INTEGRATION OF A PHENOMENOLOGICAL RADAR SENSOR MODELL IN IPG CARMAKER FOR SIMULATION OF ACC AND AEB SYSTEMS

Transcription

1 INTEGRATION OF A PHENOMENOLOGICAL RADAR SENSOR MODELL IN IPG CARMAKER FOR SIMULATION OF ACC AND AEB SYSTEMS Dr. A. Eichberger*, S. Bernteiner *, Z. Magoi *, D. Lindvai-Soo **, * Intitute of Automotive Engineering, TU Graz ** MAGNA STEYR Engineering, Graz;

2 OVERVIEW Introduction / Motivation Decription of the Model Reult Concluion / Outlook

3 INTRODUCTION / MOTIVATION Today Advanced Driver Aitance Sytem (ADAS) mot time optional equipment Euro NCAP will tart to include Autonomou Emergency Brake Sytem (AEB) and Lane Keeping Sytem (LKA) in their tar rating ADAS will become tandard equipment Validation of thee ytem i done with real tet drive which are expenive, time conuming, afety critical, The validation proce can be optimized by uing appropriate imulation tool more frequently

4 METHODS FÜR ADAS VALIDATION Prototype and road trial Man-in-the-Loop Teting - Driving imulator Hardware-in-the-Loop Teting - e.g. enor tet benche Modelling and imulation Source: MAGNA Steyr, IPG, Toyota, FTG

5 Prototype and road trial - Full vehicle required - Profeional tet driver - Sophiticated meaurement equipment - Tet track or public road - Many teting kilometer - Reproducibility - Final proof Source: MAGNA Steyr

6 Example of road baed ADAS validation by EURO-NCAP AEB tet procedure Source: MAGNA Steyr

7 Source: MAGNA Steyr

8 MAN-IN-THE-LOOP: DRIVING SIMULATORS INVESTIGATION OF HUMAN-SYSTEM INTERACTION, SAFETY, CONFIDENCE AND ACCEPTANCE Source: Hochchule Regenburg, Ftronik, FTG, imtec, BMW, Toyota

9 HIL TEST BENCHES Example: HiL tet bench for camera validation Source: IPG

10 MODELLING AND SIMULATION OF ADAS - Automatized imulation of maneuver - Automatized analyi and report

11 WHY PHENOMENOLOGICAL MODEL? Phyical radar enor model A lot of parameter are not available Model are not time efficient Bet repreentation of phyical effect in imulation Phenomenological radar enor model For concept tudie eay parameterization uing data heet Very time efficient imulation Real effect like time delay, ignal loe and noiy ignal are conidered and influence the imulation

12 MODULES OF THE SENSOR MODEL

13 GEOMETRIC MODEL Parameterization FOV Coordinate tranformation Obcuring Determination of reference point φ min,1 < φ 2 < φ max,1 Target T2 obcured

14 REAL SENSOR CHARACTERISTICS Antenna characteritic Approximated with 2 nd order polynomial SNR r, φ, σ = a 1 r 2 + a 2 r + a 3 1 ab b 1 φ 2 + b 2 φ + b 3 + N 0, σ 2 Standard deviation depending on poition and target type σ = ε 0 + r ε r + φ ε φ Type Poition

15 REAL SENSOR CHARACTERISTICS Receiver Characteritic Gauian ditribution Weather-dependent Fixed detection limit SNR i SNR lim Target i detected

16 SIGNAL PROCESSING Extended Kalman Filter Filtering of the raw ignal Handle hort term ignal loe State-pace model vx,k x k ax,k yk vy,k ay,k = x k 1 + v x,k 1 Δt a x,k 1Δt 2 v x,k 1 + a x,k 1 Δt a x,k 1 y k 1 + v y,k 1 Δt a y,k 1Δt 2 v y,k 1 + a y,k 1 Δt a y,k 1 (cont. accel. model) Nonlinear obervation model h = x 2 k + y 2 k arctan y k x k Q k = σ 2 a x σ ay Covariance matrix, where 1 2 Δa max,j σ aj Δa max,j

17 SIGNAL PROCESSING Path Prediction Steady tate cornering with low lateral acceleration curvature i contant Path prediction uing the parable approach y = 1 2 x 2 ψ v Relevant Target if reference point within predicted path

18 PARAMETRIZATION BY ROAD TRIALS Serie production enor

19 MANOEUVRE DESCRIPTION Ego and T1 driving at 130 kph T3 T4 driving at 90 kph T2 change lane within 2.5 if r 2 < 24 m Ego vehicle equipped with AEB Actuation of brake if TTC = r r < 0.9 Building up max. acceleration within 0.5

20 MANOEUVRE VIDEO Tranparent vehicle: PHENOMENOLOGICAL enor model Solid vehicle: IDEAL enor model

21 MANOEUVRE RESULTS Random ignal loe T2 appear in FOV of the phen. model Delay due to ignal proceing

22 SUMMARY Module of the phenomenological radar enor model wa decribed Comparion of the imulation reult with the phenomenological and an ideal model wa hown Significant difference in the outcome of the imulated cenario The ue of the decribed model generate more realitic reult and can improve the development proce of new driver aitance ytem

23 OUTLOOK More road trial for enhancement to weather condition and proviion of databae for tochatic event uch a ignal lo Enhancement for other enor principle uch a laer Enhancement for HiL tet benche