DESIGN AND IMPLEMENTATION OF

INTELLIGENT BRAKING SYSTEM

BY

SHAHRUL NA'IM SIDEK

A THESIS SUBMITTED IN PARTIAL FULFILLMENT

OF THE REQUIREMENT FOR THE DEGREE OF

MASTER OF SCIENCE IN COMPUTER AND

INFORMATION ENGINEERING

KULLIYYAH OF ENGINEERING

INTERNATIONAL ISLAMIC UNIVERSITY

MALAYSIA

JULY 2001

ABSTRACT

Autonomous vehicles will be seen in the very near future on our roadways. When integrated with other advanced technologies like Global Positioning System (GPS), data communication system and so forth, a system with certain level of intelligence can be developed. The vehicles can be maneuvered automatically with highly optimized journey in terms of money, time, quality and efficiency. Intelligent braking system is one of vehicle subsystems that can be unprompted to function when needed. The system must be able to sense certain parameters like the speed of target vehicle and its own speed. From these measured variables the output brake force can be generated. To do this operation the system ought to have a knowledge base so as to have decision-making ability. The problem of modeling brake system is difficult due to its nature .that inherits high nonlinear dynamics. It is possible, although laborious to come with·analytical model of the system after severe constraints being imposed on the modeling. Technique of soft computing allows natural languages to play a role in scientific theory. It marks a significant paradigm shift, especially on how people see their analytical problems. Fuzzy logic can be an excellent tool to control a complex, nonlinear system. In this research, this tool is used to govern the brake system. Another aspect that has been tackled by this research work is the use of digital signal processor to run the fuzzy algorithm. It has several advantages over universal microcontroller and a dedicated fuzzy chip. The on chip peripheral allows the system to be composed in compact circuitry suitable for real time embedded system. It also provides room for other signal processing algorithms to be run within the same processor without any burning of cash needed to buy other processors. The result shows that the TMS320LF2407 processor can be a good processing engine for the braking system. It accords the simulation results with good accuracy. The time of Fuzzy Logic Inference Per Second (FLIPS) is also less than the time of scanning the input data.

ii

APPROVAL PAGE

I certify that I have supervised and read this study and that in my opinion, it conforms to acceptable standards of scholarly presentation and is fully adequate, in scope and quality, as a thesis for the degree of Master of Science in Computer and Information Engineering

. Name: Assoc. Prof. Dr. M.J.E. Salami Supervisor

I certify that I have read this study and that in my opinion in conforms to acceptable standards of scholarly presentation and is adequate, in scope and quality, as a thesis for the degree of Master of Science in Computer and Information Engineering

Name: Prof. Dr.Ramachandran Nagarajan Examiner

This thesis was submitted to the Department of Electrical and Computer Engineering and is accepted as a partial fulfillment of the requirements for the degree of Master of Science in Computer and Information Engineering.

Name: Prof. Khalid al-Khateeb Head, Department of Electrical and Computer Engineering

This thesis was submitted to the Kulliyyah of Engineering and is accepted as partial fulfillment of the requirement for the degree of Master of Science in Computer and Information Engineering.

Name: Assoc. Prof. Dr. Ahmad Faris Ismail Dean, Kulliyyah of Engineering

iii

DECLARATION

I hereby declare that this thesis is the result of my own investigations, except where

otherwise stated. Other sources are acknowledged by footnotes giving explicit

references and a bibliography is appended.

Name: Shahrul Na'im bin Sidek

Signature: - • (

iv

Copyright by Shahrul Na'im Sidek and

International Islamic University Malaysia

V

To My Beloved Emak and Abah

Vl

ACKNOWLEDGEMENTS

B ismillahirrahmaanirrahim,

Alhamdullillah, the Almighty God, whom permission allows me to fulfill my

obligation. Special thanks go to my supervisor, Dr. Momoh Jimoh E. Salami without

whom I hardly complete my dissertation. His guideline and motivation really

encourage me to take up the hurdles and pick up the pace to do this research. Not to

mention Prof .. Badawy whose lessons are very much appreciated. My research mate,

Br. Yusuf Ismail deserves my note of thanks for being with me through out the

difficulties.

