preliminary action by pre-defining the attached object region and velocity threshold criteria before actual object detection. This preparation allows the system to quickly filter and evaluate detected objects against predetermined standards, reducing real-time processing time while maintaining high detection accuracy through the use of radar, camera, and lidar sensors.
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
This solution enhances the accuracy of vehicle control by correctly identifying attached objects and adjusting the vehicle's control systems, such as automatic braking and longitudinal control, to prevent inadvertent braking or acceleration, thereby improving safety and driving experience.
Implementation Method 1
receiving, by a processor, sensor data of an environment associated with the vehicle observed by at least one radar system associated with the vehicle
Implementation Method 2
at least one of a camera and a lidar associated with the vehicle
Implementation Method 3
at least one of a camera and a lidar associated with the vehicle
Data Source
AI summary
A method and system for tracking attached objects for controlling a vehicle. The method includes receiving, by a processor, sensor data of an environment associated with the vehicle that includes an object. The method includes determining, based on the sensor data, whether the object corresponds to an attached object type, and determining whether the sensor data includes a second vehicle. The method includes determining an attached object region associated with the second vehicle based on a distance between the second vehicle and the vehicle, and determining whether a position of the object is within the attached object region. The method includes determining whether a difference between a velocity of the object and a vehicle velocity of the vehicle is within a velocity threshold based on the distance. The method includes determining that the object is an attached object and controlling the vehicle based on the determining.