A Smart Driving Assistance System to Elevate the Driving

Experience of Drivers in Sri Lanka

18-018

Software Requirements Specification

Nuwan Kodagoda

Kiruthiga Balendran

BSc. (Hons) in Information Technology

Department of Software Engineering

Sri Lanka Institute of Information Technology

Sri Lanka

May 2018

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A Smart Driving Assistance System to Elevate the Driving

Experience of Drivers in Sri Lanka

18-018

Software Requirements Specification

(SRS documentation submitted in partial fulfilment of the requirement for the Degree

of Bachelor of Science Special (honors)

In Information Technology)

BSc. (Hons) in Information Technology

Department of Software Engineering

Sri Lanka Institute of Information Technology

Sri Lanka

May 2018

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DECLARATION

I declare that this is our own work and this SRS does not incorporate without

acknowledgement any material previously submitted for a degree or diploma in any

other university or Institute of higher learning and to the best of our knowledge and

belief it does not contain any material previously published or written by another

person except where the acknowledgement is made in the text.

The supervisor/s should certify the SRS report with the following declaration.

The above candidate is carrying out research for the undergraduate dissertation under

my supervision.

……………………………………….. …..…...………….………………

Signature of the supervisor Date

……………………………………….. …..…...………….………………

Signature of the co-supervisor Date

Name Student ID Signature

B. Kiruthiga IT15135308

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TABLE OF CONTENTS DECLARATION ......................................................................................................... 3

INDEX ......................................................................................................................... 6

LIST OF FIGURES ..................................................................................................... 7

LIST OF TABLES ....................................................................................................... 8

1 Introduction .......................................................................................................... 9

1.1 Purpose .......................................................................................................... 9

1.2 Scope ............................................................................................................. 9

1.3 Definitions, Acronyms, and Abbreviations ................................................. 10

1.4 Overview ..................................................................................................... 10

1.4.1 Main goals ............................................................................................ 10

1.4.2 Specific goals ....................................................................................... 11

1.4.3 Users .................................................................................................... 11

1.4.4 Organization of SRS ............................................................................ 11

2 Overall Descriptions .......................................................................................... 12

2.1 Product perspective ..................................................................................... 13

2.1.1 System interfaces ................................................................................. 15

2.1.2 User interfaces...................................................................................... 15

2.1.3 Hardware interfaces ............................................................................. 15

2.1.4 Software interfaces ............................................................................... 15

2.1.5 Communication interfaces ................................................................... 15

2.1.6 Memory constraints ............................................................................. 16

2.1.7 Operations ............................................................................................ 16

2.1.8 Site adaptation requirements ................................................................ 16

2.2 Product functions ......................................................................................... 16

2.2.1 High level diagram of lane departure warning system ........................ 17

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2.2.2 Use case diagram of lane departure warning system ........................... 17

2.2.3 Use case scenarios ................................................................................ 18

2.3 User characteristics ..................................................................................... 19

2.4 Constraints ................................................................................................... 19

2.5 Assumptions and dependencies ................................................................... 19

2.6 Apportioning of requirements ..................................................................... 20

3 Specific Requirements ....................................................................................... 21

3.1 External interface requirements .................................................................. 21

3.1.1 User interfaces...................................................................................... 21

3.1.2 Hardware interfaces ............................................................................. 21

3.1.3 Software interfaces ............................................................................... 21

3.1.4 Communication interfaces ................................................................... 21

3.2 Classes/Objects ............................................................................................ 22

3.3 Performance requirements ........................................................................... 22

3.4 Design constraints ....................................................................................... 23

3.5 Software system attributes .......................................................................... 23

3.5.1 Reliability ............................................................................................. 23

3.5.2 Availability .......................................................................................... 23

3.5.3 Security ................................................................................................ 23

3.5.4 Maintainability ..................................................................................... 23

3.6 Other requirements ...................................................................................... 23

4 Supporting information ...................................................................................... 24

4.1 References ................................................................................................... 24

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INDEX

Android .............................................................................. 9, 10, 12, 13, 14, 15, 19, 21

Camera ......................................................................................... 13, 15, 16, 19, 20, 21

Canny Edge Detector ................................................................................................. 13

Dashed lines ......................................................................................................... 12, 14

