"auto.mobile-driving simulator" - a new immersion IPG - - PowerPoint PPT Presentation

Fakultät Verkehrswissenschaften „Friedrich List“ - Institut für Automobiltechnik Dresden–IAD - Lehrstuhl Kraftfahrzeugtechnik

Faculty of Transportation and Traffic Sciences „Friedrich List“ - Institute for Automotive Technologies Dresden - Chair of Automotive Engineering

"auto.mobile-driving simulator" - a new immersion IPG Apply & Innovate 2016

Tüschen, T .; Prokop, G.

21.09.16 – Karlsruhe IPG Apply & Innovate ‘16 – Thomas Tüschen 2

Agenda 1 Motivation 2 State-of-the-art driving simulator 3 auto.mobile-driving simulator 4 Prediction

21.09.16 – Karlsruhe IPG Apply & Innovate ‘16 – Thomas Tüschen 3

Passive safety Active safety / ADAS

Ratable by means of the cars technical properties:

• occupant values
• intrusion values

Ratable only on the basis of the interaction of the driver and the car under realistic environmental impact (e.g. traffic):

• probability of an accident
• potential accident severity

A-priori evaluation possible due to crash-tests and simulation Mostly ex-post evaluation possible based on analysis of sufficient numerous accident statistics

• 1. Motivation

Evaluation of Advanced Driver Assistance Systems

Source: Euro NCAP Source: Euro NCAP

21.09.16 – Karlsruhe IPG Apply & Innovate ‘16 – Thomas Tüschen 4

• 1. Motivation

Use of driving simulator

Advanced Driver Assistance Systems & Automated Driving Driving Dynamics (also part of ADAS)

• high variety of driving scenarios
• highly immersive driving simulators necessary
• high (horizontal-) dynamic necessary
• unscaled motion perception

Source: BMW AG Source: Bosch

Driving Simulator Dynamics

Source: Toyota Source: Daimler Source: DLR

Driving scenarios

Source: Verlag Heinrich Vogel

Critical exemplary scenario: high frequencies, high acceleration Critical exemplary scenario: low frequencies, low acceleration

21.09.16 – Karlsruhe IPG Apply & Innovate ‘16 – Thomas Tüschen 5

• 2. State-of-the-art driving simulator

Requirements to state of the art driving simulator

Statement 2 – Free yaw motion requires a double sled system Statement 1 – Use of Tilt-Coordination* only at low frequencies possible Statement 3 – Motion without frequency gaps requires large motion space

Flat Flat

𝜔

Tilting rate threshold (𝜒 𝑚𝑗𝑛𝑗𝑢): 5 °/s

• max. acceleration gradient: 9,81 m/s²* sin(5 °/s ) = 0,85 m/s² /s

 Real translational motion mandatory! Statement 1+2+3  System with large x,y-motion space is necessary!

𝜔

Source: Toyota Source: Daimler Source: DLR Source: Verlag Heinrich Vogel Source: Dissertation Betz

 Required motion space for an optimal unscaled motion simulation: ±161m

*Tilt-Coordination: The tilting of the subject leads to a transformation of the gravity force vector in order to simulate a horizontal acceleration. Sustained accelerations are simulated by tilting the simulator. (𝑏𝑢𝑗𝑚𝑢 = 9.81 𝑛 𝑡2 ∗ sin 𝜒𝑢𝑗𝑚𝑢)

21.09.16 – Karlsruhe IPG Apply & Innovate ‘16 – Thomas Tüschen 6

• 2. State-of-the-art driving simulator

Requirements to state of the art driving simulator

Force and Energy calculation: mHexapod = 4t; mSledge = 16t; a = 9,81 m/s²; lSledge = 15m; vmax≈ 12m/s² Expansion from a 1- to a 2-sledge system, with a sledge length of only 15m, would increase the force and energy demand by factor 5.

