Collision Avoidance Using Velocity Vector and Time to Collision
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Solution Overview
Problem
Current driver assistance systems fail to provide adequate warnings and collision avoidance for vehicles when a following vehicle attempts to overtake from an adjacent lane or when stationary objects like guardrails are in the vicinity, as they are not within the conventional collision risk determination range.
Innovation Solution
A collision avoidance apparatus and method that calculates a velocity vector of a following vehicle or stationary object using camera and sensor data, determining a collision risk range and time to collision, and outputs warnings or controls the vehicle to prevent collisions by integrating camera modules, non-image sensor modules, and vehicle interior sensors with a controller or domain control unit.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional collision risk determination range is used, then system complexity is reduced, but collision detection capability is insufficient for overtaking vehicles and stationary objects
Solution Approach 1:
The patent extends the collision risk determination from traditional 2D radar detection ranges to 3D spatial coordinates by calculating velocity vectors and time-to-collision for objects in multiple dimensions including stationary objects and overtaking vehicles, thereby improving detection capability without proportionally increasing system complexity
Solution Approach 2:
The collision avoidance system is designed to detect multiple types of objects (moving vehicles, stationary objects, overtaking vehicles) using a unified detection framework that calculates collision risk based on velocity vectors and spatial coordinates, making the system versatile without requiring separate specialized subsystems for each object type
2Measurement precision
If velocity vector calculation is implemented for all detected objects, then collision risk accuracy is improved, but computational load increases
Solution Approach 1:
The system calculates velocity vectors and collision risk parameters selectively for objects that fall within the collision risk determination range, rather than processing all detected objects uniformly. This localized processing approach maintains high accuracy for critical objects while reducing overall computational load
3Reliability
If collision risk range is expanded to include stationary objects, then detection coverage is improved, but false alarm rate increases
Solution Approach 1:
The system uses different parameter thresholds and evaluation criteria for stationary objects versus moving vehicles. For stationary objects, the collision risk is determined based on vehicle trajectory and distance parameters, while for moving vehicles, velocity vectors and relative motion parameters are used, allowing the system to maintain high detection coverage while minimizing false alarms through parameter-based differentiation
Data Source
AI summary
The present disclosure is provided to a collision avoidance apparatus, system and method, configured to calculate a velocity vector of a following vehicle located behind the vehicle in the driving lane in which the vehicle is driving based on at least one of the image data and the sensing data, calculate a collision risk range between the vehicle with the following vehicle based on the driving data and the velocity vector, calculate a time to collision within the collision risk range, and output a warning based on the time to collision. According to the present disclosure, warning and control may be performed according to the collision risk range and the time to collision calculated using the velocity vector of the following vehicle, thereby preventing collision with an adjacent following vehicle.