Road Graph Generator: Mapping roads at construction sites from GPS data
We propose a new method for inferring roads from GPS trajectories to map construction sites. This task presents a unique challenge due to the erratic and non-standard movement patterns of construction machinery, which significantly diverge from typical vehicular traffic on established roads. Our proposed method first identifies intersections in the road network that serve as critical decision points, and then connects them with edges to produce a graph, which can subsequently be used for planning and task-allocation. We demonstrate the approach by mapping roads at a real-life construction site in Norway. The method is validated on four increasingly complex segments of the map. In our tests, the method achieved perfect accuracy in detecting intersections and inferring roads in data with no or low noise, while its performance was reduced in areas with significant noise and consistently missing GPS updates.
Code (1)
Methods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Machine-Assisted Map Editing
Mapping road networks today is labor-intensive. As a result, road maps have poor coverage outside urban centers in many countries. Systems to automatically infer road network graphs from aerial imagery and GPS trajectori…
graph constructionRoad Network Representation Learning: A Dual Graph based Approach
Road network is a critical infrastructure powering many applications including transportation, mobility and logistics in real life. To leverage the input of a road network across these different applications, it is neces…
Graph Neural NetworkGraph Reconstructionhyperedge classificationRepresentation LearningCrowd-Sourced Road Quality Mapping in the Developing World
Road networks are among the most essential components of a country's infrastructure. By facilitating the movement and exchange of goods, people, and ideas, they support economic and cultural activity both within and acro…
Road Mapping in Low Data Environments with OpenStreetMap
Roads are among the most essential components of any country's infrastructure. By facilitating the movement and exchange of people, ideas, and goods, they support economic and cultural activity both within and across loc…
General ClassificationAutomated Digital Twin Construction for Highway Scenarios Using LiDAR Point Clouds and OpenStreetMap
Accurate road environment modeling is fundamental to the simulation and validation of automated driving systems. However, constructing road maps in standardized formats such as ASAM OpenDRIVE from real-world sensor data …
Point Clouds