Upload
others
View
0
Download
0
Embed Size (px)
Citation preview
Abstract—Software equipment of interactive vehicle simulators
consists of two main parts; a generator of virtual reality (generating
3D graphics and surrounding sound) and a mathematical model of
vehicle dynamics. The basic elements of mathematical dynamics
model of the vehicle consists first of a physics of an engine and a set
of parameterization files that define the current values of the
parameters of the vehicle, second of the world which with each
particular vehicle can interact. The paper describes the development,
implementation and testing of such a mathematical software model,
which was subsequently used in the latest driving simulator in the
laboratories at the Faculty of Transportation Sciences of the Czech
Technical University in Prague.
Keywords— car dynamics, driving simulator, mathematical
model
I. INTRODUCTION
OFTWARE equipment of a driving simulator consists of two
basic parts, a generator of virtual reality (generating 3D
graphics and spatial sound) and the physical model.
In 2010 at the Faculty of Transportation Sciences, we have
developed mathematical-physical model, which was
subsequently fully utilized in 2011 in the newly realized
chassis simulator (Octavia II 3D). This model was developed
as a universal module, which is expected to be used in future
interactive simulators of ground vehicles.
Our driving simulators are successfully used for analyzing
problem of HMI, reliability in transportation ([4]) or ITS
applications ([5], [6], [7]).
II. CONSTRUCTION AND FUNCTIONAL DESIGN OF DRIVING
SIMULATOR
An overall system of ‘living’ simulator (equipped with tools
enabling its modifications respecting the actual needs of each
particular experiment) can be described as a multilayer model
[1]. The next figure (Fig. 1) introduces the functional structure
of our equipment from the simulator point of view.
The whole system can be divided into four layers (they are
separated by green lines on the picture).
P. Bouchner, e-mail: [email protected], S. Novotný, e-mail:
[email protected] The authors participate in Driving Simulation Research Group, Joint
Laboratory of System Reliability, Department of Transporting Technology,
Faculty of Transportation Sciences, Czech Technical University in Prague, Konviktská 20, 110 00 Prague, Czech Republic.
Fig. 1: Functional structure of the simulator
The first layer represents the simulator device itself. It
consists of software and hardware parts. As the hardware of
our “light” simulator, we consider the cockpit that is
composed of parts of a real car and PCs connected to a
network. I/O cards (like CAN bus to PC interface) are also
included in this layer. Software of the simulator consists of
Virtual Reality Engine (for generation of 3D graphics and
spatial sound) and mathematical model of the car and
environment. The physical engine is always a compromise
between a very accurate physical behavior and a very fast
(real-time) response.
The next layer represents a database of testing tracks
(sometimes called scenarios) and cars. Each experiment
requires a more or less different scenario. To get objective
results, it is necessary to have precisely defined the difficulty
of each scenario. Sometimes we need a curveted road to study
driver’s ability to keep the car on the road while he/she is
forced to fulfill an additional task. On the other hand, a
scenario for investigation of driver’s drowsiness and fatigue is
recommended to have a very boring (almost straight) highway
road which cannot divert him/her but it lets the driver get into
relaxed state [2], [3]. By the same way, we should treat the
database of cars. Strong engine with automatic gearbox is
suitable for measurement of drowsiness while a car with
Car Dynamics Model - Design for Interactive
Driving Simulation Use
Petr Bouchner and Stanislav Novotný
S
Recent Researches ιn Applied Informatics
ISBN: 978-1-61804-034-3 285
manual gearbox and weaker engine with worthier grips serves
better for classification of one’s driving style.
The last layer represents the tools for creation of assets
constituting scenarios. Those are mainly modeling of 3D
objects and tools for automation of such processes and
databases (storages) of modeled objects. Each object in virtual
reality is accompanied by a texture or a set of textures. The
texture is a picture, which simplifies the 3D object creation in
following manner: the geometry of any real object is very
complex, on the other hand it is possible to replace it with a
very simple geometry covered by a worked out digital
photography (texture). The textures can be of different types;
general, which are tillable (i.e. repeatable - like grass, road
surface…) and the unique ones (houses, signs….). The amount
of textures over one scenario could be very high but lots of
them could be reused on several different pieces of geometry.
