Machine-assisted map editing
Name
maid.pdf
Description
Accepted version
Size
13.71 MB
Format
Adobe PDF
Checksum (MD5)
e6741c042cdae20c8061baf8c3721e7f
Author(s)
Bastani, Favyen
He, Songtao
Abbar, Sofiane
Alizadeh, Mohammad
Balakrishnan, Hari
Chawla, Sanjay
Madden, Sam
Date Issued
November 6, 2018
Publisher
ACM
Citation
Bastani, Favyen, He, Songtao, Abbar, Sofiane, Alizadeh, Mohammad, Balakrishnan, Hari et al. 2018. "Machine-assisted map editing."
Version
Author's final manuscript
Abstract
© 2018 held by the owner/author(s). Publication rights licensed to ACM. 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 trajectories have been proposed to improve coverage of road maps. However, because of high error rates, these systems have not been adopted by mapping communities. We propose machine-assisted map editing, where automatic map inference is integrated into existing, human-centric map editing workflows. To realize this, we build Machine-Assisted iD (MAiD), where we extend the web-based OpenStreetMap editor, iD, with machine-assistance functionality. We complement MAiD with a novel approach for inferring road topology from aerial imagery that combines the speed of prior segmentation approaches with the accuracy of prior iterative graph construction methods. We design MAiD to tackle the addition of major, arterial roads in regions where existing maps have poor coverage, and the incremental improvement of coverage in regions where major roads are already mapped. We conduct two user studies and find that, when participants are given a fixed time to map roads, they are able to add as much as 3.5x more roads with MAiD.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1145/3274895.3274927
