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Sensor Data Fusion Based Estimation of Tyre–Road Friction to Enhance Collision Avoidance

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Sensor Data Fusion Based Estimation of Tyre–Road Friction to Enhance Collision Avoidance VTT CREATES BUSINESS FROM TECHNOLOGY Technologyandmarketforesight•Strategicresearch•Productandservicedevelopment•IPRandlicensing Dissertation VTT PUBLICATIONS 730 •Assessments,testing,inspection,certification•Technologyandinnovationmanagement•Technologypartnership • • • VTT PUBLICATIONS 730 SENSOR This dissertation discusses the estimation of maximum coefficients of friction be- tween tyres and a road surface, together with the determination of road conditions. The estimation is based on sensor data fusion, combining data from three classes DATA of sensors: environmental sensors, sensors measuring vehicle dynamics and experi- mental tyre sensors. FUSION Upcoming collision avoidance and collision mitigation systems need information on tyre grip to further improve their calculations for braking distances and evasive manoeuvres. The advantages of friction estimation for collision avoidance and col- BASED lision mitigation systems are analysed using simulations. A correct initial estimate of the maximum coefficient of friction supports the systems to efficiently improve ESTIMATION traffic safety also in slippery road conditions. OF TYRE - ROAD FRICTION... Sami Koskinen Sensor Data Fusion Based Estimation of Tyre-Road Friction to Enhance Collision Avoidance ISBN 978-951-38-7382-0 (soft back ed.) ISBN 978-951-38-7383-7 (URL: http://www.vtt.fi/publications/index.jsp) ISSN 1235-0621 (soft back ed.) ISSN 1455-0849 (URL: http://www.vtt.fi/publications/index.jsp) VTT PUBLICATIONS 730 Sensor Data Fusion Based Estimation of Tyre–Road Friction to Enhance Collision Avoidance Sami Koskinen A dissertation for the degree of Doctor of Science in Technology is to be presented by permission of the Faculty of Automation, Mechanical and Materials Engineering, the Tampere University of Technology, for public examination and debate in lecture hall K1702 in Konetalo (Korkeakoulunkatu 6) on Friday, 12 March 2010, at 12 noon. ISBN 978-951-38-7382-0 (soft back ed.) ISSN 1235-0621 (soft back ed.) ISBN 978-951-38-7383-7 (URL: http://www.vtt.fi/publications/index.jsp) ISSN 1455-0849 (URL: http://www.vtt.fi/publications/index.jsp) Copyright © VTT 2010 JULKAISIJA – UTGIVARE – PUBLISHER VTT, Vuorimiehentie 5, PL 1000, 02044 VTT puh. vaihde 020 722 111, faksi 020 722 4374 VTT, Bergsmansvägen 5, PB 1000, 02044 VTT tel. växel 020 722 111, fax 020 722 4374 VTT Technical Research Centre of Finland, Vuorimiehentie 5, P. O. Box 1000, FI-02044 VTT, Finland phone internat. +358 20 722 111, fax +358 20 722 4374 Textual editing Mark Phillips Technical editing Mirjami Pullinen Edita Prima Oy, Helsinki 2010 Sami Koskinen. Sensor Data Fusion Based Estimation of Tyre–Road Friction to Enhance Collision Avoidance [Anturidatafuusioon perustuva renkaan ja tien välisen kitkan estimointi ja tulosten hyödyntä- minen törmäyksenestossa]. Espoo 2010. VTT Publications 730. 188 p. + app. 12 p. Keywords friction, sensor, data fusion, collision avoidance, collision mitigation, environmental sensing, tyre, road, conditions, trajectory, curvature-velocity, ADAS Abstract Vehicle steering, braking and acceleration are subject to friction forces arising from contact of the tyres with the road surface. The contact force is both enabling and limiting. The ratio of the contact friction to the force of the tyres pressing on the road surface is described as the coefficient of friction. The maximum coefficient of fric- tion for different surfaces characterizes the extent of tyre grip. Collision avoidance and collision mitigation systems require information on tyre grip so as to accurately calculate braking distances and evasive manoeuvres. Estimat- ing road slipperiness (skid resistance) during driving has however proven difficult. This dissertation discusses estimating the maximum coefficient of friction (herein referred to as the friction potential) together with determining road conditions. Both estimations are based on multi-sensor data fusion; that is, combining data from several sensors. The presented sensor data fusion utilizes various sensors from three main classes: 1) environmental sensors, 2) sensors measuring vehicle dynamics and 3) ex- perimental tyre sensors. This work concentrates particularly on methods for combin- ing measurements of vehicle dynamics with environmental sensor readings; for exam- ple, wheel speed signals are linked to readings about ice, snow or water on the road. The methods were incorporated into a prototype passenger car implementation, where testing yielded a reliable estimate of friction potential for approximately 90% of driving time. The estimate of friction potential was then within 0.2 of reference values measured in braking tests. These results encapsulate a proof of concept on asphalt roads in some wet, snowy, icy and dry road conditions. The advantages of friction estimation for collision avoidance and collision miti- gation systems are analysed using mainly simulations. A correct initial estimate of the friction potential enables the systems to improve traffic safety efficiently also in slippery road conditions. However, the range of available environmental sensors does not cover long braking distances. 