An Experimental Study of Feasible Deployment of V2I ...

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An Experimental Study of Feasible Deployment of V2I Technology using OLSR in

Road Bends

by

Jayasingam Adhuran

A thesis report submitted in partial fulfillment of the requirements for the

degree of Master of Engineering in

Microelectronics and Embedded Systems

Examination Committee: Dr. Mongkol Ekpanyapong (Chairperson)

Dr. Matthew N Dailey

Dr. Surachet Pravinvongvuth

Nationality: Sri Lankan

Previous Degree: Bachelor of Science in Engineering in Electronics Engineering

Asian Institute of Technology, Thailand

Scholarship Donor: H.M King’s Scholarship

Asian Institute of Technology

School of Engineering and Technology

Thailand

July 2017

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ACKNOWLEDGMENTS

First and foremost I put forth my thanks to His Excellency, King of Thailand and the royal

family for sponsoring my education at AIT. I would like to thank Department of Industrial

Systems Engineering and AIT for the values instilled in me through master education. I

would like to express my sincere and heartfelt gratitude to my advisor Associate Profes-

sor Mongkol Ekpanyapong for his continuous guidance and support rendered towards the

betterment of the progress and perfection of my thesis.

I also extend my special thanks to my committee members Dr. Matthew N. Dailey and

Dr.Surachet Pavinvongvuth for their valuable suggestions and guidance.

My sincere gratitude to Dr. Adriano Taveras, Associate Professor in University of Minho,

Portugal for assistance, guidance and assessment provided for my thesis during my stay in

Portugal. Also I would like to thank the students Embedded Systems Research Group of

University of Minho for their continuous support.

I would also like to express my deep sense of gratitude to the secretary Khun Pornpun Pug-

sawade, and lab supervisor Mr. Chatchai Pruetong for the support while conducting the

experiments. My sincere thanks to office of facilities and assets management of AIT and

landscape unit of AIT for the support provided for test field setup.

My gratitude to my friends and fellow researchers who constantly helped me with testing,

provision of tools and on field namely, Miss. Kaavya Rathnakumar, Mr. Amila Sri Mad-

hushanka, Mr. Sachithra Kodipily, Mr. Pruek Vanna-Iampikul, Mr. Malika Rathnayake,

Mr. Sabeethan Kanagasingam, Mr. Nipuna De Silva, Mr. Theekshana Wickramathilake,

Mr. Damith Thilakarathne, Mr. Miyuru Weeratunga, Mr. Malaka Sirinimal, Mr. Purinda

Abeykoon, Mr. Prabath Wimalaratne, Mr. Pujitha Kodipily, Mr. Janitha Premasiri, Mr.

Ruvinda Masimbulla, Miss Ana Rita, Mr. Riccardo Teixeira, and Mr. Tiago Gomes.

Last but not the least, my indebted gratitude to parents, friends and well-wishers who have

always been my strength, encouragement and mental support whenever I needed it, without

which I would not have progressed.

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ABSTRACT

This research investigated a solution to reduce road accidents at road bends by providing

prior information to the vehicles drivers regarding details of the bend. The research imple-

mented a prototype with a RSU and two vehicle units and deploy a V2I communication using

IEEE 802.11 network. Communication between moving and non-moving objects which rel-

ative speeds may be greater was established. OLSR networking was implemented between

vehicles. The RSU consisted of a mini radar which detected vehicles, their coordinates and

speed. The RSU transmit the location, speed and direction of travel to the vehicle and ve-

hicle receive instruction regarding the bend. Thus, it provides a warning to the oncoming

vehicles approaching the bend. The test was carried out inside AIT premises and results

have substantiated the prototype.

KEYWORDS - V2I, OBU, RSU, OLSR

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TABLE OF CONTENTS

CHAPTER TITLE PAGE

TITLE PAGE i

ACKNOWLEDGMENTS ii

ABSTRACT iii

TABLE OF CONTENTS iv

LIST OF FIGURES vi

LIST OF TABLES ix

1 INTRODUCTION 1

1.1 Background 1

1.2 Problem Statement 2

1.3 Objectives 3

1.4 Limitations and Scope 3

2 LITERATURE REVIEW 4

2.1 Intelligent Transportation System 4

2.2 MANET 5

2.3 VANET 5

2.4 OLSR Routing Protocol 10

2.5 Raspberry Pi 12

2.6 Radar 14

2.7 Global Positioning System (GPS) 14

3 METHODOLOGY 15

3.1 Analysis Phase 15

3.2 The Overview of the Design 19

3.3 Design Setup 21

3.4 System Design 22

3.5 Hardware 24

3.6 Software 31

3.7 Threshold Values 37

3.8 GPS Distance Calculation 38

3.9 Testing 38

3.10 Implementation 40

3.11 Full Duplex System 46

4 RESULTS AND DISCUSSION 57

4.1 Results and analysis 57

4.2 Discussion 75

5 CONCLUSION AND RECOMMENDATION 78

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REFERENCES 79

APPENDICES 81

vi

LIST OF FIGURES

FIGURE TITLE PAGE

Figure 2.1 Intelligent transportation system 4

Figure 2.2 VANET Architecture - V2V communication and V2I communication 5

Figure 2.3 DSRC standard in Japan, Europe and US 6

Figure 2.4 The test setup for different scenarios 7

Figure 2.5 The summary of the result of the study 7

Figure 2.6 Key purposes of VANET architecture 8

Figure 2.7 The system of the V2I design with UMRR 9

Figure 2.8 The method flow of the V2V design using Android smart phones 9

Figure 2.9 OLSR socket flow - forward 11

Figure 2.10 OLSR socket flow - receive 11

Figure 2.11 The topology to identify the range 12

Figure 2.12 The self-healing topology 13

Figure 2.13 The multihop topology 13

Figure 2.14 Radar object detection method 14

Figure 3.1 RSU case diagram 15

Figure 3.2 RSU state diagram 16

Figure 3.3 RSU sequence diagram 17

Figure 3.4 OBU case diagram 18

Figure 3.5 OBU state diagram 18

Figure 3.6 OBU sequence diagram 19

Figure 3.7 Overview of the design 20

Figure 3.8 Overview of the RSU setup 21

Figure 3.9 Overview of the OBU setup 22

Figure 3.10 System Design 23

Figure 3.11 Raspberry Pi 2 Model B 24

Figure 3.12 TP Link USED based Wi-Fi adapter 25

Figure 3.13 smart micro Type 29 mini radar 26

Figure 3.14 U-blox NEO-6M GPS Module 27

Figure 3.15 I2C 1602 2 x 16 LCD 27

Figure 3.16 RS 485 to ethernet converter 28

Figure 3.17 33,000mAh power bank from Proda 29

Figure 3.18 Pin diagram of Raspberry Pi 2 Model B 29

Figure 3.19 Pin assignment for GPS Raspberry Pi connection 30

Figure 3.20 LCD connection with the Raspberry Pi 30

Figure 3.21 Pin assignment for LCD connection with the Raspberry Pi 30

Figure 3.22 TM configurator software 31

Figure 3.23 Thread priority diagram of RSU 33

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Figure 3.24 Thread priority diagram of OBU 34

Figure 3.25 Flow diagram of Send Message thread of RSU 34

Figure 3.26 Flow diagram of Get radar data thread of RSU 35

Figure 3.27 Flow diagram of Receive Message thread of OBU 36

Figure 3.28 Flow diagram of Display Message thread of OBU 37

Figure 3.29 Test setup to measure current drawn 39

Figure 3.30 Pin assignment for test setup to measure current drawn 39

Figure 3.31 Completed look of RSU and two OBUs 40

Figure 3.32 Implemented OLSR network - an image from wireshark 40

Figure 3.33 Topology table of OLSR network 41

Figure 3.34 Testing Location 41

Figure 3.35 Iperf output 42

Figure 3.36 Ping output 42

Figure 3.37 Data logged from current sensor 42



Figure 3.40 RSU setup during Test 43

Figure 3.41 Display of no offense message 44

Figure 3.42 Display of alert message 44

Figure 3.43 Display of speed warning message 44

Figure 3.44 Display of lane offense message 44

Figure 3.45 Functional flow diagram of RSU 46

Figure 3.46 Functional flow diagram of OBU 47

Figure 3.47 Thread priority diagram of RSU - Radar based full duplex system 48

Figure 3.48 Thread priority diagram of RSU - Gps based full duplex system 48

Figure 3.49 Flow diagram of Get Radar Data thread of RSU 49

Figure 3.50 Flow diagram of Send Message thread of RSU 50

Figure 3.51 Flow diagram of Receive Message thread of RSU 51

Figure 3.52 Thread priority diagram of OBU - Radar based full duplex system 53

Figure 3.53 Thread priority diagram of OBU - Gps based full duplex system 53


Figure 3.55 Flow diagram of Display Message thread of OBU 55


Figure 4.1 RTT with Distance and Speed for case Maximum Speed less 57

than 20 kmph


than 30 kmph


than 40 kmph


than 60 kmph

Figure 4.5 Distance travelled by vehicles during Experiment 1 of RSU and 64

one OBU on road

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one OBU on road


Two OBU on road


Two OBU on road


Two OBU on road

Figure 4.10 OBU Current consumption against Distance 75

Figure 4.11 OBU Current consumption against Speed 75

Figure A.1 Distance summary of Experiment 1 of RSU and Two OBU on road 83

Figure A.2 Speed summary of Experiment 1 of RSU and Two OBU on road 83





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LIST OF TABLES

TABLE TITLE PAGE

Table 3.1 Comparison between technology used in the implemented system 45

and implemented DSRC solution in US

Table 3.2 Comparison between implemented method and literature 45

Table 4.1 Connectivity loss for case Maximum Speed less than 20 kmph 58




Table 4.5 IPERF 62

Table 4.6 Summary of the Experiment 1 of RSU and one OBU on road 63

Table 4.7 Summary of the Experiment 2 of RSU and one OBU on road 65

Table 4.8 Summary of the Experiment 1 of RSU and Two OBU on road 66



Table 4.11 Summary of the Experiment 1 of gps system with RSU and one 72

OBU- on road


OBU- on road


OBU- on road

Table 4.14 Summary of the Experiment of full duplex system with RSU and 73

two OBUs - off field


two OBUs- on road


one OBU- on road

Table 4.17 Performance comparison between three systems 77

Table 5.1 Direction summary of Experiment 1 of RSU and one OBU on road 81

Table 5.2 Direction summary of Experiment 2 of RSU and one OBU on road 82

Table 5.3 Direction summary of Experiment 1 of RSU and Two OBU on road 84



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CHAPTER 1

INTRODUCTION

1.1 Background

Intelligent transportation systems (ITS) can be defined as a group of technological solutions in telem-

atics designed to improve the safety and efficiency of terrestrial transportation. The concept of ITS

deeply focuses into finding solution to rules and regulation compliance system, smart road navigation

system, accident avoidance and monitoring system, traffic management system, parking system, and

etc. Utilize of technology to establish communication between moving vehicles may find a solution to

avoid accidents. Short range communication can be accomplished to deploy inter vehicular commu-

nications using IEEE 802.11 protocols. Wireless access in vehicular communications and dedicated

short range communication (DSRC) standards deploy IEEE 802.11p protocol for V2V communica-

tions. This is a wireless communication in frequency range of 5.9 GHz, to minimize interferences

in traffic congested areas. However, several studies have deployed IEEE 802.11n protocols in this

regard successfully. WiMAX can be deployed to extend the radius of access to few kilometers.