For that reason, it is also very practical to have a separate
database of 3D models (objects) as well as a database of
textures.
A. Modular architecture of driving simulator
The paragraph above introduces the simulator system as a
layered architecture. In fact, the architecture of the simulator
itself is usually modular.
Considering the inputs for the simulation device, they could
be divided into two groups: first one represents the inputs into
the simulation, these are real geographical data (for example
from GIS sources), data from the real world maps, data from
micro traffic simulations and finally the data from external
high-end physical simulations and models.
On the other hand, the system should be opened for imports
from various devices, which can be connected in the car.
Those could be for example: driver assistance devices,
systems of mobile communication, GPS systems and many
other systems requiring driver’s interaction. The basic system
setup can be fortunately decomposed into subsystems, which
could be treated and solved separately. The basic modules are
as follows (see the diagram Fig. 2):
• Graphic engine
• Graphic output system
• Spatial Audio system [8]
• Motion platform and vibration system
• Scene handling and generation system [9], [10]
• Car physics engine
• General input system
• General purpose output system
• Communication and interconnection module
• Safety and emergency system
Fig. 2: Advanced driving simulation system – basic structure
The modular architecture of a system that is required to
work in almost real time should be well-designed. The
interconnection system, which we use in our modular system
of our driving simulators, is composed of three levels - see
Fig. 3 (described in more details in [11]).
Fig. 3: Modular system based on Manager-Agent-Client architecture
(by [11])
The modules can be treated and operated separately but it is
INTERCONNECTION &
COMMUNICATION
MODULE
GENERAL
INPUT
GENERAL
OUTPUT
MOTION
PLATFORM
DRIVING
CAR
PHYSICS
ENGINE
GRAPHICAL
ENGINE
AUDIO
ENGINE
SCENE
HANDLING
MODULE
ASSETS
DATABASE
AUDIO
OUTPUT
SYSTEM
VIDEO
OUTPUT
SYSTEM
MOTION
PLATFORM
+
VIBRATION
ELEMENTS
SA
FE
TY
SY
ST
EM
Recent Researches ιn Applied Informatics
ISBN: 978-1-61804-034-3 286
very useful to take advantage of their interconnection. The
results from tasks computed on one particular module could be
utilized in other modules, which process the same (or very
similar) data. As an example, we can consider a geometric
representation of an area of the virtual scenery. The graphical
engine primarily cuts off an appropriate area of the virtual
world representing the actual driver’s surroundings. Then the
geometry should be worked out according to a particular level
of detail. Such data then enter into rendering process.
Fortunately, the data could be also reused in other modules.
For example, the audio system also needs the geometrical
representation of the world to be able to render the sound
realistically. Other modules, which can take advantage from
such pre-computed data, are for example:
• collision detection subsystem
• traffic management subsystem
• general output subsystem
• car simulation physics engine
III. MATHEMATICAL – PHYSICS SIMULATION ENGINE
The model of the car is done using linear integral-
differential solver. Online processing of input data (signals
from the devices representing driver’s controlling actions) is a
basic requirement on mathematical model of physical behavior
of any interactive simulation system. Such inputs, in case of
driving simulators, are represented by the following signals
(parameters):
• Rate of depression of throttle pedal
• Rate of depression of brake pedal
• Rate of depression of clutch pedal (in case of manual
gear shifting)
• Gear shifter position
• Angle of steering wheel deflection
Those are the basic ones, which can be (and in most cases
of high fidelity simulators are) accompanied with additional
inputs which tell the simulator about the driver’s orders and
intentions (handbrake, handlers, buttons etc.). The physical
“engine” (processing the mathematical car model) should be
able to react on additional inputs which are usually realized
via direct (manual setting) or indirect (realized via activation
of some assistant system) driver’s interventions.
