Strategies for Reducing Rail Animal Collisions in Wildlife - Strategies for Avoiding Catastrophic Train Collisions
Advanced Wildlife Warning Systems Set to Prevent Train-Animal Collisions
Hesse's hunters are set to discuss the findings of a pilot project investigating the prevention of wild animal accidents on railway tracks. The presentation will take place on Friday at a meeting on the ICE route Frankfurt-Cologne near Hünfelden in the Taunus, where networked wildlife warning systems have been installed. These systems utilize acoustic and optical signals to alert animals and railway personnel about approaching trains before the collision occurs.
In collaboration with Deutsche Bahn, hunters have studied animal behavior through the use of wildlife cameras, with a focus on identifying and addressing accident hotspots, such as the area near Niedernhausen in the Taunus. By preventing such accidents, significant consequences can be averted, including severe animal suffering, emergency braking, and substantial delays to train schedules.
The networked wildlife warning systems work by employing a combination of sensors, communication technologies, and automated alerts to detect and respond to the presence of wildlife near or on railway tracks. AI and IoT technologies are utilized to analyze sensor data and communicate alerts in real-time.
When wildlife is detected, immediate alerts are sent to control offices, station masters, and loco pilots (train drivers) via visual or audio alarms, digital displays, or mobile applications. Field alarms, such as hooters or buzzers, are also triggered at rail crossings or sensitive locations to ensure both animals and railway personnel are warned. In some cases, advanced systems can even communicate directly with train control systems, signaling trains to slow down or stop if necessary.
Mobile applications enable railway officials and conservationists to monitor alarms and system status, ensuring swift responses to alerts. IoT connectivity allows for remote monitoring and management of the system across large or difficult-to-access rail networks.
Successful pilot projects in regions like West Bengal and Assam have demonstrated the effectiveness of these systems in preventing train-elephant collisions, thereby protecting endangered species and minimizing the risk of derailments or injuries to passengers. These advanced warning systems can also identify rail fractures, trespassing, and other potential hazards, further enhancing railway safety.
India boasts the Indian Railways’ Intrusion Detection System, which employs AI and optical fiber sensors to detect elephants and other large animals, enabling drivers and staff to take preventative action. Kenya has implemented extensive wildlife corridors, ground-level crossings, underground culverts, and noise-dampening overpasses, while infrared cameras monitor animal movements and ensure safe passage. Sri Lanka is also expressing interest in adopting such advanced warning systems in light of the continued loss of elephants to train accidents.
In summary, these networked wildlife warning systems are a vital development in railway safety, blending technology and ecology to safeguard both wildlife and human infrastructure. Their effectiveness in preventing collisions between trains and animals, while minimizing delays and ensuring the safety of passengers, makes them crucial components of modern railway safety strategies.
- To strengthen the community policy and protect endangered species, the implementation of networked wildlife warning systems that utilize AI, IoT, and optical fiber sensors, like the one in Indian Railways, should be considered in the local fisheries and transportation industry, similar to the initiatives taken in Kenya and Sri Lanka.
- In collaboration with the fisheries, finance, and transportation industries, it's essential to prioritize environmental conservation efforts in identifying and addressing accident hotspots, ensuring the prevention of severe animal suffering, emergency braking, and substantial delays to train schedules, as demonstrated in the pilot project investigating the prevention of wild animal accidents on railway tracks.