My family should earn a special credit for tremendous supports given. To the Dean,

Dr. Faris Ismail, my postgraduate friends and the rest of people in Kulliyyah of

Engineering, IIUM, thank you for the research environment created and continuous

succor given.

vii

TABLE OF CONTENTS

Abstract .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Approval Page . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii Declaration . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv Acknowledgements............................................................................. vii List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... xi List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... xiii List of Abbreviation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xiv

CHAPTER 1 : Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.0 General . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 1 1.1 Research Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 2 1.2 Research Problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 3

1.3 Research Methodology........................................................... 4 1.4 Thesis Outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 6

CHAPTER 2: Intelligent Vehicle Highway Systems..................................... 8 2.0 Introduction . . . . . . . . . . . . . . .. . .. . . . . . . . .. . .. . . . . .. . .. . . . . . . . . . . .. . . . . .. . . . . . . . . . . .. . .. . . . . .... 8 2.1 IVHS: Definition and Applications..................................................... 10

2.1.1 Definition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 10 2.1.2 Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 11

2.1.2.1 Advanced Traffic Management System . . . . . . . . . . . . . . . . . . . . . . . . . 11 2.1.2.2 Advanced Traveler Information System......................... 12 2.1.2.3 Advanced Public Transit System................................. 12 2.1.2.4 Advanced Rural Transportation System......................... 13 2.1.2.5 Commercial Vehicle Operations/Advanced Fleet

Management System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 2.1.2.6 Advanced Vehicle Control and Safety System . . . . . . . . . . . . . . . ... 14

2.2 A VCSS and Services . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 2.2.1 Lateral Collision Avoidance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 15 2.2.2 Intersection Collision Avoidance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 15 2.2.3 Vision Enhancement for Collision Avoidance . . . . . .. . . . . .. . . . . .. . . . . . . . ... 16 2.2.4 Safety Readiness System . . . . . . . . . . . . . . .. . .. . . . . . . . . . . .. . . . . . . . .. . . . . .. . . . . .... 16 2.2.5 Pre-Collision Restraint Deployment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 2.2.6 Automated Highway System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . 17 2.2.7 Longitudinal Collision Avoidance ..................................... : . . . .. 17

2.3 Intelligent Braking System . . .. . .. . .. . .. . .. . .. . . . . .. . .. . .. . .. . . . . .. . . . . .. . .. . .. . . . . .. . .... 18 2.3.1 Principle of Operation......................................................... 18

2.4 Non-technical Issues ofIVHS . . . . . .. . . . . .. . . . . .. . .. . . . . ...... .. . .. . .. . . . . . . . .. . .. . . . . .... 19 2.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 20

Chapter 3: Sensor for Distance Measurement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 3.0 Introduction . . .. . .. . . . . .. . . . . . . . .. . . . . .. . . . . .. . .. . . . . .. . . . . .. . .. . . . . .. . . . . .. . .. . .. . . . . .. . .... 22 3 .1 Measured Variables and Range-Finder Devices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .... 23 3 .2 Principles of Operation of Some Range Sensors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

viii

3.2.1 Ultrasonic Sensor............................................................... 23 3.2.2 Infrared Sensor.................................................................. 24 3.2.3 Photoelectric Sensor........................................................... 24

3.2.4 Microwave Sensor...................................................................... 25 3.3 Techniques to Measure the Distance . . . . . .. . . . . .. . . . . .. . . . . .. . . . . .. . .. . . . . . . . . 25 3.4 Issues Limiting these Sensors for Brake System Application . . .. . . . . . . . ... 26 3.5 Laser Radar........................................................................ 28

3.5.1 Structure of Laser Radar............................................. 29 3.5.2 Principle of Measurement............................................ 30 3.5.3 Measurement Accuracy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . 31 3.5.4 Pulse Timing Technique: Counter vs. Integration

Method in Measuring Inter-vehicle Distance using Laser Sensor . . . . . .. . .. . .. . . . . .. . . . . .. . . . . .. . .. . .. . . . . . . . .. . .. . .. . . . . .... 3 2

