A New Form of Train Detection as a Solution to Improve Level Crossing Closing Time

Area of Science:

• Transportation Engineering
• Traffic Management Systems
• Sensor Technology

Background:

• Level crossings are critical network points causing road congestion due to train traffic stops.
• Current safety regulations often lead to extended closure times, impacting traffic fluidity.
• High costs of grade-separated intersections limit their widespread implementation.

Purpose of the Study:

• To propose and evaluate a sensor-based system for reducing level crossing closure times.
• To enhance the Level of Service on road networks affected by railway traffic.
• To provide a cost-effective alternative to traditional intersection improvements.

Main Methods:

• Utilizing radar/LIDAR sensors to monitor traffic and train presence.
• Developing formulas, similar to Highway Capacity Manual (HCM) methods, for intelligent crossing control.
• Conducting simulations using PTV Vissim to analyze system performance.

Main Results:

• The proposed sensor system can reduce level crossing closure time by an average of 68.6%.
• Significant improvements in the Level of Service on adjacent road networks were observed.
• The method offers a viable solution for managing traffic at local agglomeration lines.

Conclusions:

• Implementing radar/LIDAR sensors is an effective strategy to decrease level crossing downtime.
• The developed control logic improves road network efficiency and reduces congestion.
• This approach presents a cost-effective enhancement for railway-road interactions.