Introducing Automated Obstacle Detection to British Level Crossings

Matthew Dent*, Marin Marinov

*Corresponding author for this work

Research output: Chapter in Book/Published conference outputChapter

Abstract

This paper discusses the implementation of automated obstacle detection to British level crossings to improve safety and efficiency, reduce costs and analyse how successful this could be. There are over 6000 level crossings in Britain, and they are the largest single risk to the railways; one method to improve their safety is by introducing automated obstacle detection. Over the last ten years, there have been, on average, nine deaths a year at level crossings (Rail Safety and Standards Board in Annual safety performance report. Rail Safety and Standards Board Limited, SL, 2016) (excluding suicides), making them a high priority for Network Rail to improve. Obstacle detection would not just help improve the safety of level crossings, but it could also reduce the costs associated with level crossing signallers and operators and would lower the waiting times for road vehicles and pedestrians. With research also being done into the future possibility of introducing autonomous trains to the British railways, the combination of this and the obstacle detection system proposed could see a large improvement in safety across the level crossings.

Original languageEnglish
Title of host publicationSustainable Rail Transport
Subtitle of host publication Proceedings of RailNewcastle 2017
EditorsAnna Fraszczyk, Marin Marinov
PublisherSpringer
Chapter3
Pages37-80
Number of pages44
ISBN (Electronic)978-3-319-78544-8
ISBN (Print)978-3-319-78543-1
DOIs
Publication statusPublished - 2019
EventRailExchange 2017 - Newcastle, United Kingdom
Duration: 4 Oct 20176 Oct 2017

Publication series

NameLecture Notes in Mobility
ISSN (Print)2196-5544
ISSN (Electronic)2196-5552

Conference

ConferenceRailExchange 2017
Country/TerritoryUnited Kingdom
CityNewcastle
Period4/10/176/10/17

Bibliographical note

This accepted manuscript is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).
The Version of record can be found here: https://link.springer.com/chapter/10.1007/978-3-319-78544-8_3

Keywords

  • Automated
  • Crossing
  • Detection
  • Level
  • Obstacle

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