TY - JOUR
T1 - Deployment of Autonomous Trains in Rail Transportation
T2 - Current Trends and Existing Challenges
AU - Singh, Prashant
AU - Dulebenets, Maxim A.
AU - Pasha, Junayed
AU - Gonzalez, Ernesto D.R.Santibanez
AU - Lau, Yui Yip
AU - Kampmann, Raphael
N1 - Funding Information:
This work was supported in part by the Florida Department of Transportation under Grant BDV30-977-26 and Grant BDV30-977-33.
Publisher Copyright:
© 2013 IEEE.
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
KW - Autonomous trains
KW - automation challenges
KW - automation trends
KW - autonomous vehicles
KW - connected vehicles
KW - driverless trains
UR - http://www.scopus.com/inward/record.url?scp=85112254672&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/5e02f43f-4d9e-3935-a132-2baf878b7230/
U2 - 10.1109/ACCESS.2021.3091550
DO - 10.1109/ACCESS.2021.3091550
M3 - Review article
AN - SCOPUS:85112254672
SN - 2169-3536
VL - 9
SP - 91427
EP - 91461
JO - IEEE Access
JF - IEEE Access
M1 - 9462161
ER -