e-ISSN: 2582-5208 International Research Journal of Modernization in Engineering Technology and Science Volume:03/Issue:03/March-2021
Impact Factor- 5.354
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IOT BASED ROAD SIDE UNIT FOR INTELLIGENT TRANSPORTATION SYSTEMS Dhanashree Morkhandikar*1, Manasi Vargantwar*2, Shubhada Ardhapurkar*3, Madhuri Joshi*4 *1PG
Student [M. E. (Embedded Systems)], Electronics and Telecommunication Engineering Department, Marathwada Institute of Technology (MIT), Maharashtra, India. *2.3.4Electronics and Telecommunication Engineering Department, Marathwada Institute of Technology (MIT), Maharashtra, India.
ABSTRACT From past few years some new intelligent technologies have made excellent improvisation in transportation system’s performance. For better transportation, the concept Intelligent Transportation System (ITS) is used to increase safety and traveler’s convenience and reduce traffic congestion. ITS is not just getting from one place to another, but getting there by safer, greener and more convenient way. This paper presents enhanced ITS with road side unit (RSU) using the concept of internet of things (IoT). In this paper, RSU uses Raspberry Pi Board as a main component to collect the real time information using various sensors and on-board camera and conveys it to the driver for better travelling experience. The proposed system is flexible and helps to communicate through ITS entities like vehicle to infrastructure (V2I) and infrastructure to infrastructure (V2V) communication. ITS helps to grow and develop smart cities, urban areas with less accident rate and improve road safety. Keywords: Intelligent Transportation System (ITS), Internet of Things (IoT), Road Side Unit (RSU), Vehicle Unit (VU).
I.
INTRODUCTION
The main issue in transportation is the traffic congestion and this traffic congestion effects environmental issues like carbon emission and air pollution. ITS is used to reduce traffic congestion, and improves road safety. The information related to the traffic congestion and environmental conditions is processed and proper decision is created to convey it to the traveler [1][2]. Various wireless communication technologies are implemented by ITS which enhances the communication between the RSU infrastructure and VU. In this paper, the designed system uses internet of things (IoT) wireless technology which has good communication and computing capabilities to collect the real time information from the RSU and gives updated information which makes transportation system a smart infrastructure [3]. IoT works in various fields specially in smart cities for smarter infrastructure, traffic management, parking and transit services. IoT allows people and various objects to be connected anytime and anywhere with anything and to any service with real time communication. Another wireless technology used in this system is Zigbee S2C module. Zigbee S2C module is a RF (Radio Frequency) module which sends the data serially from RSU to the VU. RSU collects the real time information like weather conditions, traffic congestion and conveys it in two ways which are: through Zigbee serial communication where it passes the information to nearby passing vehicles and other is through cloud where the web page will show the real time information of the RSU. RSU uses Raspberry Pi as the main unit where it collects the needed information from sensors and conveys it to the users. Raspberry Pi 3 Model B is used by the RSU which is a third-generation model with Broadcom BCM2837 ARM Cortex A53 Quad Core Processor which runs 50% faster than previous versions of Raspberry Pi. In the development of intelligent transportation system, various forms of wireless communications technologies were implemented. For short range and long-range communication within ITS radio modem communication UHF and VHF frequencies are widely used. Some of the major wireless technologies are wireless personal area networks (Bluetooth), wireless local area network (Wi-Fi), wireless metropolitan area network (WiMax), wireless wide area network (3G/4G mobile network) and satellite network (GPS) [4]. Some innovations show the design of RSU with Adaptive Speed Limits (ASL). Road accidents occurs because of excessive vehicles speed www.irjmets.com
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e-ISSN: 2582-5208 International Research Journal of Modernization in Engineering Technology and Science Volume:03/Issue:03/March-2021
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limit and cross lane change. ASL conveys appropriate speed limit to the traveler to reduce accident rate and also indicates the road lane change occurrence and helps to maintain distance between the vehicles. ASL system sets the ideal speed limit and compares it with the vehicle’s speed. If the vehicle’s speed limit crosses the ideal speed limit, it advises the traveler with the proper speed limit indication. Speed of vehicle depends on various factors like driving conditions, road conditions (dry roads, wet roads, low traffic, vehicle in good conditions), and current weather conditions. With this proper information about road conditions and driving conditions, overall vehicle emission can be reduced [1]. While travelling another problem is weather conditions. To minimize this problem various technologies are implemented by ITS to control and monitor activities. To monitor the weather parameters like noise, CO2 and radiation levels, environmental monitoring systems are required [5]. ITS can also be used for a specific area like ITS based Road Weather Information Systems (RWIS) to improve efficiency and provides localized information. This system shows accurate information about weather conditions like heavy rain, flooding and fog. Many surveys are done on ITS to improve its efficiency and solve the measure issues. One of the issues is large data collection from various sensors and other sources. To control and processes this large data, Data-Driven ITS (D2ITS) can be used [6]. Another major issue considered in ITS is related to the secure connection between the RSU and VU. Block chain Based ITS (B2ITS) can help to reduce the improper operation and malicious attacks [7]. All issues related with the traffic congestion, weather conditions, speed limit, transportation delays, large data processing and unsecured network can be managed by ITS. Section 2 shows proposed system of ITS and the functionality of each components used by the system is mentioned. Section 3 shows the experimental results and the performance parameters of the proposed system and lastly conclusion and future scope.
