Rail Accident

Primary reference(s)

United Nations, European Union and the International Transport Forum at the OECD, 2019. Glossary for transport statistics. 5th Edition. Accessed 28 January 2025

Annotations

Key relevant UN convention / multilateral treaty

Not identified.

Drivers

Collisions, derailments, level crossing accidents, accidents to persons caused by rolling stock in motion, and fires in rolling stock (United Nations, European Union and the International Transport Forum at the OECD, 2019). Natural hazards significantly exacerbate the challenges faced by already stressed railway infrastructure, primarily due to overloaded networks. Floods, heavy rainfall, earthquakes, cyclones, heavy snowfall, low visibility due to fog and landslides are major causes of rail accidents. For example, cyclones can damage trees along tracks, disrupting transport, while powerful cyclones may also damage bridges (Joshi et al., 2024).

The intensification of commuting flows along rail corridors creates varying safety challenges based on industry-specific travel patterns. Research shows that commuting inefficiency varies significantly across economic sectors (Ling et al., 2024), which can lead to temporal congestion patterns around rail infrastructure. These patterns, when combined with increasing urbanization along rail corridors, create distinct accident vulnerability profiles that require targeted mitigation strategies.

Impacts

Railway accidents have significant impacts, including potential fatalities and injuries, extensive disruptions to train services, and damage to railway infrastructure and the environment (Hong et al. 2023). Accidents can also lead to psychological impacts on survivors (Maltais et al, 2022).  and economic consequences for the rail industry and affected communities.  

Railway accidents involving chemical, nuclear, and explosive cargo are a serious concern due to the potential for widespread harm and environmental damage. Several incidents highlight the risks associated with transporting such materials by rail, including derailments, collisions, and explosions. As an example, on February 3, 2023, a Norfolk Southern freight train carrying hazardous materials from Madison, Illinois, to Conway, Pennsylvania, derailed in East Palestine, Ohio. Of the 150 rail cars, 38 derailed; 11 of those 38 cars contained hazardous chemicals that derailed, igniting and fuelling fires that damaged 12 other non-derailed cars (Welsh et al, 2024) 

As an example of a railway accident with significant impacts, Maltais et al (2023) reported that on the night of July 6, 2013, a train comprised of 63 tank cars carrying crude oil derailed in the downtown area of Lac-Mégantici (QC, Canada). The derailment triggered explosions, burning a large portion of the city centre, killing 47 people and destroying 66 homes and 44 businesses. This event also forced the evacuation of over 2000 people, of a population of 6000 inhabitants. The entire population experienced the impact of this technological disaster, caused by a lack of railway track maintenance and human neglect, among others (Maltais et al, 2022).

Multi-hazard context

The figure below summarises common interactions between rail accidents and other hazards. This information should be used with caution and not be solely relied upon in Disaster Risk Management, particularly as some interactions may not have been included. Note that hazardous events occurring together or locally in space or time may not necessarily cause, amplify, or be otherwise related to each other. Specific examples of multi-hazard context can be found in the ‘Hazard drivers’ and ‘Impacts’ sections above.

Multi-hazard diagram

Risk Management

The Railway Safety Directive was published with the purpose of establishing and improving rail safety and security standards across the European Union (ORR, 2004). This framework also includes Common Safety Targets (CST) to develop and improve safety performance (European Union Agency for Railways, 2023). 

It should be noted that, in contrast to other modes of transport, a large majority of rail accident fatalities occur to level crossing users or trespassers on rail tracks, as opposed to railway passengers (European Union Agency for Railways, 2020). This thus presents different hazard management challenges than for other modes of transport.  

Rail safety risk management should consider wider transportation network changes and their socioeconomic implications. Recent research across China's Yangtze River Delta shows that transport network modifications produce varying socioeconomic effects across different urban contexts (Qu et al., 2024). These insights should inform risk management strategies around rail infrastructure, particularly regarding land use regulations and infrastructure investment priorities. A regional, network-based approach to risk management can identify vulnerable nodes where accident impacts would have disproportionate socioeconomic consequences, enabling more targeted mitigation measures.

Monitoring

Early detection and preventive maintenance of potential rail accidents before they occur have proven to be highly cost-effective. Continuous monitoring of critical components not only enhances safety but also significantly boosts infrastructure availability, as monitoring systems enable repairs or replacements during routine maintenance periods. As a result, the railway industry and researchers worldwide have been developing integrated, robust methods for ongoing monitoring and maintenance of railway infrastructure. With advancements in sensors and information technology, the health of railway infrastructure is now continuously tracked using sensors on rolling stock (such as for rail and pantograph monitoring), near the track (such as for switch engine monitoring), and through crowd-sensing techniques (e.g., mobile phones measuring vibrations, temperature, pressure, etc.). This ongoing monitoring helps manage railway system performance. Additionally, databases built from continuous data collection grow over time, creating challenges in transmission, storage, and analysis. For example, high-frequency data from onboard axle box acceleration systems and laser Doppler vibrometers faces difficulties in being transferred to cloud systems or databases due to existing communication bandwidth limitations. To address this, data pre-processing and on-premises analytics could help reduce the data load. Moreover, new standards are necessary for managing data from multiple measurement sources and emerging sensing technologies, such as satellite data. In summary, the railway industry and academia are actively addressing these challenges, with increased collaboration potentially unlocking optimal solutions and overcoming barriers to the adoption of AI. (Phusakulkajorn et al., 2023).

Effective rail safety monitoring requires integration across multiple urban scales and systems. Urban systems science approaches that connect micro-level rail operations with macro-level urban development patterns can identify emerging safety risks before traditional monitoring detects them (Yang & Zhang, 2025). This integration is particularly powerful when combined with digital twin technologies that simulate interactions between transportation networks and urban development, providing predictive risk assessment capabilities rather than just reactive monitoring (Fang et al.,2022)