3.6 Rate of Data Acquisition . . .... . .. . .. . .. . .. . . . . .. . . . . .. . . . . .. . .. . .. . . . . . . . .. . .... 37 3.7 Laser Radar as a Practical Choice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 3.8 Regulation . . .. . .. . .. . .. . . . . .. . . . . .. . .. . .. . . . . .. . . . . .. . . . . .. . . . . .. . . . . .. . .. . . . . .. . .. 38 3.9'Summary ........................................................................... 39

Chapter 4: Brake System and Actuator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 40 4.0 Brake System in A VCSS.............................................................. ... 40 4.1 Anti-lock Braking System............................................................... 41 4.2 Brake Actuator . . .. . . . . .. . . . . .. . .. . .. . . . . .. . . . . .. . .. . . . . .. . . . . .. . . . . .. . . . . . . . . . . .. . . .. . .. . .. 42

4.2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 4.2.2 Operation of AHM . . .. . . . . .. . . . . .. . .. . .. . .. . .. . . . . .. . . . . .. . . . . . . . . . . .. . .. . .. . .. 43 4.2.3 Vacuum Booster............................................................... 45

4.3 Brake Dynamics and Controller Analysis............................................. 47 4.4 Summary . . . . . .. . . . . . . . .. . .. . . . . . . . .. . . . . . . . .. . . . . .. . . . . .. . . . . . . . . . . .. . .. . . . . .. . . . . . . . . . . .... 50

Chapter 5: Intelligent Controller and Software Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 5.0 Introduction . . .. . .. . . . . . . . .. . .. . . . . . . . . . . .. . . . . .. . .. . . . . . . . .. . .. . . . . .. . . . . .. . . . . .. . .. . . . . .... 52 5.1 From Conventional to Intelligent Controller........................................... 53 5.2 Fuzzy Logic Theory . . .. . .. . . . . . . . .. . .. . .. . .. . . . . .. . . . . .. . .. . .. . .. . . . . .. . . . . .. . ... . .. . . . . .. 55 5.3 Neural Network . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 5.4 Neuro-Fuzzy System.......................................................... ..... ...... 58 5.4.1. Adaptive Neuro-Fuzzy Inference System........................................... 60 5.5 System Optimization Issues.............................................................. 63 5.6 Similarities and Difference in Neuro-Fuzzy and

Conventional Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 5.7 Neuro-Fuzzy Design Consideration . . . . . .. . . . . . . . . . . .. . .. . . . . .. . . . . . . . .. . .. . ... . . . . .. . . 65

5.7.1 The Rule................................................................ 66 5.7.2 Choice of Membership Functions................................... 66

5.7.2.1 Shape......................................................... 66 5.7.2.2 Moderate Number of Function Sets . . . . . . . . . . . . . . . . . . . . . 67 5.7.2.3 Distinguishability . . . . . .. . . . . . . . . . . .. . . . . .. . . . . . . . ..... . .. . .. 67 5.7.2.4 Normality................................................... 68 5.7.2.5 Natural Zero Positioning .. .. .... .. .... .. .. .. .. .... .. .. .. .. 68 5.7.2.6 Coverage.................................................... 68

5.8 Example of Fuzzy Inference System.......................................... 68 5.9 Rules Derivation and Membership Function Tuning in FIS .. .. .... .. .. .. . 71

ix

5 .10 Additional Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 4 5.11 Simulation........................................................................ 75

5.11.1 Simulation Setup..................................................... 75 5.11.2 Experience Gained During Simulation Stage .. .. . . . .. . . . . . .... 85 5.11.3 Simulation Result.................................................... 86

5.12 Summary......................................................................... 102

Chapter 6: Implementation of the Controller................................................ 103 6.0 Brake Controller........................................................................... 103 6.1 Digital Signal Processor.................................................................. 104

6.1.1 Sample and Clock Rate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 107 6.1.2 Numeric Representation and Fast Multiply-Accumulate................. 107 6.1.3 Peripherals and 1/0 Interfaces................................................ 108 6.1.4 Memory Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108 6.1.5 On-chip Debugging Facilities .. . . . .. .. . . .. .. . . . .. .. .. . .. . .. .. .. . .. .. . . .. . . . ... 108 6))5 Code Development in TMS320LF2407 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109