II.
PROPOSED SYSTEM
ITS is configured using RSU and the VU as shown in Figure 1. In this system information of road side unit is conveyed in two ways. The first one is by using the concept IoT where the real time information is available on the web and easily accessible from anywhere around the world. The other way is using serial communication between RSU and vehicle passing by the RSU. In this system Zigbee S2C Module is used by the RSU and the vehicle unit as a serial communication where the information is conveyed when Zigbee S2C modules of both the units are connected. Raspberry Pi is the main component in the road side unit where weather sensor and camera module is interfaced. Camera module is used to monitor the traffic flow by detecting the vehicle and records the vehicle count on the road. When the vehicle passes through the RSU, the information is displayed on the vehicle unit through Zigbee serial communication.
Figure 1: Block Diagram of Proposed System. www.irjmets.com
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e-ISSN: 2582-5208 International Research Journal of Modernization in Engineering Technology and Science Volume:03/Issue:03/March-2021
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2.1 ROAD SIDE UNIT (RSU): RSU includes Raspberry Pi as the main component and various sensors are connected like, temperature and humidity sensor, rain sensor, Zigbee Module and Camera Module as shown in Figure 2. Each of the component’s functionality is mentioned below.
RASPBERRY PI 3 MODEL B
ZIGBEE MODULE
CAMERA MODULE
TEMPERATURE AND HUMIDITY SENSOR RAIN SENSOR
Figure 2: Road Side Unit (RSU) Raspberry pi: This module is the core of road side unit (RSU) where it manages the overall functionality of the modules connected which are: camera, weather sensors and Zigbee module. System uses raspberry pi 3 Model B with raspbian operating system. This also have inbuild Wi-Fi connectivity, 1 HDMI slot, 4 USB Ports and camera slot. The IoT concept is implemented by using inbuild Wi-Fi connectivity. Weather Sensor Module: This module contains various weather sensors like temperature sensor, humidity sensor, and rain sensor which are used to collect the real time information of sensors. Here DHT11 sensor is used for humidity and temperature measurement and raindrop sensor is used to detect the intensity of rain. All the information is collected by the raspberry pi unit and recorded to convey the information to the driver. Camera Module: Camera is used to monitor the traffic congestion flow so to indicate the driver about the same. This module used 6 LED Night vision webcam with 5 MP picture quality, adjustive manual 10 X zoom quality. Here Haar-like feature is used for the detection of vehicle. According to the detection of vehicles traffic flow, updates are sent to the server as well as to the user passing through the road side unit. Zigbee Module: Zigbee S2C module is used for the communication between road side unit and matched receiver unit. Zigbee module used in RSU is connected to the raspberry pi’s USB port using USB to TTL module. Zigbee module covers around 4000 ft outdoor range for connectivity. Zigbee module is capable of point to multipoint topology to communicate and transfer the information in wide area network. The information of road side unit is transferred to the nearby vehicle and also satisfies the terms: Vehicle to Infrastructure(V2I) communication and Vehicle to Vehicle(V2V) communication. 2.2 VEHICLE UNIT (VU): Figure 3 shows the Vehicle unit and consist of AVR 328 microcontroller, Zigbee S2C Module, and LCD Display. AVR 328 microcontroller is used which gives command to the Zigbee S2C Module to connect with the nearby RSU’s Zigbee S2C Module. When it comes to quick connectivity between the RSU and nearby passing vehicle unit, Zigbee S2C module is used. The information of a RSU is then transported to the vehicle after the connection between road side unit’s Zigbee module and the vehicle unit’s Zigbee module is done. Zigbee module has fast connectivity which helps to convey the RSU information quickly to the road side vehicle. The LCD display is interfaced with the on-board AVR328 Microcontroller which shows the received information from RSU Zigbee module.
