Bachelor's Thesis

BACHELOR'S THESIS

Method Development for Road Grip Correlation between Different Force Based Sensors

Marcus Lundholm Per Wallgren 2016

Bachelor of Science in Engineering Technology Automotive Engineering

Luleå University of Technology Department of Engineering Sciences and Mathematics Abstract

This thesis presents an experimental approach on how to evaluate the correlation between different force based road grip sensors. Road grip sensors are commonly used to evaluate road safety conditions, eliminating uncertainty for road maintenance. Today, different technologies has been developed to measure the interactions between tire and road to generate a friction value that describes the amount of grip a tire has on the measured surface. Differ- ent systems generates different friction values, thus depending on the measurement system, the road maintenance requirement specifications varies. A correlation between the systems is therefore important to enable specification translations for nations in the Nordic region. The Norwegian Public Road Administration, NPRA has three types of systems that use the technology of longitudinal slip to measure the friction value, with a pulse braking measurement tire. While Lule˚aUniversity of Technol- ogy has a different system, RT3 Curve, that use the technology of lateral slip, with two toe in set tires causing a slip-angle, forcing the measurement tires to slide continuously. Tests were executed in Røros, Norway for two days during winter conditions. The objectives were to investigate if there was any correlation between the systems and the main depending factors. The results showed that on compact snow and sand covered roads the NPRA systems measured approximately 70% of the RT3’s measured value. A linear regression showed that 77% of the NPRA systems variations can be explained by the variations of the RT3 system. The main depending factors are the different measurement tires and the sample-rates. Future studies are necessary to cover more different road surfaces.

i ii ABSTRACT Acknowledgements

This thesis work was performed at Lule˚aUniversity of Technology and ﬁn- ishes our studies in the B.Sc. Programme in Automotive Engineering. The journey of becoming automotive engineers has been both challenging and fun.

We sincerely thank our supervisor Johan Casselgren at the university for being very helpful throughout the whole project. He has inspired us by shar- ing his experiences. We also want to thank B˚ardNonstad and Bjørn Ove Ofstad at the Norwegian Public Road Administration for welcoming us to Røros and making this project possible.

iii iv ACKNOWLEDGEMENTS Contents

Abstracti

Acknowledgements iii

1 Introduction1 1.1 Background...... 1 1.2 Goal and objectives...... 2 1.3 Project boundaries...... 3

2 Theory5 2.1 Friction...... 6 2.2 Tire properties...... 8 2.2.1 Construction...... 8 2.2.2 Tread geometry...... 12 2.2.3 Rubber hardness...... 14 2.3 Tire Kinematics...... 16 2.4 Longitudinal Slip...... 17 2.5 Lateral Slip...... 20

3 Equipment 23 3.1 NPRA...... 23 3.1.1 OSCAR...... 23 3.1.2 ROAR Mk III...... 24 3.1.3 ViaFriction...... 26 3.2 RT3 Curve...... 27

v vi CONTENTS

4 Measurements 31 4.1 Røros 2016-02-02...... 32 4.1.1 1km Measurement on Fv541...... 32 4.1.2 Long Drive around Aursund...... 33 4.2 Røros 2016-02-03...... 34

5 Methodology 37 5.1 Data Management...... 37 5.1.1 Import...... 37 5.1.2 Modiﬁcation...... 38 5.1.3 Visualization...... 41 5.1.4 Analysis...... 41

6 Results and Discussion 43 6.1 1 km Measurement on Fv541...... 44 6.2 5 km Measurement on Fv31, Fastsand...... 50 6.3 Correlation...... 56 6.4 Discussion...... 60

7 Conclusions 63

Bibliography 63

A Appendix 69 A.1 1 km measurement on Fv541 in lane 1...... 69 A.2 1 km measurement on Fv541 in lane 2...... 74 A.3 5 km measurement on Fv31 in lane 2...... 84 List of Figures

2.1 Friction is very complex and multidimensional [1]...... 5 2.2 Static and dynamic friction [2]...... 6 2.3 Macroscopic contact between tire and road...... 7 2.4 Road contamination that prevents intermolecular bonding [3].7 2.5 Brush model [4]...... 8 2.6 Bias-ply/cross-ply construction [5]...... 9 2.7 Radial construction [5]...... 10 2.8 Example of friction in relation to inflation pressure for a ASTM 1136 SRTT radial tire [6]...... 11 2.9 Example of friction in relation to inflation pressure for a Goodyear Eagle LS radial tire [6]...... 12 2.10 OSCAR’s winter measurement tire ASTM E501 [7] and RT3’s siped Bridgestone Blizzak Nordic WN-01...... 13 2.11 Example of friction differences between tires measured with RT3 [1]...... 14 2.12 Force distribution of a tire [4]...... 16 2.13 Tire deformation and rolling resistance...... 17 2.14 Longitudinal Slip-force curve on dry surface [5]...... 19 2.15 The slip curve varies with different surfaces [8]...... 20 2.16 Lateral force coefficient in relation to slip angle [5]...... 21

3.1 OSCAR [3]...... 24 3.2 ROAR [3]...... 25 3.3 Trelleborg T520 with straight grooves [9]...... 25

vii viii LIST OF FIGURES

3.4 Viafriction [3]...... 26 3.5 Upper: transportation mode, lower: measurement mode [10].. 27 3.6 1: GEM-cell 2: Measurement wheel 3: Safety chain 4: center of rotation 5: sway bar 6: steering damper 7: shock absorber 8: transportation wheel [11]...... 28 3.7 Slip angle [11]...... 29

4.1 Map over 1km measurement...... 32 4.2 Road conditions on Fv 541...... 33 4.3 Long drive, RoAR 1...... 34 4.4 5 km drive on Fv31...... 34 4.5 Road preparation with ”Fixed-sand” ...... 35

5.1 ROAR text-ﬁle structure...... 38 5.2 ROAR parameter structure in Matlab...... 38 5.3 Sample frequency diﬀerence...... 39

6.1 Unmodified- and modified RT3 data...... 44 6.2 Friction values from RT3 for all runs on Fv541 in lane 1... 45 6.3 Friction values from OSCAR for all runs on Fv541 in lane 1. 46 6.4 Difference distribution for RT3 vs. OSCAR for all runs on Fv541 in lane 1...... 47 6.5 RT3 and OSCAR plotted vs. distance, run 1 on Fv541 in lane 1 48 6.6 Friction values from ROAR 1 for all runs on Fv541 in lane 1. 48 6.7 Difference distribution from RT3 vs. RoAR 1 for all runs on Fv541 in lane 1...... 49 6.8 Box plot of the difference of each NPRA system and run vs. RT3 on Fv541 in lane 1...... 50 6.9 Friction values from RT3 for all runs on Fv31 in lane 1.... 51 6.10 Friction values from ROAR 3 for all runs on Fv31 in lane 1.. 52 6.11 Difference distribution for RT3 vs. ROAR 3 for all runs on Fv31 in lane 1...... 53 6.12 Friction values from ROAR 5 for all runs on Fv31 in lane 1.. 54 LIST OF FIGURES ix

6.13 Diﬀerence distribution for RT3 vs. ROAR 5 for all runs on Fv31 in lane 1...... 55 6.14 Friction values from RT3, ROAR 3 & 5, ﬁrst run on Fv31 in lane 1...... 56 6.15 ROAR as a function of RT3 for two sets of measurements with regression line...... 59

A.1 Friction values from the unmodified RT3 for all runs on Fv541 in lane 1...... 69 A.2 Friction values from ROAR 2 for all runs on Fv541 in lane 1. 70 A.3 Difference distribution from RT3 vs. ROAR 2 for all runs on Fv541 in lane 1...... 71 A.4 Friction values from ROAR 4 for all runs on Fv541 in lane 1. 72 A.5 Difference distribution from RT3 vs. ROAR 4 for all runs on Fv541 in lane 1...... 73 A.6 Friction values from ViaFriction for all runs on Fv541 in lane 1 73 A.7 Difference distribution from RT3 vs. ROAR 4 for all runs on Fv541 in lane 1...... 74 A.8 Friction values from the modified RT3 for all runs on Fv541 in lane 2...... 75 A.9 Friction values from OSCAR for all runs on Fv541 in lane 2. 76 A.10 Difference distribution from RT3 vs. OSCAR for all runs on Fv541 in lane 2...... 77 A.11 Friction values from ROAR 1 for all runs on Fv541 in lane 2. 77 A.12 Difference distribution from RT3 vs. ROAR 1 for all runs on Fv541 in lane 2...... 78 A.13 Friction values from the unmodified RT3 for all runs on Fv541 in lane 2...... 79 A.14 Friction values from ROAR 2 for all runs on Fv541 in lane 2. 80 A.15 Difference distribution from RT3 vs. ROAR 2 for all runs on Fv541 in lane 2...... 81 A.16 Friction values from ROAR 4 for all runs on Fv541 in lane 2. 81 x LIST OF FIGURES

A.17 Difference distribution from RT3 vs. ROAR 2 for all runs on Fv541 in lane 2...... 82 A.18 Friction values from ViaFriction for all runs on Fv541 in lane 2 83 A.19 Difference distribution from RT3 vs. ROAR 2 for all runs on Fv541 in lane 2...... 84 A.20 Friction values from RT3 for all runs on Fv31 in lane 2.... 85 A.21 Friction values from ROAR 3 for all runs on Fv31 in lane 2.. 86 A.22 Difference distribution from RT3 vs. ROAR 3 for all runs on Fv31 in lane 2...... 87 A.23 Friction values from ROAR 5 for all runs on Fv31 in lane 2.. 87 A.24 Difference distribution from RT3 vs. ROAR 3 for all runs on Fv31 in lane 2...... 88 A.25 Friction values from RT3, ROAR 3 & 5 for run 1 on Fv31 in lane 2...... 89 List of Tables

6.1 Values of interest from RT3 for all runs on Fv541 in lane 1.. 45 6.2 Values of interest from OSCAR for all runs on Fv541 in lane 1 47 6.3 Values of interest from ROAR 1 for all runs on Fv541 in lane 1 49 6.4 Values of interest from RT3 for all runs on Fv31 in lane 1... 51 6.5 Values of interest from ROAR 3 for all runs on Fv31 in lane 1 53 6.6 Values of interest from ROAR 5 for all runs on Fv31 in lane 1 54 6.7 Mean correlation factors for all runs on Fv541 in lane 1.... 57 6.8 Mean correlation factors for all runs on Fv541 in lane 2.... 57 6.9 Mean correlation factors for all runs on Fv31 in both lanes.. 58

A.1 Values of interest from Unmodified RT3 for all runs on Fv541 in lane 1...... 70 A.2 Values of interest from ROAR 2 for all runs on Fv541 in lane 1 71 A.3 Values of interest from ROAR 4 for all runs on Fv541 in lane 1 72 A.4 Values of interest from ROAR 4 for all runs on Fv541 in lane 1 74 A.5 Values of interest from the modified RT3 for all runs on Fv541 in lane 2...... 75 A.6 Values of interest from OSCAR for all runs on Fv541 in lane 2 76 A.7 Values of interest from ROAR 1 for all runs on Fv541 in lane 2 78 A.8 Values of interest from the unmodified RT3 for all runs on Fv541 in lane 2...... 79 A.9 Values of interest from ROAR 2 for all runs on Fv541 in lane 2 80 A.10 Values of interest from ROAR 4 for all runs on Fv541 in lane 2 82 A.11 Values of interest from ROAR 4 for all runs on Fv541 in lane 2 83

xi xii LIST OF TABLES

A.12 Values of interest from RT3 for all runs on Fv31 in lane 2... 85 A.13 Values of interest from ROAR 3 for all runs on Fv31 in lane 2 86 A.14 Values of interest from ROAR 5 for all runs on Fv31 in lane 2 88 Chapter 1 Introduction

Today there are several methods to measure tire to road friction. Some systems use the theory of acceleration and restoring force while other measures some kind of slip between the tire and surface. The Norwegian road administration uses diﬀerent friction measurement systems, the ones analyzed in this report uses the theory of longitudinal slip from one measurement wheel to calculate friction. Lule˚aUniversity of Technology have another type of system, RT3 Curve that uses the theory of low lateral slip with two measurement wheels at a small toe in angle to calculate friction.