Another important source of information upon which the
mathematical model decides about future steps in car behavior
is an actual state of the objects the car is interacting with. This
includes either road surface beneath each of the wheels or any
object inside the virtual world the car could get in touch with
(drives over or collides). The objects are characterized by a set
of parameters that can be static or dynamic. Their dynamical
behavior could come either from a preprogrammed dynamical
nature (moving objects on the road, traffic, change of road
adhesion due to changeable weather conditions) or they can
result just from driver’s actions (collision with objects etc.).
Upon this above described information and information
about inner structure of the simulated system (axle
architecture, gearbox etc.) the actual behavior (next step) is
computed. The following picture (Fig. 4) illustrates a basic
arrangement of powered wheel in contemporary road vehicles
with following elements:
• Engine with flywheel (1)
• Clutch (2)
• Gearbox (3)
• Differential (4)
• Axle with wheel and suspensions (5)
Fig. 4: A simplified transmission of the initial torque from the engine
up to the wheel surface
The mathematical model of vehicle physics makes always a
kind of compromise in between physical preciseness and
ability of computer to compute online enough short simulation
steps.
The core of the physical engine is composed from partial
function blocks respecting a real structure and links. In our
model these are:
• Engine
• Gearbox
• Wheels (tires)
• Suspensions
• Car body
• Surface of interacting terrain
• Initial parameters of the whole model
• Input parameters from driver and other simulation
models
• Inner variables
In the following picture (Fig. 5), there is the architecture of
our physical engine.
Fig. 5: Architecture of the physics engine
A. Essential elements of mathematical model of vehicle
dynamics
The system of physics of an engine is composed of a
mathematical model of vehicle dynamics and a set of
parameterizing files describing parameters of the vehicle and
terrain and surface parameters with corresponding collision
geometry.
The main processing unit is the physics of the engine, in our
Calculation of
traction forces
Input Engine
Suspension Wheels
Car position Car body tilt
Transmission
Recent Researches ιn Applied Informatics
ISBN: 978-1-61804-034-3 287
implementation represented by dynamically linked C++
library, in which a rough architecture of the car is defined
(with use of an open library ODE ver. 0.11.1 [12]). The built-
in architecture corresponds to middle class European car with
McPherson front axle and multi-element rear axle. Driving
power is possible to be applied on front or rear wheels or to be
split in between both (4x4).
The requested output from the computation step is
represented by the vector of variables describing the car body
position orientation (similarly for all wheels) and dynamical
status, i.e. velocity, engine RPM, wheel forces etc. as well as
virtually any variable which would be useful for other driving
simulator subsystems (for example any input for advanced
assistance devices, dashboard, navigation system…).
In our implementation, there are also other modules -
accompanying the rough physics engine - which are intended
to help the user control the simulation module, as well as to
allow him to change some car/surface parameters and/or to
choose from predefined ones. It also serves for visualization of
inner states of the vehicle model, what can be very useful for
early detection of possible nonstandard situations by the user.
Fig. 6: Front end to physical model of the car
The figure above (Fig. 6) shows the user interface of the
mathematical model CarDynamics. The various areas contain
control and information entries. They are as follows:
1. basic controls - restarting the simulation and closure of
an application
2. selection of input devices
3. control panel - "joystick" is intended to control the
steering wheel, throttle and brake, "+" and "-" shift, hand
brake and engine ignition
4. position and rotation of the vehicle - the actual value
after the external simulation step
5. output data of the vehicle - the actual value of the
external simulation step. Velocity (m / s), engine speed
(RPM), transmission gear, the driver inputs (steering
wheel, throttle, brake, clutch, handbrake, ignition), then
the actual duration of the external simulation step (ms).