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e-ISSN: 2582-5208 International Research Journal of Modernization in Engineering Technology and Science Volume:03/Issue:03/March-2021
Impact Factor- 5.354
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AVR 328 MICROCONTROLLER
LCD DISPLAY
ZIGBEE MODULE
Figure 3: Vehicle unit
III.
EXPERIMENTAL RESULTS
Implementation of road side unit has been done with the help of OpenCV libraries. With the OpenCV libraries vehicle detection and vehicle count is measured with weather sensor information that is temperature sensors, humidity sensors and rain sensors. At the receiver end the information of RSU is transferred through Zigbee Module and is display on LCD Display as shown in Figure 4 and Figure 5. The information conveyed to the vehicle is about the Temperature(T), Humidity(H) and Rain(R) or No Rain (NR) weather conditions with the vehicle count and traffic status (medium traffic indicated).
Figure 4: Display of transmitted weather Conditions
Figure 5: Display of transmitted traffic conditions
When RSU system runs the program, it shows vehicle detection and vehicle count and weather parameters which helps to monitor and control the system as shown in Figure 6. Parameters on the RSU system is displayed on the web page where information keeps on updated on the web page with the date and time and gives real time information. This real time weather sensors and traffic congestion information as shown in Figure 7, helps the driver before travelling to that place.
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e-ISSN: 2582-5208 International Research Journal of Modernization in Engineering Technology and Science Volume:03/Issue:03/March-2021
Impact Factor- 5.354
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Figure 6: RSU Systems Output
Figure 7: Weather sensors and Vehicle count information on web page
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e-ISSN: 2582-5208 International Research Journal of Modernization in Engineering Technology and Science Volume:03/Issue:03/March-2021
Impact Factor- 5.354
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PERFORMANCE PARAMETERS: To find out the vehicle detection results, some performance parameters are calculated using following parameters: True Positive (TP): number of vehicles detected correctly. False Positive (FP): number of false vehicles detected. False Negative (FN): number of vehicles not detected. Using this above parameters, three performance metrics are measured as follows and result is shown in Table 1. 1) Recall/Completeness: This is the ratio of number of correctly predicted vehicles to the total predicted observations.
2) Precision/Correctness: This is the ratio of number of correctly predicted vehicles to the total predicted positive observation.
3) F1 score: This shows the average of both precision and recall. This measure is very important as this focuses on false positive and false negative parameters which is frequently calculated. [
]
Table 1: Performance Result VIDEO TEST
TP
FP
FN
RECISION (%)
RECALL (%)
F1 SCORE (%)
Video1.avi
40
4
0
90
100
94
Video2.avi
53
6
1
89
98
93
Video3.mp4
40
16
0
71
100
83
The receiver operating characteristics (ROC) curve as shown in Figure 8, is a graphical representation between the true positive rate (TPR) and false positive rate (FPR). TPR and FPR is calculated using true positive (TP) and false negative (FN) values from Table 1, to create the ROC curve. Here, ROC curve shows approximately 1 (binary 1) or 100% of system performance which is created using excel histogram function in data analysis. Observed in ROC, only vehicle detected (TP) and not detected (FN) values shows good system performance but it differs from the precision and recall results. Shown in Table 1, False vehicle detected (FP) value and vehicle not detected (FN) value gives recall 100%, 90% and 100% whereas, number of vehicles detected (TP) values and false vehicle detected (FP) values gives precision 90%, 89% and 71%. So, system is good according to the ROC curve but precision and recall shows actual performance where false vehicle detection is also calculated to get exact performance rate. Average of both precision and recall is also calculated as it focuses on false positive and false negative parameters and the performance is 94%, 93%, and 83%. This average calculation is called as F1-score.