Mobile ad hoc network (MANET) is a continuously self-configuring network to keep the mobile de-

vices wirelessly connected. Vehicular ad hoc network (VANET) which is a sub class of Mobile ad

hoc network (MANET) is the key network deployed to communicate between moving vehicles and

nearby vehicles and objects. There are three types of MANET protocols, they are proactive, reactive

and hybrid. In proactive each node has to maintain routing information to the other nodes and they

keep it up to date by exchanging route updates throughout the network. Proactive protocols include

Destination-Sequenced Distance-Vector (DSDV), Optimized Link State Routing Protocol (OLSR)

and etc. Reactive routing protocol, discovers a route when a node wants to send a packet to a

certain destination. Reactive protocols include protocols such as Dynamic Source Routing (DSR)

and Ad-Hoc On-Demand Distance Vector (AODV). Hybrid routing protocols is a combination of

proactive and reactive characteristics, where usually the network is partitioned and depending on the

zone, proactive or reactive protocol may be used. Hybrid protocols include Zone outing Protocol

(ZRP), Zone-Based Hierarchical Link State (ZHLS) Routing Protocol, Hybrid ad hoc Routing Proto-

col (HARP), and etc.

There has been several studies that investigated into the possible deployments of these routing protocols

using simple hardware equipment. OLSR protocols have been successfully deployed and tested with

mobile ad hoc nodes. These mobile ad hoc nodes can be implemented using raspberry pi boards and Wi-

Fi adapters. Raspberry pi boars with adapted Wi-Fi, can behave as receivers and transmitters in a

network. V2I or V2V communications comes with on board unit (OBU) or the vehicle unit which is

fixed in the vehicles. Some road side units (RSU), have similar setup as OBU. The OBU may some- times

be equipped with GPS, compass sensors as well. V2V communication is setting up continuous talk

between two OBUs and V2I would be that between OBU and RSU. There are implementations of

mini radar in RSU to detect vehicles that have no OBU.

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1.2 Problem Statement

The concept of ITS explains the significance of communication in the terrestrial transportation, that is

communication between moving vehicles (V2V), and moving vehicles and immobile objects (V2I).

This concept further expands to support vehicle to vehicle to infrastructure (V2V2I) communication.

There has been several studies that investigated into the possible deployment of V2V communications

and V2I communications. The studies include scenarios, such as traffic congested areas, following

vehicles, approaching vehicles, distant communications and etc. V2V or V2I supporting units must

be implemented on the vehicles or road side units (RSU).

Ad hoc networking facilitates wireless communication between moving nodes. VANET protocols

can be deployed to implement a V2V or a V2I network. OLSR, a link state or table driven proactive

algorithm would be ideal in V2V or V2I communication as nodes want to continuously transmit data

to the neighboring nodes or vehicles. There are few studies that suggest the use of mini radar to detect

the vehicles without V2V supporting units. However, those come with a cost of financial escalation

and legal limitation. The simple implementation of the system could use micro controllers and Wi-Fi

adapters to implement the system.

Although, there are implementation of several methods to deploy V2I communications, they have

not been practiced in many roads. IEEE 802.11p which is the dedicated network for short range

communication may take time to be implemented all over the world. A low cost and a viable solution

is always preferred to communicate between moving vehicle and non-moving objects. Also, it is

imperative that this low cost system addresses the continuity in communication where which is the

main problem in VANET communication. Relative motion may trigger the Doppler Effect, especially

in IEEE 802.11n network which operates in 2.4 GHz band with channel bandwidth around 20 MHz.

Road accidents are one of the main reasons for loss of lives of people, animals and birds. It is caused by

several reasons, one of main reasons being speed. Speed thrills, but kills is a famous phrase used by

several authorities to warn the drivers to be cautious on the road. There are several road signs

implemented to give warnings. These have reduced the accidents. It is better to have an intelligent

system that would inform the driver about the oncoming road bends as out of speed control at the

bends where there is no visibility of on coming have caused several accidents. It is always a noble

cause to reduce human causalities in whichever way possible.

This research will investigate a solution to reduce road accidents at road bends where vehicles are not

visible to each other (no-line of sight) by providing prior information to the vehicles drivers regarding

details of the bend. The research will implement a prototype with a RSU and two vehicle units and

deploy a V2I communication using IEEE 802.11 network. The main objective would be to establish a

communication between moving and non-moving objects which relative speeds may be greater. The

RSU will transmit the location, speed and direction of travel to the and vehicle will receive instruction

regarding the bend. Thus, it will provide a warning to the oncoming vehicles approaching the bend.

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1.3 Objectives

This research propose a method to find out a solution for accident avoidance using V2I technology.

The following objectives are formulated in-order to achieve the overall objective.

• To investigate a solution to prevent road accidents.

• To make the vehicle drivers aware of the oncoming bent and maximum speed that can be

travelled.

• To design a V2I communication using Wi-Fi and establish communication between a moving

object and an immobile object.

• To develop a prototype to support the design.

• To determine the location, speed and the direction of travel of moving vehicles and communi-

cate data between the vehicle and the RSU.

• To evaluate the performance of the deployed prototype.

1.4 Limitations and Scope

• The design will focus on two vehicle scenario with a fixed RSU at a road bend.

• The moving objects will directly communicate with the RSU only.

• The system will incorporate a central point managing vehicles approaching from opposite di-

rection and provide necessary warnings.

• The testing of the system will be implemented at an interference low/free site.

• It is assumed that there is only one vehicle approaching the RSU at a time from one direction.

i.e. there is sufficient time between two consecutive vehicles that approach the RSU.

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CHAPTER 2

LITERATURE REVIEW

This study attempts to propose a solution for accident avoidance in road bents using V2I technology.

Consequently the focus of the literature review is to examine previous studies conducted in relation

technologies used VANET architecture and implemented methodologies.

2.1 Intelligent Transportation System

According to European Telecommunications Standard Institute (ETSI) (ETSI,n.d.), Intelligent trans-

portation system known as the ITS include telematics and types of communications in vehicles,

among vehicles and between vehicles and infrastructures. Before Intelligent Transportation Systems

(ITS), the United States developed, planned and built the interstate highway system. Until 1980s

the development was more focused on highway transportation. To address the emerging issues with

accidents and traffic congestion, focus turned towards intelligent systems. In 1990 a concept of In-

telligent Vehicle Highway Systems (IVHS) was proposed in workshop held Dallas, Texas. Later, this

was named ITS (Harding et al.,2014). From the early 1990s, ITS researchers have been heavily

funded all over the world. ITS are not only restricted to road transportation. They apply to water,

railway and air modes transportation as well.

Figure 2.1: Intelligent transportation system

(ETSI,n.d.)

Dedicated Short-Range Communications (DSRC) provide communications between the vehicle and

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the road side infrastructures, commonly used in toll booths to charge electronic fees. Wireless Com-

munications Systems dedicated to Intelligent Transport Systems provide a. interconnectivity between

vehicles at a band of 5 GHz. In Railways, GSM signaling is used on high speed railways and con-

ventional railways when interoperating near national borders. In aeronautics, air traffic control is

one good example of ITS services. Maritime applications support various applications that include

navigation and routine maritime operations

2.2 MANET

A wireless Ad-Hoc network is a self-configuring network which does not rely on preexisting man-

aged infrastructure. A study (Contreras,2015) describes a Mobile Ad-Hoc Network (MANET) as

a collection of mobile devices (nodes or routers) dynamically creating a network, without the using

any existing network configuration that is already made. Since the devices on this network are free

to move, the network support the existence of the connection via connecting devices by single or

multiple hops. There are few issues with MANET protocols. Reliability of the wireless connection,

bandwidth of the channel, fading due to Doppler Effect, security and power source.

2.3 VANET

Figure 2.2: VANET Architecture - V2V communication and V2I communication

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VANET which is a subclass of MANET is the main architecture behind deployment of inter vehicular

communication. V2V, vehicle to vehicle communication, V2I vehicle to infrastructure communica-

tion and V2V2I vehicle to vehicle to infrastructure communications are some of VANET networks

(Tiwari & Kushwah,2013). The deployment of VANET, have been researched on different platforms

to addressing various problems.

2.3.1 Different VANET architecture

There are certain standards developed to implement VANET architecture and reduce possible inter-

ference. DSRC for VANET can be achieved by IEEE 802.11p network according to these standard

which operates in 5.9 GHz band. The following figure 2.3 shows the DSRC standard in Japan, Europe

and US.

Figure 2.3: DSRC standard in Japan, Europe and US (Su et al.,2012)

However, the studies following have shown possible deployment VANET architecture using other

networks.

A research (Sumra et al.,2011) proposes a short message service (SMS) system named vehicular

SMS system (VSS). SMS was used to transmit information between vehicles via base transceiver

stations (BTS). The information was mainly based upon safety. In addition, parking availability was

also discussed in the paper. The communication was based on 2G communication. This system did

not require OBU.

A paper (Al Masud, Mondal, & Ahmed,2009) proposes a combination of a RFID system and an

infrastructure to establish a communication system to provide vehicle safety. A different research

(Kubota, Okamoto, & Oda,2006) additionally includes pedestrian safety compared to the study

concentrated only on the vehicle safety. RSU and OBU detected and repeated the RFID tags in V2V

and V2I communications.

