This document proposes an autonomous electric vehicle that can detect roadside buildings to navigate to its destination. It uses sensors like infrared sensors, an ultrasonic sensor, and the Pixy2 camera to detect objects while an Arduino board controls the vehicle's motion. The vehicle is intended to help reduce accidents by removing human error in driving and could potentially be used to deliver products.

1. Real-Time Autonomous
Electric Vehicle for
smart cities
Presented by

2. ABSTRACT
• In this paper, an autonomous electric vehicle is proposed which can detect the
roadside buildings and use this data to reach its desired location or destination
location.
• This paper has two major aspects, one of them is self-driving ability of the vehicle
and the second one is its object detection ability.
• But both the aspects are interlinked with each other to control the motion of the
vehicle. In this model, infrared sensors are used to sense the roadside barricade.
• All these things are carried out and controlled by a simple microcontroller board i.e.
Arduino Mega 2560. Also, we make a web page and a mobile application for the
passengers to select their destination.

3. INTRODUCTION
• In India, nearly 1,51,000 deaths in road accidents have been reported in the year.
• This mainly happens because of the lack of attention of the driver, there are a lot of factors
that affect the mental state of the driver such as the awful amount of noise, pedestrians
walking or crossing the road or the phone ringing along with many other reasons.
• The element of human error cannot be removed but it is definitely possible to stop accidents
from happening.
• Self-driving cars is implemented in a proper environment can tremendously reduce the
number of accidents. As the system is prone to all distractions.

4. EXISTING SYSTEM
• The self-driving car may be more convenient for the people to travel, on
the other hand, it is possible to collapse the existing social transport
model, leading to less bus services and more congested urban traffic.
• However, few papers have surveyed the technology process of a self-
driving car due to its complexity.
• Vehicles that need some driving mode-specific tasks by the car like
steering or acceleration/deceleration assistance.

5. PROPOSED SYSTEM
• In this paper, the autonomous electric vehicle is proposed which can detect the roadside buildings to reach the destination.
• Apart from the building detection, this vehicle also detects the signboards and traffic signals to move properly on road without
causing any kind of accidents.
• All the object detection (like building detection, signboards and traffic light detection) is done precisely by the Pixy2 camera.
• This camera detects the colour code on the objects. Apart, from the Pixy2 camera, we also use the IR sensors for detecting the
roadside barriers and other vehicles on road.
• All the sensors are controlled by Arduino Mega2560.
• So, this vehicle comes out to be pretty handy. In real world scenario, the bigger version of this autonomous vehicle can be used
to deliver the products to the customer without human intervention.
• We can increase the safety of vehicle, The system will detect the distance between two vehicles moving in the same lane, in the
same direction and alert the driver whenever he or she is in danger range using a microcontroller and ultrasonic sensor

6. BLOCK DIAGRAM

7. HARDWARE REQUIREMENTS
• Arduino Mega
• Lcd display
• IR Sensors
• Ultrasonic sensor
• Wifi Modules
• Motor Drive
• Gps Receiver
• Gsm Module
• Vehicle
• Camera
• Power Supply

8. ARDUINO MEGA
• Arduino board is an open-source microcontroller board which is based on Atmega 2560 microcontroller.
• It has 54 digital input/output pins (of which 15 can be used as PWM outputs), 16 analog inputs, 4 UARTs
(hardware serial ports), a 16 MHz crystal oscillator, a USB connection, a power jack, an ICSP header, and a
reset button.
• The pin configuration of this Arduino mega 2560 board is shown below. Every pin of this board comes by a
particular function which is allied with it. All analog pins of this board can be used as digital I/O pins. By using
this board, the Arduino mega projected can be designed.

9. ARDUINO MEGA

10. PIXY2 CAMERA
• We are using Pixy2 CMUcam5 Smart Vision Sensor for detecting the buildings and sign boards on
the roadside of the city. Pixy2 camera is a smart video camera with onboard image processor chip
NXP LPC4330. Pixy2 camera can be used with any microcontroller board (like Arduino, Raspberry
Pi, etc.)
• It also uses color-based object detection with tracking algorithm (we us this feature of Pixy2 to
detect buildings). It can process entire image frame 60 times per second and it also remembers up
to 7 different color signatures.
• The application for controlling the Pixy2 camera is called Pixy-Mon. The Pixy2 has a variety of
connections that can be used to connect it to a computer, microcontroller or microcomputer.

