Road Survey Segment Boundary Detection for Single-Operator Acquisition
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Solution Overview
Problem
Existing road surveying methods require multiple human operators, leading to operational complexity, reduced data quality, and safety concerns due to the multitude of tasks performed by different operators.
Innovation Solution
A system and method for automatic determination of start and end points for road segments using onboard sensors, allowing a single operator to drive the vehicle while the system autonomously initiates and concludes data acquisition based on trigger events such as distance and heading thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If multiple human operators are used to perform road surveying tasks, then various non-driving tasks (navigation, data quality verification, marking segment boundaries) can be performed, but operational complexity increases and data quality decreases
Solution Approach 1:
The system automatically determines start and end points of road segments using onboard sensors and GPS data, eliminating the need for manual marking by operators. The system serves itself by autonomously processing survey data and identifying segment boundaries based on predefined criteria, thereby reducing operational complexity while maintaining data quality
Solution Approach 2:
Manual operations by human operators are replaced with an automated electronic system that uses GPS coordinates, onboard sensors, and computer algorithms to perform navigation, data verification, and segment boundary identification. This substitution of mechanical/manual processes with electronic automation resolves the contradiction between ease of operation and device complexity
2Productivity
If multiple human operators are used to perform road surveying tasks, then various non-driving tasks can be performed, but the number of tasks required detracts from data quality
Solution Approach 1:
The system continuously monitors GPS position data and compares it against stored road segment boundary coordinates to automatically identify start and end points. This feedback mechanism ensures precise data collection by constantly verifying the vehicle's position and automatically marking segment boundaries with high measurement precision, eliminating human error while maintaining productivity
3Reliability
If multiple human operators are used to perform road surveying tasks, then various non-driving tasks can be performed, but factors such as road safety or consistent data acquisition are influenced disadvantageously
Solution Approach 1:
The automated system independently handles data acquisition, position tracking, and segment boundary identification without requiring multiple operators. This self-service capability ensures consistent and reliable data collection while simplifying the operational structure, thereby improving reliability without increasing device complexity
Solution Approach 2:
The system maintains continuous data acquisition throughout the survey process, automatically recording position and sensor data without interruption or manual intervention. This continuous operation ensures consistent and reliable data collection, eliminating gaps or inconsistencies that may occur with manual operations by multiple operators
Data Source
AI summary
Described are systems and techniques for road surveying. Information indicative of a sequence of target road sections each comprising one or more road segments can be used to configure a vehicle to perform a road survey by traveling each target road section of the sequence. Data acquisition can be started from onboard sensors of the vehicle based on detecting a first trigger event where a current position of the vehicle is within a configured threshold distance from a first target road section of the sequence. Respective road survey data can be obtained for each road segment in each target road section of the sequence, and can comprise a subset of acquired data obtained from the onboard sensors between a corresponding start and end point automatically determined for the respective road segment based on detecting the occurrence of trigger events corresponding to the current vehicle position and/or heading.