1.1 Background

The main purpose of friction measurements is to set speciﬁc requirements for the local road maintenance to prevent accidents formed due to loss of grip. The systems autonomous setup ensures good repeatability which regularly is an issue for ocular inspections.

The Norwegian road administration, NPRA has well developed methods when it comes to friction measurements on public roads. They have a large collection of measurement vehicles stationed in all of Norway’s regions which performs daily measurements. These vehicles are connected to the NPRA’s Internet servers. By sending the information directly, they make it possible to map the current road friction statuses.

1 2 CHAPTER 1. INTRODUCTION

Today, this information is mainly used by the NPRA’s road maintenance section. From previous research tables of lowest acceptable road friction number for each season, the road maintenance only have to monitor the friction status map and check the road statuses with the table. When they spot or get informed of a location with a non acceptable friction number, they can send the appropriate support. The support is mainly sanding, salting, plowing and planing the roads. This system contributes to a very eﬀective use of the road maintenance limited capacity [3].

The Norwegian friction measurement systems are provided from Norseme- ter [12] and ViaTech [13] which are leading developers and manufacturers of pavement maintenance planning systems. These systems include friction measurement devices, pavement scanning solutions and more.

A future goal with this road condition mapping could possibly be to make the information accessible to the public. Like the way a weather forecast is presented, the road conditions could be presented for each region in a more detailed way.

1.2 Goal and objectives

An objective of this report is to investigate how to correlate the RT3 which uses stud-less winter tires and the Norwegian systems which uses smooth tires with circumferential grooves. A translation between the systems would favour future co-operations between the nations and the Nordic region. To- day, there is no official way to translate the Nordic systems with each other. If this would be made possible, many benefits would follow. The method could simplify the equipment purchase for all administrations. Instead of fo- cusing on a specific equipment. e.g. longitudinal measurement systems, the administrations could aim to purchase the most price effective equipment, thus promoting competition and cooperation between the companies offering 1.3. PROJECT BOUNDARIES 3 the friction measurement systems. This in turn, could lead to a increased rate of product development and progression towards a better understanding of the physics regarding friction.

For this project the following objectives had to be answered.

1. Is there any correlation between the RT3 Curve and the NPRA systems?

2. If so, what are the main factors the correlation depends on?

3. Is it possible to establish any translation between the systems for future use?

1.3 Project boundaries

The measurements has only been executed during the winter season on snow covered and icy surfaces. Further investigations must be done on other various road surfaces with diﬀerent grip characteristics to establish a complete analysis and result. The measurements are limited to public roads around Røros. 4 CHAPTER 1. INTRODUCTION Chapter 2 Theory

In the analyze of friction measurement systems some theory needs to be pro- cessed. There are many dimensions regarding friction were a more extensive analysis could be utilized. This section will not cover all dimensions. The focus is instead on introducing the main factors like; fundamentals of friction that explains the physics about the interaction between tire and road surface, tire kinematics that declare which forces act on a tire at diﬀerent situations and how the tire is deformed. The theory of slip, both lateral and longitudinal.

Figure 2.1: Friction is very complex and multidimensional [1].

5 6 CHAPTER 2. THEORY 2.1 Friction

Friction is an essential physical phenomena which can be found in almost all applications. Friction is represented by a force F that counteracts the relative motion between two surfaces in contact. Work done by friction converts energy to heat. The frictional force is directly proportional to the normal force N which is the net force compressing two parallel surfaces together. The relationship for friction is

F = µN (2.1) where µ is the coefficient of friction which depends on the material and nature of the interacting surfaces, in most cases µ < 1. There are two definitions of friction, that is; static and dynamic friction, illustrated in Figure 2.2. Static friction is a force that resists lateral relative motion, i.e. static force between non-moving objects and dynamic friction acts between moving objects. The coefficient of friction is usually larger for static friction.

Figure 2.2: Static and dynamic friction [2].

In the analyse of friction between the tires of a car and the road one needs to consider the nature of the interacting materials. As illustrated in Figure 2.3 the road surface contains lots of small crests and troughs which gives it a rough texture. The rubber tread of the tire is a relatively soft and viscoelastic material and can therefore deform around the crests and into the troughs of the road. 2.1. FRICTION 7

Figure 2.3: Macroscopic contact between tire and road.

As the tire travels over the road there are regions where the tire inter- acts on a macro- and microscopic level. On a macroscopic level the rubber deforms over the crests on the surface, this process is called hysteresis. The deformation is an thermodynamic irreversible process which generates energy in form of heat. Adhesion is the forces acting on a microscopic level between the molecules of the interacting materials. As seen in Figure 2.4, the contamination that lies between the surfaces prevents/complicates the intermolecular bonding i.e. the forces due to adhesion is strongly reduced in presence of contamination on the road.

Figure 2.4: Road contamination that prevents intermolecular bonding [3].

In case of a thicker layer of water on the road, the water also complicates the hysteresis. As the tire deforms in the troughs, water is pushed out over the crests preventing the hysteresis and can cause aquaplaning. This phenomenon mostly occurs at higher velocities but can also occur at lower speeds depending on the amount of water on the road.

It is convenient to describe the contact between road and tire with the so 8 CHAPTER 2. THEORY called brush model, Figure 2.5. The model states that the rubber in contact with the surface can be divided into inﬁnitesimal elements, or so called brushes. Each element of the tire tread passing through the tire contact patch exerts a shear stress which; when integrated over the contact area, is equal to the total tractive and/or lateral forces developed by the tire [14]. As the tire travels over the road with speed vx the contact area can be divided in two regions; slide- and adhesion region. In the adhesive region the brushes adhere to the road surface and the deformation force is due to static friction. In the sliding region the brushes slide on the road surface under inﬂuence of the dynamic friction [4].

Figure 2.5: Brush model [4].

2.2 Tire properties

The tire is the sole contact point between the road and the vehicle, every steering, acceleration or braking maneuver is transferred through the tread contact patch to the road. The tire is therefore the main factor for determi- nation of road safety. It is important to evaluate the properties of diﬀerent tires since it has a large impact on the grip characteristics.

2.2.1 Construction

Since the conventional tire for public vehicles was launched, Many diﬀerent designs has been utilized and discarded. Today’s modern constructional de- 2.2. TIRE PROPERTIES 9 signs can be divided into two categories, Bias and Radial.

Figure 2.6 illustrates the constructional design of a Bias-ply tire. The cords of the plies runs diagonally from bead to bead. The construction shows good results in terms of sidewall strength, ride-smoothness and suﬃcient handling. Though, the Bias-ply tires run hotter than other types, resulting in tread squirm. This leads to a higher wear rate and potential for failure, i.e. punctures [5].

Figure 2.6: Bias-ply/cross-ply construction [5].

Initially, the cords were made out of natural materials such as cotton or linnen. The first man-made material to be used in cords was rayon, which eventually was replaced with nylon. Nylon had a tendency for ”flat spotting” as it deformed from the weight of the vehicle if remained stationary for even a short period of time. The tire would regain its round shape when the vehicle was driven for a short distance. The deformation was not a good first impression and therefore the sales went down with the tires equipped with these cords [5].

A improved version of the bias-ply tire was the belted bias tire. The cords and plies were oriented like the regular bias-ply but reinforcing circumferential ﬁberglass belts had been added. The improvements resulted in a cooler running tire, decreased the tread wear rate and stopping distance[5]. Al- 10 CHAPTER 2. THEORY though, the reinforcing belts produced a stiﬀer ride and the belted bias tire was more expensive.

In the other category, Figure 2.7 illustrates a radial tire. The plies are oriented diﬀerently as they run directly across the tire, perpendicular to the direction of rotation. Like the belted bias tire, the radial tire is reinforced with circumferential belts. Steel belts is commonly the material of choice but ﬁberglass is also used. This construction provides good grip, the longest tread life because they run cooler and with a lower rolling resistance. The radial tire is the most expensive of all and has a high potentiality for punctures due to a soft sidewall structure [5].

Figure 2.7: Radial construction [5]. 2.2. TIRE PROPERTIES 11

Each tire model have a recommended inflation pressure, this is necessary to achieve the manufacturers specific requirements in terms of grip, controlled tread wear, stiffness, rolling resistance and noise. Figure 2.8 shows a ASTM 1136 radial tire’s maximum achieved friction value for different velocities in relation to the inflation pressure. For this specific tire the friction is linearly increasing with the pressure. Notify the 20 mph run were the difference between 117 kPA and 243 kPa inflation pressure is more than 10 % in the end friction.

Figure 2.8: Example of friction in relation to inﬂation pressure for a ASTM 1136 SRTT radial tire [6].

When observing Figure 2.9 the end friction for a Goodyear Eagle radial tire is decreasing with the inﬂation pressure, with some exceptions for peak values in between. The characteristics of the curves diﬀers and the behavior is more like the opposite of the ASTM-tire described above. 12 CHAPTER 2. THEORY

Figure 2.9: Example of friction in relation to inﬂation pressure for a Goodyear Eagle LS radial tire [6].

The impact of the inﬂation pressure is a complex dimension to describe as it seems to vary from tire to tire. How-ever it could still have a large impact on the end-friction value.

2.2.2 Tread geometry

To increase traction, regular tires are siped. Siping was patented 1923 by John F. Sipe whom developed a manufacturing method to increase traction in wet and icy conditions [15]. Siping is a method of cutting thin slits across the tread of the tire as seen for the Bridgestone tire in Figure 2.10. These slits give better gripping power on the road due to its numerous sharp edges. The slits also partially transport water from the contact surface, additional water transport comes from thicker grooves in the tire as seen for both tires in Figure 2.10. For winter tires the tread depth and void ratio (ratio of open space in the tire footprint) is increased to ensure good water and snow transportation [16]. 2.2. TIRE PROPERTIES 13

Figure 2.10: OSCAR’s winter measurement tire ASTM E501 [7] and RT3’s siped Bridgestone Blizzak Nordic WN-01.

As seen in Figure 2.11, in dry conditions the difference between a smooth and threaded tire is marginal. As the road conditions gets worsened the thread geometry and design plays a significant role, making it possible to maintain the grip. The relationship between different tires running on snow and ice is more complicated. Various theories exists regarding the character- istic dependencies. 14 CHAPTER 2. THEORY

Figure 2.11: Example of friction diﬀerences between tires measured with RT3 [1].

