Electric scooters (e-scooters) are proliferating rapidly as an inexpensive mode of transportation. GPS equipped smartphones are used to guide riders from points A to B, but GPS is known to have hundreds of meters of error in areas where the line of sight to navigation satellites is fully or partially obscured. To address this problem, we present ScootLoc, which enables precise e-scooter localization, by leveraging physical characteristics of sidewalk ramps, to correct for GPS error. We show that e-scooters equipped with a gyroscope and an accelerometer are able to uniquely identify sidewalk ramps and match the ramp to its physical location, thereby augmenting noisy GPS based navigation systems. We implement ScootLoc and present a preliminary evaluation on a route containing ten ramps, achieving 97% classification accuracy.
|Title of host publication||MobiSys 2019 - Proceedings of the 17th Annual International Conference on Mobile Systems, Applications, and Services|
|Publisher||Association for Computing Machinery, Inc|
|Number of pages||2|
|Publication status||Published - 2019 Jun 12|
|Event||17th ACM International Conference on Mobile Systems, Applications, and Services, MobiSys 2019 - Seoul, Korea, Republic of|
Duration: 2019 Jun 17 → 2019 Jun 21
|Name||MobiSys 2019 - Proceedings of the 17th Annual International Conference on Mobile Systems, Applications, and Services|
|Conference||17th ACM International Conference on Mobile Systems, Applications, and Services, MobiSys 2019|
|Country/Territory||Korea, Republic of|
|Period||19/6/17 → 19/6/21|
Bibliographical notePublisher Copyright:
© 2019 Copyright held by the owner/author(s).
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Computer Networks and Communications