6.2 Summary.................................................................................... 110

Chapter 7: Hardware, Test and Result of Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 111 7.0 Hardware Setup . . .. . . . . .. . . . . .. . .. . . . . . . . .. . .. . . . . .. . .. . . . . . . . .. . .. . .. . . . . . . . .. . .. . . . . . . . . 111 7 .1 Result Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115 7.2 Results . . .. . . . . .. . .. . . . . .. . . . . .. . .. . . . . . . . .. . .. . . . . .. . .. . . . . . . . . . . .. . . . . .. . .. . .. . . . . . . . .. . .... 116 7.3 Summary.................................................................................... 143

Chapter 8: Conclusion and Recommendation............................................. 144 8.0 Introduction . . .. . .. . . . . .. . . . . .. . .. . .. . .. . .. . .. . . . . .. . . . . .. . . . . . . . .. . . . . . . . . . . .. . .... 144 8.1 Conclusion and Future Direction .. . . . . . .. .. .. . . . .. . .. .. . . . .. .. .. . . . . . .. . . .. .... 145

BIBLIOGRAPHY.............................................................................. 147

APPENDIX A................................................................................. 152 APPENDIX B................................................................................. 154 APPENDIX C................................................................................. 163

X

LIST OF FIGURES \

Figure Number Page 1.1 Some Rules Governing the Brake System 5 1.2 Fuzzy Inference System Simulation Interface 5 3.1 Standard White Light 28 3.2 Laser Radar Construction 29 3.3 Principle of Distance Measurement Pulse Timing 32

Technique 3.4 Distance Measurement using Counter Method 33 3.5 Distance Measurement using Integration Method 33 3.6 RS Flip Flop and RC Low Pass Filter 34 4.1 Auxiliary Hydraulic Module 43 4.2. Duty Cycle in Pulse Width Modulation Signal 44 4.3 Vacuum Booster Block Diagram 45 4.4 Vacuum Booster Operation; (a) Apply Stage, (b) Hold 45

Stage, ( c) Release Stage 5.1 Simple Neural Net Diagram 57 5.2 Structure of ANFIS 60 5.3 Example of Membership Function 67 5.4 Fuzzy Inference System 69 5.5 Block Diagram of Simulink Model of Fuzzy Brake 77

Control System 5.6 Block Diagram of Longitudinal Car Model 78 5.7 Block Diagram of Fuzzy Brake Controller 78 5.8 Block Diagram of Supervisory Controller 79 5.9 The Mapping Between Pedal Force and Brake Force 80 5.10 Fuzzy Inference System 81 5.11 Membership Function Set Representing Two Input of FIS. 82

(a) Distance Error (b) Distance Rate of Error 5.12 Control Output Surface Generated from FIS 84 5.13 Plots for Set A: (a) Velocity Profiles ( solid - front car). 87

(dash- following car), (b) The Inter-vehicle Distance and (c) Brake Force

5.14 Plots for Set B: (a) Velocity Profiles (solid-front car). 88 (dash - following car), (b) The Inter-vehicle Distance and (c) Brake Force

5.15 Plots for Set C: (a) Velocity Profiles (solid-front car). 90 (dash- following car), (b) The Inter-vehicle Distance and (c) Brake Force

5.16 Plots for Set D: (a) Velocity Profiles (solid-front car). 92 (dash- following car), (b) The Inter-vehicle Distance and (c) Brake Force

5.17 Plots for Set E: (a) Velocity Profiles (solid-front car). 93 (dash- following car), (b) The Inter-vehicle Distance and (c) Brake Force

xi

5.18 Plots for Set F: (a) Velocity Profiles (solid-front car). 95 (dash- following car), (b) The Inter-vehicle Distance and (c) Brake Force

5.19 Plots for Set G: (a) Velocity Profiles (solid-front car). 96 (dash- following car), (b) The Inter-vehicle Distance and (c) Brake Force

5.20 Plots for Set H: (a) Velocity Profiles (solid-front car). 98 (dash- following car), (b) The Inter-vehicle Distance and (c) Brake Force

