Lane Information Determination from Vehicle Probe Data
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Solution Overview
Problem
Current traffic reporting systems often suffer from infrequent updates, data entry errors, and delayed data input, leading to inaccurate or untimely reporting of traffic incidents and congestion, which is critical for autonomous vehicles that require real-time, accurate lane information for navigation.
Innovation Solution
A system and method that utilize vehicle probe data from camera and radar sensors to determine lane information by identifying and coding lane markings, predicting the number of lanes, and calculating lane widths, allowing for real-time updates and accurate lane positioning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional traffic reporting systems are used, then data can be collected, but the data is infrequent and contains errors
Solution Approach 1:
The system enables vehicles to automatically collect and transmit their own probe data (location, speed, lane markings) without requiring manual input from traffic reporters. This self-service approach eliminates human error and ensures continuous, real-time updates of traffic conditions, directly resolving the contradiction between data accuracy and update frequency.
Solution Approach 2:
The patent replaces manual mechanical data collection methods with automated electronic sensor systems (cameras, radar, GPS) in vehicles. This substitution enables continuous, real-time data gathering without human intervention, improving both the accuracy and frequency of traffic information updates.
2Reliability
If manual traffic reporting is used, then data entry can be controlled, but delays and errors occur in data input
Solution Approach 1:
Vehicles continuously collect and pre-process traffic data in advance before it is needed for navigation decisions. The system performs preliminary actions by automatically capturing lane marking information, vehicle position, and speed data in real-time, eliminating delays associated with manual data entry and ensuring immediate availability of accurate traffic information.
3Measurement precision
If real-time data collection from multiple vehicles is implemented, then accurate lane information can be determined, but system complexity increases
Solution Approach 1:
The system segments the complex task of determining lane information into independent modules: individual vehicles collect their own probe data independently, each vehicle's sensors process local lane marking information separately, and only the aggregated results are combined to determine overall lane configuration. This segmentation reduces the complexity burden on any single system component while maintaining high measurement precision.
Data Source
AI summary
Systems, methods, and apparatuses are disclosed for determining lane information of a roadway segment from vehicle probe data. Probe data is received from vehicle camera sensors at a road segment, wherein the probe data includes lane marking data on the road segment. Lane markings are identified, to the extent present, for the left and right boundaries of the lane of travel as well as the adjacent lane boundaries to the left and right of the lane of travel. The identified lane markings are coded, wherein solid lane lines, dashed lane lines, and unidentified or non-existing lane lines are differentiated. The coded lane markings are compiled in a database. A number of lanes are predicted at the road segment from the database of coded lane markings.