Citation

Boufidis N, Salanova Grau JM, Tzenos P, Aifandopoulou G. Transp. Res. Proc. 2020; 47: 346-352.

Copyright

(Copyright © 2020, Elsevier Publications)

DOI

10.1016/j.trpro.2020.03.108

PMID

unavailable

Abstract

While cooperative services have been almost fully deployed in the road sector and are already being implemented in various cities in Europe as a pre-requisite for the introduction of autonomous vehicles, few attempts have been made in the same direction for the rail sector. This study proposes a system that aims to improve safety and minimize risk in the meeting point between road and rail, known as level crossings, by monitoring the location of floating road vehicles via a mobile device application. A neural network predictive model for estimating time of arrival of trains is also utilized. The safety system has been implemented and tested under real life conditions in the city of Thessaloniki, Greece.

Language: en

Keywords

estimated time of arrival; multimodal cooperative service; neural network