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Safety
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Railway Safety
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Railway Safety

A special issue of Safety (ISSN 2313-576X).

Deadline for manuscript submissions: closed (30 September 2019) | Viewed by 8498

Special Issue Editors

Prof. Dr. Jörn Pachl

E-Mail Website
Guest Editor
Institute of Railway Systems Engineering and Traffic Safety, Technische Universität Braunschweig, 38106 Braunschweig, Germany
Interests: railway operation; railway signaling; railway safeworking rules; human factors
Special Issues, Collections and Topics in MDPI journals
Dr. Birgit Milius

E-Mail Website
Guest Editor
Siemens Mobility GmbH, Braunschweig, Germany
Interests: railway; traffic safety; safety management

Special Issue Information

Dear Colleagues,

The railway is one of the safest modes of transportation. The aim of this special edition is to address new challenges for railway safety. These challenges are mainly caused by the introduction of digital technologies. One challenge is how to handle risk and safety analysis for the approval of new digital systems. Another challenge is that for the safe operation of a highly automated system,  appropriate degraded mode strategies are crucial. This is closely related to operating and safeworking rules that have a significant impact on the system's safety. A key element for railway safety is human factors. In a highly automated system, human operators have to maintain sufficient situational awareness to prevent them from misjudging a situation when taking action under staff resposibility in failure mode. While railway accidents are a rather common occurence, appropriate methods for accident investigation to detect weak parts of the system are also an important part of safety management. A common frame around all this is the corporate safety culture of the railway companies. Researchers may submit paper dealing with any of these aspects.

Prof. Dr. Jörn Pachl
Prof. Dr. Birgit Milius
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Safety is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • railways
  • signalling
  • interlocking
  • operating rules
  • safeworking rules 
  • human factors 
  • situation awareness 
  • risk analysis 
  • safety assessment 
  • accident investigation 
  • safety culture

Published Papers (1 paper)

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Research

22 pages, 25310 KiB  
Article
A Novel Method of Near-Miss Event Detection with Software Defined RADAR in Improving Railyard Safety
by Subharthi Banerjee, Jose Santos, Michael Hempel, Pejman Ghasemzadeh and Hamid Sharif
Safety 2019, 5(3), 55; https://0-doi-org.brum.beds.ac.uk/10.3390/safety5030055 - 14 Aug 2019
Cited by 15 | Viewed by 7539
Abstract
Railyards are one of the most challenging and complex workplace environments in any industry. Railyard workers are constantly surrounded by dangerous moving objects, in a noisy environment where distractions can easily result in accidents or casualties. Throughout the years, yards have been contributing [...] Read more.
Railyards are one of the most challenging and complex workplace environments in any industry. Railyard workers are constantly surrounded by dangerous moving objects, in a noisy environment where distractions can easily result in accidents or casualties. Throughout the years, yards have been contributing 20–30% of the total accidents that happen in railroads. Monitoring the railyard workspace to keep personnel safe from falls, slips, being struck by large object, etc. and preventing fatal accidents can be particularly challenging due to the sheer number of factors involved, such as the need to protect a large geographical space, the inherent dynamicity of the situation workers find themselves in, the presence of heavy rolling stock, blind spots, uneven surfaces and a plethora of trip hazards, just to name a few. Since workers spend the majority of time outdoors, weather conditions also play an important role, i.e., snow, fog, rain, etc. Conventional sensor deployments in yards thus fail to consistently monitor this workspace. In this paper, the authors have identified these challenges and addressed them with a novel detection method using a multi-sensor approach. They have also proposed novel algorithms to detect, classify and remotely monitor Employees-on-Duty (EoDs) without hindering real-time decision-making of the EoD. In the proposed solution, the authors have used a fast spherical-to-rectilinear transform algorithm on fish-eye images to monitor a wide area and to address blindspots in visual monitoring, and employed Software-Defined RADAR (SDRADAR) to address the low-visibility problem. The sensors manage to monitor the workspace for 100 m with blind detection and classification. These algorithms have successfully maintained real-time processing delay of ≤0.1 s between consecutive frames for both SDRADAR and visual processing. Full article
(This article belongs to the Special Issue Railway Safety)
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