2.2.3 Rubber hardness

As described from section 2.1 the tire brushes capability of deformation along the contact patch includes the rubber tread hardness. In the summer season the tire wear is both an advantage and an issue. Using softer rubber increases the treads ability to deform around the road texture. After deformation the tire reverts to its original shape with a certain delay and thus transforming the work done by friction into heat. On the other hand this is less desired from the economical perspective, since this tends to shorten the tire life cycle as the treads wear down more quickly. This leads to the conclusion that a balance between using a soft rubber compound to maintain good friction and simultaneously making it resistive to wear is important.

Although in the winter season the asphalt is usually covered with diﬀerent types of snow and ice. All of these surfaces has a less rough and more slippery texture, thus less friction and tire wear to take in consideration when designing the tires. It is a challenging task to maintain the grip on these slippery surfaces. The focus is aimed on making the rubber compound as 2.2. TIRE PROPERTIES 15 soft as possible without compromising the load limit on the tire carcass and tread handling properties. This can be done by increasing the tire width, a wider tire can distribute the vehicle load over a larger contact area, thus giving an opportunity to use softer rubber tread without having undesired deformations.

Still, a wider tire has a disadvantage when traveling through loose snow and slushy surfaces in comparison to a slim one. As the wider surface dis- tributes the load over a larger area, the tire ”surfs” on the loose surface and cannot ”dig” down to the rough texture with more traction. A slim tire has more capability to accomplish this and usually achieves more traction in these situations. 16 CHAPTER 2. THEORY 2.3 Tire Kinematics

There are several forces acting on a tire during acceleration or cornering.

The main forces regarding vehicle stability and handling are lateral, Fy, longitudinal, Fx, self-aligning torque, My, and the overturning torque, Mx, As illustrated in Figure 2.12.

Figure 2.12: Force distribution of a tire [4].

Both the lateral and longitudinal forces acting points on the tire are not directly below the wheel axis, therefore a self-aligning torque, Mz is generated. During cornering or asymmetrical diﬀerences in the tire, e.g. uneven tire wear,

Mz is forcing the wheel back to its neutral position [4].

The overturning torque, Mx, is the result of the lateral forces generated in cornering and the current camber angle on the wheel, if no greater camber angle is applied Mx is only dependant of cornering. During acceleration or braking in a straight line there are only longitudinal 2.4. LONGITUDINAL SLIP 17 forces and rolling resistance acting on the tire. Rolling resistance is deﬁned as the center contact surface of the tire is compressed and displaced from the hub axis, thus creating a counteracting torque, My due to Fz as seen in Figure 2.13

Figure 2.13: Tire deformation and rolling resistance

If the same scenario is performed in a corner when the wheels are turned, lateral forces are generated perpendicular to the wheels direction of travel, this in turn generates torque, Mz, which is forcing the tire treads in the same direction as the lateral force vector.

2.4 Longitudinal Slip

There can be a diﬀerence in longitudinal speed between the wheel axis and the surface contact area of the tire patch, this is called Slip speed which indicates how much the tire slides on the contact surface. If the wheel is free-rolling, the patch speed is equal to the wheel axis travel speed.

When braking is applied, a longitudinal velocity diﬀerence occurs between 18 CHAPTER 2. THEORY the wheel axis and the tire patch. The tire patch speed is less than the wheel axis travel speed, as it is kept constant. This is called Longitudinal slip [17] and can be described with the following equation.

S = V − Vc (2.2)

Where S is the Slip speed, V is the wheel center travel speed and Vc is the tire contact patch speed.

• Non-slip motion: V = Vc ⇒ S = 0

• Driven wheel: V < Vc ⇒ S < 0

• Braked wheel: V > Vc ⇒ S > 0

The speed of the tire contact patch can be calculated by the following equation.

Vc = 2πωh (2.3) Where h is the distance from the surface to the wheel axis, It is not appropriate to use the diameter of the tire, since it is deformed in the contact area by the weight of the vehicle it is mounted on, therefore not forming a perfect circle [3].

For vehicle safety, the braking sequence is of interest to investigate the vehicle’s maximum applicable brake force, i.e. the maximum friction coeﬃcient. To start with, one can look at the deviation of the slip speed and the vehicle’s travel speed, this is called Slip-rate, λ which is given in percent. For example 0 % for a free-rolling wheel, 100 % for a locked, purely sliding wheel. S λ = (2.4) V In order to illustrate the transferred longitudinal force, plotting it in relation to the slip-rate is necessary. This is called a Slip-force curve. 2.4. LONGITUDINAL SLIP 19

Figure 2.14: Longitudinal Slip-force curve on dry surface [5].

As seen in Figure 2.14, in dry conditions the initial slope of the slip-force curve is relatively linear i.e. Fx is proportional to the slip-rate in that interval. The linear relationship can be described by the following equation:

Fx = Cxλ (2.5)

Where Fx is the transferred circumferential force i.e. braking force, which has from experiment results its dependencies [18];

• Slip-rate, λ

• Normal force acting on the tire, Fz

• The braking stiﬀness of the tire, Cx

• Constructional parameters of the tire, rubber compound, cord orienta- tion, size, etc.

In most cases, the optimal braking force, Fx is achieved around 20% slip. This means that the tire patch circumferential speed is 20% slower than the 20 CHAPTER 2. THEORY wheel center traveling speed. This slope is a perfect example of the ABS functions great importance, developed to achieve optimal braking force in all situations, simultaneously preventing the tires from purely sliding [18].

Figure 2.15: The slip curve varies with diﬀerent surfaces [8].

As seen in Figure 2.15, the slip curve behavior varies depending on the surface measured. For instance, the ice surface does not have a clear peak friction value as for the dry and wet asphalt. This is due to the lack of adhesion [19].

2.5 Lateral Slip

When a lateral force Fy, acts on free-rolling wheel, a velocity vector is formed lateral to the tire’s rolling direction. Illustrated in Figure 2.12 the angle formed between the lateral velocity vector acting across the rolling section of the tire, parallel to the road and and the traveling direction of the wheel is called the Slip angle, α. A wheel traveling in a straight line is assumed to have zero slip angle [18]. 2.5. LATERAL SLIP 21

Figure 2.16: Lateral force coeﬃcient in relation to slip angle [5].

Initially at lower slip angles, the lateral force is directly proportional to the slip angle. The relationship can be described with the following equation:

Fy = Cyα (2.6)

Where Fy is the translated tangential force across the tire, i.e cornering force and Cy is defined as the cornering stiffness and its dependencies are similar to the longitudinal ones described in Section 2.4. When applying larger angles the contact patch deflection and the tangential stress towards the thread boundary will force the adhesion friction limit to be exceeded and sliding begins. From this state the lateral force is decreasing with increased slip angle and linearization is inapplicable [18]. 22 CHAPTER 2. THEORY Chapter 3 Equipment

Multiple measurement systems from the Norwegian Public Road Adminis- tration, NPRA has been analyzed with the RT3 Curve in this project and a general introduction is necessary to understand their main diﬀerences.

3.1 NPRA

NPRA has a great number of measurement systems, in this project; OSCAR, ROAR Mk III and ViaFriction was analyzed. All systems uses continuous longitudinal slip to measure friction, see section 2.4. The data can be analyzed directly with a tool named ViaPlot. Each vehicle has a camera mounted in the compartment which takes pictures every 10th meter to document the road conditions associated with the measurements [13].

3.1.1 OSCAR

OSCAR is the Norwegian reference system for all other friction measurement systems. It is the only one of its kind in Norway, therefore it is mainly used for reference in calibration to the other measurement vehicles and in science projects. For the winter season OSCAR uses a ASTM E501 ribbed standard measurement tire [7], Figure 2.10, with a tread durometer hardness of 58 ± 2 [20] and 2 bar inﬂation pressure. OSCAR uses both locked- and variable slip-rate, a hydraulic system sets the appropriate tire to road pressure [3].

23 24 CHAPTER 3. EQUIPMENT

Figure 3.1: OSCAR [3].

In the summer season, all measurements are done with a thin water ﬁlm being sprinkled in front of the measurement wheel. The water is used to simulate a more critical situation on the surface rather than a dry one, which in most cases displays good friction conditions [3]. The water is also used to cool the measurement wheel to prevent overheating [13].

3.1.2 ROAR Mk III

ROAR - Road Analyzer and Recorder is an advanced measurement system developed by Norsemeter which ViaTech can provide mechanical and electri- cal upgrades for. The NPRA has ﬁve ROARs stationed in each of Norway’s regions. Every measurement season the ﬁve ROAR vehicles are calibrated to OSCAR. 3.1. NPRA 25

Figure 3.2: ROAR [3].

Like the OSCAR, ROAR vehicles uses both locked- and variable slip-rate and conducts measurements in the summer season with water in front of the measurement wheel [3]. For winter season measurements ROAR uses a Trelleborg T520 [9] ribbed tire (Figure 3.3), similar to ASTM 501 but smaller.

Figure 3.3: Trelleborg T520 with straight grooves [9]. 26 CHAPTER 3. EQUIPMENT

The main application of these vehicles includes calibration to the other friction measurement vehicles like ViaFriction, mapping the public road friction status in both winter and summer season, follow-up on friction requirements as well as participating in friction measurements for science projects [3].

3.1.3 ViaFriction

The ViaFriction is a less advanced system compared to the ones described above, therefore a more aﬀordable and easy to use option. There are around 1201 ViaFriction devices stationed in Norway [3].

Figure 3.4: Viafriction [3].

This system uses locked-slip which can be set between 1 - 75 %. During winter season measurements, the slip-rate is in general at 20 %. The ViaFric- tion system also uses a Trelleborg T520 measurement tire. The ViaTech company oﬀers many diﬀerent options of custom installation solutions. The systems used in this project had no water tank installed, therefore they are only used during the winter season [13].

1B˚ardNonstad, NPRA 3.2. RT3 CURVE 27 3.2 RT3 Curve

RT3 is manufactured by Halliday Technologies in Ohio USA. RT3 was orig- inally developed for use in auto racing (Indy car and Le Mans 24 hours). Halliday technologies provides diﬀerent friction measurement systems and RT3 Curve is one of them, see Figure 3.5.

Figure 3.5: Upper: transportation mode, lower: measurement mode [10].

Since 2009, the RT3 Curve has been used by Lule˚aUniversity of Tech- nology in several research projects regarding traﬃc safety, continuous road condition measurements and advanced tire testing. It measures road friction continuously on curved, cambered and straight roads under all weather conditions. RT3 has two measurement wheels mounted at an small toe-in angle and one middle wheel for transport mode which is used as ballast weight when measuring as seen in Figure 3.5. The measurement tires is of type Bridgestone Blizzak Nordic WN-01, seen in Figure 2.10, with a measured tread Durometer hardness of 55 ± 2 (test method ASTM D2240 [20]).

RT3 uses the concept of lateral slip caused by the slip angles to measure friction, by using two measurement wheels it can compensate for the change in lateral force when cornering. The change in lateral force is linear to a quantity called Halliday Friction Number (HFN) which in turn can be con- 28 CHAPTER 3. EQUIPMENT verted to a µ-value. To measure the lateral force the RT3 uses patented GEM (Grip Evaluation and Management) force sensing hubs mounted in each of the measurement wheels, seen in Figure 3.6.