6. tuning parameters
7. position and rotation of each wheel
8. degree of depression of springs of each of the wheel - the
bottom to the top stop (0% -100%)
B. Visualization and recording module VIS
This module is designed to visualize the detailed behavior
of a vehicle with the ability to record and playback of the car
behavior (all driving parameters). It can be used both for
tuning of the vehicle parameters, online monitoring of the
experiment or for offline playback of recorded experiments
(Fig. 7). This module also serves as a recording device, which
collects all the experimental data for further data analyses.
Fig. 7: Visualization and recording module VIS
C. System parameterization
Mathematical physical simulation module is designed in
such a way its properties can be modified according to the
requirements of possible changes in the simulated track and
the vehicle. According to actual needs, it is possible to adjust
the characteristics of the simulation library. Parameterization
of models is done with use of “ini” files, which are fetched
just before the module is ran or on demand during simulation
runtime.
Setup of mathematics and physics simulation module lays
mainly in the selection of vehicles and tracks properties. The
main parameter here is to set the simulation step, which is the
basis for simulation.
The simulation step is divided into external and internal.
Internal step is the actual simulation of the smallest unit (tick),
which does not change during the course of simulation.
External step is a period, over which the physical model
provides the current status to other modules. External step
must be a whole multiple of an internal step (or can be the
same).
D. Setup of car parameters
The model of car dynamics corresponds to middle-class
European car with front wheel drive, independent suspension
for all four wheels. The gearbox is selectable automatic (with
a hydrodynamic converter) or with a driver controlled
mechanical clutch.
Each parameter of a vehicle can be adjusted in an
appropriate ini file, except of parameters of the model of
wheel that are defined within the characteristics of surface
parameterization. In fact, there is not defined the wheel model
itself, but the model of the dynamic behavior of wheels in
contact with different surfaces.
Recent Researches ιn Applied Informatics
ISBN: 978-1-61804-034-3 288
E. Setup of track parameters
The vehicle moves over the virtual track, the visual image is
provided to the driver as the 3D view of objects via
visualization modules to each of the projection channels. The
physical equivalent is mathematical-physical model to
calculate the dynamic behavior.
The individual track parameters can be set in the respective
ini files with a help of set of collision objects. There are
defined parameters including interaction of the wheel (or other
colliding parts of the simulated of the vehicle) with elements
of the virtual track. These are especially surfaces, over which
the vehicle is moving and solid collision objects placed on the
track (or alongside).
IV. CONCLUSION
The whole system of simulator hardware and software
modules is a considerably complex system that requires a
relatively difficult testing procedures before it can be launched
in full operation in real experiments. This process took place
in several stages:
• technological testing of the whole system
• practical testing of system functionality in the form of
free rides
• technology testing of communication, recording and
measuring devices in the simulator system
• undertaking a sample experiment with several probands
The simulation module of car dynamics is a compromise
between two main requirements – first, a highest possible
precession and complexity of the model; second, the available
computer power capable to compute adequate close to real-
time computations, which can include interactively “driver in
loop”. On the other hand, the fidelity the interactive simulation
is always perceived subjectively by the drivers, whose
expectations and requirements on the driving simulator (and
its physical model as well) are often different from what
vehicle engineers suppose.
Since the model of the car dynamics (mainly model of
interaction between the tire and road surface) is still quite
simplified and range of cues the simulator can provide is
limited, the main criteria are experimental drivers’ feelings.
Validation of such a model should be done with use of
sophisticated experiments comparing the drivers’ behaviour in
real vs. simulated environment.
ACKNOWLEDGMENT
The work was supported by a grant of Czech Technology
Agency TACR, TA01030574 “Laboratory for training and
education of professional truck drivers equipped with
advanced truck driving simulator with ability of measuring
and analyzing of psycho-physiological, psychological and
performance data”.
REFERENCES
[1] P. Bouchner, S. Novotný, “System with driving simulation device for HMI measurements”, 8th WSEAS International Conference on
SYSTEMS (part of the 8th CSCC Multiconference), Athens, 2005,
ISBN 960-8457-29-7.
