In this paper, we document design and a prototype implementation of a computational method for an onboard prediction of a breaking distance for a city rail vehicle|a tram. The method is based on an onboard simulation of tram braking dynamics. Inputs to this simulation are the data from a digital map and the estimated (current) position and speed, which are, in turn, estimated by combining a mathematical model of dynamics of a tram with the measurements from a GNSS/GPS receiver, an accelerometer and the data from a digital map. Experiments with real trams verify the functionality, but reliable identification of the key physical parameters turns out critically important. The proposed method provides the core functionality for a collision avoidance system based on vehicle-to-vehicle (V2V) communication.
@article{arxiv.2001.10231,
title = {Onboard Model-based Prediction of Tram Braking Distance},
author = {Loi Do and Ivo Herman and Zdeněk Hurák},
journal= {arXiv preprint arXiv:2001.10231},
year = {2020}
}