Figure 3.6: 1: GEM-cell 2: Measurement wheel 3: Safety chain 4: center of rotation 5: sway bar 6: steering damper 7: shock absorber 8: transportation wheel [11].

The HFN value is based on a linear scale were a lateral force of 0 N on the GEM cell is 0 HFN and 533 N corresponds to 85 HFN. The ratio of

HFN-value and lateral force Fy is given by F HFN = y (3.1) 511.5/81.76

Were the numbers in the denominator are calibration values given by the supplier. The corresponding coeﬃcient of friction, µ is HFN divided by 100, i.e. HFN=85 gives µ=0.85 [21].

◦ The slip angle α1 and α2 is set to be 1.5 for each measurement wheel and can be calculated by measuring the distances illustrated in Figure 3.7. The 3.2. RT3 CURVE 29 slip angles can be adjusted if needed according to instructions from the RT3 users manual [21].

Figure 3.7: Slip angle [11].

The slip angles was calculated as follows

e − a α = arctan (3.2) 1 c

f − b α = arctan (3.3) 2 d ◦ Were, in this project α1 ≈ α2 ≈ 1.5

Along with the RT3 the XC90 was equipped with a VBOX (20Hz) from Racelogic2 which is an advanced GPS system with a precision of 2cm.

2https://www.vboxautomotive.co.uk/index.php/en/. Accessed: 2016-05-30 30 CHAPTER 3. EQUIPMENT Chapter 4 Measurements

Prior to testing, the RT3 had to be mounted behind a towing vehicle, the university uses a Volvo XC90. This was done according to instructions from the RT3 user manual [21]. Some safety features had to be mounted such as sway bars to prevent the RT3 from rolling during cornering or transportation on rough surfaces and safety chains to control the maximum steering output radius of the RT3.

An initial check of the monitoring systems were made to ensure that all systems worked properly. Inﬂation pressure of the measurement tires were controlled along with the tread hardness using a type A shore durometer [20]. The XC90 was transported with the RT3 to Røros from Lule˚a,a distance of roughly 850 km. This was done using the RT3s transportation mode, seen in top of Figure 3.5.

The climate around Røros favours winter testing. Since it is situated close to the alpine region the range of diﬀerent road conditions were easily accessible. Measurements were made in Røros during two days with both the RT3 and NPRA systems on selected public roads in Røros, the tracks where later plotted on maps using GPS Visualizer1.

1http://www.gpsvisualizer.com/. Accessed: 2016-05-30

31 32 CHAPTER 4. MEASUREMENTS 4.1 Røros 2016-02-02

The day started with a brief meeting regarding the planned tests. The NPRA measurements systems were calibrated at a speciﬁc test distance of 1km at Fv30 prior to the test session. The calibration was set to ensure that the traveled distance of each system was exactly 1000 meters.

4.1.1 1km Measurement on Fv541

Several test runs on a straight 1km distance were made at Fv541, see Figure 4.1. The distance was traveled repeatedly five times in each direction to ensure a sufficient amount of data. The different directions of the test distance was named lane 1 and 2 in the measurement data.

Figure 4.1: Map over 1km measurement

The speed during measurement was held as constant as possible, roughly around 50 km/h. The road conditions where good with dry homogeneous compact snow as seen in Figure 4.2. This ensured that similar surface conditions was sampled by all systems. 4.1. RØROS 2016-02-02 33

Figure 4.2: Road conditions on Fv 541

4.1.2 Long Drive around Aursund

An attempt was made to measure over greater distances, covering different road conditions and velocities. The drive started from Statiol Røros towards Brekken on Fv31, for this drive the VBOX GPS lost connection but friction was measured. From Brekken and around the lake Aursund the data was divided into different data files i.e. start and stops due to pauses and junctions. The coordinates of all systems were plotted on a map to see the start and stop locations, see Figure 4.3 for ROAR 1 tracks. 34 CHAPTER 4. MEASUREMENTS

Figure 4.3: Long drive, RoAR 1

4.2 Røros 2016-02-03

The focus was on doing measurement runs on a public road with a generally higher friction surface. The weather conditions were stable and the temperature around −4◦ Celcius. There were only two of the ROAR vehicles participating during these tests. Illustrated in Figure 4.4 measurements were done on a distance of 5km at Fv31, three times in each direction.

Figure 4.4: 5 km drive on Fv31 4.2. RØROS 2016-02-03 35

The speed was held as constant as possible around 60 km/h. All systems measurement wheels was aimed to run in the visible track grooves. The surface of the road were relatively homogeneous. Initially ice- and snow covered, prepared with packed sand, heated before it was strewed in thin lines along the road, see Figure 4.5. The sand contained a relative high amount of water so that it became a solid that freezes ﬁrmly in the road. This method of sanding the roads are commonly used in Norway due to savings of material and better grip that lasts longer, it is called the ”Fixed-sand method”.

Figure 4.5: Road preparation with ”Fixed-sand” 36 CHAPTER 4. MEASUREMENTS Chapter 5 Methodology

5.1 Data Management

The data gathered during the measurement runs had to be named and sorted to make it easier to navigate and ﬁnd for the later analysis. Some problems were encountered with the RT3s data acquisition during the measurements. For instance, in a few runs the VBOX GPS system stopped working, and sometimes the gathered data were not synchronized with the NPRA systems correctly. The strategy for the correlation analysis can be represented as follows:

5.1.1 Import

Both RT3 and the NPRA systems logs data in text-files, with rows for each sample. The manufacturers has organized the columns into the different measured parameters. Figure 5.1 illustrates a text-file taken from a ROAR system, were for example column 4 shows the slip-rate.

37 38 CHAPTER 5. METHODOLOGY

Figure 5.1: ROAR text-ﬁle structure

The RT3 text-file has a different layout than the ROAR described above, therefore a different kind of importing method had to be used. All data were imported into Matlab and stored in different cells for each measurement run. Each cell contained a vector for every parameter with a length equal to the number of samples. Figure 5.2 shows the columns seen in Figure 5.1 as vectors.

Figure 5.2: ROAR parameter structure in Matlab

The import sequence required several programming steps to make the data manageable into structured cells.

5.1.2 Modiﬁcation

There was a difference in the RT3’s sample rate in relation to the NPRA systems as seen in Figure 5.3. The RT3 is sampling with 10 Hz continuously while the NPRA systems samples every 10th meter, i.e. depending on the traveling speed the sample rate varies, if looking at samples per second. This 5.1. DATA MANAGEMENT 39 was causing difficulties in the friction difference analysis since the RT3 data had more samples than the NPRA systems.

RT3 Curve and RoAR 1, Lane 1

0.5 RoAR 1

0.45 RT3

0.4

0.35

0.3 Friction

0.25

0.2

0.15 11.348 62.621 11.35 11.352 62.62 11.354 11.356 62.619 11.358 11.36 62.618 11.362 11.364 62.617 11.366 62.616 Longitude Latitude

Figure 5.3: Sample frequency diﬀerence

The data had to be modified so the total samples of both systems were equal. A suitable method for solving this problem was by calculating the distance from all of the RT3 coordinate points for a run to a single point of a NPRA system, in this case a ROAR system. We used a simplified method to choose, for each ROAR point, a RT3 point close to it. We looked at the coordinates of the ROAR point, and chose a RT3 point with the closest coordinates, i.e., with the minimal distance (difference) in coordinates, Dc to the ROAR point.

q 2 2 Dc = (RT 3Longk − ROARLong) + (RT 3Latk − ROARLat) (5.1) k = 1, 2, 3..., n

Were n is the length of the RT3’s coordinate vectors. This simplified method does not take into account the fact that the meridians converge towards 40 CHAPTER 5. METHODOLOGY the poles. The difference of 1/60◦ in latitude “on the map” gives the same distance “in reality” everywhere on the globe; this is the definition of the nautical mile = 1809 m approximately. However, the same difference in longitude gives a shorter distance the closer you are to the poles. A difference of 1/60◦ in longitude on the globe at latitude 60◦ gives a distance on the surface of the globe of:

Cos(60◦) ∗ (1 nautical mile) = 0.5 ∗ 1809m

The latitude of Røros is approximately 62.6◦ N, and Cosine (62,6◦) is 0.46 approx. Thus, the formula for the distance at Røros is:

q 2 2 D = ((RT 3Longk − ROARLong) ∗ 0.46) + (RT 3Latk − ROARLat) (5.2)

However, Dc and D are closely connected. You can think of the distance Dc as measuring the distance while looking at the map at an angle (62,6◦ at Røros) from the south; this makes the difference in latitude look shorter, and then a difference 1/60◦ in latitude looks the same as the same difference in longitude. Thus, we may safely say that points that are close to each other measured by Dc also are close to each other in reality (measured by D).

The operation was repeated for all ROAR coordinate points. Since the RT3 has a decimal limit on its coordinate storage, it was often more than one value. When that was the case the first of the multiple result indices was stored in a new vector of equal length as the ROAR vector. Collection of the associative friction samples was done by calculating the mean value of the result indices and stored in a vector as previously done. A plot was made with the modified and unmodified data to evaluate the reliability of the modified vectors, see Section 6.1. 5.1. DATA MANAGEMENT 41

5.1.3 Visualization

The data was visualized separately for each system and run in various Mat- lab plots. 3-D line plots with raw data showed the friction variation over the driven distance. Histograms were made to see the distribution of the diﬀer- ence between the RT3 and NPRA systems. The diﬀerence was also visualized in box plots giving the median and deviation of each set of measurements.

5.1.4 Analysis

When the modiﬁcation of the RT3 data was done, more detailed analyzes of the systems were accessible and presented in tables.

• Mean values and the diﬀerence between the systems.

• Standard- and relative standard deviations for 100 values per km measured.

• Maximum and minimum values and the relative diﬀerence.

• Regression analysis which was performed using a first order polynomial fit, generated with the Matlab tool Polyfit [22].

• Mean correlation factor between RT3 and NPRA systems for each run and set.

The mean correlation factor was calculated with the following equation: NPRA C = mean (5.3) RT 3mean 42 CHAPTER 5. METHODOLOGY Chapter 6 Results and Discussion

The 1km measurements provided a sufficient amount of data for the correlation analysis. ROAR 3 and 5 were not analyzed in the 1 km drive due to loss of data. The plots and tables for unmodified RT3, ROAR 2, 5 and ViaFric- tion for lane 1 can be found in Appendix A.1 and lane 2 in Appendix A.2 where RT3 modified, ROAR 1 and OSCAR is added. The OSCAR system did not register any longitude coordinates which was solved using ROAR coordinates. This was done using the method described in Section 5.1.

The long drive was not analyzed in this project due to several different start, stops and missing data. The different start and stops of all the systems made it very hard to categorize different runs and make sure that the same surface was measured.

43 44 CHAPTER 6. RESULTS AND DISCUSSION 6.1 1 km Measurement on Fv541

Seen in Figure 6.1 the modiﬁed data followed the original data very well, some of the spike values were neglected due to the mean value operation of multiple samples as described in 5.1.2.