3 Together with the simulations, the work introduces a new method for collision avoidance calculations and timing the activation of collision mitigation. The method is based on a large number of pre-calculated vehicle trajectories. 4 Sami Koskinen. Sensor Data Fusion Based Estimation of Tyre–Road Friction to Enhance Collision Avoidance [Anturidatafuusioon perustuva renkaan ja tien välisen kitkan estimointi ja tulosten hyödyn- täminen törmäyksenestossa]. Espoo 2010. VTT Publications 730. 188 s. + liitt. 12 s. Keywords friction, sensor, data fusion, collision avoidance, collision mitigation, environmental sensing, tyre, road, conditions, trajectory, curvature-velocity, ADAS Tiivistelmä Renkaiden ja tien välinen liikettä vastustava voima, kitka, asettaa rajat ajoneu- von ohjaukselle, jarrutukselle ja kiihdytykselle. Se on samalla sekä mahdollista- va että rajoittava kontaktivoima. Kitkan ja renkaita tietä vasten puristavan voi- man suhde ilmaistaan kitkakertoimella. Kitkakertoimen maksimiarvo eri pinnoil- la kuvaa renkaiden pitävyyttä. Kehitteillä oleviin törmäyksiä estäviin ja törmäysenergiaa lieventäviin kuljet- tajan tukijärjestelmiin tarvitaan tietoa renkaiden pitävyydestä, jotta jarrutusmat- koja ja väistömahdollisuuksia voidaan arvioida entistä tarkemmin. Tien liukkau- den määrittäminen ennalta ajon aikana, ilman renkaiden selkeää luistoa, on kui- tenkin osoittautunut hankalaksi. Tämä väitöstyö käsittelee kitkakertoimen maksimiarvon, tässä kitkapotentiaa- lin, ja kelitietojen määrittämistä. Tutkimuksessa hyödynnetään anturidatafuusio- ta eli useiden antureiden tuottamien tietojen yhdistämistä. Anturidatafuusiossa käytetyt anturit edustavat kolmea päätyyppiä: 1) ympäristöä havainnoivat antu- rit, 2) auton liiketilaa mittaavat anturit ja 3) rengasantureiden prototyypit. Työssä keskitytään erityisesti menetelmiin, joilla voidaan yhdistää ajoneuvon liiketilan mittaustietoja ympäristöä havainnoivien antureiden tuottamiin tietoihin. Esimer- kiksi renkaiden pyörimisnopeuksista saatuja tietoja yhdistetään tietoihin tiellä olevasta jäästä, lumesta tai vedestä. Esitellyillä menetelmillä ja henkilöautoon toteutetulla prototyyppijärjestelmällä on testeissä kyetty arvioimaan kitkapotentiaalia luotettavasti noin 90 prosenttia ajoajasta. Tällöin kitkapotentiaalin arvio poikkeaa enintään 0,2 jarrutustesteillä mitatuista referenssiarvoista. Järjestelmää on testattu asfalttiteillä. Menetelmien toimivuus on todennettu joukolla märkiä, lumisia, jäisiä ja kuivia kelejä. Kitka-arvion hyötyjä on analysoitu törmäyksiä estävissä ja törmäysenergiaa lieventävissä järjestelmissä pääasiassa simulaatiotuloksia käyttäen. Arvio kitka- 5 potentiaalista auttaa näitä järjestelmiä parantamaan liikenneturvallisuutta tehok- kaasti myös liukkailla keleillä. Kuitenkaan saatavilla olevien keliantureiden mit- tauskantama ei vielä kata pitkiä jarrutusmatkoja. Tämä työ esittelee simulaatioiden yhteydessä uuden, lukuisiin ennalta lasket- tuihin liikeratoihin perustuvan nopean laskentamenetelmän törmäystilanteiden arviointiin ja esteiden väistöön. 6 Preface The research for this thesis was mainly carried out in the FRICTI@N EU pro- ject, funded by the European Commission as part of the 6th Framework Pro- gramme. The project concentrated on measuring and estimating tyre–road fric- tion with several vehicle-mounted sensors. I am grateful to the whole consortium (10 partners) for their co-operation and insight into the friction phenomenon and all the different ways to detect it. The project was initiated by Dr Tapani Mäkinen (VTT), who saw the need for a dedicated project aimed at providing more information that would be useful for vehicle safety systems. He has also guided us young scientists at VTT into the networks of automotive research in the EU. Thank you for the opportunity! The author’s main responsibility in the FRICTI@N project was the high-level sensor data fusion architecture and implementation. Several people have helped to improve the initial designs and I want to express my total gratitude especially to the project co-ordinator Pertti Peussa (VTT), Dr Liang Nanying, who was visiting VTT from Singapore Technological University at the time, Thomas Haas from VDO Automotive AG, who pushed forward especially the vehicle dynamics based algorithms, and Dr Matti Kutila (VTT) for discussions on envi- ronmental sensing. This research would not have been possible without Christian
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