A study (Haider & Dongre,2015)proposes a methodology to establish V2V communication using

visible light to avoid vehicle collisions. The system uses a LED transmitter and a camera receiver,

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which incorperates an optical communication sensor. The leading vehicle contains the LED trans-

mitters and the following vehicles detects application of brakes using intensity variations subjected to

processing of the image received.

A research servey (Tiwari & Kushwah,2013)focused on implementing V2V using wi-fi and V2I

using WiMAX communication. The research concluded that deployment of V2V, V2I and V2V2I

communication networks were used to transfer data with reliability. Also, it added that WiMAX was

used for long range communication and Wi-Fi for short range communication. The study achieved

300 meter range with external antennas. The performance of Wi-Fi (IEEE 802.11n) and WiMAX

(IEEE 802.16d) implemented in different VANET architectures, V2V and V2I respectively was eval-

uated in a research study (Mojela & Booysen,2013). Also, the study investigated in to the combined

performance in V2V2I architecture. The study considered scenarios such as vehicle following, vehi-

cles crossing, line of sight (LOS) and non-line of sight (NLOS) communications for WiMAX. Wi-Fi

was always considered to be in the line of sight. The following figure 2.4 shows the test set up used

in the study.

Figure 2.4: The test setup for different scenarios (Mojela & Booysen,2013)

Figure 2.5: The summary of the result of the study (Mojela & Booysen,2013)

The summary of the result of the study is shown in the following figure 2.5. In case of vehicles

crossing, the relative motion between vehicles is larger compared to the vehicle following case. The

result depict that there has been a greater jitter, lesser data transfer in the cases where relative motion

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had been greater. In addition, lesser speed of vehicles have been achieved, thus proving the impact

of relative motion in V2V technology. However, a significance speed has been achieved. This paper

fails to mention the structure of the implemented methodology with components in specific.

2.3.2 Purposes of VANET architecture

It is known that V2V or V2I architectures are used for different purposes, such as traffic regulation,

accident avoidance, surveillance, traffic violation detection and etc. Jia and Ngoduy (Jia & Ngo-

duy,2016) proposed a solution for the cooperative driving system by bridging the gap between flow

traffic model and communication approaches on road. Also, a research (Zheng et al.,2016) proposes

an algorithm to be used to eliminate the collision probability to find a solution to improve the sig-

nal control system during congestion conditions. A study (Lee, Tseng, & Wang,2008) proposed

electronics toll fee collection using vehicle positioning. Currently, E toll collection in highways

is a common implementation, which is an extension of VANET architecture. Approach for loca-

tion identification and vehicle tracking (Thangavelul, Bhuvaneswari, Kumar, Senthilkumarl, &

Sivan,2007) and an on road surveillance (Chen, Tseng, & Syue,2014) using VANET architecture

have also been investigated. A research study (Surugiu & Alexandrescu,2013) analysed the use of

VANET architecture and concluded traffic congestion updates, accident detection and accident warn-

ings as the key purposes. The following figure 2.6 describes the key used of VANET architecture.

Figure 2.6: Key purposes of VANET architecture (Surugiu & Alexandrescu,2013)

2.3.3 Similar Models

A journal (Vlastaras, Abbas, Leston, & Tufvesson,2013) proposes a methodology to establish a V2I

communication to reduce occurrence of accidents. The research incorporates universal medium range

radar (UMRR) which is built inside the RSU to detect vehicles and their speed which have no OBU and

communicate with vehicles that have an OBU. The OBU is made up of raspberry pi and the

communication medium has been IEEE 802.11p device. The following figure 2.7 shows the system.

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Figure 2.7: The system of the V2I design with UMRR (Vlastaras et al.,2013)

A different model (Su et al.,2012) was proposed the use of Wi-Fi access point (AP)/client technology

supported by Android 2.2 and higher in smart phones to set up V2V communication and provide low

cost solution. Android supports single hop communications only (Zhuang, Baskett, & Shang,2013).

Therefore, MANET routing protocols are not applied on this. The advantage of this method is the non- use

of OBU in vehicles. The connection was only established when there was a need to communicate. The

method flow in this research is shown in the figure 2.8 below.

Figure 2.8: The method flow of the V2V design using Android smart phones (Su et al.,2012)

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2.4 OLSR Routing Protocol

OLSR is a type of proactive MANET table driven protocol based on link-state protocols. OLSR uses

the concept of Multipoint Relay (MPR) and Multipoint Relay Selector (MPR Selector), where each

node chooses few nodes as neighbors such that they are two nodes away to pass the information to.

In OLSR, each node broadcasts Hello messages to find its neighbors and link states. The, topology

control (TC) messages are sent to the nodes to build the routing table (Clausen & Jacquet,2003).

There are four system messages of the OLSR protocol which are sent periodically.

• HELLO - used for neighbor and link detection, MPR calculation and other things.

• TC- used to a subset of its link/neighbour set.

• MID- used to tell that a node runs OLSR on multiple interfaces.

• HNA -used to announce connectivity to external/non-olsr networks.

The following figure shows the packet structure of OLSR

The OLSR message contains OLSR header and the payload (message). The parameters are as follows:

• Message Type - Type of the message. For custom messages the space 127-225 can be used.

• Vtime - The time the information in this message should be considered valid.

• Message Size - including message header, in bytes.

• Originator Address - IP address of the OLSR message creator node/first OLSR node.

• Time To Live (TTL) - A value describing how many hop this message should be forwarded.

This field is decremented by 1 every time the message is forwarded.

• Hop Count - Incremented by 1 every time this message is forwarded.

• Message Sequence Number - The sequence-number of this message. Should be incremented

by 1 every time a node generates a message.

• Message - The message desired to be sent. This includes the whole IP packet.

2.4.1 OLSRd

OLSRD is a deamon to run OLSR protocols.OLSRd facilitates OLSR for local applications proving

all the OLSR features. Andreas Tonnesen had written open source code enabling to implement OLSR

in Linux. OLSRd plugins runs separately from the application, deploying OLSR protocols. Olsrd

supports loading of dynamically linked libraries, called plugins. There are two main reasons for

using the OLSR plugins. One is to send broadcast traffic using OLSR, other is to change the OLSR

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functionality without changing the source code of OLSRd. Plugin passes variables and functions to

the OLSrd and OLSRd initiate plugin and provide the registered and routed data. Peer to peer plugin will

be used to broadcast udp packets via OLSR nodes.

The following diagrams are socket functional flows of packet sending and receiving using Peer to

peer plugin where application to the plugin can be interfaced via loopback interface of the respective

system.

Figure 2.9: OLSR socket flow - forward

Figure 2.10: OLSR socket flow - receive

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2.5 Raspberry Pi

The Raspberry Pi (RPi) (Raspberry Pi Foundation,n.d.) is a low-cost Linux computer developed in

the United Kingdom by the Raspberry Pi Foundation. The raspberry pi can be used to build prototypes

and test bed for electronics project which is greatly supported by its hardware and operating system

(Raspbian). The studies have shown that raspberry pi is a good platform to implement MANET

architecture. OLSR protocol can be implemented using pi and it supports different Wi-Fi adapters.

A research study (Lumbantoruan, KOMURO, & SAKATA,n.d.) evaluated the performance of

OLSR protocols in ad hoc networks. Raspberry pi with TP Link WN722N, IEEE 802.11n 2.4 GHz

range supported USB based Wi-Fi adapters were used as ad hoc nodes. OLSRD was installed in pi.

The testing topologies used are shown in the following figures 2.11, 2.12 and 2.14.

Figure 2.11: The topology to identify the range (Lumbantoruan et al.,n.d.)

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Figure 2.12: The self-healing topology (Lumbantoruan et al.,n.d.)

Figure 2.13: The multihop topology (Lumbantoruan et al.,n.d.)

The results showed OLSR protocols using raspberry pis can do multi hop communication and have self-

healing capabilities. Also, it was found that 210 meters communication was successful.

A paper (Contreras,2015) showed the performance of an IEEE 802.11 ad-hoc network at different

levels by means of an experimental study. The ad hoc network was deployed using raspberry pis

and Wi-Fi adapters. An ad-hoc network in Raspberry Pi was deployed, establishing the combina-

tion chipset/driver to accomplish the communication between the nodes, where Atheros and Ralink

chipsets proved to be ad-hoc capable. The study investigated into the current consumption which was

about 400 mA, communication range which had a maximum range of 150 meter with support of 4

dBi antenna, throughput and delay in performances as well.

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2.6 Radar

Radar is an object-detection system that utilize radio waves to determine the range, angle, or velocity of

objects (Bureau,2013). It is used to detect aircraft, ships, spacecraft and many more. A radar

transmits and receive electromagnetic waves and processes the signal to identify the character of the

object. This information can be used to find, range and speed of the object. This research will use a

mini version of the radar with smaller range to detect vehicles.

Figure 2.14: Radar object detection method

2.7 Global Positioning System (GPS)

GPS is a space based navigation system that provide location and time in any weather condition.

General use of GPS for position determination is by using the track points (latitude and longitudes).

The average speed can be calculated by getting the track points during a given time interval (Chalko &

MSc,2007). The following equations Equation 2.1 and Equation 2.2 can be used to calculate the

instantaneous speed and average speed of a moving vehicle respectively.

∆l dl

v = lim∆→0 ∆t

= dt

(Equation 2.1)

t ̧ vdt

L ¸

dl

v̂ = 0

= 0

= L

(Equation 2.2) T T T

where ∆l is the distance covered within a time ∆t. L and T are the average distance covered and

average time taken respectively.

15

CHAPTER 3

METHODOLOGY

3.1 Analysis Phase

There are no direct users involved in the system. The users will get to see only the system messages.

However, the two system RSU and OBU function independently communicating with each other.

Each system has its own tasks and responsibilities.

3.1.1 RSU

3.1.1.1 Use Case Diagram

RSU does the following functions.

• Check if any vehicle is detected

• Get Radar Data

• Send Message to OBU

The following diagrams shows the use case diagram of RSU system.