Modiﬁed RT3 Curve, Lane 1

0.5 Unmodiﬁed

ﬁ 0.45 Modi ed

0.4

Friction 0.35

0.3

0.25 11.348 62.621 11.35 11.352 62.62 11.354 11.356 62.619 11.358 11.36 62.618 11.362 11.364 62.617 11.366 62.616 Longitude Latitude

Figure 6.1: Unmodiﬁed- and modiﬁed RT3 data

In Figure 6.2 friction values from the modiﬁed RT3 with coordinates is shown for runs 1-5, in lane 1 for the 1km measurement. The friction values varied from 0.2867 to 0.4933 even though the surface were relatively homogeneous. Variations were common between the runs due to small road irregularities and diﬀerent positioning of the measurement wheels. No repeatability was observed point by point, however the mean values in Table 6.1 shows good repeatability between the runs. 6.1. 1 KM MEASUREMENT ON FV541 45

RT3 Curve, Lane 1

0.5 Run 1 Run 2 Run 3 0.45 Run 4 Run 5

0.4

Friction 0.35

0.3

0.25 11.348 62.621 11.35 11.352 62.62 11.354 11.356 62.619 11.358 11.36 62.618 11.362 11.364 62.617 11.366 62.616 Longitude Latitude

Figure 6.2: Friction values from RT3 for all runs on Fv541 in lane 1

Table 6.1 shows values of interest from the RT3 lane 1 runs. The average road grip for all runs was 0.3771 and the relative standard deviation tells how much the values deviate from the average. The relative diﬀerence is the diﬀerence between max and min values given in percent.

Table 6.1: Values of interest from RT3 for all runs on Fv541 in lane 1 Average Relative Max Min road Relative Standard Run road grip Standard road grip grip diﬀer- deviation value deviation value value ence 1 0.3902 0.0447 11.46 0.4933 0.2933 68.19 2 0.3897 0.0335 8.596 0.4800 0.3133 53.21 3 0.3727 0.0294 7.888 0.4400 0.3000 46.67 4 0.3607 0.0329 9.121 0.4667 0.3000 55.57 5 0.3724 0.0348 9.345 0.4600 0.2867 60.45 46 CHAPTER 6. RESULTS AND DISCUSSION

For the same lane, OSCAR values were plotted for each measurement run, see Figure 6.3. The average friction values were less than the RT3 which was expected due to diﬀerences between the measurement tires. The friction values varied from 0.19 to 0.35. The variations and their dependencies were similar to the RT3’s. As for the RT3, OSCAR showed good repeatability between the mean values, seen in Table 6.2.

Oscar, Lane 1

0.36 Run 1 0.34 Run 2 Run 3 Run 4 0.32 Run 5

0.3

0.28

0.26 Friction

0.24

0.22

0.2

0.18 11.348 62.621 11.35 11.352 62.62 11.354 11.356 62.619 11.358 11.36 62.618 11.362 11.364 62.617 11.366 62.616 Longitude Latitude

Figure 6.3: Friction values from OSCAR for all runs on Fv541 in lane 1

Table 6.2 shows values of interest from OSCAR lane 1 runs. The average road grip for all runs was 0.2578 which was ≈ 68% of the RT3 average. The relative standard deviation was a little lower than for the RT3. 6.1. 1 KM MEASUREMENT ON FV541 47

Table 6.2: Values of interest from OSCAR for all runs on Fv541 in lane 1 Average Relative Max Min road Relative Standard Run road grip Standard road grip grip diﬀer- deviation value deviation value value ence 1 0.2664 0.02810 10.55 0.35 0.21 66.67 2 0.2407 0.02180 9.057 0.30 0.19 57.89 3 0.2526 0.01480 5.859 0.29 0.22 31.82 4 0.2841 0.01810 6.371 0.33 0.23 43.48 5 0.2451 0.02170 8.854 0.29 0.20 45.00

In Figure 6.4 the percentage distribution of the diﬀerence in friction values between RT3 and OSCAR for all runs in lane 1 is shown. There were a quite wide distribution but although concentrated peak values around 0.1-0.15.

Diﬀerence RT3 vs Oscar, Lane 1 9

5 % 4

0 -0.05 0 0.05 0.1 0.15 0.2 0.25 Diﬀerence

Figure 6.4: Diﬀerence distribution for RT3 vs. OSCAR for all runs on Fv541 in lane 1

Figure 6.5 shows run 1 with both RT3 and OSCAR friction values against the driven distance. No obvious correlation can be observed in this graph, but as mentioned earlier the road conditions were similar over the entire run. 48 CHAPTER 6. RESULTS AND DISCUSSION

If there had been a spot with quite higher friction the response of the systems could have been analyzed.

RT3 Curve & Oscar, Lane 1 0.5

RT3

0.45 Oscar

0.4

0.35 Friction

0.3

0.25

0.2 0 100 200 300 400 500 600 700 800 900 1000 Distance [m]

Figure 6.5: RT3 and OSCAR plotted vs. distance, run 1 on Fv541 in lane 1

For the same lane, ROAR 1 values were plotted for each measurement run, see Figure 6.6. The average friction values were less than the RT3 but larger than OSCAR. The friction values varied from 0.18 to 0.38.

RoAR 1, Lane 1

0.38 Run 1 0.36 Run 2 Run 3 0.34 Run 4 Run 5 0.32

0.3

0.28

Friction 0.26

0.24

0.22

0.2

0.18 11.348 62.621 11.35 11.352 62.62 11.354 11.356 62.619 11.358 11.36 62.618 11.362 11.364 62.617 11.366 62.616 Longitude Latitude

Figure 6.6: Friction values from ROAR 1 for all runs on Fv541 in lane 1 6.1. 1 KM MEASUREMENT ON FV541 49

Table 6.3 shows values of interest from ROAR 1 lane 1 runs. The average road grip for all runs was 0.2794 which was 74% of the RT3 average and 8.4% higher than the OSCAR average. The relative standard deviation was a little higher than for the RT3.

Table 6.3: Values of interest from ROAR 1 for all runs on Fv541 in lane 1 Average Relative Max Min road Relative Standard Run road grip Standard road grip grip diﬀer- deviation value deviation value value ence 1 0.2752 0.02840 10.32 0.35 0.19 84.21 2 0.2674 0.03480 13.01 0.34 0.18 88.89 3 0.2866 0.02620 9.142 0.36 0.20 80.00 4 0.2819 0.02590 9.188 0.34 0.21 61.90 5 0.2857 0.03730 13.06 0.38 0.21 80.95

In Figure 6.7 the percentage distribution of the diﬀerence in friction values between RT3 and ROAR 1 for all runs in lane 1 is shown. There were a slightly narrower distribution than between RT3 and OSCAR with concentrated peak values around 0.07-0.1.

Diﬀerence RT3 vs RoAR 1, Lane 1 10

5 %

0 -0.05 0 0.05 0.1 0.15 0.2 0.25 0.3 Diﬀerence

Figure 6.7: Diﬀerence distribution from RT3 vs. RoAR 1 for all runs on Fv541 in lane 1 50 CHAPTER 6. RESULTS AND DISCUSSION

The box plot in Figure 6.8 describes the diﬀerence variance for all tested NPRA systems against the RT3 for 1km in lane 1. On each box, the central mark indicates the median, and the bottom and top edges of the box indicate the 25th and 75th percentiles. The whiskers extend to the most extreme data points not considered outliers, and the outliers are shown with a ’+’ symbol. A general diﬀerence distribution can be observed for all NPRA systems vs. RT3 which was around 0.1 ± 0.02.

Rt3 vs RoAR, Oscar & ViaFriction, Lane 1

0.25

0.2

0.15 erence ﬀ Di 0.1

0.05

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Runs 1-5:RoAR1, 6-9:RoAR2, 10-14:RoAR4, 15-19:Oscar, 20-24:ViaFriction

Figure 6.8: Box plot of the diﬀerence of each NPRA system and run vs. RT3 on Fv541 in lane 1

6.2 5 km Measurement on Fv31, Fastsand

For the measurements on Fv31 there were generally higher friction values but with some short ice patches along the drive. In figure 6.9 the three runs of the RT3 in lane 1 is plotted vs. distance. RT3’s response to short road irregularities is clearly visible at around 3750 meters which was an ice patch, and 4250 meters which was a hollow spot across the road. These surface conclusions could be done with access to NPRA’s photo-material, which is described in Section 3.1. This also proves the repeatability of the system as 6.2. 5 KM MEASUREMENT ON FV31, FASTSAND 51 the major change of friction was registered in each run. Some spikes from the first run (blue curve) was not registered in the following runs. This could be due to different positioning on the road over the runs or that the surface was roughened increasingly.

RT3, Lane 1 0.6 Run 1

0.55 Run 2 Run 3 0.5

0.45

0.4

0.35 Friction 0.3

0.25

0.2

0.15

0.1 0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 Distance [m]

Figure 6.9: Friction values from RT3 for all runs on Fv31 in lane 1

Table 6.4 shows values of interest from the RT3 lane 1 runs. The average road grip for all runs was 0.4546 which were an increase in friction with 21% from the 1 km test. The relative standard deviation were also higher than from the 1 km runs, this was mostly due to the diﬀerent road conditions, i.e. no ice patches were found in the 1 km drive on Fv541.

Table 6.4: Values of interest from RT3 for all runs on Fv31 in lane 1 Average Relative Max Min road Relative Standard Run road grip Standard road grip grip diﬀer- deviation value deviation value value ence 1 0.4590 0.0543 11.83 0.5733 0.2667 115.0 2 0.4591 0.0545 11.87 0.5600 0.3000 86.67 3 0.4457 0.0551 12.36 0.5600 0.1467 281.7 52 CHAPTER 6. RESULTS AND DISCUSSION

For the same lane, ROAR 3 values were plotted for each measurement run, see Figure 6.10. For this measurement ROAR 3 used a ASTM prototype tire with circumferential grooves1. The average friction values were less than the RT3. For the ice patches noticed in the RT3 plot at around 3750 and 4250 meters ROAR 1 did not show the same signiﬁcant change in friction. The mean value of samples over 10 meters gave that the ice patch was registered but as the change in friction was over a shorter distance, the outcome was a smaller deviation.

RoAR 3, Lane 1 0.45 Run 1

Run 2

Run 3

0.4

0.35 Friction 0.3

0.25

0.2 0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 Distance [m]

Figure 6.10: Friction values from ROAR 3 for all runs on Fv31 in lane 1

Table 6.5 shows values of interest from ROAR 3 lane 1 runs. The average road grip for all runs was 0.323 which was 71% of the RT3 average.

1B˚ardNonstad, NPRA 6.2. 5 KM MEASUREMENT ON FV31, FASTSAND 53

Table 6.5: Values of interest from ROAR 3 for all runs on Fv31 in lane 1 Average Relative Max Min road Relative Standard Run road grip Standard road grip grip diﬀer- deviation value deviation value value ence 1 0.3423 0.0277 8.1 0.43 0.27 59.3 2 0.3200 0.0364 11.38 0.41 0.24 70.83 3 0.3067 0.0358 11.67 0.40 0.22 81.82

For the difference distribution seen in Figure 6.11 the peak values were slightly shifted right towards greater difference than for the 1km measurement. This indicated that there could be some kind of linear correlation, as for higher friction values the difference between the systems has to be larger to keep the ratio constant.

