Paper Info
Title
Intelligent Urban Mobility: Pedestrian and Bicycle Seamless Navigation
Abstract
Mobility is evolving in urban scenarios and multimodality is the key to a more efficient transportation. In this article we propose a multimodal intelligent navigation system for urban indoor and outdoor environments. Our method is based on wearable sensors mounted on different locations on the human body. The algorithm based on a loose INS/GNSS fusion with magnetometers switches intelligently and seamlessly between the transportation modes walking and riding a bicycle. We also propose an algorithm to cover the still unsolved issue regarding coasting and braking periods for bicycle navigation in GNSS denied scenarios. We have performed an extensive measurement campaign of more than 12 km to test the performance of the proposed algorithms and we have used a Precise Point Positioning solution as ground truth to compute the error. We prove that our method is able to successfully estimate the forward speed of the bicycle during coasting or braking periods. Likewise, we prove that our navigation system switches seamlessly between walking and riding a bicycle and is also able to bridge short GNSS outages.
Year
DOI
Venue
2018
10.1109/IPIN.2018.8533705
2018 International Conference on Indoor Positioning and Indoor Navigation (IPIN)
Keywords
Field
DocType
Magnetometer,coasting,transition,outdoors,indoors,multimodal transportation,ubiquitous navigation
Computer vision,Multimodality,Pedestrian,Wearable computer,Navigation system,Real-time computing,Ground truth,GNSS applications,Artificial intelligence,Engineering,Precise Point Positioning
Conference
ISSN
ISBN
Citations 
2162-7347
978-1-5386-5636-5
0
PageRank 
References 
Authors
0.34
4
3
Name
Order
Citations
PageRank
Estefania Munoz Diaz1527.88
Fabian de Ponte Müller2637.74
Eduardo Perez Gonzalez300.34