5.21 Plots for Set I: (a) Velocity Profiles (solid-front car). 99 (dash- following car), (b) The Inter-vehicle Distance and (c) Brake Force

5.22 Plots for Set J: (a) Velocity Profiles (solid-front car). 101 (dash - following car), (b) The Inter-vehicle Distance and (c) Brake Force

6.J. Block Diagram ofTMS320LF2407 EVM 106 7.1 TMS320LF2407 EVM Layout 111 7.2 The EVM Board and JTAG-Compliant Scan Base 112

Emulation Set 7.3 The DSP Setup 112 7.4 Software Implementation of Brake Controller 114

7.5(a) Plot of Distance Error vs. Time for Set A 116 7.5(b) Plot of Distance Error Rate of Change vs. Time for Set A 117 7.5(c) Plot of Normalized Brake Output vs. Time for Set A 118 7.6(a) Plot of Distance Error vs. Time for Set B 119 7.6(b) Plot of Distance Error Rate of Change vs. Time for Set B 120 7.6(c) Plot of Normalized Brake Output vs. Time for Set B 121 7.7(a) Plot of Distance Error vs. Time for Set C 122 7.7(b) Plot of Distance Error Rate of Change vs. Time for Set C 123 7.7(c) Plot of Normalized Brake Output vs. Time for Set C 124 7.8(a) Plot of Distance Error vs. Time for Set D 125 7.8(b) Plot of Distance Error Rate of Change vs. Time for Set D 126 7.8(c) Plot of Normalized Brake Output vs. Time for Set D 127 7.9(a) Plot of Distance Error vs. Time for Set E 128 7.9(b) Plot of Distance Error Rate of Change vs. Time for Set E 129 7.9(c) Plot of Normalized Brake Output vs. Time for Set E 130

7.lO(a) Plot of Distance Error vs. Time for Set E 131 7.lO(b) Plot of Distance Error Rate of Change vs. Time for Set F 132 7.1 O(c) Plot of Normalized Brake Output vs. Time for Set F 133 7.1 l(a) Plot of Distance Error vs. Time for Set G 134 7.1 l(b) Plot of Distance Error Rate of Change vs. Time for Set G 135 7.1 l(c) Plot of Normalized Brake Output vs. Time for Set G 136 7.12(a) Plot of Distance Error vs. Time for Set I 137 7.12(b) Plot of Distance Error Rate of Change vs. Time for Set I 138 7.12(c) Plot of Normalized Brake Output vs. Time for Set I 139 7.13(a) Plot of Distance Error vs. Time for Set J 140 7.13(b) Plot of Distance Error Rate of Change vs. Time for Set J 141 7.13(c) Plot of Normalized Brake Output vs. Time for Set J 142

xii

LIST OF TABLES

Table Number Page 3.1 Resolution Comparison Between Counter and 35

Integration Methods for Pulse Timing Technique 3.2 Uncertainty Measurement Between Counter and 36

Integration Methods 3.3 Relationship Between Distance and Width 38 5.1 Constants used in System Simulation 76 5.2 FAM Table 83 5.3 Initial values for set A 86 5.4 Initial values for set B 88 5.5 Initial values for set C 90 5.6 Initial values for set D 91 5.7 Initial values for set E 93 5.8 Initial values for set F 94 5.9 Initial values for set G 96 5.10 Initial values for set H 97 5.11 Initial values for set I 99 5.12 Initial values for set J 100

xiii

ABS

ADC

ANFIS

APTS

ARTS

ATIS

ATMS

AHM

AVCSS

BOA

LIST OF ABBREVIATIONS

anti lock braking system

analog digital converter

adaptive neuro fuzzy inference system

advanced public transportation system

advanced rural transportation system

advanced traveler information system

advanced traffic management system

auxiliary hydraulic module

advanced vehicle control and safety system

b,isector of area

COA -· 0 center of area

COFF common file format

CVO/AFMS commercial vehicle operations/advanced fleet management system

DAC digital analog converter

DMA

DSP

et. al.

etc.

