Smart road safety and vehicle accident pevention syatem for mountain roads using arduino

It uses for accident prevention for society

1. SMART ROAD SAFETY AND VEHICLE ACCIDENT PREVENTION SYSTEM FOR MOUNTAIN ROADS USING ARDUINO

2. ABSTRACT An accident prevention road safety model that uses infrared sensors and light control to improve road safety on mountain roads. The proposed model aims to detect potential hazards on the road and control LED according to prevent accidents. A warning mechanism is also included to warn the driver of potential dangers on the road. The effectiveness of the proposed model is evaluated by simulation and the results show that the number of accidents is significantly reduced and road safety is improved on mountainous roads. The results of this study can provide valuable information on the use of LED to improve road safety in harsh environments and contribute to the development of effective accident prevention systems.

3. INTRODUCTION A road and safe driving, but the complex road system on mountain terrains requires further study. One of the main challenges is the difference between actual and perceived vision, which can greatly impact a driver's behavior. Existing systems that address this issue include the use of mirrors to display approaching vehicles. However, these systems have limitations. There are only mirrors present at a blind spot on a mountain road in India . These prove to be ineffective as during winters and in monsoons fog accumulates on the surface of mirrors so reflection can’t be seen properly. During nightfall they are prevent to be useless.

4. OBJECTIVES To decrease the number of accidents on mountain roads by implementing proactive safety measures and interventions. To keep drivers informed about road conditions, potential hazards, and safe driving practices specific to mountainous terrain.

5. LITERATURE REVIEW S.NO TITLE OF PAPER TECHNOLOGY (USED IN SURVEY DOCUMENT) JOURNAL NAME VOLUME & PAGE NUMBER YEAR 1. Accident prevention system Introducing to accident prevention system using Mirror to prevent the accident IEEE 3rd International Conference on Electronic Communications, Internet of Things and Big Data (ICEIB), Coimbatore pp. 219-222, doi :   10.1109/ICEIB56496.2022.9965535 2021

6. Contd., S.NO TITLE OF PAPER TECHNOLOGY (USED IN SURVEY DOCUMENT ) JOURNAL NAME VOLUME & PAGE NUMBER YEAR 2. Vehicle accident prevention system Accidents may takes place in various factors drunk and driving, Texting while driving, speeding, Distractions, sleeping while driving. Among Drowsiness is reason for most of the accidents. 10th International Conference on Developments in Systems Engineering (DSE), Chennai pp.195-200, doi : 10.1109/DESE 36765.2020.1097835 2022

7. Contd., S.NO TITLE OF PAPER TECHNOLOGY (USED IN SURVEY DOCUMENT) JOURNAL NAME VOLUME & PAGE NUMBER YEAR 3. Diminishinng Road Accidents on Sharp Curves using Ardunio Reduce accidents on hilly and slipper roads using buzzer. International Conference on Transportation Information and Safety (ICTIS),Erode pp.75-82,   doi : 10.1109/ICTIS64597.2020.9658520 2022

8. Contd., S.NO TITLE OF PAPER TECHNOLOGY (USED IN SURVEY DOCUMENT) JOURNAL NAME VOLUME & PAGE NUMBER YEAR 4. Vehicle Accidents Prevention System for Mountain Road Light intensity problem occurs both curved roads to use buzzer alerting the driver about the vehicle coming from opposite side. 5 th International Conference on Transportation Information and Safety (ICTIS) , Noida pp.105-112, doi : 10.1109/EMTECH 46696.2022.9865535. 2023

9. EXISTING SYSTEM

10. BLOCK DIAGRAM Arduino Uno Buzzer Red Green Red Green Pair of Sensor for Road 2 Signal on Road 1 Signal on Road 2 Pair of Sensor for Road 1 Ultrasonic Sensor Ultrasonic Sensor

11. FLOW CHART Ultrasonic sensor Arduino UNO Both ultrasonic sensor detect a vehicle Turn ON Green LED Turn ON Red LED Stop Yes No Input Start

12. HARDWARE IMPLIMENTATION Arduino UNO: Arduino UNO is a microcontroller board developed by Arduino.cc and is based on Atmega328 Microcontroller. There are 14 digital pins and 6 analog I/O pins. Ultrasonic sensor: These sensors produce high-frequency sound waves and analyze the echo which is received from the sensor. The sensors measure the time interval between transmitted and received echoes so that the distance to the target. The sensing range lies between 40cm to 300 cm. LED: Electrons in the semiconductor recombine with electron holes, releasing energy in the form of photons. The P-N junction is nothing but a combination of both N-type and P-type semi-conductor materials. Buzzer: A buzzer or beeper is an audio signal ling device, which may be mechanical, electromechanical, or piezoelectric. Typical uses of buzzers and beepers include alarm devices, timers, and confirmation of user input such as a mouse click keystroke. time interval between transmitted and received echoes so that the distance to the target. The sensing range lies between 40cm to 300 cm.

