Lane-Change Collision Detection Across Non-Adjacent Lanes
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Solution Overview
Problem
Conventional collision avoidance systems for vehicles are ineffective in monitoring and providing feedback for potential collisions with vehicles not in adjacent lanes, leading to increased collision risks on multi-lane roads.
Innovation Solution
A computer-implemented method that receives sensor data from various sources, generates lane change data values for vehicles relative to a lane position, determines collision risk values, and generates output signals to notify drivers of potential collisions, including those in non-adjacent lanes by analyzing head positions, eye gaze directions, and other contextual information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional collision avoidance systems only monitor adjacent lanes, then the system complexity remains low, but the collision detection coverage is insufficient
Solution Approach 1:
The patent segments the monitoring task by dividing the road into multiple lane zones (adjacent lanes and near lanes) and assigns different monitoring strategies to each zone. Sensors selectively monitor adjacent lanes with high frequency while monitoring near lanes with lower frequency, allowing comprehensive coverage without uniformly high system complexity
Solution Approach 2:
The system applies partial monitoring action to near lanes rather than full monitoring. By detecting vehicles in near lanes only when they attempt lane changes or when proximity thresholds are met, the system achieves adequate detection coverage without the complexity of continuous full-spectrum monitoring of all lanes
2Reliability
If the system monitors only adjacent lanes, then the processing speed remains high, but the area covered for collision detection is limited
Solution Approach 1:
The patent extends monitoring from the traditional two-dimensional adjacent lane space to include the third dimension of near lanes. By incorporating vehicles from multiple lane positions into the collision risk assessment, the system achieves three-dimensional spatial awareness without proportionally increasing processing burden
3Measurement precision
If sensor data from multiple lanes is analyzed, then the collision notification accuracy improves, but the data processing time increases
Solution Approach 1:
The system performs preliminary filtering of sensor data by pre-identifying vehicles in near lanes that pose potential collision risks based on their position and movement patterns. This preliminary action allows the main collision assessment algorithm to focus only on relevant vehicles, maintaining high accuracy while reducing overall processing time
Data Source
AI summary
Embodiments of the present disclosure set forth a computer-implemented method comprising receiving, from at least one sensor, sensor data associated with an environment, generating, based on the sensor data, a set of lane change data values associated with positions of at least two vehicles relative to a first lane position in the environment, determining, based on the set of lane change data values, a collision risk value associated with the at least two vehicles attempting to occupy the first lane position, and generating, based on the collision risk value, an output signal to a first vehicle included in the at least two vehicles.