Intelligent Transport Systems (freight) / Capacity increases in rail by automatisation and digitalisation
The development of intelligent transport systems (ITS) aims to provide better quality, relevant, dynamic and real-time, automatically collected data on the performance of transport systems, including technical, operational and commercial parameters. These data can be processed and used to improve the overall transport system management and performance and can contribute to emissions reduction efforts. Railway digitalisation involves the development of several technologies, which can be classified into four main categories: internet of things (IoT) and wireless communication, cloud computing and data centralisation, big data analytics and automation. ITS adoption among truck fleets increases by 5% (in regions with below-median ITS penetration) or 15% (in regions with above-median ITS penetration) in 2025, growing to a 50% increase in 2050.
Examples of products of rail digitalisation are mobile phone applications providing real-time data to service providers and end users, e-ticketing, digital train control, signal and traffic management optimization and enhanced predictive maintenance strategies. They contribute towards generally improving the level of service of rail freight transport by reducing energy consumption and by increasing safety, reliability, capacity and traffic flows.
The effects on CO2 emissions are not direct and are difficult to quantify. While an increase in rail utilisation leads to an 11% decrease in CO2 emissions by rail in 2050 compared to the baseline level, the effect on total freight emission is marginal (-0.4%). Compared to the base year 2019 level, this scenario sees a 51% increase in total CO2 emissions by 2050. They mostly come from an improved competitiveness of the rail freight alternative, as opposed to road, air or maritime freight alternatives. This improved competitiveness can generate a mode shift to rail freight, which generates less CO2 emissions per tonne-kilometre.
Other CO2 emissions reductions come from the optimisation of the rail freight system management, increasing average load factors and decreasing empty trips and from better traffic management and train control, which can result in reduced energy requirements. Reductions are difficult to quantify as they heavily depend on the local conditions of the trip and on the technologies deployed.
Implementation of ITS for rail freight faces several obstacles. These can be categorised as user acceptance, technology development and policy obstacles. User acceptance involves convincing users to adopt new behaviours associated with these technologies; technology development refers to technological constraints and financing of the implementation of the technologies. Lastly, policy obstacles appear for technologies that are limited by former policy frames not adapted to their development. They include different legal or customs requirements across countries, states or regions for different transport modes, vehicles or goods. Specific administrative processes can also be an obstacle to introducing new solutions. For example, issues at borders due to differences in the checks required on a given cargo or having different vehicle standards in neighbouring countries limit a wide ITS implementation. The harmonisation and development of national and international standards can lift these policy obstacles.
The rail sector is still not as advanced in the adoption of ITS as the road transport sector, where such systems are now widely used by operators and mandated by some shippers as a requirement for supporting commercial operations.
Implementing ITS for rail freight can lead to cost reductions, better user experience, higher rail freight capacity, higher speeds, and improved safety and reliability.
It is estimated to have several economic impacts on the whole rail sector value chain, with rates of returns estimated between 5% and 15% for the European Rail Traffic Management System, for instance.
Implementing ITS for rail also generates opportunities for intermodal transport by easing the connection of rail with other modes with compatible ITS technologies.
The social acceptance of new technologies and the evolution of the job economy of the rail sector can be an issue when developing this measure.
ITF (2021) Transport Climate Action Directory – Intelligent Transport Systems (freight) / Capacity increases in rail by automatisation and digitalisation
https://www.itf-oecd.org/policy/intelligent-transport-systems-freight-ca...
Brebbia, C. et al. (2013) Computers in Railways XIII. WIT Press, https://books.google.fr/books?hl=fr&lr=&id=f7eE3ZaTdMcC&oi=fnd&pg=PA3&ots=a7AsJr1m6u&sig=zorHyLRc5jRWgKeRvHXT-rEyQ0Y&redir_esc=y#v=onepage&q&f=false
EC (2020) ERTMS - European Rail Traffic Management System. European Commission website, European Commission, https://ec.europa.eu/transport/modes/rail/ertms_en
Finger, M., Montero, J. and Serafimova, T. (2020) How to Revitalise Rail Freight With Digitalisation?. European University Institute and Robert Schuman Centre for Advanced Studies Pölicy Brief, https://cadmus.eui.eu/bitstream/handle/1814/65720/PB_2020_01_FSR.pdf?sequence=1&isAllowed=y
Fraga-Lamas, P., Fernandez-Carames, T. and Casted, L. (2017) Towards the Internet of Smart Trains: A Review on Industrial IoT-Connected Railways. Sensors, Volume 17(6), issue: 1457, https://doi.org/10.3390/s17061457
Harris, I. Wang, Y. and Wang, H. (2015) ICT in multimodal transport and technological trends: Unleashing potential for the future. International Journal of Production Economics, Volume 159, page(s): 88-103, https://doi.org/10.1016/j.ijpe.2014.09.005
Pieriegud, J. (2018) Digital transformation of railways. ISBN 978-83-950826-0-3, https://shift2rail.org/wp-content/uploads/2018/04/DIGITAL_TRANSFORMATION_RAILWAYS_2018_web.pdf
Thaduri, A., Galar, D. and Kumar, U. (2015) Railway assets: A potential domain for big data analytics. Procedia Computer Science, Volume 53, page(s): 457-467, https://doi.org/10.1016/j.procs.2015.07.323
Printer-friendly version