Drivers ............................................................................................ 9, 10, 11, 12, 19, 23

Hough Transform algorithm ...................................................................................... 13

Image Processing algorithms ..................................................................................... 20

Lane boundaries ....................................................................................... 11, 13, 14, 23

Lane crossings .......................................................................................... 10, 13, 14, 16

Lane departure.............................................................................. 10, 11, 13, 16, 17, 22

Lane departure warning ............................................................................................. 13

Lane Detection ................................................................................. 8, 9, 11, 12, 14, 24

Lane separator ............................................................................................................ 13

Low light .............................................................................................................. 12, 14

NDK ..................................................................................................................... 10, 21

OpenCV ............................................................................................................... 15, 21

Solid line .................................................................................................................... 13

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LIST OF FIGURES

Figure 1 - Lane detection ........................................................................................... 15

Figure 2 - High level diagram of the component ....................................................... 17

Figure 3 - Use case diagram of the component .......................................................... 17

Figure 4 - Enabling lane tracking ............................................................................... 21

Figure 5 - Class diagram of the component ............................................................... 22

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LIST OF TABLES

Table 1- Definition for the terms used in SRS ........................................................... 10

Table 2- Glossary of Acronyms ................................................................................. 10

Table 3- Comparison of Lane Detection Applications .............................................. 14

Table 4- Use case scenario 1 ...................................................................................... 18

Table 5 - Use case scenario 2 ..................................................................................... 18

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1 Introduction

1.1 Purpose

The purpose of Software Requirement Specification (SRS) is to provide a

comprehensive description to the Lane Detection component of Smart Driving

Assistance System. It will be used to assist in research study, design, system

development and testing. This document gives a clear and precise details of functional

and non-functional requirements of the component. The connection between the

functionalities and the technical aspect of design is discussed in detail in this

document.

This document specifies various kinds of interfaces such as system interfaces, user

interfaces, software interfaces and includes constraints, limitations under which the

system should work. The product work flow with the performance requirements and

the system attributes are also incorporated to the document.

The targeted audience of this document are the supervisor Mr. Nuwan Kodagoda, co-

supervisor Ms. Disni Sriyaratna who guide us throughout the research and

development of our project, project coordinators, developers, testers and end users.

1.2 Scope

This document covers the requirements of the Lane Detection in detail so that to

provide a guide to the developers in designing and building the solution. The scope of

the SRS is also to describe the tools and techniques that are going to be used in

developing this component. It is bounded to elaborate the technologies referred in the

implementation of this section. The document addresses how the process flows by

using the architecture diagram, what constraints are used to build the module and how

the quality attributes benefit the system. Further, it specifies how the system should be

accessed and the hardware and network consumption when it is launched.

Drive Assist is an Android mobile application which guides the driver to look out for

road signs, keep an eye for pedestrians, assess a safe speed and track the lane on the

road. It is developed as a solution to assist the drivers who need support in places of

difficulty and emergency. Using this system, the driver will be assisted to take smart

decisions in the long journey and this results in reducing the cause of accidents.

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1.3 Definitions, Acronyms, and Abbreviations

Table 1- Definition for the terms used in SRS

Term Definition

Android NDK Using native code to write algorithms to

improve speed

Android Open CV A standard C++ library used for

computer vision applications

Table 2- Glossary of Acronyms

Acronym / Abbreviation Definition

SRS Software Requirement Specification

GPS Global Positioning System

NDK Native Development Kit

GB Giga Bytes

RAM Random Access Memory

1.4 Overview

Smart Driving Assistance System is an Android application which is beneficial for the

drivers who need a guide to assist them in the long journey. The main tasks of Drive

Assist are to alert drivers to oncoming pedestrian crossings and road signs beforehand,

analyze a safe speed that should be followed at several points and to detect the lanes

while tracking the position of the vehicle and warn the driver on lane departure.

Finally, a voice guide is aided from the application to achieve its tasks.

1.4.1 Main goals

• Providing a guide to support the drivers in their long journey and to keep

them alerted to avoid oncoming dangers.

• Advising the drivers who take up new routes to oncoming road signs,

pedestrian crossings and assessing their speed and be aware of any lane

crossings.

