Deployment of Autonomous Trains in Rail Transportation: Current Trends and Existing Challenges

Prashant Singh, Maxim A. Dulebenets, Junayed Pasha, Ernesto D.R.Santibanez Gonzalez, Yui Yip Lau, Raphael Kampmann

Research output: Contribution to journalReview articlepeer-review

75 Citations (Scopus)

Abstract

Automation is expected to effectively address the growing demand for passenger and freight transportation, safety issues, human errors, and increasing congestion. The growth of autonomous vehicles using the state-of-the-art connected vehicle technologies has paved the way for the development of passenger and freight autonomous trains (ATs), also known as driverless trains. ATs are fully automated trains that are centrally controlled using advanced communication and internet technologies, such as high-speed internet (5G) technology, Internet of Things, dedicated short range communications, digital video detection cameras, and artificial intelligence-based methods. The current study focuses on a detailed up-to-date review of the existing trends, technologies, advancements, and challenges in the deployment of ATs with a full automation level in rail transportation. The basic AT features along with the key technologies that are instrumental for the AT deployment and operations are discussed in detail. Furthermore, a comprehensive evaluation of the state-of-the-art research efforts is performed as well with a specific emphasis on the issues associated with the AT deployment, user perception and outlook for ATs, innovative concepts and models that could be used for the AT design, and the AT operations at highway-rail grade crossings. Based on the conducted review, this study determines the main advantages and challenges from the AT deployment. The identified challenges have to be collaboratively addressed by the relevant stakeholders, including railroad companies, researchers, and government representatives, to facilitate the AT development and deployment considering the perspectives of future users and without affecting the safety level.

Original languageEnglish
Article number9462161
Pages (from-to)91427-91461
Number of pages35
JournalIEEE Access
Volume9
DOIs
Publication statusPublished - 2021

Keywords

  • Autonomous trains
  • automation challenges
  • automation trends
  • autonomous vehicles
  • connected vehicles
  • driverless trains

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