Collision Avoidance via Mutual Trajectory Influence Estimation
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Solution Overview
Problem
Existing collision avoidance systems fail to effectively reduce the risk of unsafe maneuvers by not adequately considering the influence of future trajectories of other external objects on the road, leading to potential conflicts and increased risk during lane changes.
Innovation Solution
A method and system that estimate future trajectories of external objects while accounting for the traffic situation, using a lane exit control block, future conflict estimator control block, and lane change prevention unit to apply torque against the driver's steering input, thereby preventing unsafe lane changes and maintaining driver control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the future trajectory of an object is estimated based solely on position and velocity without considering influence from other objects, then the estimation is simple and fast, but the accuracy is reduced because the trajectory may drastically change due to traffic situation
Solution Approach 1:
The system performs preliminary estimation of future trajectories for all detected objects considering their mutual influences before making collision avoidance decisions. This preliminary action accounts for how objects may alter their paths due to other objects in the traffic situation, providing more accurate trajectory predictions that incorporate traffic dynamics without requiring complex real-time adjustments during the decision-making process
Solution Approach 2:
The system uses feedback from detected objects' positions, velocities, and inferred behaviors to continuously update trajectory estimates. By monitoring the traffic situation and how objects respond to each other, the system refines its predictions of future paths, allowing accurate trajectory estimation that adapts to changing traffic conditions while maintaining computational efficiency
2Reliability
If the control system intercepts the host vehicle control by using the best predicted action, then collision risk is reduced, but the driver loses control and the system requires legal acceptance
Solution Approach 1:
The system applies preliminary anti-action by generating warning signals to alert the driver of potential collision risks before the driver takes action. This approach prevents collisions by preparing the driver in advance with information about dangerous situations, allowing the driver to maintain control while the system provides protective warnings that enable timely driver response
Solution Approach 2:
The system acts as an intermediary between the traffic situation and the driver by processing sensor data, estimating trajectories, and presenting processed information through warnings or visual displays. This intermediary role filters and interprets complex traffic dynamics for the driver, maintaining driver control while providing reliable collision avoidance support through informed decision-making assistance
Data Source
AI summary
A method for collision avoidance for a host vehicle includes the following steps; receiving input data relating to a set of objects external to the host vehicle, wherein an object position (r,Φ), and an object velocity ({dot over (r)}) are associated with each object by a sensor system arranged on the host vehicle, then estimating future trajectories of each external object, while considering influence by the future trajectories of the other external objects.