Intelligent Urban Mobility: Pedestrian and Bicycle Seamless Navigation

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.