11. CAMERA MODULE

12. LCD DISPLAY
• A 16x2 LCD display is very basic module and is very commonly used
in various devices and circuits. These modules are preferred over
seven segments and other multi segment LEDs.
• This is a basic 16 character by 2-line display. Black text on Green
background. Utilizes the extremely common HD44780 parallel
interface chipset.
• The display is named 16×2 LCD because it has 16 Columns and 2
Rows. it can be displayed (16×2=32) 32 characters in total and each
character will be made of 5×8 Pixel Dots.

13. 16X2 LCD DISPLAY

14. ULTRASONIC SENSOR
• The ultrasonic sensor (or transducer) works on the same principles as a radar system. An
ultrasonic sensor can convert electrical energy into acoustic waves and vice versa.
• The acoustic wave signal is an ultrasonic wave traveling at a frequency above 18kHz. The
famous HC SR04 ultrasonic sensor generates ultrasonic waves at 40kHz frequency.
• Then triggered, the ultrasonic sensor generates eight acoustic (ultrasonic) wave bursts and
initiates a time counter. As soon as the reflected (echo) signal is received, the timer stops.
The output of the ultrasonic sensor is a high pulse with the same duration as the time
difference between transmitted ultrasonic bursts and the received echo signal.

15. ULTRASONIC SENSOR

16. GSM MODULE
• Global Standards for Mobile Communication (GSM) is a set of standards for Second Generation
(2G) cellular networks. The GSM SIM 800 module uses any network provider’s SIM to
communicate over the telecommunication network
• The GSM modem is serially interfaced with the controller with the help of MAX 232. Here max
232 acts as driver which converts TTL levels to the RS 232 levels. For serial interface GSM
modem requires the signal based on RS 232 levels. The T1_OUT and R1_IN pin of MAX 232 is
connected to the TX and RX pin of GSM modem
• The module is supplied with continuous energy (between 3.4 and 4.5 V) and absorbs a maximum
of 0.8 A during transmission.

17. GSM MODULE

18. GPS RECEIVER
• The Global Positioning System (GPS) is a satellite-based
navigation system made up of at least 24 satellites.
• The heart of the module is a NEO-6M GPS chip from u-blox. It
can track up to 22 satellites on 50 channels and achieves the
industry’s highest level of sensitivity i.e. -161 dB tracking, while
consuming only 45mA supply current.
• It allows a reduction in system power consumption by
selectively switching parts of the receiver ON and OFF. This
dramatically reduces power consumption of the module to just
11mA making it suitable for power sensitive applications like
GPS wristwatch.

19. GPS MODULE

20. L293D MOTOR DRIVE
• L293D is a dual H-bridge motor driver integrated circuit (IC). Motor drivers act as
current amplifiers since they take a low-current control signal and provide a
higher-current signal.
• This higher current signal is used to drive the motors.
• L293D contains two inbuilt H-bridge driver circuits. In its common mode of
operation, two DC motors can be driven simultaneously, both in forward and
reverse direction.
• The motor operations of two motors can be controlled by input logic at pins will
rotate it in clockwise and anticlockwise directions, respectively.

21. L293D

22. CONCLUTION
• In this paper, the autonomous electric vehicle is proposed which can
detect the roadside buildings to reach the destination.
• The object detection is done by Pixy2 camera which uses the color
configuration of the object to detect. In order to recognize the objects, the
Pixy2 camera assign the color signatures to the object.
• We have to design the signboards and traffic lights which can be detected
by the Pixy2 camera for autonomous vehicle to perform accordingly.
• Apart from the delivery purpose, object detection technology of this vehicle
could be used by the blind person as virtual eye to guide them on the
roads and also, they can use this technology to reach the shops or malls
or any essential locations.