13. C OMPONENTS Arduino UNO Ultrasonic sensor LED Buzzer

14. ADVANTAGE Reduce the number of accidents Improve emergency response times Reduce traffic congestion and integrate Less maintenance Victim life can be save quickly Efficient time consumption Environmental friendliness

15. APPLICATION Weather Monitoring Speed limit control vehicle-to-infrastructure communication Emergency response coordination

16. CONCULSION These mountain roads have many acute turns and blind-spots. Generally Mirrors are present at these spots to spot the vehicle from other end. But they prove to be inefficient during foggy days and at nightfall. We have only used sensors and created a Signal sort of mechanism. So even in dark or in foggy days driver can easily see the signal because it is covered with radio-luminescent paint . Also the content displayed on LED can aid about what type of vehicle is ahead. This will give a driver clear idea how should he approach the turn . Thus we can reduce the number of accidents happening on mountain roads efficiently.

17. REFERENCES 1 .Ahmad A, P. Karthikeyan and S. P.Anandaraj (2023),’Road Accident Prevention SysteM’, Proceedings of 13th International Conference on Dependable Systems, Services and Technologies (DESSERT), Coimbatore, Vol.2, pp.1-7, doi:10.1109/DESSERT 56496.2023.9965535. 2. Ali V , Gayathri, A.R. Divagaran, C.D.Akhilesh (2020) ‘Analysis and Countermeasures of fatal Traffic Accidents on Road Passenger Transportation Based on Typical Cases’, Proceeding of 5th International Conference on Transportation Information and Safety (ICTIS), Coimbatore, India, 2020, Vol.2,pp.75-82,   DOI: 10.1109/ICTIS64597.2020.9658520. 3. Gogola R and Ondruš S,(2020), ‘Road safety perspective of small children’, Proceeding of XII International Science-Technical Conference AUTOMOTIVE (SAFETY), Bhimtal, India, 2020, Vol. 6,pp. 198-188,  DOI: 10.1109/SAFETY 96495.2020.1004535.

18. Contd., 4.Khalil G, V. N. Nghiem and L. E. Wang (2020), ‘A Study on Road Accidents in Abu Dhabi Implementing a Vehicle Telematics System to Reduce Cost, Risk and Improve Safety’, Proceeding of 10th International Conference on Developments in Systems Engineering (DeSE), Chennai, India, 2020, Vol 5, pp. 195-200,   DOI: 10.1109/DESE 36765.2020.1097835. 5.Jian P and A. Zaslavsky (2022),’Establishment of Causal Relationships of the Occurrence of Road Accidents’, International Conference on Engineering Management of Communication and Technology (EMCTECH), Vol.9,pp.105-112, DOI: 10.1109/EMTECH 46696.2022.9865535. 6.Rasheed Ahmad B, P.Yanambaka and A.Abdelgawad (2023), ‘Artificial Neural Network Approach To Study The Effect of Driver Characteristics on Road Traffic Accidents’, Proceeding of International Conference on Data Analytics for Business and Industry (ICDABI), Banglore , India, 2023 Vol.8,pp. 277-280,   DOI: 10.1109/IDABI967428.2023.2014675.

19. Contd., 7.Ruihua S and Zhang N,(2022),’Traffic safety information system research’, Proceeding of 2 nd International Conference on Transportation Information and Safety (ICTIS), Palladam , India, 2022 , “Mexico IEEE”, Vol .7, pp. 412-459,  DOI:10.1109/ICTIS56876.2022.9978536. 8. Yang N, Manjunath and P. G. Shah (2023), ‘Application of Big Data Analysis in Improving Traffic Safety: Database of Traffic Accidents and Violation Reports’, Proceeding of  IEEE 3rd International Conference on Electronic Communications, Internet of Things and Big Data (ICEIB), Coimbatore, India, 2023, Vol. 6,pp. 219-222,  DOI: 10.1109/ICEIB67486.2023.9738535. 9. Zhou V, P. K. Maduri and K. Kushagra (2021) ,’Regression analysis of association between vehicle performance and driver casualty risk in traffic accidents’ ,Proceeding of International Conference on Transportation Information and Safety (ICTIS), Greater Noida, India, 2021, Vol 3,pp. 345-349, DOI: 10.1109/ICTIS96486.2021.9989635.

20. Contd., 10. Chaithralakshmi , Aravinda , Deeksha , Ashutha (2020), ‘Sensor Based Accident Prevention System’, International journal of innovative research in electrical, electronic and instrumentation and control engineering, Vol. 4, Issue 6. 11. Weihua Sheng., Duy Tran, (2019), et.al.: ‘A Hidden Markov Model based driver intention prediction system’, IEEE Int. Conf. on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER) pp. 115-120. 12. Yuying ., Jiang(2020), et.al.: ‘A surveillance method for driver's fatigue and distraction based on machine vision’, IEEE Int. Conf. on Transportation, Mechanical, and Electrical Engineering (TMEE) pp. 727 – 730.

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