FCC

FIS

FLIPS

OPS

IR

!STEA

ITS

IVHS

JTAG

LED

LADAR

LIDAR

LASER

MAC

MOM

PI

PWM

RADAR

SPI

TOP

direct memory access

digital signal processor

( et alia): and others

(et cetera): and so forth

federal communication commission

fuzzy inference system

fuzzy logic inference per second

global positioning system

infrared

intermodal surface transportation efficiency act

intelligent transportation system

intelligent vehicle highway system

joint test action group

light emitting diode

laser detection and ranging

light detection and ranging

light amplification by stimulated emissions of radiation

multiply accumulate

mean of maximum

proportional integral

pulse width modulation

radio detection and ranging

serial peripheral interface

time of flight

xiv

WIM weigh-in-motion

xv

CHAPTER!

INTRODUCTION

1.0 General

Research works on smart vehicle production and intelligent highway system

development are dated back to early 1970s. Despite that, it is not until early 1990s

when it starts. to be carefully planned and clearly defined after gaining support from

United State government, academic institutions and private agencies. The result is a

comprehensive, long-term project called Intelligent Vehicle Highway System. A

specialized research study on intelligent braking system has been growing in number

ever since. The system when integrated with other subsystems like automatic traction

control system, intelligent throttle system, auto cruise system etc. will result in a smart

vehicle. The driver at the end of the day will become the passenger, safety is accorded

the highest priority and the journey will be optimized in terms of time duration, cost,

efficiency and comfortability. The impact of such design and development will cater

for the need of contemporary society that aspires quality drive as well as to

accommodate the advancement of technology especially in the area of

microelectronics, smart sensor and actuator.

In the design of intelligent braking system, the driver is allowed to overtake the

handling of the brake pedal from the controller. This is due to the lack of capability of

machines to classify and predict certain actions. Machine on the other side, has great

information processing power and it's ability to withstand the aging has always put it

ahead of human. In this research work, the implementation of intelligent braking

system hardware using digital signal processor as the heart of the system and the

communication link between sensor, actuator and other peripherals will be

investigated.

1.1 Research Background

Vehicles in the present and future will contain more electronics than mechanical parts

to improve safety, comfortability and efficiency on the road highway. Functions of

electronics parts range from low level control that can be found in the ignition and

brake systems to the high level of information integration such as the regulation of the

speed of vehicles. Many research works have been conducted in this area and

significant contribution has been made in the way human can interact with machine

(i.e. a driver with his car). For example, California Partners for Advanced Transit and

Highways (PA TH) is a prominent research group, which actively engages in the

research work related to Intelligent Vehicle Highway System (IVHS). Their works

basically try to improve quality and efficiency in driving vehicles in United States but

the idea later captivates much attention from many research groups around the world.

For instance, in France, a program called Eureka Prometheus has been established and

has successfully drawn some achievements in the area of intelligent transportation

system (ITS) [Lefort-Piat 1999]. In Japan, ITS became a national scaled project

where government, industrial sectors and academic institutions are working shoulder

to shoulder to realize this new transportation system [Int. 1]. All these activities are

done because this field has a lot of potentials for the future transportation system.

In Malaysia, the setup of the Road Engineering Association (REAM) in April 1997 is

a step towards a comprehensive ITS master plan [Int. 2]. The formulation of efficient

2

plan for strategic development of ITS in Malaysia has been finalized and submitted to

the government.

1.2 Research Problem

During the past few years, many studies have been conducted to develop computer­

controlled braking system in many leading research laboratories. The objective of

these researches is to control the vehicles in such a way that the safe inter-vehicle

distance can always be preserved while the vehicles are on the highways [Terano et.

al. 1994: 86; Lefort-Piot et. al. 1999; Raza et al. 1997]. However, a review of the

previous work has shown that many of the research projects do not put enough

attention to the case study where the front vehicle stops suddenly, leaving no room for

the following vehicle to stop before collision occurs. Consequently, this can usually

lead to fatal accident that may involve loss of innocent lives.

The other motivation towards this research work is the mounting evidence that the

current anti-lock braking system (ABS) has, towards decreasing the safety level. The

use of existing antilock-braking system even though is appealing, but very strictly

optimized due to its nature. This technology usage is very limited, infrequent and brief

[Prohaska and Devlin 1998]. On the other hand the demand for routine braking with

real time controller is almost certain to exceed the design structure of ABS system.