Figure 3.1: RSU case diagram

16

3.1.1.2 RSU State Diagram

The basic functionality of RSU system can be represented by state diagrams. RSU is the main con-

troller of the system. The radar detects if a vehicle is coming. If vehicle is detected, the system reads

data from the reader followed by the determination of distance, speed and assign a temporary ID to

the new vehicle. It sends out the message. There are three main states, IDLE, Get Radar Data, Send

Message. Also there are three substates to send message state. These substates represent four differ-

ent messages to be sent. Regular message will be sent with normal data to a single OBU. Warning

messages refer to lane offense message and over speed message. The alert message will be multi-

casted to all the OBU’s if a one vehicle is not controlling speed or committing a lane offense and

that vehicle will receive a warning message. Warning message and Alert message will receive high

priority, followed by initial message and regular message. The following diagram shows the states of

RSU system.

Figure 3.2: RSU state diagram

3.1.1.3 RSU Sequence Diagram

The following sequence diagram shows the links between each element in the RSU system and OBU

system.

17

Figure 3.3: RSU sequence diagram

3.1.2 OBU

3.1.2.1 Use Case Diagram

An OBU in the system does the following functions.

• Check if any message is received

• Receive Message from RSU

• Display the message received

• Get GPS reading

The following diagrams shows the use case diagram of RSU system.

18

Figure 3.4: OBU case diagram

3.1.2.2 OBU State Diagram

The basic functionality of OBU system can be represented by state diagrams. OBU is the mobile

unit fixed in the vehicles. A message is received from RSU. The message could have been received,

as instructed by the RSU or transferred via OLSR nodes. The message may be directed to node

in OLSR systems. Therefore, it is imperative to distinguish between the messages sent to vehicles

before displaying them. The ID of the message sender must be well noted. There are three main

states, IDLE, Receive message and Display Message. The following diagram shows the states of

OBU system.

Figure 3.5: OBU state diagram

3.1.2.3 OBU Sequence Diagram

The following sequence diagram shows the links between each element in the OBU system and RSU

system. To match the identity of the vehicle as seen by radar, the received distance from radar can

be matched with the distance calculated with gps coordinates with provision of tolerance level to

compensate inaccuracy of readings from gps.

19

Figure 3.6: OBU sequence diagram

3.2 The Overview of the Design

This design focuses on communication between two vehicles and an RSU, V2I communication. The

vehicles that travel in the opposite directions communicate through RSU. In addition, the vehicles

communicate with the RSU placed at the point of the bend (round about) via IEEE 802.11 network (Wi-

Fi). The overview of the design is illustrated in the figure 3.7.

20

Figure 3.7: Overview of the design

The RSU will be fixed near the road bend and will communicate to the vehicles that enter the Wi-

Fi range of the RSU. It is expected to cover a range around 30-100 meters. Also, there may be a

maximum of three nodes at a time.

21

3.3 Design Setup

3.3.1 RSU

Figure 3.8: Overview of the RSU setup

RSU will

• Detect the oncoming vehicles.

• Establish communication with OBU.

• Detect vehicles speed.

• Distinguish between vehicles approach and leave the bend.

• Instruct the oncoming vehicles (vehicles approach the bend) about the speed control at the

bend.

• Act as a mediator between two nodes.

22

3.3.2 OBU

Figure 3.9: Overview of the OBU setup

OBU will

• Poll to communicate with RSU

• Receive the position coordinates from the position sensors.

• Display the received details from the other vehicles and RSU.

3.4 System Design

The RSU is the main controller of the system. The radar in cooperated in the RSU detects the vehicles

and their speed and distance to the bent. Also assign a unique ID to each vehicle. This information

is sent via RS-485 to the converter which converts rs-485 to Ethernet and data is sent to the laptop

containing TM configurator software which decodes radar messages. The rs-485 to Ethernet converter

will act as TCP client while the laptop act as server. The decoded message is then live streamed to the

Wi-Fi unit with raspberry pi which broadcast the message to the OBUs. This is only a unidirectional

communication. Therefore it can be categorized as half duplex system. OBU upon reception of the

message tries to verify the ID with support of distance calculated from gps based data. The display

on the OBU gives out the necessary information to the driver.

23

Figure 3.10: System Design

24

3.5 Hardware

3.5.1 Micro controller - Raspberry Pi 2 Model B

Figure 3.11: Raspberry Pi 2 Model B

• 900MHz Quad-core ARM Cortex-A7 CPU

• 1GB RAM

• Micro SD card slot

• 40 GPIO pins

• Ethernet port

• 4 x USB 2.0 ports

• MicroUSB power port

• Audio/video jack;

Raspberry Pi will function as the controller of the both RSU and OBU systems deplyed separately.

RPi will be installed with Raspbian OS. Also olsrd package will be installed to implement OLSR in

the deployed network.

3.5.2 Wi-Fi Adapter

Wireless IEEE802.11n USB Adapter TL-WN722N is the proposed wireless adapter which will be

used as the transmitter and receiver node. USB communication will be implemented to communicate

25

with the microcontroller. The Wi-Fi adapter will be directly interfaced to the OLSRd in order to carry

out OLSR protocol. This particular Wi-Fi adapter is chosen due to its compatibility in the Ad-Hoc

mode. This will be connected to USB 1 of Raspberry Pi. An external 5 dB gain antenna was attached.

Figure 3.12: TP Link USED based Wi-Fi adapter

• USB 2.0

• 2.4 GHz operating frequency

• Wireless standard IEEE 802.11

• 150Mbps of maximum data rate

• Power Saving designed to support smart transmit power control

3.5.3 Mini Radar

A mini radar will be used for detection vehicles and determine the speed of vehicles. Can bus will

be the optimal communication medium to connect this to the the controller. Can BUS shield may be

required in this process to interface the Mini Radar to the controller. Type 29 Smartmicro Mini Radar

will be used in this project. The characteristics of the mini radar are as follows:

• Stop bar detection for close range detection

• Advance detection for long range detection

• Loop replacement (non-intrusive detection)

26

• Queue length measurement

• Speed measurement

• Full Range of 160m

• Typical range 25-130 meters

• Accuracy ±0.25m.

Figure 3.13: smart micro Type 29 mini radar

3.5.4 GPS

U-blox NEO-6M GPS module with antenna and build-in EEPROM sensor will be used to get the

position of the vehicle. UART interface will be used to connect to the microcontroller. It provide

NMEA sentences. NMEA is a combined electrical and data specification for communication between

marine electronics such as echo sounder, sonars, anemometer, gyrocompass, autopilot, GPS receivers.

A deamon is used to get the decoded data from NMEA sentenses received at UART port. The gps has

an accuracy ±3m. Its resolution is 1 Hz.

27

Figure 3.14: U-blox NEO-6M GPS Module

3.5.5 Display

A Simple 1602 2 x 16 LCD has been used. PC8574 back module has been connected to it facilitating

I2C interface with RPi. A logic level converter has been used to shift voltage levels.

Figure 3.15: I2C 1602 2 x 16 LCD

28

3.5.6 RS 485 to Ethernet Converter

USR-TCP232-304 is a low-cost serial RS485 Ethernet converter, which can realize bidirectional

transparent transmission between RS485 and local Ethernet or Internet. It is integrated with TCP/IP

protocol. It will take rs485 data from radar and send ethernet based communication to the radar data

interpreter. This device will act as TCP clint to the radar data intepreter which will be the TCP server.

Figure 3.16: RS 485 to ethernet converter

3.5.7 Power unit

A mobile power unit can be used. 33,000mAh power bank from Proda can be used for this purpose.

• Output 5V 2.1A

• Ultra reliable A+ Lithium-Ion Battery with over 500 Battery Charge-cycles

• Short-circuit protection - Automatic shutdown if a short circuit detected

29

Figure 3.17: 33,000mAh power bank from Proda

Also two rechargeable Li-Ion battery were used to power up the radar and rs485-ethernet converter

respectively

3.5.7.1 Pin Assignment

The following figure is the pin diagram of Raspberry pi 2 model B

Figure 3.18: Pin diagram of Raspberry Pi 2 Model B

The following table is the pin assignment to connect GPS module to raspberry pi

30

Figure 3.19: Pin assignment for GPS Raspberry Pi connection

The following figure shows the connection of LCD display to the Raspberry Pi. a logic level shifter

is used in between to compensate the different levels of voltages.

Figure 3.20: LCD connection with the Raspberry Pi

The following table shows the pin assignment for connection of LCD display with the Raspberry Pi

Figure 3.21: Pin assignment for LCD connection with the Raspberry Pi

31

3.6 Software

• Raspberry Operating System Raspbian Wheezy

– It will be the operating system used in all the pis used in the project. It will facilitate the

network configurations and deployment of OLSR protocols.

• OLSRD Optimized Link State Routing Demon

– The implementation of mesh networking in pi. It will help setting up the nodes (MRP)

in the network established.

• TM Configurator - This is windows opering system based software which directly interact with

Radar and decode the CAN data and livestream the decoded data via TCP/IP sockets.

Figure 3.22: TM configurator software

• C++ - Programming Language that will be used for application.

The linux c++ application uses UDP socket programming to send, multicast and receive

message. UDP uses a simple connectionless transmission model with a minimum of

protocol mechanism. IP multicast a method of sending Internet Protocol (IP) datagrams

to a group of interested receivers in a single transmission, will be used to send alert

messages. It is a form of point-to-multipoint communication.

• GPSD - It is a linux based gps deamon which reads the NMEA sentences of gps data from the

UART port and decodes it. The application can read the values at the point of request.

Message Structure

• ID

32

• message

• speed

• distance

• direction

The total OLSR Packet size can be approximated.

Total OLSR Packet Size = 160 bits (IPV4 header) + 64 bits (UDP header) + 128 bits (OLSR header)

+ 32 bits * 5 (Message Size) = 384 bits

(Equation 3.1)

3.6.1 Peer to peer plugin

Peer to peer plugin will be used to broadcast udp packets via OLSR nodes. The plugin need to be

initialized with the IP address of the destination group and ports. The packet live hops need to be

initialized before starting the OLSRD.

3.6.2 Wireless Interface

The wireless interface is the OLSR interface in the system. It needs to be configured to be in Ad-Hoc

mode by changing the network interface parameters in the Raspberry Pi. The parameters are the IP,

netmask, mode, ssid and channel. The channel must be set for low interference channel based on Wi-

Fi interference in the field of deployment.

