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Winter Test of ABD Steering Robot

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Winter Test of ABD Steering Robot RESEARCH REPORT Department of Computer Science, Electrical and Space Engineering Division of EISLAB ISSN: 1402-1528 ISBN 978-91-7439-845-8 (pdf) Luleå University of Technology 2014 Winter test of ABD steering robot Håkan Fredriksson Niclas Engström Jeremy Ash June 19, 2013, rev 1.0 Winter test of ABD steering robot H˚akan Fredrikssona, Niclas Engstr¨oma, Jeremy Ashb aLule˚aUniversity of Technology bAnthony Best Dynamics Supported by: ISSN: 1402-1528 ISBN 978-91-7439-845-8 (pdf) Luleå 2014 www.ltu.se Preface This report comprise the winter test of a steering robot that were performed during the winter 2012/2013 in Sweden. The scope for the test was to evaluate if, and subsequently how, a path-following steering robot can be used for winter test of cars. This work was performed within the Centre for Automotive Systems Technologies and Testing (CASTT) at Lule˚aUniversity of Technology, together with Anthony Best Dynamics. The ob- jective was to support the vehicle test region in the northern part of Sweden by elaborating new test tools and methods. The work was funded by the European Regional Development Fund (ERDF). The main author is H˚akan Fredriksson. Niclas Engstr¨om has been involved in the planning and execution of the experiments and partly writing of the report. Jeremy Ash supplied training on the steering robot and participated in early parts of the tests. Lule˚aJune 2013 H˚akan Fredriksson iii iv Abstract This report highlights the use of a steering robot with path-following for car testing in winter conditions. The steering robot was provided from Anthony Best Dynamics. Experiments have been made with a couple of commonly used test sequences (lane change, dual lane change, constant radius circle, handling), the result from these test are shown and discussed. The path-following algorithm gives steering commands to the car (replace the human driver), these commands affect how the car will move; hence, the car performance is affected by the behaviour of the path-following algorithm. The settings of the path-following algorithm greatly affect the car response in different situations. This is especially noticeable when the car starts to slide, a situation common when driving on a slippery winter road. The main focus for this report is to describe what happens when you push the path-following system to, and beyond, the physical limitations concerning road grip and vehicle speed. A theoretical analysis of the path-following algorithm and how it reacts on large lateral errors and high sideslip angles was done. As shown in the results, the evaluated path-following test sequences in general did work out well. Some characteristics of the algorithm, especially noticeable when driving in winter condition, were found and discussed. The overall impression is that the ABD steering robot with path-following can indeed be useful for repetitive test in winter conditions with bad road grip. v vi Contents Preface iii Abstract v Contents vii 1 Introduction 1 1.1 Steeringrobot................................... ... 1 1.2 ABDpath-following ............................... ... 2 1.3 Relatedwork ..................................... 3 1.4 Thisreport ...................................... 3 2 Method 4 2.1 Equipment ....................................... 4 2.2 Testsite........................................ 6 2.3 Testprocedure ................................... 6 2.4 Dataprocessing.................................. ... 7 3 Result 8 3.1 Theoreticalanalysis ............................. ..... 8 3.2 Experimentaltests ............................... 11 3.2.1 Testmanoeuvres ................................ 11 3.2.2 PF-settings ................................... 13 3.2.3 Othernotes................................... 17 4 Discussion 19 4.1 Conclusion ...................................... 19 4.2 Futurework...................................... 20 Bibliography 20 Appendices A Single Lane Change 22 B Double Lane Change 31 C Constant Radius Circle 33 D Handling Track 34 vii viii Chapter 1 Introduction This report discusses the experience of using one of Anthony Best Dynamics (ABD) steering robots, with path-following capability, for winter test of a car. The ABD steering robots are commonly used for vehicle testing in situations where high repeatability is of importance and/or the safety of a human driver is in danger. 1.1 Steering robot A steering robot is a device that can be mounted inside of a vehicle, on top of, or instead of, the steering wheel, see Figure 1.1. The device is controlled by a programmable computer and replaces the steering input that the human driver normally gives as input when driving. Using the steering robot system a steering manoeuvre can be repeated over and over again in a precise manner. Figure 1.1: ABD SR30 steering robot installed in a Volvo V70. There are mainly two approaches when using a steering robot for vehicle testing. The first is open loop control, and the second is closed loop control, of the angle of the steering wheel. 