Diﬀerence RT3 vs RoAR 3, Lane 1 7

4 %

0 -0.05 0 0.05 0.1 0.15 0.2 0.25 0.3 Diﬀerence

Figure 6.11: Diﬀerence distribution for RT3 vs. ROAR 3 for all runs on Fv31 in lane 1 54 CHAPTER 6. RESULTS AND DISCUSSION

ROAR 5 values were plotted for each measurement run, see Figure 6.12. For this measurement ROAR 5 used a standard Trelleborg T520 tire with straight grooves. The average friction values were less than the RT3 but slightly higher than ROAR 3. This could be due to the diﬀerent measurement tires, diﬀerent placement on the road or just small deviations in calibration.

RoAR 5, Lane 1 0.42 Run 1

Run 2 0.4 Run 3

0.38

0.36

0.34

Friction 0.32

0.3

0.28

0.26

0.24 0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 Distance [m]

Figure 6.12: Friction values from ROAR 5 for all runs on Fv31 in lane 1

Table 6.6 shows values of interest from ROAR 5 lane 1 runs. The average road grip for all runs was 0.3314 which was 73% of the RT3 average and 2.6% higher than the ROAR 3 average.

Table 6.6: Values of interest from ROAR 5 for all runs on Fv31 in lane 1 Average Relative Max Min road Relative Standard Run road grip Standard road grip grip diﬀer- deviation value deviation value value ence 1 0.3460 0.0228 6.59 0.40 0.28 42.86 2 0.3294 0.0247 7.50 0.38 0.26 46.15 3 0.3189 0.0257 8.06 0.38 0.24 58.33 6.2. 5 KM MEASUREMENT ON FV31, FASTSAND 55

In Figure 6.13 the percentage distribution of the diﬀerence in friction values between RT3 and ROAR 3 for all runs in lane 1 is shown. There were a slightly narrower distribution than between RT3 and ROAR 3 with concentrated peak values around 0.14-0.16. The peak values was also shifted right towards higher diﬀerence than for the 1km drive.

Diﬀerence RT3 vs RoAR 5, Lane 1 9

5 % 4

0 -0.05 0 0.05 0.1 0.15 0.2 0.25 0.3 Diﬀerence

Figure 6.13: Diﬀerence distribution for RT3 vs. ROAR 5 for all runs on Fv31 in lane 1

Seen in Figure 6.14 the RT3, ROAR 3 & 5 is plotted with driven distance for the ﬁrst run in lane 1. The RT3 measured higher friction but it also registered the short distances of low friction from road irregularities such as ice-covered and hollow surfaces. The same large spikes was not found for the ROAR systems, this was most likely due to the diﬀerent sample rates. ROAR measured friction from multiple samples collected at a distance of 10 meters and calculated the mean value for that distance. That is what made it unlikely for ROAR to register a large change of friction over short ice patches. 56 CHAPTER 6. RESULTS AND DISCUSSION

RT3, RoAR 3 & 5 Run 1, Lane 1 0.6 RT3

RoAR 3

0.55 RoAR 5

0.5

0.45

Friction 0.4

0.35

0.3

0.25 0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 Distance [m]

Figure 6.14: Friction values from RT3, ROAR 3 & 5, ﬁrst run on Fv31 in lane 1

6.3 Correlation

Due to the systems diﬀerence in sample rate it was not reasonable to analyze the correlation of the systems at each data point. An adequate solution was therefore to analyze the correlation between the mean values of each run. This conclusion is obviously dependant on the fact that the measured surfaces were generally homogeneous for the mean values to be valid and not misleading, e.g. measurements were only performed over a single type of road contamination. The mean correlation factor stated that it could be a linear relationship between the RT3 and NPRA systems. The factor described the ratio between the RT3 and NPRA systems, it was calculated for each system and run and is presented for the 1 km measurements in Table 6.7& 6.8. The factors were quite stable at around 0.7 ± 0.05 for all measurement runs and systems. 6.3. CORRELATION 57

Table 6.7: Mean correlation factors for all runs on Fv541 in lane 1 Lane 1 RoAR 1 RoAR 2 RoAR 4 Oscar vs. V.F vs. Runs vs. RT3 vs. RT3 vs. RT3 RT3 RT3 1 0.7052 0.6296 0.6371 0.6827 0.6871 2 0.6861 0.6596 0.6382 0.6176 0.6976 3 0.7689 0.7665 0.7090 0.6778 0.6966 4 0.7815 0.7346 0.7572 0.7876 0.7317 5 0.7673 N/A 0.8095 0.6581 0.6441 Mean 0.7418 0.6976 0.7102 0.6848 0.6914

Table 6.8: Mean correlation factors for all runs on Fv541 in lane 2 Lane 2 RoAR 1 RoAR 2 RoAR 4 Oscar vs. V.F vs. Runs vs. RT3 vs. RT3 vs. RT3 RT3 RT3 1 0.6845 0.6202 0.6586 0.6481 0.6630 2 0.7736 0.7186 0.7114 0.7704 0.6847 3 0.7676 0.7290 0.7455 0.6591 0.7058 4 0.7612 0.7193 0.7529 0.6906 0.7392 Mean 0.7467 0.6968 0.7171 0.6921 0.6982

For the 5 km measurement on Fv31 with higher friction the mean correlation factors presented in Table 6.9 was very similar to those from the 1 km with values around 0.73 ± 0.03. This gave more evidence that there could be a linear relation between the systems. 58 CHAPTER 6. RESULTS AND DISCUSSION

Table 6.9: Mean correlation factors for all runs on Fv31 in both lanes Lane 1 RoAR 3 RoAR 5 Runs vs. RT3 vs. RT3 1 0.7458 0.7540 2 0.6969 0.7175 3 0.6881 0.7154 Mean 0.7103 0.7290 Lane 2 Runs 1 0.7625 0.7798 2 0.7125 0.7563 3 0.7088 0.7456 Mean 0.7279 0.7606

Unfortunately all NPRA systems did not participate in all of the measurements. As all the ROAR vehicles was calibrated towards the same reference system (OSCAR), it was assumed that the ROAR 1 system that used the same tire type as ROAR 5 were similar in their measurements. Data was gathered for ROAR 1 in the 1km drive on FV541 and for ROAR 5 in the 5km drive on Fv31. Due to the diﬀerent road conditions between the two measurement drives it was possible to analyze the linear correlation by a polynomial regression of the scattered mean values from ROAR 1 & 5 vs. the RT3 seen in Figure 6.15. The scatter points in the lower left corner was from ROAR 1 vs. RT3 mean values for the 1 km drive from all runs and both lanes. The values in the upper right corner was from ROAR 5 vs. RT3 mean values for the 5km drive from all runs and both lanes. 6.3. CORRELATION 59

0.35

0.34 5 km on Fv31 ROAR 5 0.33

0.32

0.31 1 km on Fv541 ROAR 0.3 ROAR 1

0.29

0.28 ROAR vs. RT3

0.27 Polynomial ﬁt

0.36 0.37 0.38 0.39 0.4 0.41 0.42 0.43 0.44 0.45 0.46 RT3

Figure 6.15: ROAR as a function of RT3 for two sets of measurements with regression line

The straight line that best ﬁts all points has the equation

ROARmean(RT 3mean) = 0.6836RT 3mean + 0.02458 (6.1) with 95% conﬁdence bounds, R2 = 0.7707, and RMSE = 0.01371

The slope of the line was 0.6836 which was close to the calculated mean factors. The polynomial also intersect very close to the origin. The Correla- tion Coeﬃcient R2 indicates that 77% of the variation of friction values for ROAR is connected to variations in the RT3 data. 60 CHAPTER 6. RESULTS AND DISCUSSION 6.4 Discussion

In the 1 km measurement on Fv 541 a clear difference was observed on mean friction values between the RT3 and the NPRA systems. The RT3 measured on average a 0.1 higher friction value than the NPRA systems. When measuring the 5 km distance on Fv31 with generally better grip, the difference between the average friction values were slightly higher at 0.15. The mean correlation factor was therefore surprisingly stable around 0.7 ± 0.05. No clear difference could be observed between ROAR 3 and 5 which used different measurement tires. It has been proved very useful having access to NPRA’s photo-material to determine surface irregularities registered by the RT3. Since the road surfaces was generally homogeneous, track grooves was assumed not to interfere with the results. The tire pressure was excluded as a factor as it was equally around 2 bar for all systems. The main factors seemed to be the tire properties. The Oscar system used an ASTM E501 ribbed measurement tire seen in Figure 2.10, which was a belted bias construction and only has circumferential grooves as tread pattern. The RT3 in comparison had stud-less Bridgestone Blizzak Nordic WN-01 tires which were similar to any commonly used winter tire for cars. The Blizzak Nordic was a radial construction with an extensive variety of grooves and sipes in multiple directions as tread pattern and with a greater void ratio than the ASTM tire. The tread hardness durometer showed a minor difference with the ASTM tire measured to 58 ± 2 and the Blizzak Nordic to 55 ± 2. From section 2.2.3 it is stated that using softer rubber tread is favourable when traveling on snow and ice covered surfaces. With these facts in hand, there was nothing odd with the Blizzak Nordic generating a higher friction value than the ASTM tire.

There is possibly a difference in the end friction value due to the different measurement techniques. The RT3 measures the friction value in a moderate cornering maneuver with two measurement wheels and the goal is to investi- 6.4. DISCUSSION 61 gate the tires friction interaction with the road. The NPRA systems measures for a braking maneuver with a single tire and aims to investigate the change in road characteristics by using a neutral measurement tire which makes the friction values less controlled by e.g. the quality of the tread pattern2. The issues of the systems different sample-rates makes an instantaneous correlation for every sample point inapplicable. It also determines the end precision of the measurements, for the 5km measurement in Section 6.2 the ROAR systems could not detect small ice portions or hollow spots like the RT3 did. They could, if the road irregularities would cover a greater distance. We believe it is crucial to have capability to detect these irregularities as it could be disastrous for a car cornering. Introducing a sample-rate standard for all friction measurement systems would be useful in order to make this instantaneous correlation possible and eliminating precision differences, i.e. agree on a appropriate sample-rate capable of detecting minor road irregularities and simultaneously not generating an excessive amount of data. The RT3 has a sample-rate of 10 Hz, i.e. when travelling at 50 km/h it generates a friction value every 1.4 meters, is it enough or excessive? As previously mentioned, a lot of time was spent on modifying the data from the measurements in order to set up for a complete correlation-analysis. Unfortunately the time was not enough to investigate all of their dependencies more specifically.

Looking back at the project, a lot of planning could have been done dif- ferently. The measurement runs were done in an early phase of this project. A lot of researching were done after the measurements were made, thus many factors of importance regarding correlation for different measurement systems were unknown, resulting in some inefficient progression. If this were to be done again we would have worked for a more structured measurement progression, for instance more measurements on different surfaces would have been made with the RT3 and the OSCAR system.