3.6.3 Thread Design

The application will be written in threads for both RSU and OBU. RSU is the main controller of the

system. RSU has three threads including the main function. Get Radar data thread gets the decoded

radar data and from ethernet, decodes the string, set up the message, processes the messages to be

sent. From the message sent from radar, the direction of travel can be determined by the vehicle’s x-

direction of travel and the lane offence by setting the radar to be in par the intersection lane. The send

message threads send the data immediately. OBU has three threads including the main function. The

receive thread waits for 1.5 seconds to receive a data. However, if data is received, it is instantly decodes

the message and sets up right flags to be displayed. The display thread continuously displays

information with two seconds delay giving sufficient time for the reader. Main funtion in both RSU

and OBU which creates the other threads, configures OLSR plugins, start the olsrd and configure

network interfaces.

33

The provided messages as follows.

• No offense by any party Since communication is established a message about road bent and

maximum speed allowed in the road bent are provided.

• Over speed if the vehicle with a particular OBU travels at a speed that is greater than the speed

allowed, a speed warning message with vehicle speed and distance to the bent is given.

• Lane offense - if the vehicle with a particular OBU travels in the wrong lane approaching the

bent is given an out of lane message with vehicle speed and distance to the bent is given.

• Any offense by others If other vehicles commit any offence, a warning would be given with

speed of the other vehicle and its distance to the bent.

The figure 3.23 shows the priority assigned to the RSU threads. The figure 3.24 shows the priority

assigned to the OBU threads.

Figure 3.23: Thread priority diagram of RSU

34

Figure 3.24: Thread priority diagram of OBU

The following flow diagrams show the logic flow of the respective threads

Figure 3.25: Flow diagram of Send Message thread of RSU

35

Figure 3.26: Flow diagram of Get radar data thread of RSU

36

Figure 3.27: Flow diagram of Receive Message thread of OBU

37

Figure 3.28: Flow diagram of Display Message thread of OBU

3.7 Threshold Values

The maximum speed limit that is allowed in the bent is limited. The testing assumes 40 kmph as the

speed limit allowed. Threshold distance would be the minimum distance that can be detected by the

Mini radar. The minimum distance that Mini Radar detects is 25 m and maximum is 160 m and

optimum detection ranges from 25 m - 130 m.

38

3.8 GPS Distance Calculation

Haversine formula will be used to determine the distance between two nodes.

d = 2Ratan2(√

a, √

1 − a) (Equation 3.2)

where a = sin2 (θ2−θ1 ) + cosθ1cosθ2sin2 (β2−β1 ) 2 2

(θ2, β2)(θ1, β1) coordinates pair and R is radius of the earth.

3.9 Testing

Testing must be done to verify the performance of the system. This requires the results of four

parameters which are, current drawn, data throughput, connectivity and communication range.

System performance can be measured by the finding out the messages transfer rate from RSU and

messages received rate by OBU and the ability to provide necessary messages on the OBU display.

The following tests will be conducted to do the parameter analysis.

Iperf 2.0.5, software for linux is a platform to to measure the IPC traffic which could be used to get the

datarate, packet loss and jitter of the UDP packets.

Communication Range can be found out by logging the gps coordinates at the time of initial message

received from RSU.

Connectivity can be tested by pinging between RSU and OBU and logging the distance and speed of

the OBU simultaneously.

Current drawn by the system can be found by using INA219 Breakout board, Current Sensor to be

connected to RPi. The system RPI can be connected as the load and current reading can be obtained by

logging data in test RPi via I2C interface connected to the load RPi as shown in the figure.

39

Figure 3.29: Test setup to measure current drawn

The following figure shows the pin assignment of the test setup.

Figure 3.30: Pin assignment for test setup to measure current drawn

The following cases will be included in the performance test.

• Case 1: One car approaching the RSU.

• Case 2: One car leaving RSU.

• Case 3: Two cars approaching RSU from opposite direction

• Case 4: Two cars leaving RSU in the opposite direction.

40

3.10 Implementation

The rasperrypis were installed with raspbian wheezsy operating system. They were installed with

olsrd. The three raspperrypis were connected with Wi-Fi adapter and was configured with Ad-Hoc.

They were given an IP with the same subnet to support olsr network. The components were assembled as

per design and the code was implemented in c++. The RSU unit was connected to the laptop with TM

configurator software.

Figure 3.31: Completed look of RSU and two OBUs

Wireshark, a Wi-Fi sniffer software was used to verify the nodes connected using olsr network.

Figure 3.32: Implemented OLSR network - an image from wireshark

The topology table of olsr network was received using Textinfo plugin.

41

Figure 3.33: Topology table of OLSR network

The prototype was tested inside the premises of Asian Institute of Technology, Thailand as shown

in the figure 3.34. The RSU was fixed at coordinates 14.080327 degrees latitude and 100.613495

degrees longitude. The test drive was carried out on the road that in the line of sight of the RSU. The

test route had speed limitations due to the placements of the speed breakers. The tests were carried

at different speeds for connectivity, current consumption and data through put. There was a lot of

speed variations during the tests due to the speed breakers. A constant speed of test vehicles were not

possible.

Figure 3.34: Testing Location

The test was carried out in different ways. The connectivity, data through put and power tests were

carried out with one vehicle and RSU without the use of Radar. Also, the tests were carried out for

performance determination with instances of one vehicle and two vehicles deployed on road. The

data was logged into comma separated value files and text files.

42

Figure 3.35: Iperf output

Figure 3.37: Data logged from cur-

rent sensor

Figure 3.36: Ping output

Figure 3.38: Data logged in RSU

Figure 3.39: Data logged in OBU

43

Figure 3.40: RSU setup during Test

The radar was initially configured to match the road. They are: angle to road (elevation) 3 degrees

down, radar height 5m, angle to road (lateral) 5 degrees, offset 1 meter to the left. The offsets were set

in such a way that, x coordinate position read by radar was along the mid lane of the road facilitating

the detection of lane offense.

44

Figure 3.41: Display of no offense

message

Figure 3.43: Display of speed warn-

ing message

Figure 3.42: Display of no alert mes-

sage

Figure 3.44: Display of lane offense

message

The following table shows a comparison between a journal mentioned in the literature and the imple-

mented system.

Table 3.1: Comparison between technology used in the implemented system and implemented

DSRC solution in US

Technology US (ASTM)

This System

Communication Half Duplex

Half Duplex

Radio Frequency 5.9 GHz

2.4 GHz

Band 75 MHz

20 MHz

Channels

7 1

Transmission Rate 27 mbps

1 mbps

Coverage 1000 meters max 300 meters max

Modulation OFDM DBPSK, DQPSK

Table 3.2: Comparison between implemented method and literature

Journal - (Vlastaras et al.,2013) This System

RSU/OBU Controller Raspberry Pi Raspberry Pi

Use of Mini Radar yes yes

Radar Range 160 m 160 m

Radar typicasl range 25-130 m 25-130 m

Radar Accuracy 0.025m 0.25m

Communication between Radar Data Interpreter and Radar Can Bus RS 485

Use of Radar data interpreter Can shield with interpreter Laptop/Windows Application

Communication between Radar Data Interpreter and Raspberrypi Serial Ethernet TCP/IP

Radio Frequency 5.8 GHz 2.4 GHz

Wireless Communication Protocol 802.11p 802.11g Gain 5dB

Communication between Raspberry pi and wireless device CDC-ECM USB

Transmission Protocol UDP broadcast UDP Multicast

Communication Half Duplex Half Duplex/full duplex

No of Test Vehicles Deployed Simultaneously 1 2

Use of GPS yes yes

GPS Accuracy few centrimeters 3m

Placement of OBU Mounted on top Inside the vehicle

RSU Height 5m 5m

Localization used yes (radar and gps data fused) no (tolerance level applied)

Warning Application used 45 information not available yes

46

3.11 Full Duplex System

In addition to the implementation of the V2I system with half duplex communication, the full duplex

system was also experimented to evaluate its performance. The full duplex system developed as gps

based full duplex system and radar based full duplex system.

The functionality in both systems are similar. However, gps based full duplex system did not use

Radar. The messages were transmitted from the OBU to the RSU. The thread priority in both system

varied. In contrary to Radar based system, gps based system did not have get radar data thread. Gps

based system had receive thread and send thread as the highest priority in RSU and OBU respectively

, while they were assigned lowest and highest in radar system respectively to accommodate the use

of radar information.

The overview of functional flow of RSU and OBU can be described in the following diagrams respec-

tively.

Figure 3.45: Functional flow diagram of RSU

47

Figure 3.46: Functional flow diagram of OBU

Message Structure

• Int ID = 10-99 for RSU, 3 digits for vehicles

• Struct gpsdata {Latitude, Longtitude, UTC Hours, UTC Minutes, UTC Seconds}

• Struct data {dist RSU, dist RSU other, speed mine, speed other, direction other}

• int message

3.11.1 Thread Design

The application will be written in threads for both RSU and OBU. In both of these system, RSU will

use arrays to update, compare and manipulate information regarding nodes. Also, an array is used to

compare the two different IDs generated from radar and node to match them. Further in gps based

system, a random authentication ID will always be generated and then be replaced by the node ID

compared to radar id generated in the radar based system.

3.11.1.1 RSU

In contrary to half duplex system, the message will have proper classification about who receives the

message. Initial message will be sent with an authentication ID to a particular OBU. Regular message

will be sent with normal data to a single OBU. The alert message will be multicasted to all the OBU’s

if one vehicle is not controlling speed nor in lane of travel and that vehicle will receive a warning

48

message. Warning message and Alert message will receive high priority, followed by initial message

and regular message. Arrays will be created to temporarily keep details of vehicle IDs and data and

keep swapping data in the array when necessary. The priority of threads in shown the diagram below.

Figure 3.47: Thread priority dia-

gram of RSU - Radar

based full duplex system


gram of RSU - Gps


Get radar data thread which is only implemented in radar based system decodes, radar messages,

checks if the vehicle is in control speed, in the proper lane on the road and whether vehicle is ap-

proaching RSU and update the vehicle array and ID array. It also turn on the necessary flags. Flow

diagram of the get radar data thread is as follows.

49

Figure 3.49: Flow diagram of Get Radar Data thread of RSU

Send message thread classifies which message to be sent and send them to the particular OBUs. It

also turn of the necessary flags. Flow diagram of the send message thread is as follows.

50

Figure 3.50: Flow diagram of Send Message thread of RSU

Receive data thread, receives the messages from OBU, checks for reply from new vehicle to authenti-

cate and checks the distance of vehicle from RSU to take decision on that. Flow diagram of the send

message thread is as follows.

