Abstract: In this paper, we propose a system for monitoring, tracking, and automating the trains. In contrast to the existing methods, we employ a global position system (GPS) and Global System for Mobile communication (GSM). The messages are sent and each train is individually tracked. We utilize signaling techniques like GPS and GSM, which provide information to the loco pilot proactively. The proposed system has advantages in terms of communication range and accuracy with respect to wi-fi based rail tracking method. The work has potential applications in bad weather and emergency situations like collision.
Keywords: Train Tracking, Collision Detection, Collision Avoidance, GPS, GSM, Railway Signaling.
I. INTRODUCTION
Railway tracking in the countries like United States, Russia, China, and India assumes significant attention. The railways traverse the length and breadth of the country and carry over billions of passengers and million tons of freight daily. In recent years, a hectic problem around the world is regarding traffic densities. This is not uncommon in railway sectors either. We often hear about the word train collision and its huge impact on precious human life and time. With great passion for this issue, the paper proposes the solution for this grave problem. Especially if we consider the case of Indian railway, most of the train tracking is based on manual entry from stations. The railway is always looking for the specific tracking methodologies, which will provide prior state of the train before arriving to the station. The GPS-GSM tracking system overcomes many problems like multiple aspect color light signaling, relay interlocking, and various kinds of block working, point operation and train tracking. The proposed system is applicable for reducing the damages to a greater extent and it is helpful to both railway system and loco pilot.

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Uvaraja et al. presents advanced pre-warning system (Railways). The proposed system is an upgrade of the existing train protection warning system (TPWS) and Anti-collision device (ACD) systems. The system makes use of radio frequency identification (RFID), FLIR cameras and other embedded systems [3]. Immanuel et al. proposes real time wireless based train tracking, track identification and collision avoidance system for railway sectors [4].
Shaik et al. presents rail tracking system (RTS). For transmission and receiving of the information, GPS is utilized. A message exchange link is given between rail tracking system and control room based on the GPS. The location of the train is tracked using GSM technology herein [7, 8]. K. Vidyasagar et al. proposes signaling based system that utilizes radio frequency and infrared technology for train tracking. This paper utilizes a switching logic methodology, technique to meet the issues of the train tracking method. This work also focuses to map the train on the display screen [6]. The above systems have constraints in real time; most of these constraints can be overcome in the proposed GPS-GSM based technique.
The objective of this paper is to monitor, track and automate trains based on GPS-GSM techniques. The subsequent section of this paper is organized as follows: In Section II, we describe the GPS-GSM modules used for tracking purposes. Section III discusses the performance evaluation of the GPS-GSM module for
tracking of the train. Section IV concludes the paper and discusses the potential future work.
II. GPS-GSM MODULES FOR TRACKING AND SIGNALING
The proposed system consists of two parts, tracking and signaling. Both tracking and signaling are carried out with the help of GPS and GSM modules.
A. RAILWAY TRACKING USING GPS-GSM TECHNIQUE
Our proposed method for tracking and signaling relies greatly on the wireless communication. It uses GPS and GSM for the communication between trains and operation centres. When each train gets their own module, it connects using GPS to obtain their position. The module which is mounted on the train sends the position and train details using GSM technology proactively.
This data is received by a central sever, which in turn sends this data to the trains on that track and operation centers. Hence, within the required distance, if any train is traversing in a same track can read this data and can calculate the distance the two trains. Therefore, based on the distance between two trains, the various alarm levels are raised, when the distance is less than predefined threshold. Then, the proposed system (Train mounted Module) starts warning the driver to avoid the collision occurrence. The proposed system responds quickly and avoids the train collisions. The Figure 1 illustrates the flow chart of the GSM-GPS based rail tracking system. The distance between the trains can be calculated using latitude and longitude provided by the GPS module. Haversine formula can be used for this calculation and given in terms of inverse tangent formula to obtain the great circle distance between two locations. The formula for calculation of distance using GPS coordinates is .
Where signaling terminologies: red signifies stop instantly before entering the next track section occupied by an ahead train; yellow shows move ahead with reasonable speed (45 km/h) as far as the signal. Green signal illustrates that the subsequent track is not occupied and the train may enter that particular section at the maximum possible speed. In heavily rush tracks; two other signal terminologies are also utilized. Two yellow lights show the restricted speed, and one yellow and one green light show the reduced speed.
The working of our system is illustrated with an example of two trains A and B. Suppose there are two trains A and B on the same track, As the GPS co-ordinates of the signal post are fixed, we directly encode those positions in the module so that when the train A which is ahead of the train B crosses the signal position and signal is changed to red, the signal which is changed is directly fed into the train B using GSM module and we can show the current signal of the signal post on a screen in the locomotive. In this way it is helpful for loco pilots to observe the signal during bad weather and low visibility conditions.
III. PERFORMANCE EVALUATION
In this section, experimental setup, hardware details, results and their analysis are provided.
A. Experimental Setup
Main module used in this work is SIM 908 Module, which has GPS, GSM and GPRS combined and Arduino UNO board. Arduino UNO is a microcontroller board based on ATmega328 as shown in Figure 3. It has 14 digital input, output pins and 16 Analog pins. It can be communicated to the computer via USB cable. All sensors and communicating devices are connected using microcontroller.

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SIM908 is integrated with a GSM-GPRS technique that is of high performance and a GPS engine as shown in Figure 4. The GSM-GPRS technique is a quad-band module that works on different frequencies like EGSM 900MHz, PCS 1900MHz, DCS 1800MHz, and GSM 850MHz. SIM908 utilizes GPRS multi-slot class 10 and class 8 and CS-1 to CS-4 coding schemes are employed herein. The experimental setup is shown in Figure 5.
Figure trains are subsequently calculated using GPS coordinates and warning system as shown in Figure 6, 7 and 8. Signaling of the train is also achieved successfully. Real time results of GPS coordinates on the map are shown in Figure 9 which shows the effectiveness of the proposed system.
IV. CONCLUSION AND FUTURE WORK
The proposed system provides the promising and reliable output. The tracking system using GPS and GSM modules may enable the rail department to safeguard the human life from accidents. The position and the current status of the signal in the signal post are directly transmitted to the train and can be displayed on the screen.
In future this work may be extended for automation and driver-less train using GPS, GSM and GPRS techniques. Real time data of moving trains like speed and current location may be tracked and monitored at the control station. Such real-time information can be utilized for system upgrade so as to avert accidents due to natural calamities such as landslide and cyclone. An additional geographic sensor and interface with geographic information system may be required for the same.
Furthermore the analysis of such data is bound to provide us with much deeper insight as to why such accidents take place. Learning from such an analysis can be applied to the system, further improving it over time as their data is collected and studied.
REFERENCES
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