2Leland, T. (1995) Friksjon mellom et gummihjul og vegdekket, Statens vegvesen, Veg- direktoratet. 62 CHAPTER 6. RESULTS AND DISCUSSION Chapter 7 Conclusions

We conclude that on road surfaces of compact snow and sand covered ice, the NPRA systems measures mean friction values that are 70% ± 5% of the mean values measured with the RT3 Curve. During these conditions this factor can serve as a translation between the systems. The main diﬀerences between the systems is clearly due to the diﬀerent tire sets. The sample-rates determines the end precision of the measurements as the results showed that small patches of road irregularities could not be detected by the ROAR systems as the RT3 did.

In order to possibly prove the relationship between the RT3 and NPRA systems in a general manner, more measurements needs to be done on other various winter surfaces. Also, an interesting research would be to investigate the result of swapped tires between the systems, for example, what friction values would OSCAR measure with RT3’s tires, would the correlation per- sist?

63 64 CHAPTER 7. CONCLUSIONS Bibliography

[1] Halliday Technologies Inc. RPUG The RT3 CFME Journey. Halliday Technologies Inc, 2013.

[2] Hugh D. Young & Roger A. Freedman. University Physics with Modern Physics Technology Update. Pearson Education, Harlow, England, 2014.

[3] Alex Klein-Paste & B˚ardNonstad. Textbook Maintenance and operations of Roads, chapter 5. Norwegian Public Road Administration, 2015.

[4] Jacob Svendenius. Tire Modeling and Friction Estimation. PhD thesis, Department of Automatic Control, Lund University, Lund, Sweden, April 2007.

[5] Richard Stone & Jeﬀrey K.Ball. Automotive Engineering Fundamentals. SAE International, Warrendale, USA, 2004.

[6] National Highway Traffic Safety Administration, James D. MacIsaac Jr. & Dr. W. Riley Garrott. Preliminary Findings of the Effect of Tire Inflation Pressure on the Peak and Slide Coefficients of Friction. US Department of Transportation, 2002.

[7] ASTM E501-08. Standard Speciﬁcation for Standard Rib Tire for Pave- ment Skid-Resistance Tests. ASTM, 2015.

[8] Mathieu Gerard. Tire-road friction estimation using slip-based observers. Master’s thesis, Department of Automatic Control, Lund University, Lund, Sweden, June 2006.

65 66 BIBLIOGRAPHY

[9] B˚ardNonstad. Testing Diﬀerent Measurement Tires. Norwegian Public Road Administration, Oslo, Norway, September 2006.

[10] Halliday Technologies Inc. RT3 Curve Description. Halliday Technolo- gies Inc, 2010.

[11] Ulrika Grönlund. Experimentell utvärderingav väggreppsmätarenrt3 curve. Master’s thesis, Department of Engineering Sciences and Mathe- matics, Lule˚aUniversity of Technology, Lule˚a,Sweden, May 2015.

[12] Norsemeter Company Information. http://www.norsemeter.no/ Company/. Accessed: 2016-05-30.

[13] ViaTech Home page. http://www.viatech.no/home.aspx?lang=en. Accessed: 2016-05-30.

[14] Thomas D. Gillespie. Fundamentals of Vehicle Dynamics. Society of Automotive Engineers, Inc, Warrendale, USA, 1992.

[15] John F. Sipe. Solid elastic tire for road vehicles. http://www.google. com/patents/US1455361, May 15 1923. US Patent 1,455,361.

[16] Sven Jansen, Antoine Schmeitz & Lars Akkermans. Study on some safety-related aspects of tyre use. European Commission, Directorate- general for Mobility and Transport, Brussels, Belgium, May 2014.

[17] A. Andresen & J. C. Wambold. Friction Fundamentals, Concepts and Methodology. Transportation Development Centre, 1999.

[18] Dieter Schramm, Manfred Hiller & Roberto Bardini. Vehicle Dynamics - Modeling and Simulation. Springer-Verlag Berlin and Heidelberg GmbH & Co. K, 2014.

[19] Hans B. Pacejka. Tyre and Vehicle Dynamics. Butterworth-Heinemann, Oxford, England, 2002.

[20] ASTM D2240-15. Standard Test Method for Rubber Prop- erty—Durometer Hardness. ASTM, 2015. BIBLIOGRAPHY 67

[21] Halliday Technologies Inc. RT3 Curve Installation and Operation Man- ual. Halliday Technologies Inc, 2010.

[22] MathWorks Polyﬁt. http://se.mathworks.com/help/matlab/ref/ polyfit.html. Accessed: 2016-05-30. 68 BIBLIOGRAPHY Appendix A

Appendix

A.1 1 km measurement on Fv541 in lane 1

Plots for RT3 unmodiﬁed and the remaining NPRA systems data on Fv541 in lane 1. RT3 modiﬁed, ROAR 1 and OSCAR data can be found in Section 6.1.

Unmodiﬁed RT3 Curve, Lane 1

0.5 Run 1 Run 2 Run 3 0.45 Run 4 Run 5

0.4

Friction 0.35

0.3

0.25 11.348 62.621 11.35 11.352 62.62 11.354 11.356 62.619 11.358 11.36 62.618 11.362 11.364 62.617 11.366 62.616 Longitude Latitude

Figure A.1: Friction values from the unmodiﬁed RT3 for all runs on Fv541 in lane 1

69 70 APPENDIX A. APPENDIX

Table A.1: Values of interest from Unmodiﬁed RT3 for all runs on Fv541 in lane 1 Relative Average Relative Max Min road Standard diﬀer- Run road grip Standard road grip grip deviation ence value deviation value value % 1 0.3906 0.04240 10.86 0.4933 0.2867 72.06 2 0.3890 0.02940 7.542 0.4800 0.3133 53.21 3 0.3818 0.03420 8.958 0.4400 0.3000 46.67 4 0.3624 0.03080 8.499 0.4667 0.2933 59.12 5 0.3709 0.03340 9.005 0.4600 0.2867 60.45

RoAR 2, Lane 1

0.4 Run 1 Run 2 Run 3 0.35 Run 4

0.3

Friction 0.25

0.2

0.15 11.348 62.621 11.35 11.352 62.62 11.354 11.356 62.619 11.358 11.36 62.618 11.362 11.364 62.617 11.366 62.616 Longitude Latitude

Figure A.2: Friction values from ROAR 2 for all runs on Fv541 in lane 1 A.1. 1 KM MEASUREMENT ON FV541 IN LANE 1 71

Table A.2: Values of interest from ROAR 2 for all runs on Fv541 in lane 1 Relative Average Relative Max Min road Standard diﬀer- Run road grip Standard road grip grip deviation ence value deviation value value % 1 0.2455 0.01860 7.576 0.3100 0.2100 47.62 2 0.2570 0.03250 12.65 0.3200 0.1800 77.78 3 0.2857 0.04340 15.19 0.4000 0.1700 135.3 4 0.2649 0.02990 11.29 0.3500 0.1800 94.44

Diﬀerence RT3 vs RoAR 2, Lane 1 10

5 %

0 -0.05 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 Diﬀerence

Figure A.3: Diﬀerence distribution from RT3 vs. ROAR 2 for all runs on Fv541 in lane 1 72 APPENDIX A. APPENDIX

RoAR 4, Lane 1

0.38 Run 1 0.36 Run 2 Run 3 0.34 Run 4 Run 5 0.32

0.3

0.28

Friction 0.26

0.24

0.22

0.2

0.18 11.348 62.621 11.35 11.352 62.62 11.354 11.356 62.619 11.358 11.36 62.618 11.362 11.364 62.617 11.366 62.616 Longitude Latitude

Figure A.4: Friction values from ROAR 4 for all runs on Fv541 in lane 1

Table A.3: Values of interest from ROAR 4 for all runs on Fv541 in lane 1 Relative Average Relative Max Min road Standard diﬀer- Run road grip Standard road grip grip deviation ence value deviation value value % 1 0.2486 0.02470 9.936 0.3100 0.2000 55.00 2 0.2487 0.02930 11.78 0.3500 0.1800 94.44 3 0.2643 0.03860 14.60 0.3600 0.1800 100.0 4 0.2731 0.03550 13.00 0.3700 0.1900 94.74 5 0.3014 0.04340 14.40 0.3800 0.2000 90.00 A.1. 1 KM MEASUREMENT ON FV541 IN LANE 1 73

Diﬀerence RT3 vs RoAR 4, Lane 1 9

5 % 4

0 -0.05 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 Diﬀerence

Figure A.5: Diﬀerence distribution from RT3 vs. ROAR 4 for all runs on Fv541 in lane 1

ViaFriction, Lane 1

0.45 Run 1 Run 2 0.4 Run 3 Run 4 Run 5 0.35

0.3

0.25 Friction

0.2

0.15

0.1 11.348 62.621 11.35 11.352 62.62 11.354 11.356 62.619 11.358 11.36 62.618 11.362 11.364 62.617 11.366 62.616 Longitude Latitude

Figure A.6: Friction values from ViaFriction for all runs on Fv541 in lane 1 74 APPENDIX A. APPENDIX

Table A.4: Values of interest from ROAR 4 for all runs on Fv541 in lane 1 Relative Average Relative Max Min road Standard diﬀer- Run road grip Standard road grip grip deviation ence value deviation value value % 1 0.2681 0.04900 18.28 0.4020 0.1700 136.5 2 0.2718 0.04260 15.67 0.3680 0.1480 148.7 3 0.2596 0.06140 23.65 0.4170 0.1360 206.6 4 0.2639 0.04230 16.03 0.3960 0.1780 122.5 5 0.2510 0.04820 19.20 0.3800 0.1370 177.4

Diﬀerence RT3 vs ViaFriction, Lane 1 9

5 % 4

0 -0.05 0 0.05 0.1 0.15 0.2 0.25 0.3 Diﬀerence

Figure A.7: Diﬀerence distribution from RT3 vs. ROAR 4 for all runs on Fv541 in lane 1

A.2 1 km measurement on Fv541 in lane 2

Plots for RT3 unmodiﬁed and the remaining NPRA systems data on Fv541 in lane 2. A.2. 1 KM MEASUREMENT ON FV541 IN LANE 2 75

RT3 modiﬁed, ROAR 1 and OSCAR data for lane 1 can be found in Section 6.1.