51

Figure 3.51: Flow diagram of Receive Message thread of RSU

Following are some of the functions that will be used in the threads.

• Check ID Table This function checks if any vehicle ID matches with a selected radar ID in the

ID array

• Create ID Table This function creates the array to enter Radar ID, vehicle ID and the index of

the node of the vehicle/node array

52

• Add ID This function adds new vehicle ID, radar ID and the node index (last index + 1) to the

ID table.

• Delete ID This function removes a vehicle ID element from the ID array

• Update ID This functions changes the index of the nodes stored in each element in the ID

array according to the changes caused in the order of the elements in the Node array.

• Replace ID This function replaced the vehicle ID if an authenticated return ID (5 digit ID) is

returned from a new vehicle/node

• Inside Lane This function creates a two rectangles with coordinates of Upper right corner

and lower left corner (designed for right hand driving) to check if a coordinate of a particular

vehicle is inside the rectangle to check whether the vehicle has crossed the lane.

• Add Node - This function adds new vehicle node and its components in the node array.

• Delete Node - This function removes a node and its components from the node array

• Create Node Array This function creates a node array allowing to store all the details passed

via the message and has a similar structure of the message.

• Get Node Index This functions takes the vehicle ID and finds its index of vehicle/node array

from the ID table.

• Update Node This updates all the components of a node, checks for the speed threshold and

lane cross and new vehicle and set respective flags. If warning or new vehicle flag is raised,

the node 1 will be replaced by the selected node.

3.11.1.2 OBU

OBU is the mobile unit fixed in the vehicles. A message is received from RSU. The message could

have been received, as instructed by the RSU or trasferred via OLSR nodes. The message may be

directed to node in OLSR systems. Therefore, it is imperative to distinguish between the messages

sent to vehicles before displaying them. The ID of the message sender must be well noted. if it is an

authentication ID or the ID of the vehicle, RSU message must be displayed. Otherwise, the distance

to RSU must be displayed. There are five threads, namely the main function, receive message, get

gps data, display message and send message. A list will be used for logging and reading of gps data.

The priority of threads in shown the diagram below.

53


gram of OBU - Radar



gram of OBU - Gps


Receive Message thread will receive the message, and checks for the ID verification and message

type whether they are warning, message, initial message, alert message or a regular message and set

respective flags. Also it updates the new ID. Flow diagram of the receive message thread is as follows.

54

Figure 3.54: Flow diagram of Receive Message thread of OBU

Display message thread checks for the set ID and message flags and display the message on LCD

display. Also, it checks updates from gps reading and continue to verify the messages. The difference

between display thread of radar based system and gps based system is that distance calculation is

based upon radar and gps respectively. Flow diagram of the display message thread of GPS system is

as follows.

55

Figure 3.55: Flow diagram of Display Message thread of OBU

Send message thread simply, reads the message, updates the latest gps entries from GPSD and send

the data. Flow diagram of Send message thread is shown below.

56

Figure 3.56: Flow diagram of Send Message thread of OBU

57

CHAPTER 4

RESULTS AND DISCUSSION

4.1 Results and analysis

The obtained data as comma separated values and text during test was imported to Microsoft Excel.

At instances that data was in two separate files (i.e, RSU and OBU) the time and time difference was

used to compare.

4.1.1 Connectivity

The connectivity test results were obtained by pinging from the OBU to the RSU while travelling at

different speeds. The OBU pings 64 bytes of data every one second and waits for reply. The curves

are plotted for the round trip time of the packets sent while pinging against speed and distance.

Figure 4.1: RTT with Distance and Speed for case Maximum Speed less than 20 kmph

The above test result is obtained from a test carried out to test the connectivity against distance and

58

speed for speed less than 20 kmph. The average speed of this trip was 8 kmph. The connectivity

had been established for 88.49% out of the 304 seconds that was taken during this test for round trip

travel.

Table 4.1: Connectivity loss for case Maximum Speed less than 20 kmph

Packets No of Instances Percentage % Packet Loss Percentage % Contribution to the

total loss %

Total 304 100

35 11.51 100

Above 300 14 4.61

7 50 20

200-300 65 21.38

9 13.85 25.71

150 200 35 11.51

4 11.43 11.43

Less than 150 190 62.5

15 7.89 42.86

The table above is the summary of the packet loss. Although more packet were lost when the OBU

was less than 150 m away from RSU, the percentage loss relative to the packets transmitted during that

region is only 7.89% where as it has significantly increased to 11.43% within a range of 150-200m,

13.85% within 200-300m and reached 50% loss for distance greater than 300m. The maximum RTT

for established connection was 89.7 ms.




59


Packets No of Instances Percentage % Packet Loss Percentage % Contribution to the total loss %

Total 121 100 20 16.5 100

Above 300 12 3.94 8 40 66.66

200-300 35 11.51 5 25 14.28

150 200 14 4.6 4 20 28.57

Less than 150 60 19.73 3 15 5


travel

The table above is the summary of the packet loss. The packet lost observed when the OBU was less

than 150 m away from RSU and the percentage loss relative to the packets transmitted during that

region is 15% where as it has significantly increased to 20% within a range of 150-200m, 25% within

200-300m and reached 40% loss for distance greater than 300m. The maximum RTT for established

connection was 96.9 ms.



60



travel.



Total 177 100 31 17.51 100

Above 300 13 4.27 12 38.7 92.3

200-300 40 13.15 14 45.16 35

150 200 17 5.59 0 0 0

Less than 150 107 35.19 5 16.12 4.67

The table above is the summary of the packet loss. Therefore the packet lost when the OBU was

less than 150 m away from RSU, the percentage loss relative to the packets transmitted during that

region is 16.12% whereas in the range of 150-200m there was 0% loss , within 200-300m there was

a significant increase of 45.16% and while for a distance greater than 300m it was 38.70%. The

maximum RTT for established connection was 80.1 ms.



speed for speed less than 50 kmph. The average speed of this trip was 24.16 kmph. The connectivity

61


travel



Total 86 100 15 17.44 100

Above 300 6 1.97 2 13.33 33.33

200-300 26 8.55 10 66.66 38.46

150 200 13 4.27 2 13.33 15.38

Less than 150 41 13.48 1 6.66 2.43

The table above is the summary of the packet loss. The packet lost when the OBU was less than 150

m away from RSU, the percentage loss relative to the packets transmitted during that region is 6.66%

whereas in the range of 150-200m there was 13.33% loss, within 200-300m there was a significant

increase of 66.66% and while for a distance greater than 300m it was 13.33%. The maximum RTT

for established connection was 75.9 ms.

62

4

Distance

Bytes Sent

IPERF TEST

Bytes Received (KB)

5 mbps Bandwidth

Data Rate (Kbits/s)

Jitter (ms)

Packet Loss (%)

190-260 523 None

120-180 505 497 337 108.939 1.4

35-120 884 864 647 85.457 2.1

The table 4.5 shows the test results of iperf test for testing bandwidth of 1 mbps and 5 mbps. This

test sent 1470 bytes. It was shown that sending 1470 was not successful for distance greater than 200

meters. The full use of bandwidth was not possible as the maximum bandwidth has been used is 977

kbps when the distance to RSU was as close as 30 meters. The bandwidth continue to reduce as the

distance is further increased.

.1.2 Iperf Test

Table 4.5: IPERF

IPERF TEST 1 mbps Bandwidth

Distance Bytes Sent Bytes Received (KB) Data Rate (Kbits/s) Jitter (ms) Packet Loss (%)

260-200 165 None

190-140 446 429 336 23.506 3.9

130-40 609 606 464 55.904 0.24

30-15 1195 1190 977 13.843 0.59

63

4.1.3 Performance Analysis

Table 4.6: Summary of the Experiment 1 of RSU and one OBU on road

Avg speed 7.378769231

Max Distance 131

Max Speed 46

Avg speed 13.33333333

Max Distance 131

Max Speed 46

OBU (ID -33)

RSU (ID -33) 513 28 18.32142857

OBU (ID -33) 260 28 9.285714286 50.68226121

Total No of entries Time elapsed (s) Tx Rate (messages per second) Rx Rate (messages per second) Efficiency (Rx Rate/Tx Rate

RSU 3250 60 54.16666667

OBU 1957 105 18.63809524 34.40879121

64

Figure 4.5: Distance travelled by vehicles during Experiment of RSU and one OBU on road

In this particular experiment, RSU sent 3250 messages at a rate of 54.17 messages per second while

the OBU received the messages at a rate of 18.64 messages per second as efficiency is as low as

34.41%. There have been messages sent from RSU at a rate of 18.32 messages per second regarding

this particular OBU that was deployed in the test. This particular OBU received messages at 9.29

messages per second only. In this particular test, the selected OBU has been approaching the bent.

No of vehicle counted during this experiment were four.

65

Table 4.7: Summary of the Experiment 2 of RSU and one OBU on road

Figure 4.6: Distance travelled by vehicles during Experiment of RSU and one OBU on road

In this particular experiment, RSU sent 19327 messages at a rate of 40.26 messages per second while the

OBU received the messages at a rate of 22.82 messages per second as efficiency is 56.66%. In


RSU 19327 480 40.26458333

OBU 3468 152 22.81578947 56.66466056

Avg speed 5.353184664

Max Distance 174

Max Speed 18

66

this particular test, the selected OBU has been out of sight of the radar. In contrast to the previous

experiment, more vehicles have been counted. No of vehicle detected during this experiment were

twenty.

Table 4.8: Summary of the Experiment 1 of RSU and Two OBU on road

Total No Of Entries Time Elapsed(s) Tx Rate (messages per second) Rx Rate (messages per second) Efficiency (Rx Rate/Tx Rate

RSU 10250 201 50.99502

OBU 1 7424 201 36.93532 72.42927

OBU 2 6873 220 31.24091 61.26266

Avg Speed 6.820195

Max Distance 176

Max Speed 39

OBU 1 (ID - 91)

RSU (ID - 91) 398 20 19.9

OBU 1 (ID - 91) 311 20 15.55 78.1407

Avg Speed 17.88191

Max Distance 126

Max Speed 21

OBU 2 (ID - 91)

RSU (ID 91) 398 20 19.9

OBU 2(ID 91) 301 20 15.05 75.6281

Avg Speed 17.88191

Max Distance 126

Max Speed 21

67

Figure 4.7: Distance travelled by vehicles during Experiment 1 of RSU and Two OBU on road


the OBU1 received the messages at a rate of 36.94 messages per second as efficiency is 72.43%.

