Journal of Railway Transportation and Technology

Innovation In Renewable Energy Systems: Utilization Of Piezoelectric Sensors On Railway Tracks To Harvest Vibration Energy

Mon, 12 Jan 2026 00:00:00 +0000

Green energy development prioritizes sustainable sources like solar, wind, biomass, and geothermal to combat climate change and resource depletion. In this context, piezoelectric technology offers a promising solution for energy harvesting from vibrations and mechanical stresses, such as those generated by vehicles or trains. This technology converts mechanical pressure into electrical energy via polarization changes within piezoelectric materials.

This system has proven effective in powering electronic devices and signaling systems at railway level crossings, especially in remote areas lacking grid access. This study employs a descriptive method with a quantitative approach, utilizing experimental data. Data acquired from experiments conducted with the device positioned at a railway level crossing, observing passing trains and various motor vehicles including cars, trucks, and buses, indicated a generated power of 18,185 watts. With the series installation of ten such devices, a total power output of 165.44 Watts per day can be achieved, which is sufficient to meet the energy demands of the signaling system.

The harvested energy powers signaling systems, lighting, and other electronic equipment at level crossings. Implementing this technology not only enhances sustainability through renewable energy use but also reduces reliance on external electricity supplies. Consequently, piezoelectric technology significantly improves operational efficiency and railway safety, particularly at level crossings.

Design and development of an Early Warning System For Railway Level Crossings with arrival detection and speed monitoring based on Arduino Uno and Inductive Proximity Sensor

Arief Darmawan, Trinil Muktiningrum — Mon, 12 Jan 2026 00:00:00 +0000

Railway level crossings are critical safety points prone to accidents, necessitating a reliable Early Warning System (EWS) to protect road users. This study designs and evaluates an EWS integrating Arduino Uno and inductive proximity sensors to detect train arrivals and monitor train speed at a level crossing in Blitar Regency. Field experiments were conducted with sensors installed at an optimal maximum distance of 30 mm from the train wheel flange. Over a five-day period, the sensors achieved a wheel detection success rate of approximately 99.95%, while the speed counting system showed an accuracy of 87.22% compared to GPS tracking data. The 12.78% deviation in speed measurement falls within acceptable tolerance limits according to international standards on measurement uncertainty and railway electromagnetic compatibility. Performance decreased significantly beyond the 30 mm threshold, confirming the recommended installation distance. Compared to existing systems, this approach demonstrates improved modularity and algorithmic flexibility that enable future accuracy enhancements. Routine maintenance and regular calibration are essential to sustain system stability. Future work will focus on algorithm development for enhanced train speed calculation precision and expanded testing under

Evaluating Effectiveness Of ETLE and Designing ATCS Integration For Traffic Violation Reduction In Magelang Regecy

Hafidz Nurrohman, Zahwa, Rizal Aprianto — Mon, 12 Jan 2026 00:00:00 +0000

Transportation as a means of public mobility in Indonesia continues to face high traffic accident rates, primarily due to violations such as speeding and red-light running. Electronic Traffic Law Enforcement (ETLE) has emerged as a technology-based law enforcement solution, but its effectiveness remains limited due to the narrow coverage of static systems. This study aims to analyze the effectiveness of ETLE and design its integration with the Area Traffic Control System (ATCS) to enhance traffic violation monitoring in Magelang Regency. The research method is census approach by collecting primary violation data from static and mobile ETLE units during March 2024–2025. Analysis results indicate a decline in violations from 17,495 cases (2020) to 4,739 cases (2023), yet the limited deployment of static ETLE at only one strategic point hinders optimal detection. Integration of ETLE-ATCS across 19 traffic light (APILL) points is proposed to expand coverage through real-time detection, automated verification, and traffic signal adjustments based on real-time data. Simulations of this integrated system demonstrate the potential for more transparent and efficient law enforcement, alongside reduced accident risks. Consequently, the proposed system integration is expected to foster safer, more orderly, and sustainable transportation in Magelang Regency.

Accident Risk Analysis at Level Crossings Based on Physical and Operational Characteristics (Case Study: Crossing Points in Medan City Area)

Aldi BJ Hamdani, Mukhammad Rizka Fahmi Amrozi — Mon, 12 Jan 2026 00:00:00 +0000

Level crossings are critical safety points in railway operations due to the interaction between trains and road traffic. In Indonesia, many crossings in urban areas such as Medan operate with limited safety infrastructure, increasing the likelihood of serious accidents. This study aims to evaluate accident risks and propose mitigation strategies for selected level crossings in Medan.

A quantitative risk assessment was conducted using the Australian Level Crossing Assessment Model (ALCAM), which considers infrastructure, exposure, and consequence factors. Data were collected through field observations, interviews with crossing attendants, and secondary records from local transport authorities. Three locations were analyzed: KM 9+30 on the Medan–Binjai line, and JPL 1 (KM 0+640) and JPL 4 (KM 1+325) on the Medan–Tanjung Balai line.

The ungated crossing at KM 9+30 had a risk score of 0.053, JPL 1 the highest at 0.136, and JPL 4 at 0.076. Simulated mitigation strategies substantially reduced risks to 0.020, 0.051, and 0.038, respectively.

These findings demonstrate that ALCAM provides a reliable framework for quantifying risks and prioritizing safety improvements at level crossings in Indonesia.

Road Attributes and Traffic Characteristics Effects on Motorcycle Safety

Mon, 12 Jan 2026 00:00:00 +0000

In Indonesia, motorcycles dominate the transport landscape, with over 125 million registered motorcycles as of 2025. The country faces a significant road safety challenge, recording over 31,000 road traffic deaths annually, with motorcycles involved in many fatal crashes. Infrastructure-based interventions have shown promise in mitigating these risks. However, the implementation remains uneven, and effectiveness varies by region. Therefore, a systematic assessment of the influence of road conditions on motorcycle safety and evaluating the impact of infrastructure-based countermeasures in reducing crash risk and injury severity is needed. This study aims to systematically assess the road safety risk for motorcyclists in campus areas, with a specific focus on the role of local road attributes and traffic characteristics to propose suitable infrastructure-based countermeasures in reducing crash risk and injury severity. The method used is a road assessment tool developed by the International Road Assessment Programme (iRAP). The results show that The road attributes that play the most crucial role in determining the SRS value for a motorcycle on a road segment in the UGM campus area are those that contribute to accident likelihood: curvature, median transversability, and operating speed. Although previous research has shown operating speed to be a mediating variable rather than a direct factor in accident occurrence, it is essential to consider the factors that contribute to accidents. For intersections, the road attributes that significantly determine the level of safety are those that influence the likelihood and severity. The road attributes that influence likelihood are curvature, intersection quality, channelization, and property access points. The road attributes that influence severity are roadside severity – distance, paved shoulder width, and property access points.