RT3 Curve, Lane 2

0.48 Run 1 0.46 Run 2 Run 3 0.44 Run 4

0.42

0.4

0.38 Friction

0.36

0.34

0.32

0.3 11.366 62.616 11.364 11.362 62.617 11.36 62.618 11.358 62.619 11.356 11.354 62.62 11.352 62.621 11.35 62.622 Longitude Latitude

Figure A.8: Friction values from the modiﬁed RT3 for all runs on Fv541 in lane 2

Table A.5: Values of interest from the modiﬁed RT3 for all runs on Fv541 in lane 2 Relative Average Relative Max Min road Standard diﬀer- Run road grip Standard road grip grip deviation ence value deviation value value % 1 0.3978 0.0276 6.938 0.4600 0.3267 40.80 2 0.3820 0.0351 9.189 0.4733 0.3133 51.07 3 0.3841 0.0342 8.904 0.4600 0.3200 43.75 4 0.3829 0.0338 8.827 0.4533 0.3067 47.80 76 APPENDIX A. APPENDIX

Oscar, Lane 2

0.34 Run 1

0.32 Run 2 Run 3

Run 4 0.3

0.28

0.26 Friction

0.24

0.22

0.2 11.366 62.6165 11.364 62.617 11.362 62.6175 62.618 11.36 62.6185 11.358 62.619 11.356 62.6195 11.354 62.62 11.352 62.6205 11.35 62.621 Longitude Latitude

Figure A.9: Friction values from OSCAR for all runs on Fv541 in lane 2

Table A.6: Values of interest from OSCAR for all runs on Fv541 in lane 2 Relative Average Relative Max Min road Standard diﬀer- Run road grip Standard road grip grip deviation ence value deviation value value % 1 0.2578 0.02210 8.573 0.3100 0.2200 40.91 2 0.2943 0.01960 6.660 0.3400 0.2500 36.00 3 0.2532 0.01760 6.951 0.3000 0.2100 42.86 4 0.2644 0.02080 7.867 0.3000 0.2100 42.86 A.2. 1 KM MEASUREMENT ON FV541 IN LANE 2 77

Diﬀerence RT3 vs Oscar, Lane 2 10

5 %

0 -0.05 0 0.05 0.1 0.15 0.2 0.25 Diﬀerence

Figure A.10: Diﬀerence distribution from RT3 vs. OSCAR for all runs on Fv541 in lane 2

RoAR 1, Lane 2

0.35 Run 1

Run 2

Run 3

Run 4 0.3 Friction

0.25

0.2 11.366 62.6165 11.364 62.617 11.362 62.6175 62.618 11.36 62.6185 11.358 62.619 11.356 62.6195 11.354 62.62 11.352 62.6205 11.35 62.621 Longitude Latitude

Figure A.11: Friction values from ROAR 1 for all runs on Fv541 in lane 2 78 APPENDIX A. APPENDIX

Table A.7: Values of interest from ROAR 1 for all runs on Fv541 in lane 2 Relative Average Relative Max Min road Standard diﬀer- Run road grip Standard road grip grip deviation ence value deviation value value % 1 0.2723 0.02860 10.50 0.3300 0.2200 50.00 2 0.2955 0.02030 6.870 0.3500 0.2500 40.00 3 0.2948 0.01600 5.427 0.3300 0.2600 26.92 4 0.2914 0.02480 8.511 0.3400 0.2100 61.90

Diﬀerence RT3 vs RoAR 1, Lane 2 12

6 %

0 -0.05 0 0.05 0.1 0.15 0.2 0.25 0.3 Diﬀerence

Figure A.12: Diﬀerence distribution from RT3 vs. ROAR 1 for all runs on Fv541 in lane 2 A.2. 1 KM MEASUREMENT ON FV541 IN LANE 2 79

Unmodiﬁed RT3 Curve

0.55 Run 1 Run 2 Run 3 0.5 Run 4

0.45

Friction 0.4

0.35

0.3 11.368 11.366 62.616 11.364 62.617 11.362 62.618 11.36 11.358 62.619 11.356 62.62 11.354 11.352 62.621 11.35 62.622 Longitude Latitude

Figure A.13: Friction values from the unmodiﬁed RT3 for all runs on Fv541 in lane 2

Table A.8: Values of interest from the unmodiﬁed RT3 for all runs on Fv541 in lane 2 Relative Average Relative Max Min road Standard diﬀer- Run road grip Standard road grip grip deviation ence value deviation value value % 1 0.4023 0.03080 7.656 0.4600 0.3200 43.75 2 0.3850 0.03320 8.623 0.4733 0.3133 51.07 3 0.3894 0.03750 9.630 0.4733 0.3000 57.77 4 0.4012 0.04340 10.82 0.5067 0.3067 65.21 80 APPENDIX A. APPENDIX

RoAR 2, Lane 2

0.45 Run 1 Run 2 0.4 Run 3 Run 4 0.35

0.3 Friction

0.25

0.2

0.15 11.368 11.366 62.616 11.364 62.617 11.362 62.618 11.36 11.358 62.619 11.356 62.62 11.354 11.352 62.621 11.35 62.622 Longitude Latitude

Figure A.14: Friction values from ROAR 2 for all runs on Fv541 in lane 2

Table A.9: Values of interest from ROAR 2 for all runs on Fv541 in lane 2 Relative Average Relative Max Min road Standard diﬀer- Run road grip Standard road grip grip deviation ence value deviation value value % 1 0.2467 0.02400 9.728 0.3100 0.2000 55.00 2 0.2745 0.02870 10.46 0.3300 0.1900 73.68 3 0.2800 0.04680 16.71 0.4100 0.1900 115.8 4 0.2754 0.03930 14.27 0.3600 0.2100 71.43 A.2. 1 KM MEASUREMENT ON FV541 IN LANE 2 81

Diﬀerence RT3 vs RoAR 2, Lane 2 10

5 %

0 -0.05 0 0.05 0.1 0.15 0.2 0.25 0.3 Diﬀerence

Figure A.15: Diﬀerence distribution from RT3 vs. ROAR 2 for all runs on Fv541 in lane 2

RoAR 4, Lane 2

0.36 Run 1

0.34 Run 2

Run 3 0.32 Run 4 0.3

0.28

0.26 Friction

0.24

0.22

0.2

0.18 11.366 62.6165 11.364 62.617 11.362 62.6175 62.618 11.36 62.6185 11.358 62.619 11.356 62.6195 11.354 62.62 11.352 62.6205 11.35 62.621 Longitude Latitude

Figure A.16: Friction values from ROAR 4 for all runs on Fv541 in lane 2 82 APPENDIX A. APPENDIX

Table A.10: Values of interest from ROAR 4 for all runs on Fv541 in lane 2 Relative Average Relative Max Min road Standard diﬀer- Run road grip Standard road grip grip deviation ence value deviation value value % 1 0.2620 0.03260 12.44 0.3500 0.2000 75.00 2 0.2718 0.02030 7.469 0.3400 0.2300 47.83 3 0.2864 0.03140 10.96 0.3600 0.2300 56.52 4 0.2882 0.03500 12.14 0.3600 0.1900 89.47

Diﬀerence RT3 vs RoAR 4, Lane 2 10

5 %

0 -0.05 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 Diﬀerence

Figure A.17: Diﬀerence distribution from RT3 vs. ROAR 2 for all runs on Fv541 in lane 2 A.2. 1 KM MEASUREMENT ON FV541 IN LANE 2 83

ViaFriction, Lane 2

0.45 Run 1

Run 2 0.4 Run 3

Run 4 0.35

0.3 Friction

0.25

0.2

0.15 11.366 62.6165 11.364 62.617 11.362 62.6175 62.618 11.36 62.6185 11.358 62.619 11.356 62.6195 11.354 62.62 11.352 62.6205 11.35 62.621 Longitude Latitude

Figure A.18: Friction values from ViaFriction for all runs on Fv541 in lane 2

Table A.11: Values of interest from ROAR 4 for all runs on Fv541 in lane 2 Relative Average Relative Max Min road Standard diﬀer- Run road grip Standard road grip grip deviation ence value deviation value value % 1 0.2637 0.04660 17.67 0.3700 0.1600 131.3 2 0.2615 0.02810 10.75 0.3470 0.2040 70.10 3 0.2711 0.04750 17.52 0.3720 0.1730 115.0 4 0.2830 0.05400 19.08 0.4150 0.1670 148.5 84 APPENDIX A. APPENDIX

Diﬀerence RT3 vs ViaFriction, Lane 2 8

4 %

0 -0.05 0 0.05 0.1 0.15 0.2 0.25 0.3 Diﬀerence

Figure A.19: Diﬀerence distribution from RT3 vs. ROAR 2 for all runs on Fv541 in lane 2

A.3 5 km measurement on Fv31 in lane 2

Plots for RT3, ROAR 3 and 5 data on Fv31 in lane 2. RT3, ROAR 3 and 5 data for lane 1 data can be found in Section 6.2. A.3. 5 KM MEASUREMENT ON FV31 IN LANE 2 85

RT3, Lane 2 0.6 Run 1

Run 2 0.55 Run 3

0.5

0.45

0.4 Friction

0.35

0.3

0.25

0.2 0 1000 2000 3000 4000 5000 6000 Distance [m]

Figure A.20: Friction values from RT3 for all runs on Fv31 in lane 2

Table A.12: Values of interest from RT3 for all runs on Fv31 in lane 2 Relative Average Relative Max Min road Standard diﬀer- Run road grip Standard road grip grip deviation ence value deviation value value % 1 0.4455 0.05000 11.22 0.5533 0.2000 176.7 2 0.4479 0.05140 11.48 0.5467 0.2933 86.4 3 0.4316 0.05370 12.44 0.5533 0.2667 107.5 86 APPENDIX A. APPENDIX

RoAR 3, Lane 2 0.45 Run 1

Run 2

0.4 Run 3

0.35 Friction 0.3

0.25

0.2 0 1000 2000 3000 4000 5000 6000 Distance [m]

Figure A.21: Friction values from ROAR 3 for all runs on Fv31 in lane 2

Table A.13: Values of interest from ROAR 3 for all runs on Fv31 in lane 2 Relative Average Relative Max Min road Standard diﬀer- Run road grip Standard road grip grip deviation ence value deviation value value % 1 0.3397 0.02310 6.800 0.4300 0.2800 53.57 2 0.3191 0.02950 9.245 0.4200 0.2400 75.00 3 0.3059 0.03100 10.13 0.4100 0.2300 78.26 A.3. 5 KM MEASUREMENT ON FV31 IN LANE 2 87

Diﬀerence RT3 vs RoAR 3, Lane 2 8

4 %

0 -0.05 0 0.05 0.1 0.15 0.2 0.25 0.3 Diﬀerence

Figure A.22: Diﬀerence distribution from RT3 vs. ROAR 3 for all runs on Fv31 in lane 2

RoAR 5, Lane 2 0.42 Run 1

Run 2 0.4 Run 3

0.38

0.36

0.34

Friction 0.32

0.3

0.28

0.26

0.24 0 1000 2000 3000 4000 5000 6000 Distance [m]

Figure A.23: Friction values from ROAR 5 for all runs on Fv31 in lane 2 88 APPENDIX A. APPENDIX

Table A.14: Values of interest from ROAR 5 for all runs on Fv31 in lane 2 Relative Average Relative Max Min road Standard diﬀer- Run road grip Standard road grip grip deviation ence value deviation value value % 1 0.3474 0.02060 5.930 0.4000 0.2800 42.86 2 0.3388 0.02290 6.759 0.3900 0.2500 56.00 3 0.3218 0.02690 8.359 0.3900 0.2400 62.50

Diﬀerence RT3 vs RoAR 5, Lane 2 9

5 % 4

0 -0.05 0 0.05 0.1 0.15 0.2 0.25 0.3 Diﬀerence

Figure A.24: Diﬀerence distribution from RT3 vs. ROAR 3 for all runs on Fv31 in lane 2 A.3. 5 KM MEASUREMENT ON FV31 IN LANE 2 89

RT3, RoAR 3 & 5 Run 1, Lane 2 0.6 RT3

RoAR 3 0.55 RoAR 5

0.5

0.45

0.4 Friction

0.35

0.3

0.25

0.2 0 1000 2000 3000 4000 5000 6000 Distance [m]

Figure A.25: Friction values from RT3, ROAR 3 & 5 for run 1 on Fv31 in lane 2