Margdarshak: A Smart Driverless Vehicle Using IR-Based Traffic and Sign Recognition

Abstract

Therapidadvancementofintelligenttransportationsystemshasled to growing interest in autonomous vehicles. This paper presents Margdarshak, a low-cost, sensor-based driverless car prototype designed to recognize and respond to traffic lights, speed limit boards,directionalsignboards,andobstacles.ThesystemutilizesIR transmitters and a TSOP-based IR receiver to interpret encoded signals from traffic elements. Lane following is achieved using infrared sensors, while ultrasonicsensors enable obstacle detection andavoidance.AnATmega328microcontrollerprocessesreal-time input from sensors and controls the vehicle’s motion via a motor driver module. This prototype demonstrates the feasibility of creating a modular, scalable, andautonomous vehicle using simple embedded electronics, making it suitable for academic, smart city, and controlled-environment transport applications. Unlike traditional autonomous vehicles that rely on image processing and costly AI modules, Margdarshak is built on a simplified IR communication mechanism that simulates traffic scenarios in a structured and repeatable manner. Each traffic signboardisembeddedwithanIRtransmitterthatsendsadistinct signal pattern representing specific actions like stop, turn, or set speed. These signals are received by the TSOP module, decoded by the microcontroller, and acted upon using motor drivers. By minimizing complexity and cost, this design serves as a learning platform for students and a stepping-stone toward more complex automation. The hardware setup includes IR sensors for line detection, ultrasonic sensors for proximity sensing, and relay modules for directional control. Testing shows accurate responses to red and green light signals, speed adjustments based on IR input, and precise turns at curve indicators. The modular design allows for easy future upgrades such as GPS, voice assistance, or camera- based AI. This paper highlights the effectiveness of combining basic embedded components with logic-based programming to buildanefficient,reliable,andreplicabledriverlesscarprototype with real-time environmental interaction

Introduction

1. Background & Motivation

• Growing concerns over road safety, traffic congestion, and vehicular accidents have driven interest in intelligent transportation systems.

• India reported over 1.5 lakh road deaths in 2022, largely due to human error (e.g., speeding, poor lane discipline).

• Autonomous vehicles are a promising solution to reduce human intervention and enhance safety.

2. Project Overview – Margdarshak Prototype

• Margdarshak is a compact, low-cost driverless car prototype.

• It is designed to:

  • Recognize traffic lights via IR signals

  • Follow lanes autonomously

  • Detect and avoid obstacles in real-time

• Built using basic sensors and an ATmega328 microcontroller, it provides a functional alternative to expensive AI-based systems.

3. Key Features

1. IR-Based Signal Recognition

   • IR transmitters on signboards send encoded signals.

   • The car’s TSOP1838 IR receiver detects and decodes them to act (e.g., stop, turn, adjust speed).

2. Autonomous Lane Following

   • Downward-facing IR sensors detect contrast (black lines) to guide the vehicle along a predefined path.

3. Obstacle Detection and Avoidance

   • A front-mounted ultrasonic sensor stops or reroutes the car upon detecting an obstacle.

4. Real-Time Control via Microcontroller

   • All sensor data is processed by the ATmega328, which controls the vehicle’s motors using an L298N motor driver.

4. Literature Review Insights

• Earlier methods used GPS, AI, and image processing, but were costly and resource-intensive.

• Simple IR and ultrasonic systems lacked integration and real-time decision-making.

• Margdarshak overcomes these with integrated, low-cost sensor coordination.

5. System Architecture & Methodology

• The system includes:

  • IR transmitters on signs

  • TSOP IR receivers

  • Ultrasonic obstacle sensors

  • IR lane sensors

  • ATmega328 microcontroller and L298N motor driver

• Key operations:

  • Signal decoding for traffic behavior

  • Lane tracking using contrast detection

  • Obstacle avoidance through proximity sensing

  • Motor control for movement via PWM signals

6. Results

• Accurate detection of traffic signals

• Stable lane following performance

• Reliable obstacle avoidance

• Smooth real-time processing in indoor environments

• Demonstrated the feasibility of a low-cost autonomous vehicle prototype

7. Use Cases

1. Smart Campus Mobility

   • Automating short-distance transport within institutions or industries.

2. Warehouse & Factory Automation

   • Moving goods along predefined paths with collision prevention.

3. Educational & Research Applications

   • Teaching tool for robotics, IoT, and embedded systems.

4. Traffic Control Demonstration Models

   • Simulating traffic flow, signal response, and urban planning strategies.

Conclusion

The development and successful implementation of the Margdarshak prototype demonstrates the potential of integrating simplesensorsystemswithmicrocontroller-basedlogictosimulate the core functionalities ofan autonomous vehicle. Thisproject was driven by the vision to create a low-cost, scalable, and effective solution for interpreting traffic signals, managing speed, and navigating lanes autonomously. Unlike modern commercial autonomous vehicles that rely heavily on costly GPS modules, camera-basedsystems,andAImodels,Margdarshakreliesoncost- effective and widely available components such as IR transmitters, TSOP1838 IR receivers, ultrasonic sensors, and ATmega328 microcontrollers. This makes it not only an affordable solution for developing countries but also a strong academic and educational prototype to teach automation and embedded system concepts. The system architecture enables the vehicle to take real-time decisions such as stopping at red signals, moving on green, turning as per signboard directions, following lanes using IR sensors, and haltingwhenanobstacleisdetected.Thesuccessfulsynchronization of all sensor modules with logical programming validates the efficiencyoftheoveralldesign.

References

1) A. Mehta and S. Desai, “Autonomous Vehicle Control Using Sensor Fusionfor Obstacleand Signal Detection,” International Journal of Intelligent Systems and Applications, vol. 13, no. 6, pp. 28–35, June 2021. 2) A.Verma,P.Singh,andR.Gupta,“DesignofLow-Cost IR Sensor-Based Line Follower Robot,” IEEE InternationalConferenceonRoboticsandAutomation, pp.112–117, 2020. 3) Vishay Intertechnology, “TSOP1838 IR Receiver Datasheet,”

Copyright

Copyright © 2025 Rahul Soni, Raj Shrivastava , Vikash Banwari, Rashmi Gour, Durgesh Nagar , Dr. Ravi Shankar Mishra. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.