1 1.2. ABD PATH-FOLLOWING CHAPTER 1. INTRODUCTION Table 1.1: List of symbols. α Angle to aimpoint Θ Vehicle heading offset γ Angular error due to lateral offset b Lateral offset q Projected lateral error due to heading offset v Vehicle forward velocity lad look ahead distance Kp(v) Proportional gain function p(v) Preview distance function LAC Look Ahead Constant P Proportional gain I Integral gain D Differential gain Using the open loop control the steering wheel is turned in an exact predefined pattern. There are today several different test sequences defined for these kinds of static steering manoeuvres, Sine-dwell and the Fishhook test are two examples of such tests. Using closed loop control the vehicle position and orientation is continually compared with a predefined drive path, i.e. path-following. If the vehicle deviates from the path, the controller tries to compensate for this and strives to steer the car back to the track. 1.2 ABD path-following The path-following algorithm in the ABD robot controller is primarily implemented according to paper [1]. It is described as ”...essentially a proportional feedback controller on ’path error’...” [1] where the path error is defined as the projected lateral position offset at a specified distance in front of the vehicle. I.e. the algorithm utilise a look ahead distance, lad to find out if the vehicle, given its current position and orientation, will end up on the defined track at a certain distance ahead. If not, the controller will control the steering angle to steer the vehicle back towards the track. A list of the most commonly used symbols throughout the report is shown in Table 1.1. The path-following controller is implemented as a PID-controller, using the projected path error as input. Figure 1.2 shows the key aspects on how the error is defined. The path error can be divided into two parts: the lateral error b due to the vehicle not located on the path, and the projected lateral error q due to the vehicle heading not pointing in the desired travel direction. Hence, the total path error used as input to the controller is b + q. Regarding path-following, there are mainly four parameters to tune when setting up the ABD steering robot in a new vehicle, the Proportional gain P , Integral gain I, Differential gain D, and the Look ahead constant LAC. As described in the paper [1], both the proportional gain, as well as the look ahead distance (a.k.a. preview distance), are speed dependent according to given functions, namely 2 Kp(v)= −0.99v − 7.1v + 602.2, v ≤ 15m/s 2 Kp(v) = 61380/v , v> 15m/s (1.1) and 2 p(v) = 0.0227v − 0.0671v + 1.6781 (1.2) respectively. 2 CHAPTER 1. INTRODUCTION 1.3. RELATED WORK Y Aimpoint b q α γ ϴ lad X Figure 1.2: Description of the path error used in the path-following controller. The vehicle (shown as a tricycle) is set to follow a straight line located on the y-axis. If desired by the user, these functions may be adjusted. However, throughout the tests presented in this report these functions where left unchanged. When changing the parameters P or LAC, the output from these two functions is scaled accordingly. Hence, the look ahead distance lad is calculated with LAC ∗ p(v) and the proportional gain used in the controller is P ∗ Kp(v). 1.3 Related work So far there is not much written knowledge and experience for the use of steering robot in winter conditions. The Swedish research institute VTI has made some experiments aiming at testing the ESP system of a car [2] and provoking over steering on ice and snow with different winter tires [3]. However, in these tests they only use static pre-programmed steering manoeuvres (sine with dwell). No feedback control based on the vehicle position is used. 1.4 This report The experiments described in this report focus on the use of closed loop control of the steering angle of the car, i.e. path-following, on road surfaces like snow and ice. Extensive tests have been performed on a test track located on a frozen lake. Several different test manoeuvres has been performed and evaluated. The main question this report tries to answer is: • What happen when you push the path-following system to, and beyond, the physical limitations concerning road grip and vehicle speed? This is something that does indeed occur when driving during winter conditions on low friction surfaces such as ice and snow. One important part when winter testing cars is to provoke the car in such a manner so that the Electronic Stability Control (ESC) of the car is activated. How well does the path-following algorithm cope with under-steering and over-steering behaviour of the car? To fully understand the details in this report it is necessary to know how the path-following algorithm used in the ABD steering robot works.
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