Consequently, one of the aims of this research work is to develop electronically

controlled hydraulic brake-by-wire (BBW) where human interventions should be very

minimum during the vehicle maneuvering.

3

1.3 Research Methodology

A new mechanism of controlling brake system is proposed in this research work. The

new DSP-based fuzzy controller is developed using Texas Instrument digital signal

processor platform and its performance has been investigated. When compared to

universal microprocessor and dedicated fuzzy chip, it provides certain advantages

suitable for braking application. The on-chip peripheral allows the system to be

composed in compact circuitry suitable for real time embedded system. It also

provides room for other signal processing algorithms to be run within the same

processor without any additional cost in buying other processors.

For the vehicles to maintain a safe distance, the system must be able to sense the

environment continuously so that it can make decision on any event encountered

without any intervention from the driver. This factor is very important especially in a

scenario where the front vehicle stops abruptly, leaving the driver with a hard time to

take any considerate action.

The mechanism of the intelligent braking system starts when the infrared laser sensor

and the vehicle speedometer input the values of the front and the following vehicle

velocities into the DSP for signal processing. This information is then used to

calculate the distance between two vehicles and their safe distance. The inputs for the

fuzzy algorithm are the error difference between the current distance and the safe

distance and the rate of change of the error difference. The output of the fuzzy

algorithm is then used to command the actuator with appropriate signaling. A set of

fuzzy rules shown in Fig. 1.1, having the ability to mimic the control action of braking

system by human, is developed and simulated using graphical interface as illustrated

4

m Fig. 1.2. The fmal set of rules 1s then programmed m the DSP for real time

application .

.Eile !;_dit '.'.iiew Options

r, .. .:1 2. If (Error is ZE) and (Error_Change_Rate is Z) then (brake is R2) (1)

·11 3. II [Error is ZE) and (Error_Change_Rate is PS) then [brake is R3) [1) I I 4. II (Error is ZE) and [Error_Change_Rate is PM) then (brake is R4) (1) ......... 5. If (Error isZE) and (Error_Change_Rate is PL) then [brake is R5) (1) l 6. If (Error is VS) and [Error_Change_Rate is NS) then (brake is R6) (1 J

I 7. If (Error is VS) and (Error_Change_Rate isZ) then (brake is R7) (1) 8. If (Error is VS] and (Error_Change_Rate is PS] then [brake is RB) (1 J 9. If [Error is VS) and [Error_Change_Rate is PM) then (brake is R9) (1) I 10. If (Error is VS) and (Error_Change_Rate is PL) then (brake is R10) (1)

. 11. II !Error is Sland IError.Chanoe Rate isNSl then !brake isR111111 ... ----- . --- ---- ... [El

If and Then Error is ~rror_ Change_R ate brake is ~] r:-:-1

FJ vs r· z R2 s PS i R3 M

-~

PM R4 B PL R5 VB none ~l R6 El

Qnot i:;:Jnot 1-:-1 not

Connection Weight:

C, or

€J and I_ 1 I rroe1ete"7ui; ·1 n=Add rule -in- Chang~ ;;..1;"'·1 ILJICJ FIS Name: distancetrim2

Figure 1.1: Some Rules Governing the Brake System

__ ., ·--- --- --- . -·-. - -·----Error• 60

1 ""--=----r------, 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30_

q

Opened system sugenofis. 30 rules

-

broke• 0.425

Figure 1.2: Fuzzy Inference System Simulation Interface

5

1.4 Thesis Outline

This thesis consists of eight chapters. In Chapter 2 the definition and structure of

IVHS is defined. A brief discussion on the system objective and what have been

achieved so far are included. The chapter also examines the system feasibility and the

issue that may arise. Toward the end, the chapter elaborates on the relationship

between intelligent braking system and Advanced Vehicle Control Systems and Safety

(AVCSS).