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1.4.2 Specific goals

Specific objectives of Lane Detection are listed below

• Identifying lane boundaries and separators to detect lane by considering

several environmental factors.

• Alert the driver using a voice guide on lane departure

1.4.3 Users

The users of the application are the drivers who need a guide to assist their journey.

These drivers are both regular commuters and long journey travelers.

1.4.4 Organization of SRS

This SRS is mainly concerned on the research component ‘Lane Detection’. The

document is mainly organized into four chapters. The first chapter gives an outline on

this document and specifies the purpose, scope and structure of the document.

The second chapter contains an overall description of the system while explaining the

product perspective with interfaces, constraints and limitations. Further, it describes

the product functions and informal requirements of the system and focuses on the

assumptions and dependencies.

The third chapter is ‘Specific Objectives’ which discusses about the specific

requirements of the system. It describes the external interfaces that communicate with

this system and explains on the non-functional requirements. Final chapter includes all

the supporting information such as references and appendices in this document.

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2 Overall Descriptions

In a long journey, high level of concentration and the necessity of assistance are very

much needed for drivers. In situations like driving in a new route, a lone driver will

need assistance and might need support in places of difficulty and emergency. A guide

who suggests on average speed to be taken at the bends, forewarns of the nearby road

signs and pedestrian crossings, alerts when the vehicle is departing from the lane and

directs on the path and navigations would be a great advantage to the drivers.

There are systems that provide the drivers with some of the above-stated guidance.

These systems help to solve some of the issues faced by the drivers and they reduce

the level of causing accidents in minor level. Thus, the proposed system is there to

bind all the major difficulties addressed by the drivers and to be a guide to assist in the

long journey to make smart decisions. This will help in reducing the cause of accidents

and ensures that drivers are obeying the law.

The proposed system is a smart driving assistant which will be built on Android

platform. The key tasks of this application are to assess safe speed, forewarn the driver

to oncoming pedestrian crossing and road signboards and track the lane and warn the

driver on lane departures.

Lane Detection

Observing lane discipline is an essential safety measure on the road. Paying more

attention to the lane position is essential as there are so many accidents take place.

Sometimes, it is very easy to identify the lanes using human eyes. However, at certain

situations such as poor road lines, shadows cast from trees and buildings, parked

vehicles and low light areas it is difficult [1]. The following are the main essential cues

in detecting lanes for a smart driving.

• Lane boundaries - They are identified by different shapes and colors. These

identifiers may vary from solid lines through dashed lines. In Sri Lanka, these

line marks subject to change. Some places in our country use white and orange

whereas some use yellow.

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• Lane departure warning - An alert which tries to make a road driving safer and

prevent accidents related to a moving vehicle outside of its lane due to driver

inattention. The idea behind this is to notify a driver in a situation when a

vehicle is moving outside of its lane but this movement is not desired by a

driver [2].

Lane detection algorithms are implemented to identify lane boundaries and separators

so that to calculate the position of the vehicle on the road. The steps that are followed

in the real-time lane detection process are as follows.

1) Video acquisition

2) Matrix down sampling and set Region of Interest

3) Line detection

4) Lane detection

5) Lane tracking

6) Warn the driver on lane departure

Vision-based approach is used for video acquisition. In this project, we will be using

Android phone camera instead of an external camera to capture the video stream to be

used as an input to the system. The region of the lane boundaries is focused by

removing the other unwanted area in the frame. Edges are identified by an algorithm

called Canny Edge Detector. Then the feature extraction is done. The main feature that

is extracted are road lines and this is detected by Hough Transform algorithm. Finally,

paths of the lanes are detected and the position of the vehicle is tracked. As a result,

warnings are given to the driver on lane crossings.

2.1 Product perspective

There are few number of products developed using smartphone video camera and used

for real-time detection. The iOnRoad [3] was developed to run on both Android and

iOS platforms. One of the main functions of this application is lane detection. The

drawback that we figured in this app is that it detects only the solid line and warns the

driver whenever crossing a solid line. The aCoDriver 5 [4] is an Android app

developed to warn the driver when the vehicle tries to cross the lane separator.

However, this application is designed to detect lanes in Europe only.

