Traffic Stream Sensing for Lateral Positioning Without Clear Lane Lines
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Solution Overview
Problem
Current intelligent driving systems face challenges in accurately identifying lane lines due to factors like congested traffic, low vehicle speed, and unclear lane lines, which affect vehicle lateral positioning and target travel path generation.
Innovation Solution
A method for determining traffic stream information by grouping target vehicles based on motion and state information, calculating fitting weights, and generating current traffic stream information through fitting, which can replace lane line sensing for vehicle lateral positioning and control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If lane line recognition is used for vehicle lateral positioning, then the system can provide positioning information, but under congested traffic conditions with low speed and dense traffic stream, the recognition accuracy deteriorates
Solution Approach 1:
The patent introduces traffic stream information as an intermediary element to bridge the gap between vehicle positioning needs and lane line recognition limitations. By detecting and analyzing the motion patterns of surrounding vehicles (traffic stream), the system obtains alternative positioning references that are reliable even when lane lines are unclear or congested
Solution Approach 2:
The patent replaces the optical/mechanical lane line recognition system with a computational approach based on traffic stream analysis. Instead of relying on visual detection of road markings, the system uses mathematical modeling and fitting algorithms to infer lane boundaries from the collective motion information of multiple vehicles
2Loss of information
If forward camera is used for lane line detection, then the system can identify lane markings, but the sensing distance and field of view are limited under congested conditions
Solution Approach 1:
The patent merges information from multiple vehicles' sensors to create a composite traffic stream model. By combining data from several vehicles moving in the same lane, the system effectively expands the sensing coverage beyond what a single camera can provide, inferring lane boundaries from the aggregated positional information of multiple vehicles
3Measurement precision
If lane line recognition is used for target travel path generation, then the system can determine driving paths, but accuracy deteriorates when lane lines are unclear or insufficiently cleaned
Solution Approach 1:
The patent creates a virtual copy of lane line information through traffic stream modeling. Instead of directly detecting physical lane markings, the system generates a digital representation of lane boundaries by fitting mathematical models to the observed positions and trajectories of vehicles in the traffic stream, effectively copying the lane structure from vehicle behavior patterns
Data Source
AI summary
A method and a device for determining traffic stream information, electronic equipment and a storage medium are provided. The method includes: grouping each of target vehicles based on motion information of a host vehicle and state information of one or more of the target vehicles to obtain grouping information; determining a fitting weight for each of the target vehicles based on the state information and the grouping information for each of the target vehicles; and generating, by the fitting, one or more pieces of current traffic stream information based on the motion information of the host vehicle, the state information of each of the target vehicles, the fitting weights and the grouping information of each of the target vehicles. The method can generate the current traffic stream information to achieve the sensing of traffic stream.