[2] M. Jiřina, P. Bouchner, S. Novotný, “Identification of driver's
drowsiness using driving information, Neural Network World
Volume:20, Issue:6, Pages:773-79, 2010
[3] S. Novotny, P. Bouchner, “Advanced methodology for evaluation of
driver's actual state with use of technical driving data”, PROCEEDINGS OF THE 8TH WSEAS INTERNATIONAL CONFERENCE ON
SYSTEMS THEORY AND SCIENTIFIC COMPUTATION
(ISTAC'08) Book Series: Mathematics and Computers in Science and Engineering, 160-165, 2008
[4] P. Moos, M. Novak, Z. Votruba et al., ”Estimation of failures probability
in alliances of transportation systems” , International Multi-Conference on Engineering and Technological Innovation Location: Orlando, FL
Date: JUN 29-JUL 02, 2008
[5] P. Bures, Z. Belinova, P. Jesty, “Intelligent Transport System architecture Different Approaches and Future Trends”, Data and
Mobility: Transforming Information into Intelligent Traffic and
Transportation Services, Proceedings of the Lakeside Conference 2010. vol. 81, J. Duh, et al., Springer-Verlag Berlin, 2010, pp. 115-125.
[6] P. Bures, “The architecture of traffic and travel information system
based on protocol TPEG”, Proceedings of the 2009 Euro American Conference on Telematics and Information Systems: New Opportunities
to increase Digital Citizenship, Prague, Czech Republic, 2009.
[7] T. Zelinka , M. Svitek, “Adaptive communications solutions in complex transport telematics systems”, Proceedings of the 12th WSEAS
international conference on communications - new aspects of
communications: book series: Recent advances in electrical engineering. Heraklion, Greece, 2008. pp. 206-212
[8] P. Larsson, D. Västfjäll, M. Kleiner “Perception of Self-motion and Presence in Auditory Virtual Environments”, Department of Applied
Acoustics, Chalmers University of Technology, Göteborg, Sweden.
Department of Psychology, Göteborg University, Göteborg, Sweden,Program in Architectural Acoustics, Rensselaer Polytechnic
Institute, Troy, NY, USA.
[9] B. E. Riecke, J. Schulte-Pelkum, M. N. Avraamides, M. Heyde, H. H.
Bülthoff, “Scene Consistency and Spatial Presence Increase the
Sensation of Self-Motion in Virtual Reality”, Max Planck Institute for
Biological Cybernetics, Tübingen, Germany,Department of Psychology, University of Cyprus, SCC, Bauhaus-Universität Weimar, Germany.
[10] D. Krajzewicz, G. Hertkorn, J. Ringel, P. Wagner, “Preparation of
Digital Maps for Traffic Simulation; Part 1: Approach and Algorithms”, German Aerospace Centre, Institute of Transportation Research, Berlin,
Germany.
[11] M. Lalcek ,“A Framework for Modular Architecture of Car Simulators”, (in Czech), Diploma thesis, FTS CTU, Prague, 2006
[12] Russell Smith, Open Dynamic Engine (ODE), Available at:
http://www.ode.org (accessed July 2011)
Petr Bouchner obtained his master degree (2003) in Computer Sciences from Faculty of Electrical Engineering of the Czech Technical University in Prague
and his doctor degree (2007) in Engineering Informatics from Faculty of
Transportation Sciences of the Czech Technical University in Prague. From 2002, he actively participates in projects dealing with driving simulator
development and research in a field of human factors in transportation.
Recently he works as an assistant professor and head of Department of Transporting Technology at the same faculty. He founded and leads the
Driving Simulation Research Group.
Stanislav Novotný obtained his master degree in 2005 in Automation of
Transportation and Telecommunications from Faculty of Transportation
Sciences of Czech Technical University in Prague. He finished his doctoral
studies at the same faculty in 2009 and he contemporarily works there as a
researcher in the Driving Simulation Research Group.
Recent Researches ιn Applied Informatics
ISBN: 978-1-61804-034-3 289