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Even though, there are existing products like iOnRoad and aCoDriver 5, they limit

themselves in showing some important features. In most of the roads, lane separators

are drawn in dashed lines and lane boundaries are drawn in solid lines. Moreover, the

paint of the lines will be faded and detecting lanes would not be an easy task. Some

researchers have explained on how to detect lanes from a video clip which is not done

at real-time. Although there are some systems which is used for lane detection but

identifies only the straight lines.

Table 3- Comparison of Lane Detection Applications

Existing Products Comparison

iOnRoad

This application mainly focuses on collision warning

and lane detection.

Similarities

Both the applications do a real-time lane detection and

identify solid lines at night time and low light. They

alert the user on lane crossings.

Drawbacks in the

application

Solution in the

proposed system

Fails to identify dashed lines Identifies all type of

lines

aCoDriver 5

An Android application which assesses speed limits,

does distance controlling and lane detection.

Similarities

Both the applications identify all types of lines and

warn the user on lane crossings.

Drawbacks in the

application

Solution in the

proposed system

Fails to detect lines at night

time and low light

Provide assistance at

any time of the day.

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Warns the driver with only

audio alerts

Warnings are given in

both audio and video

modes

2.1.1 System interfaces

Lane detection component doesn’t have any communication with other systems or

other components. Therefore, it doesn’t have any system interfaces.

2.1.2 User interfaces

Figure 1 - Lane detection

2.1.3 Hardware interfaces

Lane detection module is a mobile application which acquires the video from its rear

facing camera. Therefore, it doesn’t requisite any special hardware except a

smartphone with 8MP rear-camera.

2.1.4 Software interfaces

The component needs Android 5.0 or above to run the system. As the lane detection is

done at real time, processing the frames and detecting the lanes are done from

Android’s OpenCV.

2.1.5 Communication interfaces

Lane detection system can be worked in offline mode. Hence, there is no need of an

active internet connection.

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2.1.6 Memory constraints

A minimum of 1GB RAM with a storage space of 100MB is required by the

application to run it effectively. 200MB of space is needed to install the application

from Google Play Store.

2.1.7 Operations

• Drive Assist system will be available in Google Play Store. Therefore, users

should download the application and install it in their smart phone.

• The placement of the phone should be properly set so that the rear camera

would capture the clear view of the lanes

• User should set the volume of the smart phone to an appropriate volume to hear

the lane departure warnings.

2.1.8 Site adaptation requirements

The user doesn’t need to do any specific training for this component to run. Frames

analyzation and lane detection are done by the system itself. The user only needs to

toggle the activation of lane detection module before he starts the journey.

2.2 Product functions

The lane detection component acquires the image frames from the rear camera and

analyzes the frames. Image processing techniques are applied to the frames to find the

lane markers on the road. Then lane detection is done to identify the current lane of

the driver. Finally, driver is assisted with the warnings on any lane crossings.

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2.2.1 High level diagram of lane departure warning system

Figure 2 - High level diagram of the component

2.2.2 Use case diagram of lane departure warning system

Figure 3 - Use case diagram of the component

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2.2.3 Use case scenarios

Table 4- Use case scenario 1

Use case ID UC_1

Use case name Start tracking lanes

Goal in context User’s current lane is tracked

Pre-condition The application is started

Post-condition None

Primary actor Driver

Secondary actor None

Main flow

Step Action

1 User clicks on the icon

to start the lane

detection

2 The current lane on

which the user

travelling is identified

3 User departs from the

current lane

4 Extend (Get alert)

Table 5 - Use case scenario 2

Use case ID UC_2

Use case name Get Alert

Goal in context User gets a warning

Pre-condition The application is started

Post-condition None

Primary actor Driver

Secondary actor None

Main flow Step Action

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1 The user’s lane is

detected

2 User receives an audio

of an alert

2.3 User characteristics

The Android application, Drive Assist is mainly targeted on drivers. The

characteristics of a driver are as follows

• A driver license with knowing the basic rules and regulations that must be

followed on the road are essential.

• Ability to understand English

• Ability to operate an Android application

2.4 Constraints

• Running all four components, which include two real time tracking

functionalities might slow down the performance

• Bad weather conditions would be an obstacle to identify the lane trackers

• The rear facing camera of android phone should be 8MP to obtain a higher

definition of video stream.