OBU2 received the messages at a rate of 31.24 messages per second as efficiency is 61.26%. In this

particular test, the both the OBUs have been following each other. It was also noted that both OBUs

have received the same ID (91). One of the vehicles is indicated by false ID. This may have caused

due to the error in the authentication of the vehicle. No of vehicle counted during this experiment

were twenty seven. It is possible that both vehicle have identified them as ID 91. Radar may have

assigned different IDs. It is also noted that ID 91 and ID 26 have travelled similar distance in the

same direction.

68


Total No of entries Time elapsed (s) Tx Rate (messages per second) Rx Rate (messages per second) Efficiency (Rx Rate/Tx Rate)

RSU 18265 415 44.01205

OBU 1 7159 261 27.42912 62.32184

OBU 2 13813 506 27.29842 62.02488

Avg speed 14.38352

Max Distance 186

Max Speed 56

OBU 1 (ID -47)

RSU (ID -47) 195 11 17.72727

OBU 1 (ID -47) 148 11 13.45455 75.89744

Avg speed 45.33846

Max Distance 130

Max Speed 53

OBU 2 (ID -41)

RSU (ID -41) 441 22 20.04545

OBU 2 (ID -41) 358 22 16.27273 81.17914

Avg speed 6.056689

Max Distance 88

Max Speed 8

69


In this particular experiment, RSU sent 18265 messages at a rate of 44.012 messages per second

while the OBU1 received the messages at a rate of 27.43 messages per second as efficiency is 62.32%.

OBU2 received the messages at a rate of 27.3 messages per second as efficiency is 62.02%. In this

particular test, the both the OBUs have been following each other. There have been messages sent

from RSU at a rate of 17.73 messages per second regarding OBU 1 that was deployed in the test.

OBU 1 received messages at 13.45 messages per second. Also messages have been sent from RSU at

a rate of 20.05 messages per second regarding OBU 2 that was deployed in the test. OBU 2 received

messages at 16.27 messages per second. No of vehicle counted during this experiment were twenty

eight.

70



RSU 7022 207 33.92270531

OBU 1 5265 158 33.32278481 98.23150749

OBU 2 4668 140 33.34285714 98.29067829

Avg speed 23.09242381

Max Distance 179

Max Speed 56

OBU 1 (ID -37)

RSU (ID -37) 466 23 20.26086957

OBU 1 (ID -37) 336 23 14.60869565 72.10300429

Avg speed 15.73221757

Max Distance 98

Max Speed 39

OBU 2 (ID - 35)

RSU (ID - 35) 308 15 20.53333333

OBU 2 (ID - 35) 210 15 14 68.18181818

Avg speed 42.95779221

Max Distance 135

Max Speed 46

71



the OBU1 received the messages at a rate of 33.32 messages per second as efficiency is as high as

98.23%. OBU2 received the messages at a rate of 33.34 messages per second as efficiency is 98.29%.

In this particular test, the both the OBUs have been following each other. There have been messages

sent from RSU at a rate of 20.26 messages per second regarding OBU 1 that was deployed in the test.

OBU 1 received messages at 14.60 messages per second. Also messages have been sent from RSU at

a rate of 20.53 messages per second regarding OBU 2 that was deployed in the test. OBU 2 received

messages at 14 messages per second. No of vehicle counted during this experiment were twelve. The

count is two vehicle less than the actual.

The experimented carried out with RSU and one OBU using gps based full duplex system shows that

message transfer rates obtained in three experiments are as low as 0.28, 0.36 and 0.20 respectively.

The reception rate by the RSU were 0.23, 0.21 and 0.11 respectively. The ID authentication delay

was 2 seconds.

72

Table 4.11: Summary of the Experiment 1 of gps system with RSU and one OBU- on road

Total No of OBU1 messages Time elapsed (s)

OBU 1 52 186

RSU 42 185

Efficiency 80.76923077

OBU 1

Tx Rate 0.279569892

Rx Rate 0.227027027


Authentication Delay (s) 2

Avg speed 10.23076923

Max Distance 374

Max Speed 38



OBU 1 13 36

RSU 7 33


OBU 1

Tx Rate 0.361111111

Rx Rate 0.212121212



Avg speed 15.46153846

Max Distance 277

Max Speed 48

73



OBU 1 27 133

RSU 4 36


OBU 1

Tx Rate 0.203007519

Rx Rate 0.111111111



Avg speed 11.74074074

Max Distance 172

Max Speed 32

Table 4.14: Summary of the Experiment of full duplex system with RSU and two OBUs - off

field

Total No of messages sent Time elapsed (s) No of messages received Time elapsed (s) Authentication delay Tx Rate (messages per second) Rx Rate (messages per second)

RSU 60 50 2 3 1.2 0.666666667

OBU 1 (ID -201) 5 35 58 60 43 0.142857143 0.966666667

OBU 2 (ID -101) 5 35 60 65 45 0.142857143 0.923076923

Avg speed 7.378769231

Max Distance 131

Max Speed 46

The experiment carried out with RSU and two OBU using radar based full duplex system off the

field shows that RSU sent messages at a rate of 1.2 messages per second while OBU 1 received at

0.96 messages per second and OBU 2 received at 0.92 messages per second. OBU 1 and 2 sent

out 5 messages each at 0.14 and 0.14 messages per seconds. RSU received only 2 messages at 0.66

messages per second. There was a huge authentication delay of 43 seconds to authenticate OBU 1

and 45 seconds to authenticate OBU 2.

74

Table 4.15: Summary of the Experiment of full duplex system with RSU and two OBUs- on

road


RSU 216 213 0 1.014084507

OBU 1 (ID -201) 0 164 178 No Authentication 0.921348315

OBU 2 (ID -101) 0 60 65 No Authentication 0.923076923

The experiment carried out with RSU and two OBU using radar based full duplex system on the

field shows that RSU sent messages at a rate of 1.01 messages per second while OBU 1 received at

0.92 messages per second and OBU 2 received at 0.92 messages per second. Since there was no

authentication, there was no message sent out from the OBUs nor RSU received any messages.

Table 4.16: Summary of the Experiment of full duplex system with RSU and one OBU- on

road

The experiment carried out with RSU and one OBU using radar based full duplex system on the field

shows that RSU sent messages at a rate of 1.02 messages per second while OBU 1 received at 0.84

messages per second. Since there was no authentication, there was no message sent out from the

OBUs nor RSU received any messages.

4.1.4 Current consumption

The below figures show the current consumption of the OBU as the OBU needed mobile power units.

Regardless of the distance and speed, the average current consumption has been between 450 - 500

mA.


RSU 151 148 0 1.02027027

OBU 1 (ID -201) 0 121 144 43 0.840277778

75

Figure 4.10: OBU Current consumption against Distance

Figure 4.11: OBU Current consumption against Speed

4.2 Discussion

The system was implemented on the field to verify its functionality. The testing site had very low Wi-

Fi interference. There may have been interference caused from the Wi-Fi emitters that were placed

inside the building. The signal strength may have been reduced as the system units consisted a 5 db

gain antennas only and the OBU was placed inside the car. However, the results show that there has

not been any significant influence of these factors. In addition, there were other factors affecting the

experiments. The test field was not perfect enough to drive a vehicle at a constant speed due to the

76

placement of speed breakers and vehicles that are parked on the road. The vehicles parked on roads

was one of the main reasons why testing vehicles continue to breach the lane limits. Also, higher

speed was not achieved.

The connectivity graphs show that the connectivity of the system remains well above 80% at all

instances with speed under 20 kmph reaching the top with 88.49%. The maximum loss has been

accounted at distances above 200 meters accounting for nearly or greater than 65% of the total loss.

Packet loss for distance less than 150 meters is around 15% of the total loss.

Iperf test show that regardless of the given bandwidth, the maximum attainable has been limited. Ping

test continuously checks on the connectivity whereas the iperf test sends a bulk data at a particular

instance. Iperf test gives the time delay taken for OBU to send the messages to RSU. Since the

networking is OLSR and packets are sent by UDP, it can be assumed the results are valid for vice

versa implementation. Since, the data sent in the system is very small and only two nodes were

used in the test, a greater bandwidth was not required. In case of very large number of vehicles, the

bandwidth optimization may heavily be needed.

Since the radars optimal range is between 25 meters to 130 meters, the connectivity and the through-

put are sufficient for the system for vehicles travelling at a speed less than 60 kmph.

A vehicle travelling at 60 kmph, travels 100 meters in 6 seconds. Therefore it is required to provide

necessary information at least 50 meters prior to the bent, giving sufficient time to make decisions

and avoid accidents. That narrows the limit to 3 seconds. Therefore, it is required to give information as

much as possible. The half-duplex method provides better transfer and reception rates with lowest

recorded reception rate being 9.29 messages per second, lowest transfer rate being around 33 mes-

sages per second and negligible authentication delay as two way communication is not allowed. This

implies that 80% of the time at least 9.29 messages will be transmitted and received in one second.

Although, efficiency of transfer of messages vary between 35 - 75%, except in one case where it

touches 98%, the rate of transfer remains sufficient. The experiments conducted on the road between

RSU and two OBUs show that, transmission rate reduces with increment of average speed. Since

connectivity does not affect the transmission rate, this may have been the delay in processing from

radar. Also it was observed that, OBU receiving false ID. It is a false detection and it is due to the

error of the gps reading, it’s resolution and the tolerance level of 10 m provided to compensate that.

Therefore accuracy of the system is as low as ± 10m. This inaccuracy applies at the point of authen-

tication. Afterwards, the accuracy of the radar depends on the accuracy of the radar measurements

which is ± 0.25m. This implies that all the warnings generated are subjected to this inaccuracy.

Further, the number of vehicles detected by the radar varied compared to the manual count slightly in

the experiments. Although radar, was mentioned to be having a maximum range of 160 m, it had

obviously detected vehicles greater than that number. The manual count was limited to distance of

160 meters in the test field and ignored vehicles that appeared at greater distance than that. However,

the sample size of very small to bring up an assumption to neglect any hypothesis regarding false

detection. Certain lines in the vehicle distance travel diagram suggest, the continuity of the previous

vehicle. However, there is no sufficient evidence to support that argument.