Chapter 3 discusses the selection of sensors as this stage plays a significant role to the

system under study. The sensor must be able to detect the inter-vehicle distance with

certain level of accuracy. The chosen sensor ought to be affordable to the market and

advanced sensor should be avoided to prevent wastage of resources, and to

demonstrate the capability of fuzzy logic approach to handle the system.

Chapter 4 gives a summary of braking system and the actuator to be integrated with

this system. Auxiliary Hydraulic Module (AHM) is used to provide forces on the

brake pedal so brake pressure can be produced.

Chapter 5 describes the meaning of intelligent controller and its function to

complement the already available control strategies. Topics on fuzzy logic, neural

network and neuro fuzzy systems are also discussed. Special attention has been given

to the structure of the applied fuzzy inference system in this research study. The

discussion on the simulation setup and some of the results are explained here. It

includes a description on the longitudinal car model employed.

6

Chapter 6 discusses the digital signal processor (DSP) used and its appropriate setup.

The reason for its usage and a comparison between other available chips like a

dedicated fuzzy chip and universal micro controller are covered.

Chapter 7 shows the results of simulation and their comparison with the result

obtained using the DSP processor. An experimental setup is also discussed and it

includes the necessary actions that must be taken in order for the DSP to work

properly.

Finally the research efforts needed to improve this system are highlighted in chapter 8.

7

CHAPTER2

INTELLIGENT VEHICLE HIGHWAY SYSTEM

2.0 Introduction

Intelligent Vehicle Highway System (!VHS), also recently referred to Intelligent

Transportation System (ITS) [Int. 3] is a massive plan that has been carefully designed

and currently undergone intensive research and development. Some people label it as

the second Apollo project whereas others doubt its feasibility. As a matter of fact,

!VHS is actually focusing on upgrading and solving problems that are presently

encountered in the current transportation system. It has been reported in [Ashley

1999] that the estimated losses in the productivity in United States annually had

reached about $50 billions due to the congestion of the highways system. The same

trend applies to all big cities in the world including Kuala Lumpur. The lingering

traffic jams meanwhile, cause the vehicles to emit copious quantities of exhaust to the

space decreasing the quality of air. The traditional approach to tackle this problem is

to construct more highways as well as to enlarge the existing ones. But this seems not

to be the best solution as it involves huge financial injection and may create social and

environmental inconveniences.

In the light of the above scenario plus several other factors like the safety level,

optimized journey and so on initiate the implementation of !VHS. !VHS basically

involves the application of modern computer and communication technologies

together with advanced control algorithms on road users, vehicles and highway

systems. The ultimate aim is to automate the operation of vehicles on the instrumented

8

highways without sacrificing the capacity (the number of vehicles that the highway

can accommodate at certain instance), safety, efficiency, productivity (cost of the time

spent by vehicles on the road), service, energy, mobility and environment (the amount

of substances produced by the exhaust). Eventually, the drivers of such vehicles will

become the passengers and the operations of these vehicles are analogous to the bits in

the computer buses system. Although the mission seems futuristic and impractical,

many experts advocate that the idea is feasible but needs a full force and support from

many people ,for it to be successful. In fact, part of the mission has been successfully

designed and implemented; as such the leading project done by the research group

called California Partners for Advanced Transit and Highways (PATH) [Ashley 1999;

Int. 4] at University of California, Berkeley. Their research concentrates on

automating the vehicle maneuvering by using a technique called 'platooning'. By

utilizing the specialized sensors and wireless communication systems a small convoy

of vehicles can be continuously monitored and controlled at closely spaced distance.

This vehicle-to-vehicle interaction will coordinate the vehicles harmonically and

reduce the speed fluctuation and traffic-shock waves. The fuel consumption and the

exhaust emission is related to a specific driving cycle. By smoothing the flow of the

traffic, it can increase the mileage and reduce the air pollution.

The automatic driving on the other hand can be envisioned from many angles where

the degree of automation varies from one vehicle to another. On one end of the ranges,

the vehicle may behave like a 'free agent' and works fully independent of human

intervention. From another angle, to operate, the vehicle needs support from highway

infrastructure and the driver. In order for the vehicle to work by following its 'instinct',

it must have the ability to sense the surrounding environment. Obstacle detection and

9