• The application will be designed only in English language

• System failures may occur due to network failure or power failure

2.5 Assumptions and dependencies

Certain assumptions are required in this application

• A valid driver’s license is needed and the driver knows how to drive a vehicle

• Drivers should be aware to handle the mobile application

• Other objects that cover the lane markings should not be presented on the

road

• A minimum of more than 1GB of RAM is required

Certain dependencies related to lane detection module are as follows

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• Video stream should be obtained from the phone camera buffer

• The video should be processed using Image Processing algorithms to identify

lane markers

2.6 Apportioning of requirements

The major functions of the component and its outcomes won’t change. However, the

technologies and some methodologies mentioned in this document might change in

order to provide more feasible and accurate product.

Section 1 and 2 of this document describe the requirements which are also referred as

primary specifications. Section 3 is referred as desirable requirements. These

requirements are to be implemented in this release if possible, but are not committed

to by the developers. It is anticipated that they will be part of future release. 'Optional

requirements' will be implemented at the discretion of developers.

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3 Specific Requirements

3.1 External interface requirements

3.1.1 User interfaces

Figure 4 - Enabling lane tracking

When the user opens the application, the above ‘Enable Lane Tracking’ interface will

appear. The icon on the top left corner should be selected to enable the lane tracking

process. Once it is selected by the user, it will detect the lane as shown in figure 1 in

section 2.1.2 in which the user is travelling by marking the lane separators.

3.1.2 Hardware interfaces

The component will be running in Android smart phone which uses its rear camera to

acquire the image frames to do a real-time lane detection. The camera module will be

connected with Android NDK to do the processing.

3.1.3 Software interfaces

Lane detection component is built in Android. It doesn’t have any connection with the

server. All the line identification and drawing lane markers on the video require high

computational power. Therefore, Android NDK is used in which C++ along with

OpenCV handle the process.

3.1.4 Communication interfaces

The software module doesn’t require any internet connection to retrieve or update data

since the data gathering happens inside the Android platform itself.

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3.2 Classes/Objects

The class diagram below shows various classes that interact with the Lane Departure

Warning System. Classes are shown in rectangular boxes with the attributes and

operations they may perform. Lines show the association between the classes.

Figure 5 - Class diagram of the component

3.3 Performance requirements

Capacity:

• The system is built on mobile platform. Therefore, processor speed of

1.6GHz, 1GB of RAM and the storage of minimum 32GB are required to do

a real-time lane detection.

Response time:

• The system will track the lanes in real-time with no delay.

User interface:

• The user interface of the lane departure warning system displays the over-

layered path of the lane within one second.

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3.4 Design constraints

Along with identifying lanes, departure warnings should be given to the user which

don’t interrupt the concentration of drivers but provide an appropriate assistance in

his journey. The user should also be able to toggle the activation of the lane detection

module.

3.5 Software system attributes

3.5.1 Reliability

In a real time driving environment, identifying lanes and giving departure warnings

should be accurate. Algorithms are designed in a way that track the correct path in

which the user is travelling.

3.5.2 Availability

The lane detection module will be available for 99.99% as no data is retrieved from

the server. However, the maintenance would be required at the initial stage for more

accuracy.

3.5.3 Security

No security related to data privacy is required for the lane detection module as no data

is saved to identify the lanes. However, data privacy mechanisms are imposed to other

modules to protect the location, speed and other details.

3.5.4 Maintainability

The system should be maintained in a way so that further enhancements could be

plugged in to the system easily. Components should be built using modularity concepts

to achieve future goals with minimal effort.

3.6 Other requirements

A better visualization of the lane boundaries would give a clear image to the driver on

his path. Improving the performance of the app by achieving higher frames per second

rate.

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4 Supporting information

4.1 References

[1] M. Aly, "Real time Detection of Lane Markers in Urban Streets", Intelligent

Vehicles Symposium, IEEE, pp. 7-12, 2008.

[2] A.B.Hillel, R.Lerner, D.Levi and G.Raz, “Recent Progress in Road and Lane

Detection - A survey”, Machine Vision and Applications, vol. 25, Apr. , pp. 727 - 745,

2014

[3] iOnRoad Augmented Driving Lite. iOnRoad, 2011.

[4] aCo Driver 5. EvoTegra GmbH, 2013.