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e-ISSN: 2582-5208 International Research Journal of Modernization in Engineering Technology and Science Volume:03/Issue:03/March-2021
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True Positive Rate
Reciever Operating Characterisitics (ROC) 1 0.8 0.6 0.4 0.2 0 0
0.2
0.4
0.6
0.8
1
False Positive Rate
Figure 8: Receiver Operating Characteristics (ROC) Curve
IV.
CONCLUSION
In this paper, proposed system uses the concept of IoT based road side unit that collects real time information from sensors and camera and conveys it to the driver through web page. Another medium to send the RSU information is through Zigbee wireless technology. Zigbee Module is used in RSU and Vehicle Unit for shortrange communication. Vehicle passing through the nearby RSU will receive the information through this shortrange communication. In RSU entity, Raspberry Pi 3 Model B is used as a core component where all the sensors are connected. The main upgradation used in Raspberry Pi is its Broadcom BCM2837 ARM Cortex A53 Quad Core Processor which has 1.2 GHz speed that makes the system 10 X faster. Two performance parameters are calculated to measure the exact system performance from the three-video source. Receiver Operating Characteristics (ROC) Curve is created by taking the values of true positive and false positive. With these values, ROC curve shows approximately 1 (binary 1) or 100% of system performance. Observed in ROC, only vehicle detected (TP) and not detected (FN) values shows good system performance but it differs from the precision and recall results. False vehicle detected (FP) value and vehicle not detected (FN) value gives recall 100%, 90% and 100% whereas, number of vehicles detected (TP) values and false vehicle detected (FP) values gives precision 90%, 89% and 71%. In future from metropolitan to smart cities or villages ITS can be implemented according to the need. Some problems in ITS like overlapping of vehicles cannot get the precise vehicle count and can be overcome by using advanced techniques like machine learning (ML), image processing, or artificial intelligence (AI). With the help of new generation Raspberry Pi, system can solve bigger and more powerful real-world issues. From location to location, variety of features can be added to make the transportation system more intelligent and efficient. The advancement in wireless technologies, sensor technologies, embedded systems, and related software and cloud platforms, will keep on enhancing the system in future. ITS will certainly be a great help to human kind as it will reduce time, fuel, pollution and accident rate.
V. [1]
[2] [3]
[4]
REFERENCE
Arafat Al-Dweik, Radu Muresam, Matthew Mayhew, Mark Lieberma, “IOT-Based Multifunctional Scalable Real Time Enhanced Road Side Unit for Intelligent Transportation Systems”, IEEE 30th Canadian Conference on Electrical and Computing Engineering (CCECE), 2017. Kashif Naseer Qureshi, Abdul Hanan Abdullah, “A Survey on Intelligent Transportation Systems”, ResearchGate Publication, pp. 629-642, Jan 2013. Anitha Chepuru, Dr. K. Venugopal Rao, “A SURVEY ON IOT APPLICATIONS FOR INTELLIGENT TRANSPORT SYSTEMS”, International Journal of Current Engineering and Scientific Research (IJCESR), vol. 2, Issue 8, pp. 116-127, 2015. Hasan Omar Al-Sakran, “Intelligent Traffic Information System based on Integration of Internet of Things and Agent Technology”, International Journal of Advanced Computer Science and Application (IJACSA), vol. 6, no. 2, pp. 37-43, 2015.
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[6]
[7]
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Bulipe Srinivas Rao, Prof. Dr. K. Srinivasa Rao, Mr. N. Ome, “Internet of Things (IOT) Based Weather Monitoring System”, International Journal of Advanced Research in Computer Communication Engineering (IJARCCE), vol. 5, Issue 9, pp. 312-319, Sept 2016. Junping Zhang, Fei-Yue Wang, Kungfeng Wang, Wei-Hua Lin, Xin Xu, Cheng Chen, “Data-Driven Intelligent Transportation Systems: A Survey”, IEEE Transactions on Intelligent Transportation Systems, vol. 12, no. 4, pp. 1624-1639, Dec 2011. Yong Yuan, Fei-Yue Wang, “Towards Blockchain-Based Intelligent Transportation Systems”, IEEE 19th International Conference on Intelligent Transportation Systems (ITSC), pp. 2663-2668, 2016.
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