Although, connectivity curves showed a maximum range of 374 m of established connectivity, the

maximum radar detection has been 186 m compared to the 160 meters mentioned range of the radar.

Therefore effective communication range is 180 meters.

77

The gps based full duplex system has very poor message transfer rates. Although, it has very small

authentication delay of 2 seconds, the poor message transfer rate reduces the speed of system func-

tionality. The main issue is due to delay in obtaining gps data which is around 1 second per reading,

while in motion and management of vehicle data and processing.

The radar based full duplex system had very poor performance as the authentication did not happen

during the on field test and it had very long authentication delay during off field test which eliminates

this method from real time application.

However, all performance based analysis were completed upon the assumption that radar provides

highly accurate information.

Table 4.17: Performance comparison between three systems

System Half Duplex Full Duplex Radar Full Duplex GPS

Use of Mini Radar yes yes No

Communication Half Duplex Full Duplex Full Duplex

No of Test Vehicles Deployed Simultaneously two two one

Use of GPS yes yes yes

Authentication Random ID Specific ID Specific ID

Authentication Unit OBU RSU RSU

Authentication Delay less than a second more than 40 seconds 2 seconds

Maximum transmission rate 54.16 messages per second 0.36 messages per second 1.02 messages per second

Maximum reception rate 36.93 messages per second 0.23 messages per second 0.84 messages per second

There are few advantages of this system compared to the system mentioned in the literature.

• Unlicensed wireless communication

• Low cost gps and low cost Wi-Fi adapter

• An implemented application

78

CHAPTER 5

CONCLUSION AND RECOMMENDATION

The V2I system to provide bent information to the vehicle was deployed and experimented. It is

conclusive that the system functions according the requirements of the objective. Necessary warnings

can be provided to the vehicle driver upon approaching the bent. The tests results substantiate the

deployment of the system. This system has not included any vehicle localization process. That had

caused the false authentication at some instances. All the results obtained are subjected to limitations.

Therefore the derived conclusions are limited by those conditions as well.This is applicable to vehicles

travelling at a speed less than 60 kmph and vehicles that are apart from each other by at least 10 m at

the point of authentication, generally the maximum and minimum distances detected by the radar.

It is important to test the unit on highways to test its performance on high speed roads. It is rec-

ommended that system be upgraded with vehicle localization system using radar, gps and Wi-Fi for

precise authentication. Also it is highly recommended the use high precision gps sensor and Wi-

Fi antenna with bigger gain. Further, the display unit could be developed graphically to facilitate the

viewer. It is also important to increase its functionality to support 180 degrees of rotation. The system

can also be developed to use at cross junction by deploying additional radar unit and inter managing

several units. This V2I system can be developed to address traffic congestion problems as well. Also

address other smart vehicular problems as well.

There are issues with Wi-Fi connection, security of the public network and accuracy of the system.

Regardless of the issues this system can provide actual warnings to avoid accidents.

79

References

1. Al Masud, A., Mondal, M. N. I., & Ahmed, K. M. (2009). Vehicular communication system for

vehicle safety using rfid. In Communications (micc), 2009 ieee 9th malaysia international

conference on (pp. 697–702).

2. Bureau, T. (2013). Radar definition. Public Works and Government Services Canada. Retrieved

November, 8, 2013.

3. Chalko, T. J., & MSc, P. (2007). High accuracy speed measurement using gps (global

positioning system). NU Journal of Discovery, 4, 1–9.

4. Chen, L.-W., Tseng, Y.-C., & Syue, K.-Z. (2014). Surveillance on-the-road: Vehicular tracking

and reporting by v2v communications. Computer Networks, 67, 154–163.

5. Clausen, T., & Jacquet, P. (2003). Optimized link state routing protocol (olsr) (Tech. Rep.).

6. Contreras, O. J. A. (2015). Performance evaluation of an ieee 802.11 ad-hoc network on the

raspberry pi.

7. Dey, K. C., Rayamajhi, A., Chowdhury, M., Bhavsar, P., & Martin, J. (2016). Vehicle-to-

vehicle (v2v) and vehicle-to-infrastructure (v2i) communication in a heterogeneous wireless

network– performance evaluation. Transportation Research Part C: Emerging Technologies, 68,

168– 184.

8. ETSI. (n.d.). Intelligent Transportation

System. http://www.etsi.org/ technologies-

clusters/technologies/intelligent-transport. ([On- line; accessed 19-June-

2016])

9. Haider, M., & Dongre, M. (2015). Vehicle to vehicle communication using visible light

communication technology. In Proceedings of 24th irf international conference (pp. 64–66).

10. Harding, J., Powell, G., Yoon, R., Fikentscher, J., Doyle, C., Sade, D., et al. (2014). Vehicle-to-

vehicle communications: Readiness of v2v technology for application (Tech. Rep.).

11. Jia, D., & Ngoduy, D. (2016). Enhanced cooperative car-following traffic model with the

combination of v2v and v2i communication. Transportation Research Part B: Methodological, 90,

172–191.

12. Kim, O. T. T., Nguyen, V., & Hong, C. S. (2014). Which network simulation tool is better for

simulating vehicular ad-hoc network? 2014 41 , 930–932.

13. Kubota, S., Okamoto, Y., & Oda, H. (2006). Safety driving support system using rfid for

prevention of pedestrian-involved accidents. In 2006 6th international conference on its

telecommunications (pp. 226–229).

14. Lee, W.-H., Tseng, S.-S., & Wang, C.-H. (2008). Design and implementation of electronic

toll collection system based on vehicle positioning system techniques. Computer

Communications, 31(12), 2925–2933.

15. Lumbantoruan, D., KOMURO, N., & SAKATA, S. (n.d.). Ber-based routing control for

performance improvement in olsr.

16. Mojela, L. S., & Booysen, M. J. (2013). On the use of wimax and wi-fi to provide in-vehicle

connectivity and media distribution. In Industrial technology (icit), 2013 ieee international

conference on (pp. 1353–1358).

http://www.etsi.org/technologies-clusters/technologies/intelligent-transport



80

17. Oda, T., Elmazi, D., Ishitaki, T., Matsuo, K., Ikeda, M., & Barolli, L. (2015). Implementation and

experimental results of a raspberry pi and olsr based wireless content-centric network testbed.

In 2015 10th international conference on broadband and wireless computing, communication

and applications (bwcca) (pp. 263–268).

18. Raspberry Pi Foundation. (n.d.). https://www.raspberrypi.org/. ([Online; accessed

26- June-2016])

19. Su, K.-C., Wu, H.-M., Chang, W.-L., & Chou, Y.-H. (2012). Vehicle-to-vehicle

communication system through wi-fi network using android smartphone. In 2012 international

conference on connected vehicles and expo (iccve) (pp. 191–196).

20. Sumra, I. A., Hasbullah, H., Ab Manan, J., Iftikhar, M., Ahmad, I., & Alghamdi, A. S. (2011).

A novel vehicular sms system (vss) approach for intelligent transport system (its). In Its

telecommunications (itst), 2011 11th international conference on (pp. 540–546).

21. Surugiu, M. C., & Alexandrescu, R. V. (2013). Analysis of the development and implementation

of vanet network intervehiculary communication systems. In Electronics, computers and

artificial intelligence (ecai), 2013 international conference on (pp. 1–6).

22. Thangavelul, A., Bhuvaneswari, K., Kumar, K., Senthilkumarl, K., & Sivan, S. (2007). Location

identification and vehicle tracking using vanet (vetrac).

23. Tiwari, P., & Kushwah, R. S. (2013). Enhancement of vanet communication range using wimax

and wi-fi: A survey.

24. Vlastaras, D., Abbas, T., Leston, D., & Tufvesson, F. (2013). Universal medium range radar and

ieee

25. 802.11 p modem solution for integrated traffic safety. In Its telecommunications (itst), 2013

13th international conference on (pp. 193–197).

26. Zheng, Y., Jin, L., Gao, L., Li, K., Wang, Y., & Wang, F. (2016). Development of a distributed

cooperative vehicles control algorithm based on v2v communication. Procedia Engineering,

137, 649–658.

27. Zhuang, T., Baskett, P., & Shang, Y. (2013). Managing ad hoc networks of smartphones.

International Journal of Information and Education Technology, 3(5), 540.

https://www.raspberrypi.org/

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APPENDIX A

EXPERIMENTAL DATA

Experiments of RSU and one OBU on road

Table 5.1: Direction summary of Experiment 1 of RSU and one OBU on road

Vehicle ID Start Distance End Distance Direction

32 18 55 Leaving

33 131 9 Approaching

34 19 100 Leaving

35 18 59 Leaving

82

Table 5.2: Direction summary of Experiment 2 of RSU and one OBU on road


1 69 43 Approaching

2 20 52 Leaving

3 27 25 Approaching

4 83 22 Approaching

5 75 56 Approaching

6 30 94 Leaving

7 42 29 Approaching

8 24 81 Leaving

9 78 123 Leaving


11 133 137 Leaving




15 27 79 Leaving

59 20 79 Leaving





Experiments of RSU and two OBU on road

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Figure A.1: Distance summary of Experiment 1 of RSU and Two OBU on road

Figure A.2: Speed summary of Experiment 1 of RSU and Two OBU on road

84

Table 5.3: Direction summary of Experiment 1 of RSU and Two OBU on road






14 16 79 Leaving


16 73 132 Leaving

17 135 145 Leaving

18 15 107 Leaving

19 18 76 Leaving

20 109 144 Leaving


22 152 154 Leaving

23 17 111 Leaving


25 16 30 Leaving


27 27 39 Leaving


29 44 81 Leaving

30 109 140 Leaving



33 170 173 Leaving

34 54 55 Leaving



85



86




36 67 67 Leaving

37 28 29 Leaving


39 16 50 Leaving


41 53 88 Leaving



44 18 28 Leaving

45 22 86 Leaving

46 102 186 Leaving

47 60 130 Leaving

48 127 163 Leaving

49 14 75 Leaving

50 96 139 Leaving

51 140 156 Leaving

52 28 75 Leaving


54 80 80 Leaving

55 14 32 Leaving



58 21 54 Leaving

59 38 94 Leaving


61 91 128 Leaving

62 129 136 Leaving

87



88




29 149 150 Leaving


31 196 197 Leaving

32 15 26 Leaving





37 26 102 Leaving



40 97 144 Leaving


42 19 81 Leaving


An Experimental Study of Feasible Deployment of V2I ...

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