Source: Toyota Source: Daimler Source: DLR Source: Verlag Heinrich Vogel

FHexapod = 4t*9,81m/s² ≈ 39kN FSledge = (4t + 16t)*9,81m/s² ≈ 196kN EHexapod = 0,5*4t*(12 m/s)² ≈ 288kJ ESledge = 0,5*(4t + 16t)*(12m/s)² ≈ 1440kJ Sledge Hexapod

21.09.16 – Karlsruhe IPG Apply & Innovate ‘16 – Thomas Tüschen 7

• 3. auto.mobile-driving simulator

Concept Details

DOF – Degree of Freedom

Accumulator Visualization screen Modifiable cockpit concept Motion platform – Tripod (3 DOF) 4 Wheel pairs with 8 electric motor Main structure (3 DOF) Ring bearing (1 DOF) Dual suspension

Source: AMST-Systemtechnik GmbH

21.09.16 – Karlsruhe IPG Apply & Innovate ‘16 – Thomas Tüschen 8

• 3. auto.mobile-driving simulator

Mobility Concept

Driving simulator center General driving area

Source: AMST-Systemtechnik GmbH Source: AMST-Systemtechnik GmbH

21.09.16 – Karlsruhe IPG Apply & Innovate ‘16 – Thomas Tüschen 9

• Motion of the simulated/real car ≠ Motion of the

driving simulator (e.g. car is driving and simulator stands still)

• Active build-up of lateral forces only possible with a

rolling speed ≠ 0  Tire must never stand still

• 3. auto.mobile-driving simulator

Problems of a wheel-based system

• Tire has a relaxation length
• No sudden build-up of lateral forces possible  Run-in

time (approximately PT-1 behavior) - which is mainly a function of the rolling speed

• Phase delay of the simulator is theoretically depending
• n the current motion speed

 The tires rolling speed should always be on a same level

Rotational speed depending phase delay Tire as a non holonomic constraint

xt yt zt ψt θt φt

Fy=0

𝜄 t=0 ψt=const.

xt yt zt ψt θt φt

𝜄 t≠0 ψt=const.

t1 t2 t3

Fy

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! !

• 3. auto.mobile-driving simulator

Motion Concept

Acting inertia force (I-System) Drivers view Rotation Velocity Driving area

Representation

• f driving

maneuver

End of driving maneuver – return into initial position Initial position

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• 3. auto.mobile-driving simulator

Motion Concept

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• 3. auto.mobile-driving simulator

Control System Overview

Car Maker

(Simulated vehicle)

Motion Filter Motion Control auto.mobile-driving simulator

Vehicle acceleration/ angular velocity (6 DoF) Simulator acceleration/ angular velocity (7 DoF) Acceleration (COG)  4 forces (wheel-pair) based on wheel load Force (wheel-pair)  2 drive torques (with related steering angles) Force Distribution Force Control 8 wheel torques; 4 steering angles

CoG

4 Wheel forcesx,y; slip angle (long., lat.) 4 Wheel loads Position

CoG

Source: IPG Source: IPG

21.09.16 – Karlsruhe IPG Apply & Innovate ‘16 – Thomas Tüschen 13

• 4. Prediction

Phase delay

Driver Cockpit Car Maker & Control Sys. Drive Sim CGI

(Computer generated imagery)

time

Driver input Cockpit input Motion input Position physical

• bjects

Cockpit output Tactile stimuli Kinesthetic stimuli Visual/auditory stimuli

ttot ttac Δtkin Δtvis Δtkin

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• 4. Prediction

Phase delay: CarMaker 2 Cars

Master CarMaker for Simulink

Coordinates for Ego Vehicle from Master Coordinates for Ego Vehicle from Slave UDP Communication

Host PC

Source: IPG

Slave CarMaker for Simulink

t Fy t Fy Δt Master tire model with relaxation length Slave tire model without relaxation length Driver (Master) Vehicle (Master) Environment (Master) Driver (Slave) Vehicle (Slave) Environment (Slave)

UDP Communication

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• 4. Prediction

Phase delay: CarMaker 2 Cars

Problems

• UDP communication:

step size leads to a noisy signal

• No synchronization of vehicle position:

vehicle position of master and slave are drifting away Results

• Time delay of about 10ms in yaw rate and lateral

acceleration  Results can be used as an indicator for predictive control system

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• 4. Prediction

Motion space

Predictive Motion Filter [variable scaling 0,6; wash out acceleration max. 4 m/s², 0,85 m/s³] Predictive model in vehicle simulation and Motion Filter

Driving area

!

Source: IPG

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Thank you for your attention!

Dipl.-Ing. Thomas Tüschen Tel.: +49 (0) 351/463-32831 Email: thomas.tueschen@tu-dresden.de URL: www.tu-dresden.de/kft Technische Universitaet Dresden Institute for Automotive Technologies Dresden Chair of Automotive Engineering George-Baehr-Strasse 1c 01062 Dresden Germany